The Next Frontier: LEO Satellites for Internet Services.

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THE SPACE RACE IS ON.

If all current commercial satellite plans were to be realized within the next decade, we would have more, possibly substantially more, than 65 thousand satellites circling Earth. Today, that number is less than 10 thousand, with more than half that number realized by StarLink’s Low Earth Orbit (LEO) constellation over the last couple of years (i.e., since 2018).

While the “Arms Race” during the Cold War was “a thing” mainly between The USA and the former Soviet Union, the Space Race will, in my opinion, be “battled out” between the commercial interests of the West against the political interest of China (as illustrated in Figure 1 below). The current numbers strongly indicate that Europe, Canada, the Middle East, Africa, and APAC (minus China) will likely and largely be left on the sideline to watch the US and China impose, in theory, a “duopoly” in LEO satellite-based services. However, in practice, it will be a near-monopoly when considering security concerns between the West and the (re-defined) East block.

Figure 1 Illustrates my thesis that we will see a Space Race over the next 10 years between a (or very few) commercial LEO constellation, represented by a Falcon-9 like design (for maybe too obvious reasons), and a Chinese-state owned satellite constellation. (Courtesy: DALL-E).

As of end of 2023, more than 50% of launched and planned commercial LEO satellites are USA-based. Of those, the largest fraction is accounted for by the US-based StarLink constellation (~75%). More than 30% are launched or planned by Chinese companies headed by the state-owned Guo Wang constellation rivaling Elon Musk’s Starlink in ambition and scale. Europe comes in at a distant number 3 with about 8% of the total of fixed internet satellites. Apart from being disappointed, alas, not surprised by the European track record, it is somewhat more baffling that there are so few Indian and African satellite (there are none) constellations given the obvious benefits such satellites could bring to India and the African continent.

India is a leading satellite nation with a proud tradition of innovative satellite designs and manufacturing and a solid track record of satellite launches. However, regarding commercial LEO constellations, India still needs to catch up on some opportunities here. Having previously worked on the economics and operationalizing a satellite ATC (i.e., a satellite service with an ancillary terrestrial component) internet service across India, it is mind-blowing (imo) how much economic opportunity there is to replace by satellite the vast terrestrial cellular infrastructure in rural India. Not to mention a quantum leap in communication broadband services resilience and availability that could be provided. According to the StarLink coverage map, the regulatory approval in India for allowing StarLink (US) services is still pending. In the meantime, Eutelsat’s OneWeb (EU) received regulatory approval in late 2023 for its satellite internet service over India in collaboration with Barthi Enterprises (India), that is also the largest shareholder in the recently formed Eutelsat Group with 21.2%. Moreover, Jio’s JioSpaceFiber satellite internet services were launched in several Indian states at the end of 2023, using the SES (EU) MEO O3b mPower satellite constellation. Despite the clear satellite know-how and capital available, it appears there is little activity for Indian-based LEO satellite development, taking up the competition with international operators.

The African continent is attracting all the major LEO satellite constellations such as StarLink (US), OneWeb (EU), Amazon Kuipers (US), and Telesat Lightspeed (CAN). However, getting regulatory approval for their satellite-based internet services is a complex, time-consuming, and challenging process with Africa’s 54 recognized sovereign countries. I would expect that we will see the Chinese-based satellite constellations (e.g., Guo Wang) taking up here as well due to the strong ties between China and several of the African nations.

This article is not about SpaceX’s StarLink satellite constellation. Although StarLink is mentioned a lot and used as an example. Recently, at the Mobile World Congress 2024 in Barcelona, talking to satellite operators (but not StarLink) providing fixed broadband satellite services, we joked about how long into a meeting we could go before SpaceX and StarLink would be mentioned (~ 5 minutes where the record, I think).

This article is about the key enablers (frequencies, frequency bandwidth, antenna design, …) that make up an LEO satellite service, the LEO satellite itself, the kind of services one should expect from it, and its limitations.

There is no doubt that LEO satellites of today have an essential mission: delivering broadband internet to rural and remote areas with little or no terrestrial cellular or fixed infrastructure to provide internet services. Satellites can offer broadband internet to remote areas with little population density and a population spread out reasonably uniformly over a large area. A LEO satellite constellation is not (in general) a substitute for an existing terrestrial communications infrastructure. Still, it can enhance it by increasing service availability and being an important remedy for business continuity in remote rural areas. Satellite systems are capacity-limited as they serve vast areas, typically with limited spectral resources and capacity per unit area.

In comparison, we have much smaller coverage areas with demand-matched spectral resources in a terrestrial cellular network. It is also easier to increase capacity in a terrestrial cellular system by adding more sectors or increasing the number of sites in an area that requires such investments. Adding more cells, and thus increasing the system capacity, to satellite coverage requires a new generation of satellites with more advanced antenna designs, typically by increasing the number of phased-array beams and more complex modulation and coding mechanisms that boost the spectral efficiency, leading to increased capacity and quality for the services rendered to the ground. Increasing the system capacity of a cellular communications system by increasing the number of cells (i.e., cell splitting) works the same in satellite systems as it does for a terrestrial cellular system.

So, on average, LEO satellite internet services to individual customers (or households), such as those offered by StarLink, are excellent for remote, lowly populated areas with a nicely spread-out population. If we de-average this statement. Clearly, within the satellite coverage area, we may have towns and settlements where, locally, the population density can be fairly large despite being very small over the larger footprint covered by the satellite. As the capacity and quality of the satellite is a shared resource, serving towns and settlements of a certain size may not be the best approach to providing a sustainable and good customer experience as the satellite resources exhaust rapidly in such scenarios. In such scenarios, a hybrid architecture is of much better use as well as providing all customers in a town or settlement with the best service possible leveraging the existing terrestrial communications infrastructure, cellular as well as fixed, with that of a satellite backhaul broadband connection between a satellite ground gateway and the broadband internet satellite. This is offered by several satellite broadband providers (both from GEO, MEO and LEO orbits) and has the beauty of not only being limited to one provider. Unfortunately, this particular finesse, is often overlooked by the awe of massive scale of the StarLink constellation.

AND SO IT STARTS.

When I compared the economics of stratospheric drone-based cellular coverage with that of LEO satellites and terrestrial-based cellular networks in my previous article, “Stratospheric Drones: Revolutionizing Terrestrial Rural Broadband from the Skies?”, it was clear that even if LEO satellites are costly to establish, they provide a substantial cost advantage over cellular coverage in rural and remote areas that are either scarcely covered or not at all. Although the existing LEO satellite constellations have limited capacity compared to a terrestrial cellular network and would perform rather poorly over densely populated areas (e.g., urban and suburban areas), they can offer very decent fixed-wireless-access-like broadband services in rural and remote areas at speeds exceeding even 100 Mbps, such as shown by the Starlink constellation. Even if the provided speed and capacity is likely be substantially lower than what a terrestrial cellular network could offer, it often provides the missing (internet) link. Anything larger than nothing remains infinitely better.

Low Earth Orbit (LEO) satellites represent the next frontier in (novel) communication network architectures, what we in modern lingo would call non-terrestrial networks (NTN), with the ability to combine both mobile and fixed broadband services, enhancing and substituting terrestrial networks. The LEO satellites orbit significantly closer to Earth than their Geostationary Orbit (GEO) counterparts at 36 thousand kilometers, typically at altitudes between 300 to 2,000 kilometers, LEO satellites offer substantially reduced latency, higher bandwidth capabilities, and a more direct line of sight to receivers on the ground. It makes LEO satellites an obvious and integral component of non-terrestrial networks, which aim to extend the reach of existing fixed and mobile broadband services, particularly in rural, un-and under-served, or inaccessible regions as a high-availability element of terrestrial communications networks in the event of natural disasters (flooding, earthquake, …), or military conflict, in which the terrestrial networks are taken out of operation.

Another key advantage of LEO satellite is that the likelihood of a line-of-sight (LoS) to a point on the ground is very high compared to establishing a LoS for terrestrial cellular coverage that, in general, would be very low. In other words, the signal propagation from a LEO satellite closely approximates that of free space. Thus, all the various environmental signal loss factors we must consider for a standard terrestrial-based cellular mobile network do not apply to our satellite with signal propagation largely being determined by the distance between the satellite and the ground (see Figure 2).

Figure 2 illustrates the difference between terrestrial cellular coverage from a cell tower and that of a Low Earth Orbit (LEO) Satellite. The benefit of seeing the world from above is that environmental and physical factors have substantially less impact on signal propagation and quality primarily being impacted by distance as it approximates free space propagation with signal attenuation mainly determined by the Line-of-Sight (LoS) distance from antenna to Earth. This situation is very different for a terrestrial-based cellular tower with its radiated signal being substantially compromised by environmental factors.

Low Earth Orbit (LEO) satellites, compared to GEO and MEO-based higher-altitude satellite systems, in general, have simpler designs and smaller sizes, weights, and volumes. Their design and architecture are not just a function of technological trends but also a manifestation of their operational environment. The (relative) simplicity of LEO satellites also allows for more standardized production, allowing for off-the-shelf components and modular designs that can be manufactured in larger quantities, such as the case with CubeSats standard and SmallSats in general. The lower altitude of LEO satellites translates to a reduced distance from the launch site to the operational orbit, which inherently affects the economics of satellite launches. This proximity to Earth means that the energy required to propel a satellite into LEO is significantly less than needed to reach Geostationary Earth Orbit (GEO), resulting in lower launch costs.

The advent of LEO satellite constellations marks an important shift in how we approach global connectivity. With the potential to provide ubiquitous internet coverage in rural and remote places with little or no terrestrial communications infrastructure, satellites are increasingly being positioned as vital elements in global communication. The LEO satellites, as well as stratospheric drones, have the ability to provide economical internet access, as addressed in my previous article, in remote areas and play a significant role in disaster relief efforts. For example, when terrestrial communication networks may be disrupted after a natural disaster, LEO satellites can quickly re-establish communication links to normal cellular devices or ad-how earth-based satellite systems, enabling efficient coordination of rescue and relief operations. Furthermore, they offer a resilient network backbone that complements terrestrial infrastructure.

The Internet of Things (IoT) benefits from the capabilities of LEO satellites. Particular in areas where there is little or no existing terrestrial communications networks. IoT devices often operate in remote or mobile environments, from sensors in agricultural fields to trackers across shipping routes. LEO satellites provide reliable connectivity to IoT networks, facilitating many applications, such as non- and near real-time monitoring of environmental data, seamless asset tracking over transcontinental journeys, and rapid deployment of smart devices in smart city infrastructures. As an example, let us look at the minimum requirements for establishing a LEO satellite constellation that can gather IoT measurements. At an altitude of 550 km the satellite would take ca. 1.5 hour to return to a given point on its orbit. Earth rotates (see also below) which require us to deploy several orbital planes to ensure that we have continuous coverage throughout the 24 hours of a day (assuming this is required). Depending on the satellite antenna design, the target coverage area, and how often a measurement is required, a satellite constellation to support an IoT business may not require much more than 20 (lower measurement frequency) to 60 (higher measurement frequency, but far from real real-time data collection) LEO satellites (@ 550 km).

For defense purposes, LEO satellite systems present unique advantages. Their lower orbits allow for high-resolution imagery and rapid data collection, which are crucial for surveillance, reconnaissance, and operational awareness. As typically more LEO satellites will be required, compared to a GEO satellite, such systems also offer a higher degree of redundancy in case of anti-satellite (ASAT) warfare scenarios. When integrated with civilian applications, military use cases can leverage the robust commercial infrastructure for communication and geolocation services, enhancing capabilities while distributing the system’s visibility and potential targets.

Standalone military LEO satellites are engineered for specific defense needs. These may include hardened systems for secure communication, resistance to jamming, and interception. For instance, they can be equipped with advanced encryption algorithms to ensure secure transmission of sensitive military data. They also carry tailored payloads for electronic warfare, signal intelligence, and tactical communications. For example, they can host sensors for detecting and locating enemy radar and communication systems, providing a significant advantage in electronic warfare. As the line between civilian and military space applications blurs, dual-use LEO satellite systems are emerging, capable of serving civilian broadband and specialized military requirements. It should be pointed out that there also military applications, such as signal gathering, that may not be compatible with civil communications use cases.

In a military conflict, the distributed architecture and lower altitude of LEO constellations may offer some advantages regarding resilience and targetability compared to GEO and MEO-based satellites. Their more significant numbers (i.e., 10s to 1000s) compared to GEO, and the potential for quicker orbital resupply can make them less susceptible to complete system takedown. However, their lower altitudes could make them accessible to various ASAT technologies, including ground-based missiles or space-based kinetic interceptors.

It is not uncommon to encounter academic researchers and commentators who give the impression that LEO satellites could replace existing terrestrial-based infrastructures and solve all terrestrial communications issues known to man. That is (of course) not the case. Often, such statements appears to be based an incomplete understanding of the capacity limitation of satellite systems. Due to satellites’ excellent coverage with very large terrestrial footprints, the satellite capacity is shared over very large areas. For example, consider an LEO satellite at 550 km altitude. The satellite footprint, or coverage area (aka ground swath), is the area on the Earth’s surface over which the satellite can establish a direct line of sight. The satellite footprint in our example diameter would be ca. five thousand five hundred kilometers. An equivalent area of ca. 23 million square kilometers is more than twice that of the USA (or China or Canada). Before you get too excited, the satellite antenna will typically restrict the surface area the satellite will cover. The extent of the observable world that is seen at any given moment by the satellite antenna is defined as the Field of View (FoV) and can vary from a few degrees (narrow beams, small coverage area) to 40 degrees or higher (wide beams, large coverage areas). At a FoV of 20 degrees, the antenna footprint would be ca. 2 thousand 400 kilometers, equivalent to a coverage area of ca. 5 million square kilometers.

In comparison, for a FoV of 0.8 degrees, the antenna footprint would only be 100 kilometers. If our satellite has a 16-satellite beam capability, it would translate into a coverage diameter of 24 km per beam. For the StarLink system based on the Ku-band (13 GHz) and a cell downlink (Satellite-to-Earth) capacity of ca. 680 Mbps (in 250 MHz) we would have ca. 2 Mbps per km2 unit coverage area. Compared to a terrestrial rural cellular site with 85 MHz (Downlink, Base station antenna to customer terminal), it would deliver 10+ Mbps per km2 unit coverage area.

It is always good to keep in mind that “Satellites mission is not to replace terrestrial communications infrastructures but supplement and enhance them”, and furthermore, “Satellites offer the missing (internet) link in areas where there is no terrestrial communications infrastructure present”. Satellites offer superior coverage to any terrestrial communications infrastructure. Satellites limitations are in providing capacity, and quality, at population scale as well as supporting applications and access technologies requiring very short latencies (e.g., smaller than 10 ms).

In the following, I will focus on terrestrial cellular coverage and services that LEO satellites can provide. At the end of my blog, I hope I have given you (the reader) a reasonable understanding of how terrestrial coverage, capacity, and quality work in a (LEO) satellite system and have given you an impression of key parameters we can add to the satellite to improve those.

EARTH ROTATES, AND SO DO SATELLITES.

Before getting into the details of low earth orbit satellites, let us briefly get a couple of basic topics off the table. Skipping this part may be a good option if you are already into and in the know satellites. Or maybe carry on an get a good laugh of those terra firma cellular folks that forgot about the rotation of Earth 😉

From an altitude and orbit (around Earth) perspective, you may have heard of two types of satellites: The GEO and the LEO satellites. Geostationary (GEO) satellites are positioned in a geostationary orbit at ~36 thousand kilometers above Earth. That the satellite is geostationary means it rotates with the Earth and appears stationary from the ground, requiring only one satellite to maintain constant coverage over an area that can be up to one-third of Earth’s surface. Low Earth Orbit (LEO) satellites are positioned at an altitude between 300 to 2000 kilometers above Earth and move relative to the Earth’s surface at high speeds, requiring a network or constellation to ensure continuous coverage of a particular area.

I have experienced that terrestrial cellular folks (like myself) when first thinking about satellite coverage are having some intuitive issues with satellite coverage. We are not used to our antennas moving away from the targeted coverage area, and our targeted coverage area, too, is moving away from our antenna. The geometry and dynamics of terrestrial cellular coverage are simpler than they are for satellite-based coverage. For LEO satellite network planners, it is not rocket science (pun intended) that the satellites move around in their designated orbit over Earth at orbital speeds of ca. 70 to 80 km per second. Thus, at an altitude of 500 km, a LEO satellite orbits Earth approximately every 1.5 hours. Earth, thankfully, rotates. Compared to its GEO satellite “cousin,” the LEO satellite ” is not “stationary” from the perspective of the ground. Thus, as Earth rotates, the targeted coverage area moves away from the coverage provided by the orbital satellite.

We need several satellites in the same orbit and several orbits (i.e., orbital planes) to provide continuous satellite coverage of a target area. This is very different from terrestrial cellular coverage of a given area (needles to say).

WHAT LEO SATELLITES BRING TO THE GROUND.

Anything is infinitely more than nothing. The Low Earth Orbit satellite brings the possibility of internet connectivity where there previously was nothing, either because too few potential customers spread out over a large area made terrestrial-based services hugely uneconomical or the environment is too hostile to build normal terrestrial networks within reasonable economics.

Figure 3 illustrates a low Earth satellite constellation providing internet to rural and remote areas as a way to solve part of the digital divide challenge in terms of availability. Obviously, the affordability is likely to remain a challenge unless subsidized by customers who can afford satellite services in other places where availability is more of a convenience question. (Courtesy: DALL-E)

The LEO satellites represent a transformative shift in internet connectivity, providing advantages over traditional cellular and fixed broadband networks, particularly for global access, speed, and deployment capabilities. As described in “Stratospheric Drones: Revolutionizing Terrestrial Rural Broadband from the Skies?”, LEO satellite constellations, or networks, may also be significantly more economical than equivalent cellular networks in rural and remote areas where the economics of coverage by satellite, as depicted in the above Figure 3, is by far better than by traditional terrestrial cellular means.

One of the foremost benefits of LEO satellites is their ability to offer global coverage as well as reasonable broadband and latency performance that is difficult to match with GEO and MEO satellites. The GEO stationary satellite obviously also offers global broadband coverage, the unit coverage being much more extensive than for a LEO satellite, but it is not possible to offer very low latency services, and it is more difficult to provide high data rates (in comparison to a LEO satellite). LEO satellites can reach the most remote and rural areas of the world, places where laying cables or setting up cell towers is impractical. This is a crucial step in delivering communications services where none exist today, ensuring that underserved populations and regions gain access to internet connectivity.

Another significant advantage is the reduction in latency that LEO satellites provide. Since they orbit much closer to Earth, typically at an altitude between 350 to 700 km, compared to their geostationary counterparts that are at 36 thousand kilometers altitude, the time it takes for a communications signal to travel between the user and the satellite is significantly reduced. This lower latency is crucial for enhancing the user experience in real-time applications such as video calls and online gaming, making these activities more enjoyable and responsive.

An inherent benefit of satellite constellations is their ability for quick deployment. They can be deployed rapidly in space, offering a quicker solution to achieving widespread internet coverage than the time-consuming and often challenging process of laying cables or erecting terrestrial infrastructure. Moreover, the network can easily be expanded by adding more satellites, allowing it to dynamically meet changing demand without extensive modifications on the ground.

LEO satellite networks are inherently scalable. By launching additional satellites, they can accommodate growing internet usage demands, ensuring that the network remains efficient and capable of serving more users over time without significant changes to ground infrastructure.

Furthermore, these satellite networks offer resilience and reliability. With multiple satellites in orbit, the network can maintain connectivity even if one satellite fails or is obstructed, providing a level of redundancy that makes the network less susceptible to outages. This ensures consistent performance across different geographical areas, unlike terrestrial networks that may suffer from physical damage or maintenance issues.

Another critical advantage is (relative) cost-effectiveness compared to a terrestrial-based cellular network. In remote or hard-to-reach areas, deploying satellites can be more economical than the high expenses associated with extending terrestrial broadband infrastructure. As satellite production and launch costs continue to decrease, the economics of LEO satellite internet become increasingly competitive, potentially reducing the cost for end-users.

LEO satellites offer a promising solution to some of the limitations of traditional connectivity methods. By overcoming geographical, infrastructural, and economic barriers, LEO satellite technology has the potential to not just complement but effectively substitute terrestrial-based cellular and fixed broadband services, especially in areas where such services are inadequate or non-existent.

Figure 4 below provides an overview of LEO satellite coverage with fixed broadband services offered to customers in the Ku band with a Ka backhaul link to ground station GWs that connect to, for example, the internet. Having inter-satellite communications (e.g., via laser links such as those used by Starlink satellites as per satellite version 1.5) allows for substantially less ground-station gateways. Inter-satellite laser links between intra-plane satellites are a distinct advantage in ensuring coverage for rural and remote areas where it might be difficult, very costly, and impractical to have a satellite ground station GW to connect to due to the lack of global internet infrastructure.

Figure 4 In general, a satellite is required to have LoS to its ground station gateway (GW); in other words, the GW needs to be within the coverage footprint of the satellite. For LEO satellites, which are at low altitudes, between 300 and 2000 km, and thus have a much lower footprint than MEO and GEO satellites, this would result in a need for a substantial amount of ground stations. This is depicted in (a) above. With inter-satellite laser links (SLL), e.g., those implemented by Starlink, it is possible to reduce the ground station gateways significantly, which is particularly helpful in rural and very remote areas. These laser links enable direct communication between satellites in orbit, which enhances the network’s performance, reliability, and global reach.

Inter-satellite laser links (ISLLs), or, as it is also called Optical Inter-satellite Links (OISK), are an advanced communication technology utilized by satellite constellations, such as for example Starlink, to facilitate high-speed secure data transmission directly between satellites. Inter-satellite laser links are today (primarily) designed for intra-plane communication within satellite constellations, enabling data transfer between satellites that share the same orbital plane. This is due to the relatively stable geometries and predictable distances between satellites in the same orbit, which facilitate maintaining the line-of-sight connections necessary for laser communications. ISLLs mark a significant departure from traditional reliance on ground stations for inter-satellite communication, and as such the ISL offers many benefits, including the ability to transmit data at speeds comparable to fiber-optic cables. Additionally, ISLLs enable satellite constellations to deliver seamless coverage across the entire planet, including over oceans and polar regions where ground station infrastructure is limited or non-existent. The technology also inherently enhances the security of data transmissions, thanks to the focused nature of laser beams, which are difficult to intercept.

However, the deployment of ISLLs is not without challenges. The technology requires a clear line of sight between satellites, which can be affected by their orbital positions, necessitating precise control mechanisms. Moreover, the theoretical limit to the number of satellites linked in a daisy chain is influenced by several factors, including the satellite’s power capabilities, the network architecture, and the need to maintain clear lines of sight. High-power laser systems also demand considerable energy, impacting the satellite’s power budget and requiring efficient management to balance operational needs. The complexity and cost of developing such sophisticated laser communication systems, combined with very precise pointing mechanisms and sensitive detectors, can be quite challenging and need to be carefully weighted against building satellite ground stations.

Cross-plane ISLL transmission, or the ability to communicate between satellites in different orbital planes, presents additional technical challenges, as it is technically highly challenging to maintain a stable line of sight between satellites moving in different orbital planes. However, the potential for ISLLs to support cross-plane links is recognized as a valuable capability for creating a fully interconnected satellite constellation. The development and incorporation of cross-plane ISLL capabilities into satellites are an area of active research and development. Such capabilities would reduce the reliance on ground stations and significantly increase the resilience of satellite constellations. I see the development as a next-generation topic together with many other important developments as described in the end of this blog. However, the power consumption of the ISLL is a point of concern that needs careful attention as it will impact many other aspects of the satellite operation.

THE DIGITAL DIVIDE.

The digital divide refers to the “internet haves and haves not” or “the gap between individuals who have access to modern information and communication technology (ICT),” such as the internet, computers, and smartphones, and those who do not have access. This divide can be due to various factors, including economic, geographic, age, and educational barriers. Essentially, as illustrated in Figure 5, it’s the difference between the “digitally connected” and the “digitally disconnected.”.

The significance of the digital divide is considerable, impacting billions of people worldwide. It is estimated that a little less than 40% of the world’s population, or roughly 2.9 billion people, had never used the internet (as of 2023). This gap is most pronounced in developing countries, rural areas, and among older populations and economically disadvantaged groups.

The digital divide affects individuals’ ability to access information, education, and job opportunities and impacts their ability to participate in digital economies and the modern social life that the rest of us (i.e., the other side of the divide or the privileged 60%) have become used to. Bridging this divide is crucial for ensuring equitable access to technology and its benefits, fostering social and economic inclusion, and supporting global development goals.

Figure 5 illustrates the digital divide, that is, the gap between individuals with access to modern information and communication technology (ICT), such as the internet, computers, and smartphones, and those who do not have access. (Courtesy: DALL-E)

CHALLENGES WITH LEO SATELLITE SOLUTIONS.

Low-Earth-orbit satellites offer compelling advantages for global internet connectivity, yet they are not without challenges and disadvantages when considered substitutes for cellular and fixed broadband services. These drawbacks underscore the complexities and limitations of deploying LEO satellite technology globally.

The capital investment required and the ongoing costs associated with designing, manufacturing, launching, and maintaining a constellation of LEO satellites are substantial. Despite technological advancements and increased competition driving costs down, the financial barrier to entry remains high. Compared to their geostationary counterparts, the relatively short lifespan of LEO satellites necessitates frequent replacements, further adding to operational expenses.

While LEO satellites offer significantly reduced latency (round trip times, RTT ~ 4 ms) compared to geostationary satellites (RTT ~ 240 ms), they may still face latency and bandwidth limitations, especially as the number of users on the satellite network increases. This can lead to reduced service quality during peak usage times, highlighting the potential for congestion and bandwidth constraints. This is also the reason why the main business model of LEO satellite constellations is primarily to address coverage and needs in rural and remote locations. Alternatively, the LEO satellite business model focuses on low-bandwidth needs such as texting, voice messaging, and low-bandwidth Internet of Things (IoT) services.

Navigating the regulatory and spectrum management landscape presents another challenge for LEO satellite operators. Securing spectrum rights and preventing signal interference requires coordination across multiple jurisdictions, which can complicate deployment efforts and increase the complexity of operations.

The environmental and space traffic concerns associated with deploying large numbers of satellites are significant. The potential for space debris and the sustainability of low Earth orbits are critical issues, with collisions posing risks to other satellites and space missions. Additionally, the environmental impact of frequent rocket launches raises further concerns.

FIXED-WIRELESS ACCESS (FWA) BASED LEO SATELLITE SOLUTIONS.

Using the NewSpace Index database, updated December 2023, there are currently more than 6,463 internet satellites launched, of which 5,650 (~87%) from StarLink, and 40,000+ satellites planned for launch, with SpaceX’s Starlink satellites having 11,908 planned (~30%). More than 45% of the satellites launched and planned support multi-application use cases. Thus internet, together with, for example, IoT (~4%) and/or Direct-2-Device (D2D, ~39%). The D2D share is due to StarLink’s plans to provide services to mobile terminals with their latest satellite constellation. The first six StarLink v2 satellites with direct-to-cellular capability were successfully launched on January 2nd, 2024. Some care should be taken in the share of D2D satellites in the StarLink number as it does not consider the different form factors of the version 2 satellite that do not all include D2D capabilities.

Most LEO satellites, helped by StarLink satellite quantum, operational and planned, support satellite fixed broadband internet services. It is worth noting that the Chinese Guo Wang constellation ranks second in terms of planned LEO satellites, with almost 13,000 planned, rivaling the StarLink constellation. After StarLink and Guo Wang are counted there is only 34% or ca. 16,000 internet satellites left in the planning pool across 30+ satellite companies. While StarLink is privately owned (by Elon Musk), the Guo Wang (國網 ~ “The state network”) constellation is led by China SatNet and created by the SASAC (China’s State-Owned Assets Supervision and Administration Commission). SASAC oversees China’s biggest state-owned enterprises. I expect that such an LEO satellite constellation, which would be the second biggest LEO constellation, as planned by Guo Wang and controlled by the Chinese State, would be of considerable concern to the West due to the possibility of dual-use (i.e., civil & military) of such a constellation.

StarLink coverage as of March 2024 (see StarLink’s availability map) does not provide services in Russia, China, Iran, Iraq, Afghanistan, Venezuela, and Cuba (20% of Earth’s total land base surface area). There are still quite a few countries in Africa and South-East Asia, including India, where regulatory approval remains pending.

Figure 6 NewSpace Index data of commercial satellite constellations in terms of total number of launched and planned (top) per company (or constellation name) and (bottom) per country.

While the term FWA, fixed wireless access, is not traditionally used to describe satellite internet services, the broadband services offered by LEO satellites can be considered a form of “wireless access” since they also provide connectivity without cables or fiber. In essence, LEO satellite broadband is a complementary service to traditional FWA, extending wireless broadband access to locations beyond the reach of terrestrial networks. In the following, I will continue to use the term FWA for the fixed broadband LEO satellite services provided to individual customers, including SMEs. As some of the LEO satellite businesses eventually also might provide direct-to-device (D2D) services to normal terrestrial mobile devices, either on their own acquired cellular spectrum or in partnership with terrestrial cellular operators, the LEO satellite operation (or business architecture) becomes much closer to terrestrial cellular operations.

Figure 7 Illustrating a Non-Terrestrial Network consisting of a Low Earth Orbit (LEO) satellite constellation providing fixed broadband services, such as Fixed Wireless Access, to individual terrestrial users (e.g., Starlink, Kuiper, OneWeb,…). Each hexagon represents a satellite beam inside the larger satellite coverage area. Note that, in general, there will be some coverage overlap between individual satellites, ensuring a continuous service. The operating altitude of an LEO satellite constellation is between 300 and 2,000 km, with most aiming to be at 450 to 550 km altitude. It is assumed that the satellites are interconnected, e.g., laser links. The User Terminal antenna (UT) is dynamically orienting itself after the best line-of-sight (in terms of signal quality) to a satellite within UT’s field-of-view (FoV). The FoV has not been shown in the picture above so as not to overcomplicate the illustration.

Low Earth Orbit (LEO) satellite services like Starlink have emerged to provide fixed broadband internet to individual consumers and small to medium-sized enterprises (SMEs) targeting rural and remote areas often where no other broadband solutions are available or with poor legacy copper- or coax-based infrastructure. These services deploy constellations of satellites orbiting close to Earth to offer high-speed internet with the significant advantage of reaching rural and remote areas where traditional ground-based infrastructure is absent or economically unfeasible.

One of the most significant benefits of LEO satellite broadband is the ability to deliver connectivity with lower latency compared to traditional satellite internet delivered by geosynchronous satellites, enhancing the user experience for real-time applications. The rapid deployment capability of these services also means that areas in dire need of internet access can be connected much quicker than waiting for ground infrastructure development. Additionally, satellite broadband’s reliability is less affected by terrestrial challenges, such as natural disasters that can disrupt other forms of connectivity.

The satellite service comes with its challenges. The cost of user equipment, such as satellite dishes, can be a barrier for some users. So, can the installation process be of the terrestrial satellite dish required to establish the connection to the satellite. Moreover, services might be limited by data caps or experience slower speeds after reaching certain usage thresholds, which can be a drawback for users with high data demands. Weather conditions can also impact the signal quality, particularly at the higher frequencies used by the satellite, albeit to a lesser extent than geostationary satellite services. However, the target areas where the fixed broadband satellite service is most suited are rural and remote areas that either have no terrestrial broadband infrastructure (terrestrial cellular broadband or wired broadband such as coax or fiber)

Beyond Starlink, other providers are venturing into the LEO satellite broadband market. OneWeb is actively developing a constellation to offer internet services worldwide, focusing on communities that are currently underserved by broadband. Telesat Lightspeed is also gearing up to provide broadband services, emphasizing the delivery of high-quality internet to the enterprise and government sectors.

Other LEO satellite businesses, such as AST SpaceMobile and Lynk Mobile, are taking a unique approach by aiming to connect standard mobile phones directly to their satellite network, extending cellular coverage beyond the reach of traditional cell towers. More about that in the section below (see “New Kids on the Block – Direct-to-Devices LEO satellites”).

I have been asked why I appear somewhat dismissive of the Amazon’s Project Kuiper in a previous version of article particular compared to StarLink (I guess). The expressed mission is to “provide broadband services to unserved and underserved consumers, businesses in the United States, …” (FCC 20-102). Project Kuiper plans for a broadband constellation of 3,226 microsatellites at 3 altitudes (i.e., orbital shells) around 600 km providing fixed broadband services in the Ka-band (i.e.,~ 17-30 GHz). In its US-based FCC (Federal Communications Commission) filling and in the subsequent FCC authorization it is clear that the Kuiper constellation primarily targets contiguous coverage of the USA (but mentions that services cannot be provided in the majority of Alaska, … funny I thought that was a good definition of a underserved remote and scarcely populated area?). Amazon has committed to launch 50% (1,618 satellites) of their committed satellites constellation before July 2026 (until now 2+ has been launched) and the remaining 50% before July 2029. There is however far less details on the Kuiper satellite design, than for example is available for the various versions of the StarLink satellites. Given the Kuiper will operate in the Ka-band there may be more frequency bandwidth allocated per beam than possible in the StarLink satellites using the Ku-band for customer device connectivity. However, Ka-band is at a higher frequency which may result in a more compromised signal propagation. In my opinion based on the information from the FCC submissions and correspondence, the Kuiper constellation appear less ambitious compared to StarLink vision, mission and tangible commitment in terms of aggressive launches, very high level of innovation and iterative development on their platform and capabilities in general. This may of course change over time and as more information becomes available on the Amazon’s Project Kuiper.

FWA-based LEO satellite solutions – takeaway:

  • LoS-based and free-space-like signal propagation allows high-frequency signals (i.e., high throughput, capacity, and quality) to provide near-ideal performance only impacted by the distance between the antenna and the ground terminal. Something that is, in general, not possible for a terrestrial-based cellular infrastructure.
  • Provides satellite fixed broadband internet connectivity typically using the Ku-band in geographically isolated locations where terrestrial broadband infrastructure is limited or non-existent.
  • Lower latency (and round trip time) compared to MEO and GEO satellite internet solutions.
  • Current systems are designed to provide broadband internet services in scarcely populated areas and underserved (or unserved) regions where traditional terrestrial-based communications infrastructures are highly uneconomical and/or impractical to deploy.
  • As shown in my previous article (i.e., “Stratospheric Drones: Revolutionizing Terrestrial Rural Broadband from the Skies?”), LEO satellite networks may be an economical interesting alternative to terrestrial rural cellular networks in countries with large scarcely populated rural areas requiring tens of thousands of cellular sites to cover. Hybrid models with LEO satellite FWA-like coverage to individuals in rural areas and with satellite backhaul to major settlements and towns should be considered in large geographies.
  • Resilience to terrestrial disruptions is a key advantage. It ensures functionality even when ground-based infrastructure is disrupted, which is an essential element for maintaining the Business Continuity of an operator’s telecommunications services. Particular hierarchical architectures with for example GEO-satellite, LEO satellite and Earth-based transport infrastructure will result in very high reliability network operations (possibly approaching ultra-high availability, although not with service parity).
  • Current systems are inherently capacity-limited due to their vast coverage areas (i.e., lower performance per unit coverage area). In the peak demand period, they will typically perform worse than terrestrial-based cellular networks (e.g., LTE or 5G).
  • In regions where modern terrestrial cellular and fixed broadband services are already established, satellite broadband may face challenges competing with these potentially cheaper, faster, and more reliable services, which are underpinned by the terrestrial communications infrastructure.
  • It is susceptible to weather conditions, such as heavy rain or snow, which can degrade signal quality. This may impact system capacity and quality, resulting in inconsistent customer experience throughout the year.
  • Must navigate complex regulatory environments in each country, which can affect service availability and lead to delays in service rollout.
  • Depending on the altitude, LEO satellites are typically replaced on a 5—to 7-year cycle due to atmospheric drag (which increases as altitude decreases; thus, the lower the altitude, the shorter a satellite’s life). This ultimately means that any improvements in system capacity and quality will take time to be thoroughly enjoyed by all customers.

SATELLITE BACKHAUL SOLUTIONS.

Figure 8 illustrates the architecture of a Low Earth Orbit (LEO) satellite backhaul system used by providers like OneWeb as well as StarLink with their so-called “Community Gateway”. It showcases the connectivity between terrestrial internet infrastructure (i.e., Satellite Gateways) and satellites in orbit, enabling high-speed data transmission. The network consists of LEO satellites that communicate with each other (inter-satellite Comms) using the Ku and Ka frequency bands. These satellites connect to ground-based satellite gateways (GW), which interface with Points of Presence (PoP) and Internet Exchange Points (IXP), integrating the space-based network with the terrestrial internet (WWW). Note: The indicated speeds and frequency bands (e.g., Ku: 12–18 GHz, Ka: 28–40 GHz) and data speeds illustrate the network’s capabilities.

LEO satellites providing backhaul connectivity, such as shown in Figure 8 above, are extending internet services to the farthest reaches of the globe. These satellites offer many benefits, as already discussed above, in connecting remote, rural, and previously un- and under-served areas with reliable internet services. Many remote regions lack foundational telecom infrastructure, particularly long-haul transport networks needed for carrying traffic away from remote populated areas. Satellite backhauls do not only offer a substantially better financial solution for enhancing internet connectivity to remote areas but are often the only viable solution for connectivity.

Take, for example, Greenland. The world’s largest non-continental island, the size of Western Europe, is characterized by its sparse population and distinct unconnected by road settlement patterns mainly along the West Coast (as well as a couple of settlements on the East Coast), influenced mainly by its vast ice sheets and rugged terrain. With a population of around 56+ thousand, primarily concentrated on the west coast, Greenland’s demographic distribution is spread out over ca. 50+ settlements and about 20 towns. Nuuk, the capital, is the island’s most populous city, housing over 18+ thousand residents and serving as the administrative, economic, and cultural hub. Terrestrial cellular networks serve settlements’ and towns’ communication and internet services needs, with the traffic carried back to the central switching centers by long-haul microwave links, sea cables, and satellite broadband connectivity. Several settlements connectivity needs can only be served by satellite backhaul, e.g., settlements on the East Coast (e.g., Tasiilaq with ca. 2,000 inhabitants and Ittoqqotooormiit (an awesome name!) with around 400+ inhabitants). LEO satellite backhaul solutions serving Satellite-only communities, such as those operated and offered by OneWeb (Eutelsat), could provide a backhaul transport solution that would match FWA latency specifications due to better (round trip time) performance than that of a GEO satellite backhaul solution.

It should also be clear that remote satellite-only settlements and towns may have communications service needs and demand that a localized 4G (or 5G) terrestrial cellular network with a satellite backhaul can serve much better than, for example, relying on individual ad-hoc connectivity solution from for example Starlink. When the area’s total bandwidth demand exceeds the capacity of an FWA satellite service, a localized terrestrial network solution with a satellite backhaul is, in general, better.

The LEO satellites should offer significantly reduced latency compared to their geostationary counterparts due to their closer proximity to the Earth. This reduction in delay is essential for a wide range of real-time applications and services, from adhering to modern radio access (e.g., 4G and 5G) requirements, VoIP, and online gaming to critical financial transactions, enhancing the user experience and broadening the scope of possible services and business.

Among the leading LEO satellite constellations providing backhaul solutions today are SpaceX’s Starlink (via their community gateway), aiming to deliver high-speed internet globally with a preference of direct to consumer connectivity; OneWeb, focusing on internet services for businesses and communities in remote areas; Telesat’s Lightspeed, designed to offer secure and reliable connectivity; and Amazon’s Project Kuiper, which plans to deploy thousands of satellites to provide broadband to unserved and underserved communities worldwide.

Satellite backhaul solutions – takeaway:

  • Satellite-backhaul solutions are excellent, cost-effective solution for providing an existing isolated cellular (and fixed access) network with high-bandwidth connectivity to the Internet (such as in remote and deep rural areas).
  • LEO satellites can reduce the need for extensive and very costly ground-based infrastructure by serving as a backhaul solution. For some areas, such as Greenland, the Sahara, or the Brazilian rainforest, it may not be practical or economical to connect by terrestrial-based transmission (e.g., long-haul microwave links or backbone & backhaul fiber) to remote settlements or towns.
  • An LEO-based backhaul solution supports applications and radio access technologies requiring a very low round trip time scale (RTT<50 ms) than is possible with a GEO-based satellite backhaul. However, the optimum RTT will depend on where the LEO satellite ground gateway connects to the internet service provider and how low the RTT can be.
  • The collaborative nature of a satellite-backhaul solution allows the terrestrial operator to focus on and have full control of all its customers’ network experiences, as well as optimize the traffic within its own network infrastructure.
  • LEO satellite backhaul solutions can significantly boost network resilience and availability, providing a secure and reliable connectivity solution.
  • Satellite-backhaul solutions require local ground-based satellite transmission capabilities (e.g., a satellite ground station).
  • The operator should consider that at a certain threshold of low population density, direct-to-consumer satellite services like Starlink might be more economical than constructing a local telecom network that relies on satellite backhaul (see above section on “Fixed Wireless Access (FWA) based LEO satellite solutions”).
  • Satellite backhaul providers require regulatory permits to offer backhaul services. These permits are necessary for several reasons, including the use of radio frequency spectrum, operation of satellite ground stations, and provision of telecommunications services within various jurisdictions.
  • The Satellite life-time in orbit is between 5 to 7 years depending on the LEO altitude. A MEO satellite (2 to 36 thousand km altitude) last between 10 to 20 years (GEO). This also dictates the modernization and upgrade cycle as well as timing of your ROI investment case and refinancing needs.

NEW KIDS ON THE BLOCK – DIRECT-TO-DEVICE LEO SATELLITES.

A recent X-exchange (from March 2nd):

Elon Musk: “SpaceX just achieved peak download speed of 17 Mb/s from a satellite direct to unmodified Samsung Android Phone.” (note: the speed correspond to a spectral efficiency of ~3.4 Mbps/MHz/beam).

Reply from user: “That’s incredible … Fixed wireless networks need to be looking over their shoulders?”

Elon Musk: “No, because this is the current peak speed per beam and the beams are large, so this system is only effective where there is no existing cellular service. This services works in partnership with wireless providers, like what @SpaceX and @TMobile announced.”

Figure 9 illustrating a LEO satellite direct-to-device communication in a remote areas without any terrestrially-based communications infrastructure. Satellite being the only means of communications either by a normal mobile device or by classical satphone. (Courtesy: DALL-E).

Low Earth Orbit (LEO) Satellite Direct-to-Device technology enables direct communication between satellites in orbit and standard mobile devices, such as smartphones and tablets, without requiring additional specialized hardware. This technology promises to extend connectivity to remote, rural, and underserved areas globally, where traditional cellular network infrastructure is absent or economically unfeasible to deploy. The system can offer lower latency communication by leveraging LEO satellites, which orbit closer to Earth than geostationary satellites, making it more practical for everyday use. The round trip time (RTT), the time it takes the for the signal to travel from the satellite to the mobile device and back, is ca. 4 milliseconds for a LEO satellite at 550 km compared to ca. 240 milliseconds for a geosynchronous satellite (at 36 thousand kilometers altitude).

The key advantage of a satellite in low Earth orbit is that the likelihood of a line-of-sight to a point on the ground is very high compared to establishing a line-of-sight for terrestrial cellular coverage that, in general, would be very low. In other words, the cellular signal propagation from a LEO satellite closely approximates that of free space. Thus, all the various environmental signal loss factors we must consider for a standard terrestrial-based mobile network do not apply to our satellite. In other, more simplistic words, the signal propagation directly from the satellite to the mobile device is less compromised than it typically would be from a terrestrial cellular tower to the same mobile device. The difference between free-space propagation, which considers only distance and frequency, and the terrestrial signal propagation models, which quantifies all the gains and losses experienced by a terrestrial cellular signal, is very substantial and in favor of free-space propagation.  As our Earth-bound cellular intuition of signal propagation often gets in the way of understanding the signal propagation from a satellite (or antenna in the sky in general), I recommend writing down the math using the formula of free space propagation loss and comparing this with terrestrial cellular link budget models, such as for example the COST 231-Hata Model (relatively simple) or the more recent 3GPP TR 38.901 Model (complex). In rural and sub-urban areas, depending on the environment, in-door coverage may be marginally worse, fairly similar, or even better than from terrestrial cell tower at a distance. This applies to both the uplink and downlink communications channel between the mobile device and the LEO satellite, and is also the reason why higher frequency (with higher frequency bandwidths available) use on LEO satellites can work better than in a terrestrial cellular network.

However, despite its potential to dramatically expand coverage, after all that is what satellites do, LEO Satellite Direct-to-Device technology is not a replacement for terrestrial cellular services and terrestrial communications infrastructures for several reasons: (a) Although the spectral efficiency can be excellent, the frequency bandwidth (in MHz) and data speeds (in Mbps) available through satellite connections are typically lower than those provided by ground-based cellular networks, limiting its use for high-bandwidth applications. (b) The satellite-based D2D services are, in general, capacity-limited and might not be able to handle higher user density typical for urban areas as efficiently as terrestrial networks, which are designed to accommodate large numbers of users through dense deployment of cell towers. (c) Environmental factors like buildings or bad weather can more significantly impact satellite communications’ reliability and quality than terrestrial services. (d) A satellite D2D service requires regulatory approval (per country), as the D2D frequency typically will be limited to terrestrial cellular services and will have to be coordinated and managed with any terrestrial use to avoid service degradation (or disruption) for customers using terrestrial cellular services also using the frequency. The satellites will have to be able to switch off their D2D service when the satellite covers jurisdictions that have not provided approval or where the relevant frequency/frequencies are in use terrestrially.

Using the NewSpace Index database, updated December 2023, there are current more than 8,000 Direct-to Device (D2D), or Direct-2-Cell (D2C), satellites planned for launch, with SpaceX’s Starlink v2 having 7,500 planned. The rest, 795 satellites, are distributed on 6 other satellite operators (e.g. AST Mobile, Sateliot (Spain), Inmarsat (HEO-orbit), Lynk,…). If we look at satellites designed for IoT connectivity we get in total 5,302, with 4,739 (not including StarLink) still planned, distributed out over 50+ satellite operators. The average IoT satellite constellation including what is currently planned is ~95 satellites with the majority targeted for LEO. The the satellite operators included in the 50+ count have confirmed funding with a minimum amount of US$2 billion (half of the operators have only funding confirmed without an amount). About 2,937 (435 launched) satellites are being planned to only serve IoT markets (note: I think this seems a bit excessive). With Swarm Technologies, a SpaceX subsidiary rank number 1 in terms of both launched and planned satellites. Swarm Technologies having launched at least 189 CubeSats (e.g., both 0.25U and 1U types) and have planned an addition 150. The second ranked IoT-only operator is Orbcomm with 51 satellites launched and an additional 52 planned. The average launched of the remaining IoT specific satellites operators are 5 with on average planning to launch 55 (over 42 constellations).

There are also 3 satellite operators (i.e., Chinese-based Galaxy Space: 1,000 LEO-sats; US-based Mangata Networks: 791 MEO/HEO-sats, and US-based Omnispace: 200 LEO?-sats) that have planned a total of 2,000 satellites to support 5G applications with their satellite solutions and one operator (i.e., Hanwha Systems) has planned 2,000 LEO satellites for 6G.

The emergence of LEO satellite direct-to-device (D2D) services, as depicted in the Figure 10 below, is at the forefront of satellite communication innovations, offering a direct line of connectivity between devices that bypasses the need for traditional cellular-based ground-based network infrastructure (e.g., cell towers). This approach benefits from the relatively short distance of hundreds of kilometers between LEO satellites and the Earth, reducing communication latency and broadening bandwidth capabilities compared to their geostationary counterparts. One of the key advantages of LEO D2D services is their ability to provide global coverage with an extensive number of satellites, i.e., in their 100s to 1000s depending the targeted quality of service, to support the services, ensuring that even the most remote and underserved areas have access to reliable communication channels. They are also critical in disaster resilience, maintaining communications when terrestrial networks fail due to emergencies or natural disasters.

Figure 10 This schematic presents the network architecture for satellite-based direct-to-device (D2D) communication facilitated by Low Earth Orbit (LEO) satellites, exemplified by collaborations like Starlink and T-Mobile US, Lynk Mobile, and AST Space Mobile. It illustrates how satellites in LEO enable direct connectivity between user equipment (UE), such as standard mobile devices and IoT (Internet of Things) devices, using terrestrial cellular frequencies and VHF/UHF bands. The system also shows inter-satellite links operating in the Ka-band for seamless network integration, with satellite gateways (GW) linking the space-based network to ground infrastructure, including Points of Presence (PoP) and Internet Exchange Points (IXP), which connect to the wider internet (WWW). This architecture supports innovative services like Omnispace and Astrocast, offering LEO satellite IoT connectivity. The network could be particularly crucial for defense and special operations in remote and challenging environments, such as the deserts or the Arctic regions of Greenland, where terrestrial networks are unavailable. As an example shown here, using regular terrestrial cellular frequencies in both downlink (~300 MHz to 7 GHz) and uplinks (900 MHz or lower to 2.1 GHz) ensures robust and versatile communication capabilities in diverse operational contexts.

While the majority of the 5,000+ Starlink constellation is 13 GHz (Ku-band), at the beginning of 2024, SpaceX launched a few 2nd generation Starlink satellites that support direct connections from the satellite to a normal cellular device (e.g., smartphone), using 5 MHz of T-Mobile USA’s PCS band (1900 MHz). The targeted consumer service, as expressed by T-Mobile USA, provides texting capabilities across the USA for areas with no or poor existing cellular coverage. This is fairly similar to services at similar cellular coverage areas presently offered by, for example, AST SpaceMobileOmniSpace, and Lynk Global LEO satellite services with reported maximum downlink speed approaching 20 Mbps. The so-called Direct-2-Device, where the device is a normal smartphone without satellite connectivity functionality, is expected to develop rapidly over the next 10 years and continue to increase the supported user speeds (i.e., utilized terrestrial cellular spectrum) and system capacity in terms of smaller coverage areas and higher number of satellite beams.

Table 1 below provides an overview of the top 13 LEO satellite constellations targeting (fixed) internet services (e.g., Ku band), IoT and M2M services, and Direct-to-Device (or Direct-to-Cell, D2C) services. The data has been compiled from the NewSpace Index website, which should be with data as of 31st of December 2023. The Top-satellite constellation rank has been based on the number of launched satellites until the end of 2023. Two additional Direct-2-Cell (D2C or Direct-to-Device, D2D) LEO satellite constellations are planned for 2024-2025. One is SpaceX Starlink 2nd generation, which launched at the beginning of 2024, using T-Mobile USA’s PCS Band to connect (D2D) to normal terrestrial cellular handsets. The other D2D (D2C) service is Inmarsat’s Orchestra satellite constellation based on L-band (for mobile terrestrial services) and Ka for fixed broadband services. One new constellation (Mangata Networks, see also the NewSpace constellation information) targeting 5G services. With two 5G constellations already launched, i.e., Galaxy Space (Yinhe) launched 8 LEO satellites, 1,000 planned using Q- and V-bands (i.e., not a D2D cellular 5G service), and OmniSpace launched two satellites and appear to have planned a total of 200 satellites. Moreover, currently, there is one planned constellation targeting 6G by the South Korean Hanwha Group (a bit premature, but interesting to follow nevertheless) with 2,000 6G (LEO) satellites planned.

Most currently launched and planned satellite constellations offering (or plan to provide) Direct-2-Cell services, including IoT and M2M, are designed for low-frequency bandwidth services that are unlikely to compete with terrestrial cellular networks’ quality of service where reasonable good coverage (or better) exists.

Table 1 An overview of the Top-14 LEO satellite constellations targeting (fixed) internet services (e.g., Ku band), IoT and M2M services, and Direct-to-Device (or direct-to-cell) services. The data has been compiled from the NewSpace Index website, which should be with data as of 31st of December 2023.

The deployment of LEO D2D services also navigates a complicated regulatory landscape, with the need for harmonized spectrum allocation across different regions. Managing interference with terrestrial cellular networks and other satellite operations is another interesting challenge albeit complex aspect, requiring sophisticated solutions to ensure signal integrity. Moreover, despite the cost-effectiveness of LEO satellites in terms of launch and operation, establishing a full-fledged network for D2D services demands substantial initial investment, covering satellite development, launch, and the setup of supporting ground infrastructure.

LEO satellites with D2D-based capabilities – takeaway:

  • Provides lower-bandwidth services (e.g., GPRS/EDGE/HSDPA-like) where no existing terrestrial cellular service is present.
  • (Re-)use on Satellite of the terrestrial cellular spectrum.
  • D2D-based satellite services may become crucial in business continuity scenarios, providing redundancy and increased service availability to existing terrestrial cellular networks. This is particularly essential as a remedy for emergency response personnel in case terrestrial networks are not functional. Limited capacity (due to little assigned frequency bandwidth) over a large coverage area serving rural and remote areas with little or no cellular infrastructure.
  • Securing regulatory approval for satellite services over independent jurisdictions is a complex and critical task for any operator looking to provide global or regional satellite-based communications. The satellite operator may have to switch off transmission over jurisdictions where no permission has been granted.
  • If the spectrum is also deployed on the ground, satellite use of it must be managed and coordinated (due to interference) with the terrestrial cellular networks.
  • Require lowly or non-utilized cellular spectrum in the terrestrial operator’s spectrum portfolio.
  • D2D-based communications require a more complex and sophisticated satellite design, including the satellite antenna resulting in higher manufacturing and launch cost.
  • The IoT-only commercial satellite constellation “space” is crowded with a total of 44 constellations (note: a few operators have several constellations). I assume that many of those plans will eventually not be realized. Note that SpaceX Swarm Technology is leading and in terms of total numbers (available in the NewSpace Index) database will remain a leader from the shear amount of satellites once their plan has been realized. I expect we will see a Chinese constellation in this space as well unless the capability will be built into the Guo Wang constellation.
  • The Satellite life-time in orbit is between 5 to 7 years depending on the altitude. This timeline also dictates the modernization and upgrade cycle as well as timing of your ROI investment and refinancing needs.
  • Today’s D2D satellite systems are frequency-bandwidth limited. However, if so designed, satellites could provide a frequency asymmetric satellite-to-device connection. For instance, the downlink from the satellite to the device could utilize a high frequency (not used in the targeted rural or remote area) and a larger bandwidth, while the uplink communication between the terrestrial device and the LEO satellite could use a sufficiently lower frequency and smaller frequency bandwidth.

MAKERS OF SATELLITES.

In the rapidly evolving space industry, a diverse array of companies specializes in manufacturing satellites for Low Earth Orbit (LEO), ranging from small CubeSats to larger satellites for constellations similar to those used by OneWeb (UK) and Starlink (USA). Among these, smaller companies like NanoAvionics (Lithuania) and Tyvak Nano-Satellite Systems (USA) have carved out niches by focusing on modular and cost-efficient small satellite platforms typically below 25 kg. NanoAvionics is renowned for its flexible mission support, offering everything from design to operation services for CubeSats (e.g., 1U, 3U, 6U) and larger small satellites (100+ kg). Similarly, Tyvak excels in providing custom-made solutions for nano-satellites and CubeSats, catering to specific mission needs with a comprehensive suite of services, including design, manufacturing, and testing.

UK-based Surrey Satellite Technology Limited (SSTL) stands out for its innovative approach to small, cost-effective satellites for various applications, with cost-effectiveness in achieving the desired system’s performance, reliability, and mission objectives at a lower cost than traditional satellite projects that easily runs into USD 100s of million. SSTL’s commitment to delivering satellites that balance performance and budget has made it a popular satellite manufacturer globally.

On the larger end of the spectrum, companies like SpaceX (USA) and Thales Alenia Space (France-Italy) are making significant strides in satellite manufacturing at scale. SpaceX has ventured beyond its foundational launch services to produce thousands of small satellites (250+ kg) for its Starlink broadband constellation, which comprises 5,700+ LEO satellites, showcasing mass satellite production. Thales Alenia Space offers reliable satellite platforms and payload integration services for LEO constellation projects.

With their extensive expertise in aerospace and defense, Lockheed Martin Space (USA) and Northrop Grumman (USA) produce various satellite systems suitable for commercial, military, and scientific missions. Their ability to support large-scale satellite constellation projects from design to launch demonstrates high expertise and reliability. Similarly, aerospace giants Airbus Defense and Space (EU) and Boeing Defense, Space & Security (USA) offer comprehensive satellite solutions, including designing and manufacturing small satellites for LEO. Their involvement in high-profile projects highlights their capacity to deliver advanced satellite systems for a wide range of use cases.

Together, these companies, from smaller specialized firms to global aerospace leaders, play crucial roles in the satellite manufacturing industry. They enable a wide array of LEO missions, catering to the burgeoning demand for satellite services across telecommunications, Earth observation, and beyond, thus facilitating access to space for diverse clients and applications.

ECONOMICS.

Before going into details, let’s spend some time on an example illustrating the basic components required for building a satellite and getting it to launch. Here, I point at a super cool alternative to the above-mentioned companies, the USA-based startup Apex, co-founded by CTO Max Benassi (ex-SpaceX and Astra) and CEO Ian Cinnamon. To get an impression of the macro-components of a satellite system, I recommend checking out the Apex webpage and “playing” with their satellite configurator. The basic package comes at a price tag of USD 3.2 million and a 9-month delivery window. It includes a 100 kg satellite bus platform, a power system, a communication system based on X-band (8 – 12 GHz), and a guidance, navigation, and control package. The basic package does not include a solar array drive assembly (SADA), which plays a critical role in the operation of satellites by ensuring that the satellite’s solar panels are optimally oriented toward the Sun. Adding the SADA brings with it an additional USD 500 thousand. Also, the propulsion mechanism (e.g., chemical or electric; in general, there are more possibilities) is not provided (+ USD 450 thousand), nor are any services included (e.g., payload & launch vehicle integration and testing, USD 575 thousand), including SADAs, propulsion, and services, Apex will have a satellite launch ready for an amount of close to USD 4.8 million.

However, we are not done. The above solution still needs to include the so-called payload, which relates to the equipment or instruments required to perform the LEO satellite mission (e.g., broadband communications services), the actual satellite launch itself, and the operational aspects of a successful post-launch (i.e., ground infrastructure and operation center(s)).

Let’s take SpaceX’s Starlink satellite as an example illustrating mission and payload more clearly. The Starlink satellite’s primary mission is to provide fixed-wireless access broadband internet to an Earth-based fixed antenna using. The Starlink payload primarily consists of advanced broadband internet transmission equipment designed to provide high-speed internet access across the globe. This includes phased-array antennas for communication with user terminals on the ground, high-frequency radio transceivers to facilitate data transmission, and inter-satellite links allowing satellites to communicate in orbit, enhancing network coverage and data throughput.

The economical aspects of launching a Low Earth Orbit (LEO) satellite project span a broad spectrum of costs from the initial concept phase to deployment and operational management. These projects commence with research and development, where significant investments are made in designengineering, and the iterative process of prototyping and testing to ensure the satellite meets its intended performance and reliability standards in harsh space conditions (e.g., vacuum, extreme temperature variations, radiation, solar flares, high-velocity impacts with micrometeoroids and man-made space debris, erosion, …).

Manufacturing the satellite involves additional expenses, including procuring high-quality components that can withstand space conditions and assembling and integrating the satellite bus with its mission-specific payload. Ensuring the highest quality standards throughout this process is crucial to minimizing the risk of in-orbit failure, which can substantially increase project costs. The payload should be seen as the heart of the satellite’s mission. It could be a set of scientific instruments for measuring atmospheric data, optical sensors for imaging, transponders for communication, or any other equipment designed to fulfill the satellite’s specific objectives. The payload will vary greatly depending on the mission, whether for Earth observation, scientific research, navigation, or telecommunications.

Of course, there are many other types and more affordable options for LEO satellites than a Starlink-like one (although we should also not ignore achievements of SpaceX and learn from them as much as possible). As seen from Table 1, we have a range of substantially smaller satellite types or form factors. The 1U (i.e., one unit) CubeSat is a satellite with a form factor of 10x10x11.35 cm3 and weighs no more than 1.33 kilograms. A rough cost range for manufacturing a 1U CubeSat could be from USD 50 to 100+ thousand depending on mission complexity and payload components (e.g., commercial-off-the-shelf or application or mission-specific design). The range includes considering the costs associated with the satellite’s design, components, assembly, testing, and initial integration efforts. The cost range, however, does not include other significant costs associated with satellite missions, such as launch services, ground station operations, mission control, and insurance, which is likely to (significantly) increase the total project cost. Furthermore, we have additional form factors, such as 3U CubeSat (10x10x34.05 cm3, <4 kg), manufacturing cost in the range of USD 100 to 500+ thousand, 6U CubeSat (20x10x34 cm3, <12 kg), that can carry more complex payload solutions than the smaller 1U and 3U, with the manufacturing cost in the range of USD 200 thousand to USD 1+ million and 12U satellites (20x20x34 cm3, <24 kg) that again support complex payload solutions and in general will be significantly more expensive to manufacture.

Securing a launch vehicle is one of the most significant expenditures in a satellite project. This cost not only includes the price of the rocket and launch itself but also encompasses integration, pre-launch services, and satellite transportation to the launch site. Beyond the launch, establishing and maintaining the ground segment infrastructure, such as ground stations and a mission control center, is essential for successful satellite communication and operation. These facilities enable ongoing tracking, telemetry, and command operations, as well as the processing and management of the data collected by the satellite.

The SpaceX Falcon rocket is used extensively by other satellite businesses (see above Table 1) as well as by SpaceX for their own Starlink constellation network. The rocket has a payload capability of ca. 23 thousand kg and a volume handling capacity of approximately 300 cubic meters. SpaceX has launched around 60 Starlink satellites per Falcon 9 mission for the first-generation satellites. The launch cost per 1st generation satellite would then be around USD 1 million per satellite using the previously quoted USD 62 million (2018 figure) for a Falcon 9 launch. The second-generation Starlink satellites are substantially more advanced compared to the 1st generation. They are also heavier, weighing around a thousand kilograms. A Falcon 9 would only be able to launch around 20 generation 2 satellites (only considering the weight limitation), while a Falcon Heavy could lift ca. 60 2nd gen. satellites but also at a higher price point of USD 90 million (2018 figure). Thus the launch cost per satellite would be between USD 1.5 million using Falcon Heavy and USD 3.1 million using Falcon 9. Although the launch cost is based on price figures from 2018, the expected efficiency gained from re-use may have either kept the cost level or reduced it further as expected, particularly with Falcon Heavy.

Satellite businesses looking to launch small volumes of satellites, such as CubeSats, have a variety of strategies at their disposal to manage launch costs effectively. One widely adopted approach is participating in rideshare missions, where the expenses of a single launch vehicle are shared among multiple payloads, substantially reducing the cost for each operator. This method is particularly attractive due to its cost efficiency and the regularity of missions offered by, for example, SpaceX. Prices for rideshare missions can start from as low as a few thousand dollars for very small payloads (like CubeSats) to several hundred thousand dollars for larger small satellites. For example, SpaceX advertises rideshare prices starting at $1 million for payloads up to 200 kg. Alternatively, dedicated small launcher services cater specifically to the needs of small satellite operators, offering more tailored launch options in terms of timing and desired orbit. Companies such as Rocket Lab (USA) and Astra (USA) launch services have emerged, providing flexibility that rideshare missions might not, although at a slightly higher cost. However, these costs remain significantly lower than arranging a dedicated launch on a larger vehicle. For example, Rocket Lab’s Electron rocket, specializing in launching small satellites, offers dedicated launches with prices starting around USD 7 million for the entire launch vehicle carrying up to 300 kg. Astra has reported prices in the range of USD 2.5 million for a dedicated LEO launch with their (discontinued) Rocket 3 with payloads of up to 150 kg. The cost for individual small satellites will depend on their share of the payload mass and the specific mission requirements.

Satellite ground stations, which consist of arrays of phased-array antennas, are critical for managing the satellite constellation, routing internet traffic, and providing users with access to the satellite network. These stations are strategically located to maximize coverage and minimize latency, ensuring that at least one ground station is within the line of sight of satellites as they orbit the Earth. As of mid-2023, Starlink operated around 150 ground stations worldwide (also called Starlink Gateways), with 64 live and an additional 33 planned in the USA. The cost of constructing a ground station would be between USD 300 thousand to half a million not including the physical access point, also called the point-of-presence (PoP), and transport infrastructure connecting the PoP (and gateway) to the internet exchange where we find the internet service providers (ISPs) and the content delivery networks (CDNs). The Pop may add another USD 100 to 200 thousand to the ground infrastructure unit cost. The transport cost from the gateway to the Internet exchange can vary a lot depending on the gateway’s location.

Insurance is a critical component of the financial planning for a satellite project, covering risks associated with both the launch phase and the satellite’s operational period in orbit. These insurances are, in general, running at between 5% to 20% of the total project cost depending on the satellite value, the track record of the launch vehicle, mission complexity, and duration (i.e., typically 5 – 7 years for a LEO satellite at 500 km) and so forth. Insurance could be broken up into launch insurance and insurance covering the satellite once it is in orbit.

Operational costs, the Opex, include the day-to-day expenses of running the satellite, from staffing and technical support to ground station usage fees.

Regulatory and licensing fees, including frequency allocation and orbital slot registration, ensure the satellite operates without interfering with other space assets. Finally, at the end of the satellite’s operational life, costs associated with safely deorbiting the satellite are incurred to comply with space debris mitigation guidelines and ensure a responsible conclusion to the mission.

The total cost of an LEO satellite project can vary widely, influenced by the satellite’s complexity, mission goals, and lifespan. Effective project management and strategic decision-making are crucial to navigating these expenses, optimizing the project’s budget, and achieving mission success.

Figure 11 illustrates an LEO CubeSat orbiting above the Earth, capturing the satellite’s compact design and its role in modern space exploration and technology demonstration. Note that the CubeSat design comes in several standardized dimensions, with the reference design, also called 1U, being almost 1 thousandth of a cubic meter and weighing less than 1.33 kg. More advanced CubeSat satellites would typically be 6U or higher.

CubeSats (e.g., 1U, 3U, 6U, 12U):

  • Manufacturing Cost: Ranges from USD 50,000 for a simple 1U CubeSat to over USD 1 million for a more complex missions supported by 6U (or higher) CubeSat with advanced payloads (and 12U may again amount to several million US dollars).
  • Launch Cost: This can vary significantly depending on the launch provider and the rideshare opportunities, ranging from a few thousand dollars for a 1U CubeSat on a rideshare mission to several million dollars for a dedicated launch of larger CubeSats or small satellites.
  • Operational Costs: Ground station services, mission control, and data handling can add tens to hundreds of thousands of dollars annually, depending on the mission’s complexity and duration.

Small Satellites (25 kg up to 500 kg):

  • Manufacturing Cost: Ranges from USD 500,000 to over 10 million, depending on the satellite’s size, complexity, and payload requirements.
  • Launch Cost: While rideshare missions can reduce costs, dedicated launches for small satellites can range from USD 10 million to 62 million (e.g., Falcon 9) and beyond (e.g., USD 90 million for Falcon Heavy).
  • Operational Costs: These are similar to CubeSats, but potentially higher due to the satellite’s larger size and more complex mission requirements, reaching several hundred thousand to over a million dollars annually.

The range for the total project cost of a LEO satellite:

Given these considerations, the total cost range for a LEO satellite project can vary from as low as a few hundred thousand dollars for a simple CubeSat project utilizing rideshare opportunities and minimal operational requirements to hundreds of millions of dollars for more complex small satellite missions requiring dedicated launches and extensive operational support.

It is important to note that these are rough estimates, and the actual cost can vary based on specific mission requirements, technological advancements, and market conditions.

CAPACITY AND QUALITY

Figure 12 Satellite-based cellular capacity, or quality measured, by the unit or total throughput in Mbps is approximately driven by the amount of spectrum (in MHz) times the effective spectral efficiency (in Mbps/MHz/units) times the number of satellite beams resulting in cells on the ground.

The overall capacity and quality of satellite communication systems, given in Mbps, is on a high level, the product of three key factors: (i) the amount of frequency bandwidth in MHz allocated to the satellite operations multiplied by (ii) the effective spectral efficiency in Mbps per MHz over a unit satellite-beam coverage area multiplied by (iii) the number of satellite beams that provide the resulting terrestrial cell coverage. Thus, in other words:

Satellite Capacity (in Mbps) =
Frequency Bandwidth in MHz ×
Effective Spectral Efficiency in Mbps/MHz/Beam ×
Number of Beams (or Cells)

Consider a satellite system supporting 8 beams (and thus an equivalent of terrestrial coverage cells), each with 250 MHz allocated within the same spectral frequency range, can efficiently support ca. 680 Mbps per beam. This is achieved with an antenna setup that effectively provides a spectral efficiency of ~2.7 Mbps/MHz/cell (or beam) in the downlink (i.e., from the satellite to the ground). Moreover, the satellite typically will have another frequency and antenna configuration that establishes a robust connection to the ground station that connects to the internet via, for example, third-party internet service providers. The 680 Mbps is then shared among users that are within the satellite beam coverage, e.g., if you have 100 customers demanding a service, the speed each would experience on average would be around 7 Mbps. This may not seem very impressive compared to the cellular speeds we are used to getting with an LTE or 5G terrestrial cellular service. However, such speeds are, of course, much better than having no means of connecting to the internet.

Higher frequencies (i.e., in the GHz range) used to provide terrestrial cellular broadband services are in general quiet sensitive to the terrestrial environment and non-LoS propagation. It is a basic principle of physics that signal propagation characteristics, including the range and penetration capabilities of an electromagnetic waves, is inversely related to their frequency. Vegetation and terrain becomes an increasingly critical factor to consider in higher frequency propagation and the resulting quality of coverage. For example trees, forests, and other dense foliage can absorb and scatter radio waves, attenuating signals. The type and density of vegetation, along with seasonal changes like foliage density in summer versus winter, can significantly impact signal strength. Terrains often include varied topographies such as housing, hills, valleys, and flat plains, each affecting signal reach differently. For instance, housing, hilly or mountainous areas may cause signal shadowing and reflection, while flat terrains might offer less obstruction, enabling signals to travel further. Cellular mobile operators tend to like high frequencies (GHz) for cellular broadband services as it is possible to get substantially more system throughput in bits per second available to deliver to our demanding customers than at frequencies in the MHz range. As can be observed in Figure 12 above, we see that the frequency bandwidth is a multiplier for the satellite capacity and quality. Cellular mobile operators tend to “dislike” higher frequencies because of their poorer propagation conditions in their terrestrially based cellular networks resulting in the need for increased site densification at a significant incremental capital expense.

The key advantage of a LEO satellite is that the likelihood of a line-of-sight to a point on the ground is very high compared to establishing a line-of-sight for terrestrial cellular coverage that, in general, would be very low. In other words, the cellular signal propagation from an satellite closely approximates that of free space. Thus, all the various environmental signal loss factors we must consider for a standard terrestrial-based mobile network do not apply to our satellite having only to overcome the distance from the satellite antenna to the ground.

Let us first look at the satellite frequency component of the above satellite capacity, and quality, formula:

FREQUENCY SPECTRUM FOR SATELLITES.

The satellite frequency spectrum encompasses a range of electromagnetic frequencies allocated specifically for satellite communication. These frequencies are divided into bands, commonly known as L-band (e.g., mobile broadband), S-band (e.g., mobile broadband), C-band, X-band (e.g., mainly used by military), Ku-band (e.g., fixed broadband), Ka-band (e.g., fixed broadband), and V-band. Each serves different satellite applications due to its distinct propagation characteristics and capabilities. The spectrum bandwidth used by satellites refers to the width of the frequency range that a satellite system is licensed to use for transmitting and receiving signals.

Careful management of satellite spectrum bandwidth is critical to prevent interference with terrestrial communications systems. Since both satellite and terrestrial systems can operate on similar frequency ranges, there is a potential for crossover interference, which can degrade the performance of both systems. This is particularly important for bands like C-band and Ku-band, which are also used for terrestrial cellular networks and other applications like broadcasting.

Using the same spectrum for both satellite and terrestrial cellular coverage within the same geographical area is challenging due to the risk of interference. Satellites transmit signals over vast areas, and if those signals are on the same frequency as terrestrial cellular systems, they can overpower the local ground-based signals, causing reception issues for users on the ground. Conversely, the uplink signals from terrestrial sources can interfere with the satellite’s ability to receive communications from its service area.

Regulatory bodies such as the International Telecommunication Union (ITU) are crucial in mitigating these interference issues. They coordinate the allocation of frequency bands and establish regulations that govern their use. This includes defining geographical zones where certain frequencies may be used exclusively for either terrestrial or satellite services, as well as setting limits on signal power levels to minimize the chance of interference. Additionally, technology solutions like advanced filtering, beam shaping, and polarization techniques are employed to further isolate satellite communications from terrestrial systems, ensuring that both may coexist and operate effectively without mutual disruption.

The International Telecommunication Union (ITU) has designated several frequency bands for Fixed Satellite Services (FSS) and Mobile Satellite Services (MSS) that can be used by satellites operating in Low Earth Orbit (LEO). The specific bands allocated for satellite services, FSS and MSS, are determined by the ITU’s Radio Regulations, which are periodically updated to reflect global telecommunication’s evolving needs and address emerging technologies. Here are some of the key frequency bands commonly considered for FSS and MSS with LEO satellites:

V-Band 40 GHz to 75 GHz (microwave frequency range).
The V-band is appealing for Low Earth Orbit (LEO) satellite constellations designed to provide global broadband internet access. LEO satellites can benefit from the V-band’s capacity to support high data rates, which is essential for serving densely populated areas and delivering competitive internet speeds. The reduced path loss at lower altitudes, compared to GEO, also makes the V-band a viable option for LEO satellites. Due to the higher frequencies offered by V-band it also is significant more sensitive to atmospheric attenuation, (e.g., oxygen absorption around 60 GHz), including rain fade, which is likely to affect signal integrity. This necessitates the development of advanced technologies for adaptive coding and modulation, power amplification, and beamforming to ensure reliable communication under various weather conditions. Several LEO satellite operators have expressed an interest in operationalizing the V-band in their satellite constellations (e.g., StarLink, OneWeb, Kuiper, Lightspeed). This band should be regarded as an emergent LEO frequency band.

Ka-Band 17.7 GHz to 20.2 GHz (Downlink) & 27.5 GHz to 30.0 GHz (Uplink).
The Ka-band offers higher bandwidths, enabling greater data throughput than lower bands. Not surprising this band is favored by high-throughput satellite solutions. It is widely used by fixed satellite services (FSS). This makes it ideal for high-speed internet services. However, it is more susceptible to absorption and scattering by atmospheric particles, including raindrops and snowflakes. This absorption and scattering effect weakens the signal strength when it reaches the receiver. To mitigate rain fade effects in the Ka-band, satellite, and ground equipment must be designed with higher link margins, incorporating more powerful transmitters and more sensitive receivers. Additionally, adaptive modulation and coding techniques can be employed to adjust the signal dynamically in response to changing weather conditions. Overall, the system is more costly and, therefore, primarily used for satellite-to-earth ground station communications and high-performance satellite backhaul solutions.

For example, Starlink and OneWeb use the Ka-band to connect to satellite Earth gateways and point-of-presence, which connect to Internet Exchange and the wider internet. It is worth noticing that the terrestrial 5 G band n256 (26.5 to 29.5 GHz) falls within the Ka-band’s uplink frequency band. Furthermore, SES’s mPower satellites, operating at Middle Earth Orbit (MEO), operate exclusively in this band, providing internet backhaul services.

Ku-Band 12.75 GHz to 13.25 GHz (Downlink) & 14.0 GHz to 14.5 GHz (Uplink).
The Ku-band is widely used for FSS satellite communications, including fixed satellite services, due to its balance between bandwidth availability and susceptibility to rain fade. It is suitable for broadband services, TV broadcasting, and backhaul connections. For example, Starlink and OneWeb satellites are using this band to provide broadband services to earth-based customer terminals.

X-Band 7.25 GHz to 7.75 GHz (Downlink) & 7.9 GHz to 8.4 GHz (Uplink).
The X-band in satellite applications is governed by international agreements and national regulations to prevent interference between different services and to ensure the efficient use of the spectrum. The X-band is extensively used for secure military satellite communications, offering advantages like high data rates and relative resilience to jamming and eavesdropping. It supports a wide range of military applications, including mobile command, control, communications, computer, intelligence, surveillance, and reconnaissance (i.e., C4ISR) operations. Most defense-oriented satellites operate at geostationary orbit, ensuring constant coverage of specific geographic areas (e.g., Airbus Skynet constellations, Spain’s XTAR-EUR, and France’s Syracuse satellites). Most European LEO defense satellites, used primarily for reconnaissance, are fairly old, with more than 15 years since the first launch, and are limited in numbers (i.e., <10). The most recent European LEO satellite system is the French-based Multinational Space-based Imaging System (MUSIS) and Composante Spatiale Optique (CSO), where the first CSO components were launched in 2018. There are few commercial satellites utilizing the X-band.

C-Band 3.7 GHz to 4.2 GHz (Downlink) & 5.925 GHz to 6.425 GHz (Uplink)
C-band is less susceptible to rain fade and is traditionally used for satellite TV broadcasting, maritime, and aviation communications. However, parts of the C-band are also being repurposed for terrestrial 5G networks in some regions, leading to potential conflicts and the need for careful coordination. The C-band is primarily used in geostationary orbit (GEO) rather than Low Earth Orbit (LEO), due to the historical allocation of C-band for fixed satellite services (FSS) and its favorable propagation characteristics. I haven’t really come across any LEO constellation using the C-band. GEO FSS satellite operators using this band extensively are SES (Luxembourg), Intelsat (Luxembourg/USA), Eutelsat (France), Inmarsat (UK), etc..

S-Band 2.0 GHz to 4.0 GHz
S-band is used for various applications, including mobile communications, weather radar, and some types of broadband services. It offers a good compromise between bandwidth and resistance to atmospheric absorption. Both Omnispace (USA) and Globalstar (USA) LEO satellites operate in this band. Omnispace is also interesting as they have expressed intent to have LEO satellites supporting the 5G services in the band n256 (26.5 to 29.5 GHz), which falls within the uplink of the Ka-band.

L-Band 1.0 GHz to 2.0 GHz
L-band is less commonly used for fixed satellite services but is notable for its use in mobile satellite services (MSS), satellite phone communications, and GPS. It provides good coverage and penetration characteristics. Both Lynk Mobile (USA), offering Direct-2-Device, IoT, and M2M services, and Astrocast (Switzerland), with their IoT/M2M services, are examples of LEO satellite businesses operating in this band.

UHF 300 MHz to 3.0 GHz
The UHF band is more widely used for satellite communications, including mobile satellite services (MSS), satellite radio, and some types of broadband data services. It is favored for its relatively good propagation characteristics, including the ability to penetrate buildings and foliage. For example, Fossa Systems LEO pico-satellites (i.e., 1p form-factor) use this frequency for their IoT and M2M communications services.

VHF 30 MHz to 300 MHz

The VHF band is less commonly used in satellite communications for commercial broadband services. Still, it is important for applications such as satellite telemetry, tracking, and control (TT&C) operations and amateur satellite communications. Its use is often limited due to the lower bandwidth available and the higher susceptibility to interference from terrestrial sources. Swarm Technologies (USA and a SpaceX subsidiary) using 137-138 MHz (Downlink) and 148-150 MHz (Uplink). However, it appears that they have stopped taking new devices on their network. Orbcomm (USA) is another example of a satellite service provider using the VHF band for IoT and M2M communications. There is very limited capacity in this band due to many other existing use cases, and LEO satellite companies appear to plan to upgrade to the UHF band or to piggyback on direct-2-cell (or direct-2-device) satellite solutions, enabling LEO satellite communications with 3GPP compatible IoT and M2M devices.

SATELLITE ANTENNAS.

Satellites operating in Geostationary Earth Orbit (GEO), Medium Earth Orbit (MEO), and Low Earth Orbit (LEO) utilize a variety of antenna types tailored to their specific missions, which range from communication and navigation to observation (e.g., signal intelligence). The satellite’s applications influence the selection of an antenna, the characteristics of its orbit, and the coverage area required.

Antenna technology is intrinsically linked to spectral efficiency in satellite communications systems and of course any other wireless systems. Antenna designs influence how effectively a communication system can transmit and receive signals within a given frequency band, which is the essence of spectral efficiency (i.e., how much information per unit time in bits per second can I squeeze through my communications channel).

Thus, advancements in antenna technology are fundamental to improving spectral efficiency, making it a key area of research and development in the quest for more capable and efficient communication systems.

Parabolic dish antennas are prevalent for GEO satellites due to their high gain and narrow beam width, making them ideal for broadcasting and fixed satellite services. These antennas focus a tight beam on specific areas on Earth, enabling strong and direct signals essential for television, internet, and communication services. Horn antennas, while simpler, are sometimes used as feeds for larger parabolic antennas or for telemetry, tracking, and command functions due to their reliability. Additionally, phased array antennas are becoming more common in GEO satellites for their ability to steer beams electronically, offering flexibility in coverage and the capability to handle multiple beams and frequencies simultaneously.

Phased-array antennas are indispensable in for MEO satellites, such as those used in navigation systems like GPS (USA), BeiDou (China), Galileo (European), or GLONASS (Russian). These satellite constellations cover large areas of the Earth’s surface and can adjust beam directions dynamically, a critical feature given the satellites’ movement relative to the Earth. Patch antennas are also widely used in MEO satellites, especially for mobile communication constellations, due to their compact and low-profile design, making them suitable for mobile voice and data communications.

Phased-array antennas are very important for LEO satellites use cases as well, which include broadband communication constellations like Starlink and OneWeb. Their (fast) beam-steering capabilities are essential for maintaining continuous communication with ground stations and user terminals as the satellites quickly traverse the sky. The phased-array antenna also allow for optimizing coverage with both narrow as well as wider field of view (from the perspective of the satellite antenna) that allow the satellite operator to trade-off cell capacity and cell coverage.

Simpler Dipole antennas are employed for more straightforward data relay and telemetry purposes in smaller satellites and CubeSats, where space and power constraints are significant factors. Reflect array antennas, which offer a mix of high gain and beam steering capabilities, are used in specific LEO satellites for communication and observation applications (e.g., for signal intelligence gathering), combining features of both parabolic and phased array antennas.

Mission specific requirements drive the choice of antenna for a satellite. For example, GEO satellites often use high-gain, narrowly focused antennas due to their fixed position relative to the Earth, while MEO and LEO satellites, which move relatively closer to the Earth’s surface, require antennas capable of maintaining stable connections with moving ground terminals or covering large geographical areas.

Advanced antenna technologies such as beamforming, phased-arrays, and Multiple In Multiple Out (MMO) antenna configurations are crucial in managing and utilizing the spectrum more efficiently. They enable precise targeting of radio waves, minimizing interference, and optimizing bandwidth usage. This direct control over the transmission path and signal shape allows more data (bits) to be sent and received within the same spectral space, effectively increasing the communication channel’s capacity. In particular, MIMO antenna configurations and advanced antenna beamforming have enabled terrestrial mobile cellular access technologies (e.g., LTE and 5G) to quantum leap the effective spectral efficiency, broadband speed and capacity orders of magnitude above and beyond older technologies of 2G and 3G. Similar principles are being deployed today in modern advanced communications satellite antennas, providing increased capacity and quality within the satellite cellular coverage area provided by the satellite beam.

Moreover, antenna technology developments like polarization and frequency reuse directly impact a satellite system’s ability to maximize spectral resources. Allowing simultaneous transmissions on the same frequency through different polarizations or spatial separations effectively double the capacity without needing additional spectrum.

WHERE DO WE END UP.

If all current commercial satellite plans were realized, within the next decade, we would have more, possibly substantially more than 65 thousand satellites circling Earth. Today, that number is less than 10 thousand, with more than half that number realized by StarLink’s LEO constellation. Imagine the increase in, and the amount of, space debris circling Earth within the next 10 years. This will likely pose a substantial increase in operational risk for new space missions and will have to be addressed urgently.

Over the next decade, we may have at least 2 major LEO satellite constellations. One from Starlink with an excess of 12 thousand satellites, and one from China, the Guo Wang, the state network, likewise with 12 thousand LEO satellites. One global satellite constellation is from an American-based commercial company; the other is a worldwide satellite constellation representing the Chinese state. It would not be too surprising to see that by 2034, the two satellite constellations will divide Earth in part, being serviced by a commercial satellite constellation (e.g., North America, Europe, parts of the Middle East, some of APAC including India, possibly some parts of Africa). Another part will likely be served by a Chinese-controlled LEO constellation providing satellite broadband service to China, Russia, significant parts of Africa, and parts of APAC.

Over the next decade, satellite services will undergo transformative advancements, reshaping the architecture of global communication infrastructures and significantly impacting various sectors, including broadband internet, global navigation, Earth observation, and beyond. As these services evolve, we should anticipate major leaps in satellite technologies, driven by innovation in propulsion systems, miniaturization of technology, advancements in onboard processing capabilities, increasing use of AI and machine learning leapfrogging satellites operational efficiency and performance, breakthrough in material science reducing weight and increasing packing density, leapfrogs in antenna technology, and last but not least much more efficient use of the radio frequency spectrum. Moreover, we will see the breakthrough innovation that will allow better co-existence and autonomous collaboration of frequency spectrum utilization between non-terrestrial and terrestrial networks reducing the need for much regulatory bureaucracy that might anyway be replaced by decentralized autonomous organizations (DAOs) and smart contracts. This development will be essential as satellite constellations are being integrated into 5G and 6G network architectures as the non-terrestrial network cellular access component. This particular topic, like many in this article, is worth a whole new article on its own.

I expect that over the next 10 years we will see electronically steerable phased-array antennas, as a notable advancement. These would offer increased agility and efficiency in beamforming and signal direction. Their ability to swiftly adjust beams for optimal coverage and connectivity without physical movement makes them perfect for the dynamic nature of Low Earth Orbit (LEO) satellite constellations. This technology will becomes increasingly cost-effective and energy-efficient, enabling widespread deployment across various satellite platforms (not only LEO designs). The advance in phased-array antenna technology will facilitate substantial increase in the satellite system capacity by increasing the number of beams, the variation on beam size (possibly down to a customer ground station level), and support multi-band operations within the same antenna.

Another promising development is the integration of metamaterials in antenna design, which will lead to more compact, flexible, and lightweight antennas. The science of metamaterials is super interesting and relates to manufacturing artificial materials to have properties not found in naturally occurring materials with unique electromagnetic behaviors arising from their internal structure. Metamaterial antennas is going to offer superior performance, including better signal control and reduced interference, which is crucial for maintaining high-quality broadband connections. These materials are also important for substantially reducing the weight of the satellite antenna, while boosting its performance. Thus, the technology will also support bringing the satellite launch cost down dramatically.

Although primarily associated MIMO antennas with terrestrial networks, I would also expect that massive MIMO technology will find applications in satellite broadband systems. Satellite systems, just like ground based cellular networks, can significantly increase their capacity and efficiency by utilizing many antenna elements to simultaneously communicate with multiple ground terminals. This could be particularly transformative for next-generation satellite networks, supporting higher data rates and accommodating more users. The technology will increase the capacity and quality of the satellite system dramatically as it has done on terrestrial cellular networks.

Furthermore, advancements in onboard processing capabilities will allow satellites to perform more complex signal processing tasks directly in space, reducing latency and improving the efficiency of data transmission. Coupled with AI and machine learning algorithms, future satellite antennas could dynamically optimize their operational parameters in real-time, adapting to changes in the network environment and user demand.

Additionally, research into quantum antenna technology may offer breakthroughs in satellite communication, providing unprecedented levels of sensitivity and bandwidth efficiency. Although still early, quantum antennas could revolutionize signal reception and transmission in satellite broadband systems. In the context of LEO satellite systems, I am particularly excited about utilizing the Rydberg Effect to enhance system sensitivity could lead to massive improvements. The heightened sensitivity of Rydberg atoms to electromagnetic fields could be harnessed to develop ultra-sensitive detectors for radio frequency (RF) signals. Such detectors could surpass the performance of traditional semiconductor-based devices in terms of sensitivity and selectivity, enabling satellite systems to detect weaker signals, improve signal-to-noise ratios, and even operate effectively over greater distances or with less power. Furthermore, space could potentially be the near-ideal environment for operationalizing Rydberg antenna and communications systems as space had near-perfect vacuum, very low-temperatures (in Earth shadow at least or with proper thermal management), relatively free of electromagnetic radiation (compared to Earth), as well as its micro-gravity environment that may facilitate long-range “communications” between Rydberg atoms. This particular topic may be further out in the future than “just” a decade from now, although it may also be with satellites we will see the first promising results of this technology.

One key area of development will be the integration of LEO satellite networks with terrestrial 5G and emerging 6G networks, marking a significant step in the evolution of Non-Terrestrial Network (NTN) architectures. This integration promises to deliver seamless, high-speed connectivity across the globe, including in remote and rural areas previously underserved by traditional broadband infrastructure. By complementing terrestrial networks, LEO satellites will help achieve ubiquitous wireless coverage, facilitating a wide range of applications and use cases from high-definition video streaming to real-time IoT data collection.

The convergence of LEO satellite services with 5G and 6G will also spur network management and orchestration innovation. Advanced techniques for managing interference, optimizing handovers between terrestrial and non-terrestrial networks, and efficiently allocating spectral resources will be crucial. It would be odd not to mention it here, so artificial intelligence and machine learning algorithms will, of course, support these efforts, enabling dynamic network adaptation to changing conditions and demands.

Moreover, the next decade will likely see significant improvements in the environmental sustainability of LEO satellite operations. Innovations in satellite design and materials, along with more efficient launch vehicles and end-of-life deorbiting strategies, will help mitigate the challenges of space debris and ensure the long-term viability of LEO satellite constellations.

In the realm of global connectivity, LEO satellites will have bridged the digital divide, offering affordable and accessible internet services to billions of people worldwide unconnected today. In 2023 the estimate is that there are about 3 billion people, almost 40% of all people in the world today, that have never used internet. In the next decade, it must be our ambition that with LEO satellite networks this number is brought down to very near Zero. This will have profound implications for education, healthcare, economic development, and global collaboration.

FURTHER READING.

  1. A. Vanelli-Coralli, N. Chuberre, G. Masini, A. Guidotti, M. El Jaafari, “5G Non-Terrestrial Networks.”, Wiley (2024). A recommended reading for deep diving into NTN networks of satellites, typically the LEO kind, and High-Altitude Platform Systems (HAPS) such as stratospheric drones.
  2. I. del Portillo et al., “A technical comparison of three low earth orbit satellite constellation systems to provide global broadband,” Acta Astronautica, (2019).
  3. Nils Pachler et al., “An Updated Comparison of Four Low Earth Orbit Satellite Constellation Systems to Provide Global Broadband” (2021).
  4. Starlink, “Starlink specifications” (Starlink.com page). The following Wikipedia resource is quite good as well: Starlink.
  5. Quora, “How much does a satellite cost for SpaceX’s Starlink project and what would be the cheapest way to launch it into space?” (June 2023). This link includes a post from Elon Musk commenting on the cost involved in manufacturing the Starlink satellite and the cost of launching SpaceX’s Falcon 9 rocket.
  6. Michael Baylor, “With Block 5, SpaceX to increase launch cadence and lower prices.”, nasaspaceflight.com (May, 2018).
  7. Gwynne Shotwell, TED Talk from May 2018. She quotes here a total of USD 10 billion as a target for the 12,000 satellite network. This is just an amazing visionary talk/discussion about what may happen by 2028 (in 4-5 years ;-).
  8. Juliana Suess, “Guo Wang: China’s Answer to Starlink?”, (May 2023).
  9. Makena Young & Akhil Thadani, “Low Orbit, High Stakes, All-In on the LEO Broadband Competition.”, Center for Strategic & International Studies CSIS, (Dec. 2022).
  10. AST SpaceMobile website: https://ast-science.com/ Constellation Areas: Internet, Direct-to-Cell, Space-Based Cellular Broadband, Satellite-to-Cellphone. 243 LEO satellites planned. 2 launched.
  11. Lynk Global website: https://lynk.world/ (see also FCC Order and Authorization). It should be noted that Lynk can operate within 617 to 960 MHz (Space-to-Earth) and 663 to 915 MHz (Earth-to-Space). However, only outside the USA. Constellation Area: IoT / M2M, Satellite-to-Cellphone, Internet, Direct-to-Cell. 8 LEO satellites out of 10 planned.
  12. Omnispace website: https://omnispace.com/ Constellation Area: IoT / M2M, 5G. Ambition to have the world’s first global 5G non-terrestrial network. Initial support 3GPP-defined Narrow-Band IoT radio interface. Planned 200 LEO and <15 MEO satellites. So far, only 2 satellites have been launched.
  13. NewSpace Index: https://www.newspace.im/ I find this resource to have excellent and up-to-date information on commercial satellite constellations.
  14. R.K. Mailloux, “Phased Array Antenna Handbook, 3rd Edition”, Artech House, (September 2017).
  15. A.K. Singh, M.P. Abegaonkar, and S.K. Koul, “Metamaterials for Antenna Applications”, CRC Press (September 2021).
  16. T.L. Marzetta, E.G. Larsson, H. Yang, and H.Q. Ngo, “Fundamentals of Massive MIMO”, Cambridge University Press, (November 2016).
  17. G.Y. Slepyan, S. Vlasenko, and D. Mogilevtsev, “Quantum Antennas”, arXiv:2206.14065v2, (June 2022).
  18. R. Huntley, “Quantum Rydberg Receiver Shakes Up RF Fundamentals”, EE Times, (January 2022).
  19. Y. Du, N. Cong, X. Wei, X. Zhang, W. Lou, J. He, and R. Yang, “Realization of multiband communications using different Rydberg final states”, AIP Advances, (June 2022). Demonstrating the applicability of the Rydberg effect in digital transceivers in the Ku and Ka bands.

ACKNOWLEDGEMENT.

I greatly acknowledge my wife, Eva Varadi, for her support, patience, and understanding during the creative process of writing this article.

Telco energy consumption – a path to a greener future?

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To my friend Rudolf van der Berg this story is not about how volumetric demand (bytes or bits) results in increased energy consumption (W·h). That notion is silly, as we both “violently” agree on ;-). I recommend that readers also check out Rudolf’s wonderful presentation, “Energy Consumption of the Internet (May 2023),” which he delivered at the RIPE86 student event this year in 2023.

Recently, I had the privilege to watch a presentation by a seasoned executive talk about what his telco company is doing for the environment regarding sustainability and CO2 reduction in general. I think the company is doing something innovative beyond compensating shortfalls with buying certificates and (mis)use of green energy resources.

They replace (reasonably) aggressively their copper infrastructure (country stat for 2022: ~90% of HH/~16% subscriptions) with green sustainable fiber (country stat for 2022: ~78%/~60%). This is an obvious strategy that results in a quantum leap in customer experience potential and helps reduce overall energy consumption resulting from operating the ancient copper network.

Missing a bit imo, was the consideration of and the opportunity to phase out the HFC network (country stat for 2022: ~70%/~60%) and reduce the current HFC+Fibre overbuild of 1.45 and, of course, reduce the energy consumption and operational costs (and complexity) of operating two fixed broadband technologies (3 if we include the copper). However, maybe understandably enough, substantial investments have been made in upgrading to Docsis 3.1. An investment that possibly still is somewhat removed from having been written off.

The “wtf-moment” (in an otherwise very pleasantly and agreeable session) came when the speaker alluded that as part of their sustainability and CO2 reduction strategy, the telco was busy migrating from 4G LTE to 5G with the reasoning that 5G is 90% more energy efficient compared to 4G.

Firstly, it is correct that 5G is (in apples-for-apples comparisons!) ca. 90% more efficient in delivering a single bit compared to 4G. The metric we use is Joules-per-bit or Watts-seconds-per-bit. It is also not uncommon at all to experience Telco executives hinting at the relative greenness of 5G (it is, in my opinion, decidedly not a green broadband communications technology … ).

Secondly, so what! Should we really care about relative energy consumption? After all, we pay for absolute energy consumption, not for whatever relativized measure of consumed energy.

I think I know the answer from the CFO and the in-the-know investors.

If the absolute energy consumption of 5G is higher than that of 4G, I will (most likely) have higher operational costs attributed to that increased power consumption with 5G. If I am not in an apples-for-apples situation, which rarely is the case, and I am anyway really not in, the 5G technology requires substantially more power to provide for new requirements and specifications. I will be worse off regarding the associated cost in absolute terms of money. Unless I also have a higher revenue associated with 5G, I am economically worse off than I was with the older technology.

Having higher information-related energy efficiency in cellular communications systems is a feature of the essential requirement of increasingly better spectral efficiency all else being equal. It does not guarantee that, in absolute monetary terms, a Telco will be better off … far from it!

THE ENERGY OF DELIVERING A BIT.

Energy, which I choose to represent in Joules, is equal to the Power (in Watt or W) that I need to consume per time-unit for a given output unit (e.g., a bit) times the unit of time (e.g., a second) it took to provide the unit.

Take a 4G LTE base station that consumes ca. 5.0kW to deliver a maximum throughput of 160 Mbps per sector (@ 80 MHz per sector). The information energy efficiency of the specific 4G LTE base station (e.g., W·s per bit) would be ca. 10 µJ/bit. The 4G LTE base station requires 10 micro (one millionth) Joules to deliver 1 bit (in 1 second).

In the 5G world, we would have a 5G SA base station, using the same frequency bands as 4G and with an additional 10 MHz @ 700MHz and 100 MHz @ 3.5 GHz included. The 3.5 GHz band is supported by an advanced antenna system (AAS) rather than a classical passive antenna system used for the other frequency bands. This configuration consumes 10 kW with ~40% attributed to the 3.5 GHz AAS, supporting ~1 Gbps per sector (@ 190 MHz per sector). This example’s 5G information energy efficiency would be ca. 0.3 µJ/bit.

In this non-apples-for-apples comparison, 5G is about 30 times more efficient in delivering a bit than 4G LTE (in the example above). Regarding what an operator actually pays for, 5G is twice as costly in energy consumption compared to 4G.

It should be noted that the power consumption is not driven by the volumetric demand but by the time that demand exists and the load per unit of time. Also, base stations will have a power consumption even when idle with the degree depending on the intelligence of the energy management system applied.

So, more formalistic, we have

E per bit = P (in W) · time (in sec) per bit, or in the basic units

J / bit = W·s / bit = W / (bit/s) = W / bps = W / [ MHz · Mbps/MHz/unit · unit-quantity ]

E per bit = P (in W) / [ Bandwidth (in MHz) · Spectral Efficiency (in Mbps/MHz/unit) · unit-quantity ]

It is important to remember that this is about the system spec information efficiency and that there is no direct relationship between the Power that you need and the outputted information your system will ultimately support bit-wise.

and

Thus, the relative efficiency between 4G and 5G is

Currently (i.e., 2023), the various components of the above are approximately within the following ranges.

The power consumption of a 5G RAT is higher than that of a 4G RAT. As we add higher frequency spectrum (e.g., C-band, 6GHz, 23GHz,…) to the 5G RAT, increasingly more spectral bandwidth (B) will be available compared to what was deployed for 4G. This will increase the bit-wise energy efficiency of 5G compared to 4G, although the power consumption is also expected to increase as higher frequencies are supported.

If the bandwidth and system power consumption is the same for both radio access technologies (RATs), then we have the relative information energy efficiency is

Depending on the relative difference in spectral efficiency. 5G is specified and designed to have at least ten times (10x) the spectral efficiency of 4G. If you do the math (assuming apples-to-apples applies), it is no surprise that 5G is specified to be 90% more efficient in delivering a bit (in a given unit of time) compared to 4G LTE.

And just to emphasize the obvious,

RAT refers to the radio access technology, BB is the baseband, freq the cellular frequencies, and idle to the situation where the system is not being utilized.

Volume in Bytes (or bits) does not directly relate to energy consumption. As frequency bands are added to a sector (of a base station), the overall power consumption will increase. Moreover, the more computing is required in the antenna, such as for advanced antenna systems, including massive MiMo antennas, the more power will be consumed in the base station. The more the frequency bands are being utilized in terms of time, the higher will the power consumption be.

Indirectly, as the cellular system is being used, customers consume bits and bytes (=8·bit) that will depend on the effective spectral efficiency (in bps/Hz), the amount of effective bandwidth (in Hz) experienced by the customers, e.g., many customers will be in a coverage situation where they may not benefit for example from higher frequency bands), and the effective time they make use of the cellular network resources. The observant reader will see that I like the term “effective.” The reason is that customers rarely enjoy the maximum possible spectral efficiency. Likely, not all the frequency spectrum covering customers is necessarily being applied to individual customers, depending on their coverage situation.

In the report “A Comparison of the Energy Consumption of Broadband Data Transfer Technologies (November 2021),” the authors show the energy and volumetric consumption of mobile networks in Finland over the period from 2010 to 2020. To be clear, I do not support the author’s assertion of causation between volumetric demand and energy consumption. As I have shown above, volumetric usage does not directly cause a given power consumption level. Over the 10-year period shown in the report, they observe a 70% increase in absolute power consumption (from 404 to 686 GWh, CAGR ~5.5%) and a factor of ~70 in traffic volume (~60 TB to ~4,000 TB, CAGR ~52%). Caution should be made in resisting the temptation to attribute the increase in energy over the period to be directly related to the data volume increase, however weak it is (i.e., note that the authors did not resist that temptation). Rudolf van der Berg has raised several issues with the approach of the above paper (as well as with many other related works) and indicated that the data and approach of the authors may not be reliable. Unfortunately, in this respect, it appears that systematic, reliable, and consistent data in the Telco industry is hard to come by (even if that data should be available to the individual telcos).

Technology change from 2G/3G to 4G, site densification, and more frequency bands can more than easily explain the increase in energy consumption (and all are far better explanations than data volume). It should be noted that there will also be reasons that decrease power consumption over time, such as more efficient electronics (e.g., via modernization), intelligent power management applications, and, last but not least, switching off of older radio access technologies.

The factors that drive a cell site’s absolute energy consumption is

  • Radio access technology with new technologies generally consumes more energy than older ones (even if the newer technologies have become increasingly more spectrally efficient).
  • The antenna type and configuration, including computing requirements for advanced signal processing and beamforming algorithms (that will improve the spectral efficiency at the expense of increased absolute energy consumption).
  • Equipment efficiency. In general, new generations of electronics and systems designs tend to be more energy-efficient for the same level of performance.
  • Intelligent energy management systems that allow for effective power management strategies will reduce energy consumption compared to what it would have been without such systems.
  • The network optimization goal policy. Is the cellular network planned and optimized for meeting the demands and needs of the customers (i.e., the economic design framework) or for providing the peak performance to as many customers as possible (i.e., the Umlaut/Ookla performance-driven framework)? The Umlaut/Ookla-optimized network, maxing out on base station configuration, will observe substantially higher energy consumption and associated costs.
The absolute cellular energy consumption has continued to rise as new radio access technologies (RAT) have been introduced irrespective of the leapfrog in those RATS spectral (bits per Hz) and information-related (Joules per bit) efficiencies.

WHY 5G IS NOT A GREEN TECHNOLOGY?

Let’s first re-acquaint ourselves with the 2015 vision of the 5G NGMN whitepaper;

“5G should support a 1,000 times traffic increase in the next ten years timeframe, with energy consumption by the whole network of only half that typically consumed by today’s networks. This leads to the requirement of an energy efficiency increase of x2000 in the next ten years timeframe.” (Section 4.2.2 Energy Efficiency, 5G White Paper by NGMN Alliance, February 2015).

The bold emphasis is my own and not in the paper itself. There is no doubt that the authors of the 5G vision paper had the ambition of making 5G a sustainable and greener cellular alternative than historically had been the case.

So, from the above statement, we have two performance figures that illustrate the ambition of 5G relative to 4G. Firstly, we have a requirement that the 5G energy efficiency should be 2000x higher than 4G (as it was back in the beginning of 2015).

or

if

Getting more spectrum bandwidth is relatively trivial as you go up in frequency and into, for example, the millimeter wave range (and beyond). However, getting 20+ GHz (e.g., 200+x100 MHz @ 4G) of additional practically usable spectrum bandwidth would be rather (=understatement) ambitious.

And that the absolute energy consumption of the whole 5G network should be half of what it was with 4G

If you think about this for a moment. Halfing the absolute energy consumption is an enormous challenge, even if it would have been with the same RAT. It requires innovation leapfrogs across the RAT electronic architecture, design, and material science underlying all of it. In other words, fundamental changes are required in the RF frontend (e.g., Power amplifiers, transceivers), baseband processing, DSP, DAC, ADC, cooling, control and management systems, algorithms, compute, etc…

But reality eats vision for breakfast … There really is no sign that the super-ambitious goal set by the NGMN Alliance in early 2015 is even remotely achievable even if we would give it another ten years (i.e., 2035). We are more than two orders of magnitude away from the visionary target of NGMN, and we are almost at the 10-year anniversary of the vision paper. We more or less get the benefit of the relative difference in spectral efficiency (x10), but no innovation beyond that has contributed very much to quantum leap cellular energy efficiency bit-wise.

I know many operators who will say that from a sustainability perspective, at least before the energy prices went through the roof, it really does not matter that 5G, in absolute terms, leads to substantial increases in energy consumption. They use green energy to supply the energy demand from 5G and pay off $CO_2$ deficits with certificates.

First of all, unless the increased cost can be recovered with the customers (e.g., price plan increase), it is a doubtful economic venue to pursue (and has a bit of a Titanic feel to it … going down together while the orchestra is playing).

Second, we should ask ourselves whether it is really okay for any industry to greedily consume sustainable and still relatively scarce green resources without being incentivized (or encouraged) to pursue alternatives and optimize across mobile and fixed broadband technologies. Particularly when fixed broadband technologies, such as fiber, are available, that would lead to a very sizable and substantial reduction in energy consumption … as customers increasingly adapt to fiber broadband.

Fiber is the greenest and most sustainable access technology we can deploy compared to cellular broadband technologies.

SO WHAT?

5G is a reality. Telcos are and will continue to invest substantially into 5G as they migrate their customers from 4G LTE to what ultimately will be 5G Standalone. The increase in customer experience and new capabilities or enablers are significant. By now, most Telcos will (i.e., 2023) have a very good idea of the operational expense associated with 5G (if not … you better do the math). Some will have been exploring investing in their own green power plants (e.g., solar, wind, hydrogen, etc.) to mitigate part of the energy surge arising from transitioning to 5G.

I suspect that as Telcos start reflecting on Open RAN as they pivot towards 6G (-> 2030+), above and beyond what 6G, as a RAT, may bring of additional operational expense pain, there will be new energy consumption and sustainability surprises to the cellular part of Telcos P&L. In general, breaking up an electronic system into individual (non-integrated) parts, as opposed to being integrated into a single unit, is likely to result in an increased power consumption. Some of the operational in-efficiencies that occur in breaking up a tightly integrated design can be mitigated by power management strategies. Though in order to get such power management strategies to work at the optimum may force a higher degree of supplier uniformity than the original intent of breaking up the tightly integrated system.

However, only Telcos that consider both their mobile and fixed broadband assets together, rather than two silos apart, will gain in value for customers and shareholders. Fixed-mobile (network) conversion should be taken seriously and may lead to very different considerations and strategies than 10+ years ago.

With increasing coverage of fiber and with Telcos stimulating aggressive uptake, it will allow those to redesign the mobile networks for what they were initially supposed to do … provide convenience and service where there is no fixed network present, such as when being mobile and in areas where the economics of a fixed broadband network makes it least likely to be available (e.g., rural areas) although LEO satellites (i.e., here today), maybe stratospheric drones (i.e., 2030+), may offer solid economic alternatives for those places. Interestingly, further simplifying the cellular networks supporting those areas today.

TAKE AWAY.

Volume in Bytes (or bits) does not directly relate to the energy consumption of the underlying communications networks that enable the usage.

The duration, the time scale, of the customer’s usage (i.e., the use of the network resources) does cause power consumption.

The bit-wise energy efficiency of 5G is superior to that of 4G LTE. It is designed that way via its spectral efficiency. Despite this, a 5G site configuration is likely to consume more energy than a 4G LTE site in the field and, thus, not a like-for-like in terms of number of bands and type of antennas deployed.

The absolute power consumption of a 5G configuration is a function of the number of bands deployed, the type of antennas deployed, intelligent energy management features, and the effective time 5G resources that customers have demanded.

Due to its optical foundation, Fiber is far more energy efficient in both bit-wise relative terms and absolute terms than any other legacy fixed (e.g., xDSL, HFC) or cellular broadband technology (e.g., 4G, 5G).

Looking forward and with the increasing challenges of remaining sustainable and contributing to CO2 reduction, it is paramount to consider an energy-optimized fixed and mobile converged network architecture as opposed to today’s approach of optimizing the fixed network separately from the cellular network. As a society, we should expect that the industry works hard to achieve an overall reduction in energy consumption, relaxing the demand on existing green energy infrastructures.

With 5G as of today, we are orders of magnitude from the original NGMN vision of energy consumption of only half of what was consumed by cellular networks ten years ago (i.e., 2014), requiring an overall energy efficiency increase of x2000.

Be aware that many Telcos and Infrastructure providers will use bit-wise energy efficiency when they report on energy consumption. They will generally report impressive gains over time in the energy that networks consume to deliver bits to their customers. This is the least one should expect.

Last but not least, the telco world is not static and is RAT-wise not very clean, as mobile networks will have several RATs deployed simultaneously (e.g., 2G, 4G, and 5G). As such, we rarely (if ever) have apples-to-apples comparisons on cellular energy consumption.

ACKNOWLEDGEMENT.

I greatly acknowledge my wife, Eva Varadi, for her support, patience, and understanding during the creative process of writing this article. I also greatly appreciate the discussion on this topic that I have had with Rudolf van der Berg over the last couple of years. I thank him for pointing out and reminding me (when I forget) of the shortfalls and poor quality of most of the academic work and lobbying activities done in this area.

PS

If you are aiming at a leapfrog in absolute energy reduction of your cellular network, above and beyond what you get with your infrastructure suppliers (e.g., Nokia, Ericsson, Huawei…), I really recommend you take a look at Opanga‘s machine learning-based Joule ML solution. The Joules ML has been proven to reduce RAN energy costs by 20% – 40% on top of what the RAT supplier’s (e.g., Ericsson, Nokia, Huawei, etc.) own energy management solutions may bring.

Disclosure: I am associated with Opanga and on their Industry Advisory Board.

5G Economics – The Numbers (Appendix X).

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100% COVERAGE.

100% 5G coverage is not going to happen with 30 – 300 GHz millimeter-wave frequencies alone.

The “NGMN 5G white paper” , which I will in the subsequent parts refer to as the 5G vision paper, require the 5G coverage to be 100%.

At 100% cellular coverage it becomes somewhat academic whether we talk about population coverage or geographical (area) coverage. The best way to make sure you cover 100% of population is covering 100% of the geography. Of course if you cover 100% of the geography, you are “reasonably” ensured to cover 100% of the population.

While it is theoretically possible to cover 100% (or very near to) of population without covering 100% of the geography, it might be instructive to think why 100% geographical coverage could be a useful target in 5G;

  1. Network-augmented driving and support for varous degrees of autonomous driving would require all roads to be covered (however small).
  2. Internet of Things (IoT) Sensors and Actuators are likely going to be of use also in rural areas (e.g., agriculture, forestation, security, waterways, railways, traffic lights, speed-detectors, villages..) and would require a network to connect to.
  3. Given many users personal area IoT networks (e.g., fitness & health monitors, location detection, smart-devices in general) ubiquitous becomes essential.
  4. Internet of flying things (e.g., drones) are also likely to benefit from 100% area and aerial coverage.

However, many countries remain lacking in comprehensive geographical coverage. Here is an overview of the situation in EU28 (as of 2015);

For EU28 countries, 14% of all house holds in 2015 still had no LTE coverage. This was approx.30+ million households or equivalent to 70+ million citizens without LTE coverage. The 14% might seem benign. However, it covers a Rural neglect of 64% of households not having LTE coverage. One of the core reasons for the lack of rural (population and household) coverage is mainly an economic one. Due to the relative low number of population covered per rural site and compounded by affordability issues for the rural population, overall rural sites tend to have low or no profitability. Network sharing can however improve the rural site profitability as site-related costs are shared.

From an area coverage perspective, the 64% of rural households in EU28 not having LTE coverage is likely to amount to a sizable lack of LTE coverage area. This rural proportion of areas and households are also very likely by far the least profitable to cover for any operator possibly even with very progressive network sharing arrangements.

Fixed broadband, Fiber to the Premises (FTTP) and DOCSIS3.0, lacks further behind that of mobile LTE-based broadband. Maybe not surprisingly from an business economic perspective, in rural areas fixed broadband is largely unavailable across EU28.

The chart below illustrates the variation in lack of broadband coverage across LTE, Fiber to the Premises (FTTP) and DOCSIS3.0 (i.e., Cable) from a total country perspective (i.e., rural areas included in average).

We observe that most countries have very far to go on fixed broadband provisioning (i.e., FTTP and DOCSIS3.0) and even on LTE coverage lacks complete coverage. The rural coverage view (not shown here) would be substantially worse than the above Total view.

The 5G ambition is to cover 100% of all population and households. Due to the demographics of how rural households (and populations) are spread, it is also likely that fairly large geographical areas would need to be covered in order to come true on the 100% ambition.

It would appear that bridging this lack of broadband coverage would be best served by a cellular-based technology. Given the fairly low population density in such areas relative higher average service quality (i.e., broadband) could be delivered as long as the cell range is optimized and sufficient spectrum at a relative low carrier frequency (< 1 GHz) would be available. It should be remembered that the super-high 5G 1 – 10 Gbps performance cannot be expected in rural areas. Due to the lower carrier frequency range need to provide economic rural coverage both advanced antenna systems and very large bandwidth (e.g., such as found in the mm-frequency range)  would not be available to those areas. Thus limiting the capacity and peak performance possible even with 5G.

I would suspect that irrespective of the 100% ambition, telecom providers would be challenged by the economics of cellular deployment and traffic distribution. Rural areas really sucks in profitability, even in fairly aggressive sharing scenarios. Although multi-party (more than 2) sharing might be a way to minimize the profitability burden on deep rural coverage.

The above chart shows the relationship between traffic distribution and sites. As a rule of thumb 50% of revenue is typically generated by 10% of all sites (i.e., in a normal legacy mobile network) and approx. 50% of (rural) sites share roughly 10% of the revenue. Note: in emerging markets the distribution is somewhat steeper as less comprehensive rural coverage typically exist. (Source: The ABC of Network Sharing – The Fundamentals.).

Irrespective of my relative pessimism of the wider coverage utility and economics of millimeter-wave (mm-wave) based coverage, there shall be no doubt that mm-wave coverage will be essential for smaller and smallest cell coverage where due to density of users or applications will require extreme (in comparison to today’s demand) data speeds and capacities. Millimeter-wave coverage-based architectures offer very attractive / advanced antenna solutions that further will allow for increased spectral efficiency and throughput. Also the possibility of using mm-wave point to multipoint connectivity as last mile replacement for fiber appears very attractive in rural and sub-urban clutters (and possible beyond if the cost of the electronics drop according the expeced huge increase in demand for such). This last point however is in my opinion independent of 5G as Facebook with their Terragraph development have shown (i.e., 60 GHz WiGig-based system). A great account for mm-wave wireless communications systems  can be found in T.S. Rappaport et al.’s book “Millimeter Wave Wireless Communications” which not only comprises the benefits of mm-wave systems but also provides an account for the challenges. It should be noted that this topic is still a very active (and interesting) research area that is relative far away from having reached maturity.

In order to provide 100% 5G coverage for the mass market of people & things, we need to engage the traditional cellular frequency bands from 600 MHz to 3 GHz.

1 – 10 Gbps PEAK DATA RATE PER USER.

Getting a Giga bit per second speed is going to require a lot of frequency bandwidth, highly advanced antenna systems and lots of additional cells. And that is likely going to lead to a (very) costly 5G deployment. Irrespective of the anticipated reduced unit cost or relative cost per Byte or bit-per-second.

At 1 Gbps it would take approx. 16 seconds to download a 2 GB SD movie. It would take less than a minute for the HD version (i.e., at 10 Gbps it just gets better;-). Say you have a 16GB smartphone, you loose maybe up to 20+% for the OS, leaving around 13GB for things to download. With 1Gbps it would take less than 2 minutes to fill up your smartphones storage (assuming you haven’t run out of credit on your data plan or reached your data ceiling before then … of course unless you happen to be a customer of T-Mobile US in which case you can binge on = you have no problems!).

The biggest share of broadband usage comes from video streaming which takes up 60% to 80% of all volumetric traffic pending country (i.e., LTE terminal penetration dependent). Providing higher speed to your customer than is required by the applied video streaming technology and smartphone or tablet display being used, seems somewhat futile to aim for. The Table below provides an overview of streaming standards, their optimal speeds and typical viewing distance for optimal experience;

Source: 5G Economics – An Introduction (Chapter 1).

So … 1Gbps could be cool … if we deliver 32K video to our customers end device, i.e., 750 – 1600 Mbps optimal data rate. Though it is hard to see customers benefiting from this performance boost given current smartphone or tablet display sizes. The screen size really have to be ridiculously large to truly benefit from this kind of resolution. Of course Star Trek-like full emersion (i.e., holodeck) scenarios would arguably require a lot (=understatement) bandwidth and even more (=beyond understatement) computing power … though such would scenario appears unlikely to be coming out of cellular devices (even in Star Trek).

1 Gbps fixed broadband plans have started to sell across Europe. Typically on Fiber networks although also on DOCSIS3.1 (10Gbps DS/1 Gbps US) networks as well in a few places. It will only be a matter of time before we see 10 Gbps fixed broadband plans being offered to consumers. Irrespective of compelling use cases might be lacking it might at least give you the bragging rights of having the biggest.

From European Commissions “Europe’s Digital Progress Report 2016”,  22 % of European homes subscribe to fast broadband access of at least 30 Mbps. An estimated 8% of European households subscribe to broadband plans of at least 100 Mbps. It is worth noticing that this is not a problem with coverage as according with the EC’s “Digital Progress Report” around 70% of all homes are covered with at least 30 Mbps and ca. 50% are covered with speeds exceeding 100 Mbps.

The chart below illustrates the broadband speed coverage in EU28;

Even if 1Gbps fixed broadband plans are being offered, still majority of European homes are at speeds below the 100 Mbps. Possible suggesting that affordability and household economics plays a role as well as the basic perceived need for speed might not (yet?) be much beyond 30 Mbps?

Most aggregation and core transport networks are designed, planned, built and operated on a assumption of dominantly customer demand of lower than 100 Mbps packages. As 1Gbps and 10 Gbps gets commercial traction, substantial upgrades are require in aggregation, core transport and last but not least possible also on an access level (to design shorter paths). It is highly likely distances between access, aggregation and core transport elements are too long to support these much higher data rates leading to very substantial redesigns and physical work to support this push to substantial higher throughputs.

Most telecommunications companies will require very substantial investments in their existing transport networks all the way from access to aggregation through the optical core switching networks, out into the world wide web of internet to support 1Gbps to 10 Gbps. Optical switching cards needs to be substantially upgraded, legacy IP/MPLS architectures might no longer work very well (i.e., scale & complexity issue).

Most analysts today believe that incumbent fixed & mobile broadband telecommunications companies with a reasonable modernized transport network are best positioned for 5G compared to mobile-only operators or fixed-mobile incumbents with an aging transport infrastructure.

What about the state of LTE speeds across Europe? OpenSignal recurrently reports on the State of LTE, the following summarizes LTE speeds in Mbps as of June 2017 for EU28 (with the exception of a few countries not included in the OpenSignal dataset);

The OpenSignal measurements are based on more than half a million devices, almost 20 billion measurements over the period of the 3 first month of 2017.

The 5G speed ambition is by todays standards 10 to 30+ times away from present 2016/2017 household fixed broadband demand or the reality of provided LTE speeds.

Let us look at cellular spectral efficiency to be expected from 5G. Using the well known framework;

In essence, I can provide very high data rates in bits per second by providing a lot of frequency bandwidth B, use the most spectrally efficient technologies maximizing η, and/or add as many cells N that my economics allow for.

In the following I rely largely on Jonathan Rodriquez great book on “Fundamentals of 5G Mobile Networks” as a source of inspiration.

The average spectral efficiency is expected to be coming out in the order of 10 Mbps/MHz/cell using advanced receiver architectures, multi-antenna, multi-cell transmission and corporation. So pretty much all the high tech goodies we have in the tool box is being put to use of squeezing out as many bits per spectral Hz available and in a sustainable matter. Under very ideal Signal to Noise Ratio conditions, massive antenna arrays of up to 64 antenna elements (i.e., an optimum) seems to indicate that 50+ Mbps/MHz/Cell might be feasible in peak.

So for a spectral efficiency of 10 Mbps/MHz/cell and a demanded 1 Gbps data rate we would need 100 MHz frequency bandwidth per cell (i.e., using the above formula). Under very ideal conditions and relative large antenna arrays this might lead to a spectral requirement of only 20 MHz at 50 Mbps/MHz/Cell. Obviously, for 10 Gbps data rate we would require 1,000 MHz frequency bandwidth (1 GHz!) per cell at an average spectral efficiency of 10 Mbps/MHz/cell.

The spectral efficiency assumed for 5G heavily depends on successful deployment of many-antenna segment arrays (e.g., Massive MiMo, beam-forming antennas, …). Such fairly complex antenna deployment scenarios work best at higher frequencies, typically above 2GHz. Also such antenna systems works better at TDD than FDD with some margin on spectral efficiency. These advanced antenna solutions works perfectly  in the millimeter wave range (i.e., ca. 30 – 300 GHz) where the antenna segments are much smaller and antennas can be made fairly (very) compact (note: resonance frequency of the antenna proportional to half the wavelength with is inverse proportional to the carrier frequency and thus higher frequencies need smaller material dimension to operate).

Below 2 GHz higher-order MiMo becomes increasingly impractical and the spectral efficiency regress to the limitation of a simple single-path antenna. Substantially lower than what can be achieved at much high frequencies with for example massive-MiMo.

So for the 1Gbps to 10 Gbps data rates to work out we have the following relative simple rationale;

  • High data rates require a lot of frequency bandwidth (>100 MHz to several GHz per channel).
  • Lots of frequency bandwidth are increasingly easier to find at high and very high carrier frequencies (i.e., why millimeter wave frequency band between 30 – 300 GHz is so appealing).
  • High and very high carrier frequencies results in small, smaller and smallest cells with very high bits per second per unit area (i.e., the area is very small!).
  • High and very high carrier frequency allows me to get the most out of higher order MiMo antennas (i.e., with lots of antenna elements),
  • Due to fairly limited cell range, I boost my overall capacity by adding many smallest cells (i.e., at the highest frequencies).

We need to watch out for the small cell densification which tends not to scale very well economically. The scaling becomes a particular problem when we need hundreds of thousands of such small cells as it is expected in most 5G deployment scenarios (i.e., particular driven by the x1000 traffic increase). The advanced antenna systems required (including the computation resources needed) to max out on spectral efficiency are likely going to be one of the major causes of breaking the economical scaling. Although there are many other CapEx and OpEx scaling factors to be concerned about for small cell deployment at scale.

Further, for mass market 5G coverage, as opposed to hot traffic zones or indoor solutions, lower carrier frequencies are needed. These will tend to be in the usual cellular range we know from our legacy cellular communications systems today (e.g., 600 MHz – 2.1 GHz). It should not be expected that 5G spectral efficiency will gain much above what is already possible with LTE and LTE-advanced at this legacy cellular frequency range. Sheer bandwidth accumulation (multi-frequency carrier aggregation) and increased site density is for the lower frequency range a more likely 5G path. Of course mass market 5G customers will benefit from faster reaction times (i.e., lower latencies), higher availability, more advanced & higher performing services arising from the very substantial changes expected in transport networks and data centers with the introduction of 5G.

Last but not least to this story … 80% and above of all mobile broadband customers usage, data as well as voice, happens in very few cells (e.g., 3!) … representing their Home and Work.

Source: Slideshare presentation by Dr. Kim “Capacity planning in mobile data networks experiencing exponential growth in demand.”

As most of the mobile cellular traffic happen at the home and at work (i.e., thus in most cases indoor) there are many ways to support such traffic without being concerned about the limitation of cell ranges.

The giga bit per second cellular service is NOT a service for the mass market, at least not in its macro-cellular form.

≤ 1 ms IN ROUND-TRIP DELAY.

A total round-trip delay of 1 or less millisecond is very much attuned to niche service. But a niche service that nevertheless could be very costly for all to implement.

I am not going to address this topic too much here. It has to a great extend been addressed almost to ad nauseam in 5G Economics – An Introduction (Chapter 1) and 5G Economics – The Tactile Internet (Chapter 2). I think this particular aspect of 5G is being over-hyped in comparison to how important it ultimately will turn out to be from a return on investment perspective.

Speed of light travels ca. 300 km per millisecond (ms) in vacuum and approx. 210 km per ms in fiber (some material dependency here). Lately engineers have gotten really excited about the speed of light not being fast enough and have made a lot of heavy thinking abou edge this and that (e.g., computing, cloud, cloudlets, CDNs,, etc…). This said it is certainly true that most modern data centers have not been build taking too much into account that speed of light might become insufficient. And should there really be a great business case of sub-millisecond total (i.e., including the application layer) roundtrip time scales edge computing resources would be required a lot closer to customers than what is the case today.

It is common to use delay, round-trip time or round-trip delay, or latency as meaning the same thing. Though it is always cool to make sure people really talk about the same thing by confirming that it is indeed a round-trip rather than single path. Also to be clear it is worthwhile to check that all people around the table talk about delay at the same place in the OSI stack or  network path or whatever reference point agreed to be used.

In the context of  the 5G vision paper it is emphasized that specified round-trip time is based on the application layer (i.e., OSI model) as reference point. It is certainly the most meaningful measure of user experience. This is defined as the End-2-End (E2E) Latency metric and measure the complete delay traversing the OSI stack from physical layer all the way up through network layer to the top application layer, down again, between source and destination including acknowledgement of a successful data packet delivery.

The 5G system shall provide 10 ms E2E latency in general and 1 ms E2E latency for use cases requiring extremely low latency.

The 5G vision paper states “Note these latency targets assume the application layer processing time is negligible to the delay introduced by transport and switching.” (Section 4.1.3 page 26 in “NGMN 5G White paper”).

In my opinion it is a very substantial mouthful to assume that the Application Layer (actually what is above the Network Layer) will not contribute significantly to the overall latency. Certainly for many applications residing outside the operators network borders, in the world wide web, we can expect a very substantial delay (i.e., even in comparison with 10 ms). Again this aspect was also addressed in my two first chapters.

Very substantial investments are likely needed to meet E2E delays envisioned in 5G. In fact the cost of improving latencies gets prohibitively more expensive as the target is lowered. The overall cost of design for 10 ms would be a lot less costly than designing for 1 ms or lower. The network design challenge if 1 millisecond or below is required, is that it might not matter that this is only a “service” needed in very special situations, overall the network would have to be designed for the strictest denominator.

Moreover, if remedies needs to be found to mitigate likely delays above the Network Layer, distance and insufficient speed of light might be the least of worries to get this ambition nailed (even at the 10 ms target). Of course if all applications are moved inside operator’s networked premises with simpler transport paths (and yes shorter effective distances) and distributed across a hierarchical cloud (edge, frontend, backend, etc..), the assumption of negligible delay in layers above the Network Layer might become much more likely. However, it does sound a lot like America Online walled garden fast forward to the past kind of paradigm.

So with 1 ms E2E delay … yeah yeah … “play it again Sam” … relevant applications clearly need to be inside network boundary and being optimized for processing speed or silly & simple (i.e., negligible delay above the Network Layer), no queuing delay (to the extend of being in-efficiency?), near-instantaneous transmission (i.e., negligible transmission delay) and distances likely below tenth of km (i.e., very short propagation delay).

When the speed of light is too slow there are few economic options to solve that challenge.

≥ 10,000 Gbps / Km2 DATA DENSITY.

The data density is maybe not the most sensible measure around. If taken too serious could lead to hyper-ultra dense smallest network deployments.

This has always been a fun one in my opinion. It can be a meaningful design metric or completely meaningless.

There is of course nothing particular challenging in getting a very high throughput density if an area is small enough. If I have a cellular range of few tens of meters, say 20 meters, then my cell area is smaller than 1/1000 of a km2. If I have 620 MHz bandwidth aggregated between 28 GHz and 39 GHz (i.e., both in the millimeter wave band) with a 10 Mbps/MHz/Cell, I could support 6,200 Gbps/km2. That’s almost 3 Petabyte in an hour or 10 years of 24/7 binge watching of HD videos. Note given my spectral efficiency is based on an average value, it is likely that I could achieve substantially more bandwidth density and in peaks closer to the 10,000 Gbps/km2 … easily.

Pretty Awesome Wow!

The basic; a Terabit equals 1024 Gigabits (but I tend to ignore that last 24 … sorry I am not).

With a traffic density of ca. 10,000 Gbps per km2, one would expect to have between 1,000 (@ 10 Gbps peak) to 10,000 (@ 1 Gbps peak) concurrent users per square km.

At 10 Mbps/MHz/Cell one would expect to have a 1,000 Cell-GHz/km2. Assume that we would have 1 GHz bandwidth (i.e., somewhere in the 30 – 300 GHz mm-wave range), one would need 1,000 cells per km2. On average with a cell range of about 20 meters (smaller to smallest … I guess what Nokia would call an Hyper-Ultra-Dense Network;-). Thus each cell would minimum have between 1 to 10 concurrent users.

Just as a reminder! 1 minutes at 1 Gbps corresponds to 7.5 GB. A bit more than what you need for a 80 minute HD (i.e., 720pp) full movie stream … in 1 minutes. So with your (almost) personal smallest cell what about the remaining 59 minutes? Seems somewhat wasteful at least until kingdom come (alas maybe sooner than that).

It would appear that the very high 5G data density target could result in very in-efficient networks from a utilization perspective.

≥ 1 MN / Km2 DEVICE DENSITY.

One million 5G devices per square kilometer appears to be far far out in a future where one would expect us to be talking about 7G or even higher Gs.

1 Million devices seems like a lot and certainly per km2. It is 1 device per square meter on average. A 20 meter cell-range smallest cell would contain ca. 1,200 devices.

To give this number perspective lets compare it with one of my favorite South-East Asian cities. The city with one of the highest population densities around, Manila (Philippines). Manila has more than 40 thousand people per square km. Thus in Manila this would mean that we would have about 24 devices per person or 100+ per household per km2. Overall, in Manila we would then expect approx. 40 million devices spread across the city (i.e., Manila has ca. 1.8 Million inhabitants over an area of 43 km2. Philippines has a population of approx. 100 Million).

Just for the curious, it is possible to find other more populated areas in the world. However, these highly dense areas tends to be over relative smaller surface areas, often much smaller than a square kilometer and with relative few people. For example Fadiouth Island in Dakar have a surface area of 0.15 km2 and 9,000 inhabitants making it one of the most pop densest areas in the world (i.e., 60,000 pop per km2).

I hope I made my case! A million devices per km2 is a big number.

Let us look at it from a forecasting perspective. Just to see whether we are possibly getting close to this 5G ambition number.

IHS forecasts 30.5 Billion installed devices by 2020, IDC is also believes it to be around 30 Billion by 2020. Machina Research is less bullish and projects 27 Billion by 2025 (IHS expects that number to be 75.4 Billion) but this forecast is from 2013. Irrespective, we are obviously in the league of very big numbers. By the way 5G IoT if at all considered is only a tiny fraction of the overall projected IoT numbers (e.g., Machine Research expects 10 Million 5G IoT connections by 2024 …that is extremely small numbers in comparison to the overall IoT projections).

A consensus number for 2020 appears to be 30±5 Billion IoT devices with lower numbers based on 2015 forecasts and higher numbers typically from 2016.

To break this number down to something that could be more meaningful than just being Big and impressive, let just establish a couple of worldish numbers that can help us with this;

  • 2020 population expected to be around 7.8 Billion compared to 2016 7.4 Billion.
  • Global pop per HH is ~3.5 (average number!) which might be marginally lower in 2020. Urban populations tend to have less pop per households ca. 3.0. Urban populations in so-called developed countries are having a pop per HH of ca. 2.4.
  • ca. 55% of world population lives in Urban areas. This will be higher by 2020.
  • Less than 20% of world population lives in developed countries (based on HDI). This is a 2016 estimate and will be higher by 2020.
  • World surface area is 510 Million km2 (including water).
  • of which ca. 150 million km2 is land area
  • of which ca. 75 million km2 is habitable.
  • of which 3% is an upper limit estimate of earth surface area covered by urban development, i.e., 15.3 Million km2.
  • of which approx. 1.7 Million km2 comprises developed regions urban areas.
  • ca. 37% of all land-based area is agricultural land.

Using 30 Billion IoT devices by 2020 is equivalent to;

  • ca. 4 IoT per world population.
  • ca. 14 IoT per world households.
  • ca. 200 IoT per km2 of all land-based surface area.
  • ca. 2,000 IoT per km2 of all urban developed surface area.

If we limit IoT’s in 2020 to developed countries, which wrongly or rightly exclude China, India and larger parts of Latin America, we get the following by 2020;

  • ca. 20 IoT per developed country population.
  • ca. 50 IoT per developed country households.
  • ca. 18,000 IoT per km2 developed country urbanized areas.

Given that it would make sense to include larger areas and population of both China, India and Latin America, the above developed country numbers are bound to be (a lot) lower per Pop, HH and km2. If we include agricultural land the number of IoTs will go down per km2.

So far far away from a Million IoT per km2.

What about parking spaces, for sure IoT will add up when we consider parking spaces!? … Right? Well in Europe you will find that most big cities will have between 50 to 200 (public) parking spaces per square kilometer (e.g., ca. 67 per km2 for Berlin and 160 per km2 in Greater Copenhagen). Aha not really making up to the Million IoT per km2 … what about cars?

In EU28 there are approx. 256 Million passenger cars (2015 data) over a population of ca. 510 Million pops (or ca. 213 million households). So a bit more than 1 passenger car per household on EU28 average. In Eu28 approx. 75+% lives in urban area which comprises ca. 150 thousand square kilometers (i.e., 3.8% of EU28’s 4 Million km2). So one would expect little more (if not a little less) than 1,300 passenger cars per km2. You may say … aha but it is not fair … you don’t include motor vehicles that are used for work … well that is an exercise for you (too convince yourself why that doesn’t really matter too much and with my royal rounding up numbers maybe is already accounted for). Also consider that many EU28 major cities with good public transportation are having significantly less cars per household or population than the average would allude to.

Surely, public street light will make it through? Nope! Typical bigger modern developed country city will have on average approx. 85 street lights per km2, although it varies from 0 to 1,000+. Light bulbs per residential household (from a 2012 study of the US) ranges from 50 to 80+. In developed countries we have roughly 1,000 households per km2 and thus we would expect between 50 thousand to 80+ thousand lightbulbs per km2. Shops and business would add some additions to this number.

With a cumulated annual growth rate of ca. 22% it would take 20 years (from 2020) to reach a Million IoT devices per km2 if we will have 20 thousand per km2 by 2020. With a 30% CAGR it would still take 15 years (from 2020) to reach a Million IoT per km2.

The current IoT projections of 30 Billion IoT devices in operation by 2020 does not appear to be unrealistic when broken down on a household or population level in developed areas (even less ambitious on a worldwide level). The 18,000 IoT per km2 of developed urban surface area by 2020 does appear somewhat ambitious. However, if we would include agricultural land the number would become possible a more reasonable.

If you include street crossings, traffic radars, city-based video monitoring (e.g., London has approx. 300 per km2, Hong Kong ca. 200 per km2), city-based traffic sensors, environmental sensors, etc.. you are going to get to sizable numbers.

However, 18,000 per km2 in urban areas appears somewhat of a challenge. Getting to 1 Million per km2 … hmmm … we will see around 2035 to 2040 (I have added an internet reminder for a check-in by 2035).

Maybe the 1 Million Devices per km2 ambition is not one of the most important 5G design criteria’s for the short term (i.e., next 10 – 20 years).

Oh and most IoT forecasts from the period 2015 – 2016 does not really include 5G IoT devices in particular. The chart below illustrates Machina Research IoT forecast for 2024 (from August 2015). In a more recent forecast from 2016, Machine Research predict that by 2024 there would be ca. 10 million 5G IoT connections or 0.04% of the total number of forecasted connections;

The winner is … IoTs using WiFi or other short range communications protocols. Obviously, the cynic in me (mea culpa) would say that a mm-wave based 5G connections can also be characterized as short range … so there might be a very interesting replacement market there for 5G IoT … maybe? 😉

Expectations to 5G-based IoT does not appear to be very impressive at least over the next 10 years and possible beyond.

The un-importance of 5G IoT should not be a great surprise given most 5G deployment scenarios are focused on millimeter-wave smallest 5G cell coverage which is not good for comprehensive coverage of  IoT devices not being limited to those very special 5G coverage situations being thought about today.

Only operators focusing on comprehensive 5G coverage re-purposing lower carrier frequency bands (i.e., 1 GHz and lower) can possible expect to gain a reasonable (as opposed to niche) 5G IoT business. T-Mobile US with their 600 MHz  5G strategy might very well be uniquely positions for taking a large share of future proof IoT business across USA. Though they are also pretty uniquely position for NB-IoT with their comprehensive 700MHz LTE coverage.

For 5G IoT to be meaningful (at scale) the conventional macro-cellular networks needs to be in play for 5G coverage .,, certainly 100% 5G coverage will be a requirement. Although, even with 5G there maybe 100s of Billion of non-5G IoT devices that require coverage and management.

≤ 500 km/h SERVICE SUPPORT.

Sure why not?  but why not faster than that? At hyperloop or commercial passenger airplane speeds for example?

Before we get all excited about Gbps speeds at 500 km/h, it should be clear that the 5G vision paper only proposed speeds between 10 Mbps up-to 50 Mbps (actually it is allowed to regress down to 50 kilo bits per second). With 200 Mbps for broadcast like services.

So in general, this is a pretty reasonable requirement. Maybe with the 200 Mbps for broadcasting services being somewhat head scratching unless the vehicle is one big 16K screen. Although the users proximity to such a screen does not guaranty an ideal 16K viewing experience to say the least.

What moves so fast?

The fastest train today is tracking at ca. 435 km/h (Shanghai Maglev, China).

Typical cruising airspeed for a long-distance commercial passenger aircraft is approx. 900 km/h. So we might not be able to provide the best 5G experience in commercial passenger aircrafts … unless we solve that with an in-plane communications system rather than trying to provide Gbps speed by external coverage means.

Why take a plane when you can jump on the local Hyperloop? The proposed Hyperloop should track at an average speed of around 970 km/h (faster or similar speeds as commercial passengers aircrafts), with a top speed of 1,200 km/h. So if you happen to be in between LA and San Francisco in 2020+ you might not be able to get the best 5G service possible … what a bummer! This is clearly an area where the vision did not look far enough.

Providing services to moving things at a relative fast speed does require a reasonable good coverage. Whether it being train track, hyperloop tunnel or ground to air coverage of commercial passenger aircraft, new coverage solutions would need to be deployed. Or alternative in-vehicular coverage solutions providing a perception of 5G experience might be an alternative that could turn out to be more economical.

The speed requirement is a very reasonable one particular for train coverage.

50% TOTAL NETWORK ENERGY REDUCTION.

If 5G development could come true on this ambition we talk about 10 Billion US Dollars (for the cellular industry). Equivalent to a percentage point on the margin.

There are two aspects of energy efficiency in a cellular based communication system.

  • User equipment that will benefit from longer intervals without charging and thus improve customers experience and overall save energy from less frequently charges.
  • Network infrastructure energy consumption savings will directly positively impact a telecom operators Ebitda.

Energy efficient Smartphones

The first aspect of user equipment is addressed by the 5G vision paper under “4.3 Device Requirements”  sub-section “4.3.3 Device Power Efficiency”; Battery life shall be significantly increased: at least 3 days for a smartphone, and up tp 15 years for a low-cost MTC device.” (note: MTC = Machine Type Communications).

Apple’s iPhone 7 battery life (on a full charge) is around 6 hours of constant use with 7 Plus beating that with ca. 3 hours (i.e., total 9 hours). So 3 days will go a long way.

From a recent 2016 survey from Ask Your Target Market on smartphone consumers requirements to battery lifetime and charging times;

  • 64% of smartphone owners said they are at least somewhat satisfied with their phone’s battery life.
  • 92% of smartphone owners said they consider battery life to be an important factor when considering a new smartphone purchase.
  • 66% said they would even pay a bit more for a cell phone that has a longer battery life.

Looking at the mobile smartphone & tablet non-voice consumption it is also clear why battery lifetime and not in-important the charging time matters;

Source: eMarketer, April 2016. While 2016 and 2017 are eMarketer forecasts (why dotted line and red circle!) these do appear well in line with other more recent measurements.

Non-voice smartphone & tablet based usage is expected by now to exceed 4 hours (240 minutes) per day on average for US Adults.

That longer battery life-times are needed among smartphone consumers is clear from sales figures and anticipated sales growth of smartphone power-banks (or battery chargers) boosting the life-time with several more hours.

It is however unclear whether the 3 extra days of a 5G smartphone battery life-time is supposed to be under active usage conditions or just in idle mode. Obviously in order to matter materially to the consumer one would expect this vision to apply to active usage (i.e., 4+ hours a day at 100s of Mbps – 1Gbps operations).

Energy efficient network infrastructure.

The 5G vision paper defines energy efficiency as number of bits that can be transmitted over the telecom infrastructure per Joule of Energy.

The total energy cost, i.e., operational expense (OpEx), of telecommunications network can be considerable. Despite our mobile access technologies having become more energy efficient with each generation, the total OpEx of energy attributed to the network infrastructure has increased over the last 10 years in general. The growth in telco infrastructure related energy consumption has been driven by the consumer demand for broadband services in mobile and fixed including incredible increase in data center computing and storage requirements.

In general power consumption OpEx share of total technology cost amounts to 8% to 15% (i.e., for Telcos without heavy reliance of diesel). The general assumption is that with regular modernization, energy efficiency gain in newer electronics can keep growth in energy consumption to a minimum compensating for increased broadband and computing demand.

Note: Technology Opex (including NT & IT) on average lays between 18% to 25% of total corporate Telco Opex. Out of the Technology Opex between 8% to 15% (max) can typically be attributed to telco infrastructure energy consumption. The access & aggregation contribution to the energy cost typically would towards 80% plus. Data centers are expected to increasingly contribute to the power consumption and cost as well. Deep diving into the access equipment power consumption, ca. 60% can be attributed to rectifiers and amplifiers, 15% by the DC power system & miscellaneous and another 25% by cooling.

5G vision paper is very bullish in their requirement to reduce the total energy and its associated cost; it is stated “5G should support a 1,000 times traffic increase in the next 10 years timeframe, with an energy consumption by the whole network of only half that typically consumed by today’s networks. This leads to the requirement of an energy efficiency of x2,000 in the next 10 years timeframe.” (sub-section “4.6.2 Energy Efficiency” NGMN 5G White Paper).

This requirement would mean that in a pure 5G world (i.e., all traffic on 5G), the power consumption arising from the cellular network would be 50% of what is consumed todayIn 2016 terms the Mobile-based Opex saving would be in the order of 5 Billion US$ to 10+ Billion US$ annually. This would be equivalent to 0.5% to 1.1% margin improvement globally (note: using GSMA 2016 Revenue & Growth data and Pyramid Research forecast). If energy price would increase over the next 10 years the saving / benefits would of course be proportionally larger.

As we have seen in the above, it is reasonable to expect a very considerable increase in cell density as the broadband traffic demand increases from peak bandwidth (i.e., 1 – 10 Gbps) and traffic density (i.e., 1 Tbps per km2) expectations.

Depending on the demanded traffic density, spectrum and carrier frequency available for 5G between 100 to 1,000 small cell sites per km2 could be required over the next 10 years. This cell site increase will be required in addition to existing macro-cellular network infrastructure.

Today (in 2017) an operator in EU28-sized country may have between ca. 3,500 to 35,000 cell sites with approx. 50% covering rural areas. Many analysts are expecting that for medium sized countries (e.g., with 3,500 – 10,000 macro cellular sites), operators would eventually have up-to 100,000 small cells under management in addition to their existing macro-cellular sites. Most of those 5G small cells and many of the 5G macro-sites we will have over the next 10 years, are also going to have advanced massive MiMo antenna systems with many active antenna elements per installed base antenna requiring substantial computing to gain maximum performance.

It appears with today’s knowledge extremely challenging (to put it mildly) to envision a 5G network consuming 50% of today’s total energy consumption.

It is highly likely that the 5G radio node electronics in a small cell environment (and maybe also in a macro cellular environment?) will consume less Joules per delivery bit (per second) due to technology advances and less transmitted power required (i.e., its a small or smallest cell). However, this power efficiency technology and network cellular architecture gain can very easily be destroyed by the massive additional demand of small, smaller and smallest cells combined with highly sophisticated antenna systems consuming additional energy for their compute operations to make such systems work. Furthermore, we will see operators increasingly providing sophisticated data center resources network operations as well as for the customers they serve. If the speed of light is insufficient for some services or country geographies, additional edge data centers will be introduced, also leading to an increased energy consumption not present in todays telecom networks. Increased computing and storage demand will also make the absolute efficiency requirement highly challenging.

Will 5G be able to deliver bits (per second) more efficiently … Yes!

Will 5G be able to reduce the overall power consumption of todays telecom networks with 50% … highly unlikely.

In my opinion the industry will have done a pretty good technology job if we can keep the existing energy cost at the level of today (or even allowing for unit price increases over the next 10 years).

The Total power reduction of our telecommunications networks will be one of the most important 5G development tasks as the industry cannot afford a new technology that results in waste amount of incremental absolute cost. Great relative cost doesn’t matter if it results in above and beyond total cost.

≥ 99.999% NETWORK AVAILABILITY & DATA CONNECTION RELIABILITY.

A network availability of 5Ns across all individual network elements and over time correspond to less than a second a day downtime anywhere in the network. Few telecom networks are designed for that today.

5 Nines (5N) is a great aspiration for services and network infrastructures. It also tends to be fairly costly and likely to raise the level of network complexity. Although in the 5G world of heterogeneous networks … well its is already complicated.

5N Network Availability.

From a network and/or service availability perspective it means that over the cause of the day, your service should not experience more than 0.86 seconds of downtime. Across a year the total downtime should not be more than 5 minutes and 16 seconds.

The way 5N Network Availability is define is “The network is available for the targeted communications in 99.999% of the locations  where the network is deployed and 99.999% of the time”. (from “4.4.4 Resilience and High Availability”, NGMN 5G White Paper).

Thus in a 100,000 cell network only 1 cell is allowed experience a downtime and for no longer than less than a second a day.

It should be noted that there are not many networks today that come even close to this kind of requirement. Certainly in countries with frequent long power outages and limited ancillary backup (i.e., battery and/or diesel) this could be a very costly design requirement. Networks relying on weather-sensitive microwave radios for backhaul or for mm-wave frequencies 5G coverage would be required to design in a very substantial amount of redundancy to keep such high geographical & time availability requirements

In general designing a cellular access network for this kind of 5N availability could be fairly to very costly (i.e., Capex could easily run up in several percentage points of Revenue).

One way out from a design perspective is to rely on hierarchical coverage. Thus, for example if a small cell environment is un-available (=down!) the macro-cellular network (or overlay network) continues the service although at a lower service level (i.e., lower or much lower speed compared to the primary service). As also suggested in the vision paper making use of self-healing network features and other real-time measures are expected to further increase the network infrastructure availability. This is also what one may define as Network Resilience.

Nevertheless, the “NGMN 5G White Paper” allows for operators to define the level of network availability appropriate from their own perspective (and budgets I assume).

5N Data Packet Transmission Reliability.

The 5G vision paper, defines Reliability as “… amount of sent data packets successfully delivered to a given destination, within the time constraint required by the targeted service, divided by the total number of sent data packets.”. (“4.4.5 Reliability” in “NGMN 5G White Paper”).

It should be noted that the 5N specification in particular addresses specific use cases or services of which such a reliability is required, e.g., mission critical communications and ultra-low latency service. The 5G allows for a very wide range of reliable data connection. Whether the 5N Reliability requirement will lead to substantial investments or can be managed within the overall 5G design and architectural framework, might depend on the amount of traffic requiring 5Ns.

The 5N data packet transmission reliability target would impose stricter network design. Whether this requirement would result in substantial incremental investment and cost is likely dependent on the current state of existing network infrastructure and its fundamental design.

 

5G Economics – An Introduction (Chapter 1)

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After 3G came 4G. After 4G comes 5G. After 5G comes 6G. The Shrivatsa of Technology.

This blog (over the next months a series of Blogs dedicated to 5G), “5G Economics – An Introduction”, has been a very long undertaking. In the making since 2014. Adding and then deleting as I change my opinion and then changed it again. The NGNM Alliance “NGMN 5G White Paper” (here after the NGMN whitepaper) by Rachid El Hattachi & Javan Erfanian has been both a source of great visionary inspiration as well as a source of great worry when it comes to the economical viability of their vision. Some of the 5G ideas and aspirations are truly moonshot in nature and would make the Singularity University very proud.

So what is the 5G Vision?

“5G is an end-to-end ecosystem to enable a fully mobile and connected society. It empowers value creation towards customers and partners, through existing and emerging use cases, delivered with consistent experience, and enabled by sustainable business models.” (NGMN 5G Vision, NGMN 5G whitepaper).

The NGMN 5G vision is not only limited to enhancement of the radio/air interface (although it is the biggest cost & customer experience factor). 5G seeks to capture the complete end-2-end telecommunications system architecture and its performance specifications. This is an important difference from past focus on primarily air interface improvements (e.g., 3G, HSPA, LTE, LTE-adv) and relative modest evolutionary changes to the core network architectural improvements (PS CN, EPC). In particular, the 5G vision provides architectural guidance on the structural separation of hardware and software. Furthermore, it utilizes the latest development in software defined telecommunications functionality enabled by cloudification and virtualization concepts known from modern state-of-the art data centers. The NGMN 5G vision most likely have accepted more innovation risk than in the past as well as being substantially more ambitious in both its specifications and the associated benefits.

“To boldly go where no man has gone before”

In the following, I encourage the reader to always keep in the back of your mind; “It is far easier to criticize somebody’s vision, than it is to come with the vision yourself”. I have tons of respect for the hard and intense development work, that so far have been channeled into making the original 5G vision into a deployable technology that will contribute meaningfully to customer experience and the telecommunications industry.

For much of the expressed concerns in this blog and in other critiques, it is not that those concerns have not been considered in the NGMN whitepaper and 5G vision, but more that those points are not getting much attention.

The cellular “singularity”, 5G that is, is supposed to hit us by 2020. In only four years. Americans and maybe others, taking names & definitions fairly lightly, might already have “5G” ( a l’Americaine) in a couple of years before the real thing will be around.

The 5G Vision is a source of great inspiration. The 5G vision will (and is) requiring a lot of innovation efforts, research & development to actually deliver on what for most parts are very challenging improvements over LTE.

My own main points of concern are in particular towards the following areas;

  • Obsession with very high sustainable connection throughputs (> 1 Gbps).
  • Extremely low latencies (1 ms and below).
  • Too little (to none) focus on controlling latency variation (e.g., jitter), which might be of even greater importance than very low latency (<<10 ms) in its own right. I term this network predictability.
  • Too strong focus on frequencies above 3 GHz in general and in particular the millimeter wave range of 30 GHz to 300 GHz.
  • Backhaul & backbone transport transformation needed to support the 5G quantum leap in performance has been largely ignored.
  • Relative weak on fixed – mobile convergence.

Not so much whether some of the above points are important or not .. they are of course important. Rather it is a question of whether the prioritization and focus is right. A question of channeling more efforts into very important (IMO) key 5G success factors, e.g., transport, convergence and designing 5G for the best user experience (and infinitely faster throughput per user is not the answer) ensuring the technology to be relevant for all customers and not only the ones who happens to be within coverage of a smallest cell.

Not surprisingly the 5G vision is a very mobile system centric. There is too little attention to fixed-mobile convergence and the transport solutions (backhaul & backbone) that will enable the very high air-interface throughputs to be carried through the telecoms network. This is also not very surprising as most mobile folks, historically did not have to worry too much about transport at least in mature advanced markets (i.e., the solutions needed was there without innovation an R&D efforts).

However, this is a problem. The required transport upgrade to support the 5G promises is likely to be very costly. The technology economics and affordability aspects of what is proposed is still very much work in progress. It is speculated that new business models and use cases will be enabled by 5G. So far little has been done in quantifying those opportunities and see whether those can justify some of the incremental cost that surely operators will incur as the deploy 5G.

CELLULAR CAPACITY … IT WORKS FOR 5G TOO!

To create more cellular capacity measured in throughput is easy or can be made so with a bit of approximations. “All” we need is an amount of frequency bandwidth Hz, an air-interface technology that allow us to efficiently carry a certain amount of information in bits per second per unit bandwidth per capacity unit (i.e., we call this spectral efficiency) and a number of capacity units or multipliers which for a cellular network is the radio cell. The most challenging parameter in this game is the spectral efficiency as it is governed by the laws of physics with a hard limit (actually silly me … bandwidth and capacity units are obviously as well), while a much greater degree of freedom governs the amount of bandwidth and of course the number of cells.

 

Spectral efficiency is given by the so-called Shannon’s Law (for the studious inclined I recommend to study his 1948 paper “A Mathematical Theory of Communications”). The consensus is that we are very close to the Shannon Limit in terms of spectral efficiency (in terms of bits per second per Hz) of the cellular air-interface itself. Thus we are dealing with diminishing returns of what can be gained by further improving error correction, coding and single-input single-output (SISO) antenna technology.

I could throw more bandwidth at the capacity problem (i.e., the reason for the infatuation with the millimeter wave frequency range as there really is a lot available up there at 30+ GHz) and of course build a lot more cell sites or capacity multipliers (i.e., definitely not very economical unless it results in a net positive margin). Of course I could (and most likely will if I had a lot of money) do both.

I could also try to be smart about the spectral efficiency and Shannon’s law. If I could reduce the need for or even avoid building more capacity multipliers or cell sites, by increasing my antenna system complexity it is likely resulting in very favorable economics. It turns out that multiple antennas acts as a multiplier (simplistic put) for the spectral efficiency compared to a simple single (or legacy) antenna system. Thus, the way to improve the spectral efficiency inevitable leads us to substantially more complex antenna technologies (e.g., higher order MiMo, massive MiMo, etc…).

Building new cell sites or capacity multiplier should always be the last resort as it is most likely the least economical option available to boost capacity.

Thus we should be committing increasingly more bandwidth (i.e., 100s – 1000s of Mhz and beyond) assuming it is available (i.e, if not we are back to adding antenna complexity and more cell sites). The need for very large bandwidths, in comparison with what is deployed in today’s cellular systems, automatically forces the choices into high frequency ranges, i.e., >3 GHz and into the millimeter wave range of above 30 GHz. The higher frequency band leads in inevitably to limited coverage and a high to massive demand for small cell deployment.

Yes! It’s a catch 22 if there ever was one. The higher carrier frequency increases the likelihood of more available bandwidth. higher carrier frequency also results in a reduced the size of our advanced complex antenna system (which is good). Both boost capacity to no end. However, my coverage area where I have engineered the capacity boost reduces approx. with the square of the carrier frequency.

Clearly, ubiquitous 5G coverage at those high frequencies (i.e., >3 GHz) would be a very silly endeavor (to put it nicely) and very un-economical.

5G, as long as the main frequency deployed is in the high or very high frequency regime, would remain a niche technology. Irrelevant to a large proportion of customers and use cases.

5G needs to be macro cellular focused to become relevant for all customers and economically beneficial to most use cases.

THE CURIOUS CASE OF LATENCY.

The first time I heard about the 5G 1 ms latency target (communicated with a straight face and lots of passion) was to ROFL. Not a really mature reaction (mea culpa) and agreed, many might have had the same reaction when J.F. Kennedy announced to put a man on the moon and safely back on Earth within 10 years. So my apologies for having had a good laugh (likely not the last to laugh though in this matter).

In Europe, the average LTE latency is around 41±9 milliseconds including pinging an external (to the network) server but does not for example include the additional time it takes to load a web page or start a video stream. The (super) low latency (1 ms and below) poses other challenges but at least relevant to the air-interface and a reasonable justification to work on a new air-interface (apart from studying channel models in the higher frequency regime). The best latency, internal to the mobile network itself, you can hope to get out of “normal” LTE as it is commercially deployed is slightly below 20 ms (without considering re-transmission). For pre-allocated LTE this can further be reduced towards the 10 ms (without considering re-transmission which adds at least 8 ms). In 1 ms light travels ca. 200 km (in optical fiber). To support use cases requiring 1 ms End-2-End latency, all transport & processing would have to be kept inside the operators network. Clearly, the physical transport path to the location, where processing of the transported data would occur, would need to be very short to guaranty 1 ms. The relative 5G latency improvement over LTE would need to be (much) better than 10 (LTE pre-allocated) to 20 times (scheduled “normal” LTE), ignoring re-transmission (which would only make the challenge bigger.

An example. Say that 5G standardization folks gets the latency down to 0.5 ms (vs the ~ 20 – 10 ms today), the 5G processing node (i.e., Data Center) cannot be more than 50 km away from the 5G-radio cell (i..e, it takes light ca. 0.5 ms travel 100 km in fiber). This latency (budget) challenge has led the Telco industry to talk about the need for so-called edge computing and the need for edge data centers to provide the 5G promise of very low latencies. Remember this is opposing the past Telco trend of increasing centralization of computing & data processing resources. Moreover, it is bound to lead to incremental cost. Thus, show me the revenues.

There is no doubt that small, smaller and smallest 5G cells will be essential for providing the very lowest latencies and the smallness is coming for “free” given the very high frequencies planned for 5G. The cell environment of a small cell is more ideal than a macro-cellular harsh environment. Thus minimizing the likelihood of re-transmission events. And distances are shorter which helps as well.

I believe that converged telecommunications operators, are in a better position (particular compared to mobile only operations) to leverage existing fixed infrastructure for a 5G architecture relying on edge data centers to provide very low latencies. However, this will not come for free and without incremental costs.

How much faster is fast enough from a customer experience perspective? According with John Carmack, CTO of Oculus Rift, “.. when absolute delays are below approximately 20 milliseconds they are generally imperceptible.” particular as it relates to 3D systems and VR/AR user experience which is a lot more dynamic than watching content loading. According to recent research specific to website response time indicates that anything below 100 ms wil be perceived as instantaneous. At 1 second users will sense the delay but would be perceived as seamless. If a web page loads in more than 2 seconds user satisfaction levels drops dramatically and a user would typically bounce. Please do note that most of this response or download time overhead has very little to do with connection throughput, but to do with a host of other design and configuration issues. Cranking up the bandwidth will not per se solve poor browsing performance.

End-2-End latency in the order of 20 ms are very important for a solid high quality VR user experience. However, to meet this kind of performance figure the VR content needs to be within the confines for the operator’s own network boundaries.

End-2-End (E2E) latencies of less than 100 ms would in general be perceived as instantaneous for normal internet consumption (e.g., social media, browsing, …). However that this still implies that operators will have to focus on developing internal to their network’s latencies far below the over-all 100 ms target and that due to externalities might try to get content inside their networks (and into their own data centers).

A 10-ms latency target, while much less moonshot, would be a far more economical target to strive for and might avoid substantial incremental cost of edge computing center deployments. It also resonates well with the 20 ms mentioned above, required for a great VR experience (leaving some computing and process overhead).

The 1-ms vision could be kept for use cases involving very short distances, highly ideal radio environment and with compute pretty much sitting on top of the whatever needs this performance, e.g., industrial plants, logistic / warehousing, …

Finally, the targeted extreme 5G speeds will require very substantial bandwidths. Such large bandwidths are readily available in the high frequency ranges (i.e., >3 GHz). The high frequency domain makes a lot of 5G technology challenges easier to cope with. Thus cell ranges will be (very) limited in comparison to macro cellular ones, e.g., Barclays Equity Research projects 10x times more cells will be required for 5G (10x!). 5G coverage will not match that of the macro cellular (LTE) network. In which case 5G will remain niche. With a lot less relevance to consumers. Obviously, 5G will have to jump the speed divide (a very substantial divide) to the macro cellular network to become relevant to the mass market. Little thinking appears to be spend on this challenge currently.     

THE VERY FINE ART OF DETECTING MYTH & BALONEY.

Carl Sagan, in his great article  The Fine Art of Baloney Detection, states that one should “Try not to get overly attached to a hypothesis just because it’s yours.”. Although Carl Sagan starts out discussing the nature of religious belief and the expectations of an afterlife, much of his “Baloney Detection Kit” applies equally well to science & technology. In particular towards our expert expectations towards consumerism and its most likely demand. After all, isn’t Technology in some respects our new modern day religion?

Some might have the impression that expectations towards 5G, is the equivalent of a belief in an afterlife or maybe more accurately resurrection of the Telco business model to its past glory. It is almost like a cosmic event, where after entropy death, the big bang gives birth to new, and supposedly unique (& exclusive) to our Telco industry, revenue streams that will make  all alright (again). There clearly is some hype involved in current expectations towards 5G, although the term still has to enter the Gartner hype cycle report (maybe 2017 will be the year?).

The cynic (mea culpa) might say that it is in-evitable that there will be a 5G after 4G (that came after 3G (that came after 2G)). We also would expect 5G to be (a lot) better than 4G (that was better than 3G, etc..).

so …

Well … Better for who? … Better for Telcos? Better for Suppliers? Better revenues? Their Shareholders? Better for our Consumers? Better for our Society? Better for (engineering) job security? … Better for Everyone and Everything? Wow! Right? … What does better mean?

  • Better speed … Yes! … Actually the 5G vision gives me insanely better speeds than LTE does today.
  • Better latency … Internal to the operator’s own network Yes! … Not per default noticeable for most consumer use cases relying on the externalities of the internet.
  • Better coverage … well if operators can afford to provide 100% 5G coverage then certainly Yes! Consumers would benefit even at a persistent 50 Mbps level.
  • Better availability …I don’t really think that Network Availability is a problem for the general consumer where there is coverage (at least not in mature markets, Myanmar absolutely … but that’s an infrastructure problem rather than a cellular standard one!) … Whether 100% availability is noticeable or not will depend a lot on the starting point.
  • Better (in the sense of more) revenues … Work in Progress!
  • Better margins … Only if incremental 5G cost to incremental 5G revenue is positive.
  • etc…

Recently William Webb published a book titled “The 5G Myth: And why consistent connectivity is a better future” (reminder: a myth is a belief or set of beliefs, often unproven or false, that have accrued around a person, phenomenon, or institution). William Web argues;

  • 5G vision is flawed and not the huge advance in global connectivity as advertised.
  • The data rates promised by 5G will not be sufficiently valued by the users.
  • The envisioned 5G capacity demand will not be needed.
  • Most operators can simply not afford the cost required to realize 5G.
  • Technology advances are in-sufficient to realize the 5G vision.
  • Consistent connectivity is the more important aim of a 5G technology.

I recommend all to read William Webb’s well written and even better argued book. It is one for the first more official critiques of the 5G Vision. Some of the points certainly should have us pause and maybe even re-evaluate 5G priorities. If anything, it helps to sharpen 5G arguments.

Despite William Webb”s critique of 5G, one need to realize that a powerful technology vision of what 5G could be, even if very moonshot, does leapfrog innovation, needed to take a given technology too a substantially higher level, than what might otherwise be the case. If the 5G whitepaper by Rachid El Hattachi & Javan Erfanian had “just” been about better & consistent coverage, we would not have had the same technology progress independent of whether the ultimate 5G end game is completely reachable or not. Moreover, to be fair to the NGMN whitepaper, it is not that the whitepaper does not consider consistent connectivity, it very much does. It is more a matter of where lies the main attention of the industry at this moment. That attention is not on consistent connectivity but much more on niche use cases (i.e., ultra high bandwidth at ultra low latencies).

Rest assured, over the next 10 to 15 years we will see whether William Webb will end up in the same category as other very smart in the know people getting their technology predictions proven wrong (e.g., IBM Chairman Thomas Watson’s famous 1943 quote that “… there is a world market for maybe five computers.” and NO! despite claims of the contrary Bill Gates never said “640K of memory should be enough for anybody.”).

Another, very worthy 5G analysis, also from 2016, is the Barclays Equity Research “5G – A new Dawn”  (September 2016) paper. The Barclays 5G analysis concludes ;

  • Mobile operator’s will need 10x more sites over the next 5 to 10 years driven by 5G demand.
  • There will be a strong demand for 5G high capacity service.
  • The upfront cost for 5G will be very substantial.
  • The cost of data capacity (i.e., Euro per GB) will fall approx. a factor 13 between LTE and 5G (note: this is “a bit” of a economic problem when capacity is supposed to increase a factor 50).
  • Sub-scale Telcos, including mobile-only operations, may not be able to afford 5G (note: this point, if true, should make the industry very alert towards regulatory actions).
  • Having a modernized super-scalable fixed broadband transport network likely to be a 5G King Maker (note: Its going to be great to be an incumbent again).

To the casual observer, it might appear that Barclays is in strong opposition to William Webb’s 5G view. However, maybe that is not completely so.

If it is true, that only very few Telco’s, primarily modernized incumbent fixed-mobile Telco’s, can afford to build 5G networks, one might argue that the 5G Vision is “somewhat” flawed economically. The root cause for this assumed economical flaw (according with Barclays, although they do not point out it is a flaw!) clearly is the very high 5G speeds, assumed to be demanded by the user. Resulting in massive increase in network densification and need for radically modernized & re-engineered transport networks to cope with this kind of demand.

Barclays assessments are fairly consistent with the illustration shown below of the likely technology cost impact, showing the challenges a 5G deployment might have;

Some of the possible operational cost improvements in IT, Platforms and Core shown in the above illustration arises from the natural evolving architectural simplifications and automation strategies expected to be in place by the time of the 5G launch. However, the expected huge increase in small cells are the root cause of most of the capital and operational cost pressures expected to arise with 5G. Depending on the original state of the telecommunications infrastructure (e.g., cloudification, virtualization,…), degree of transport modernization (e.g., fiberization), and business model (e.g., degree of digital transformation), the 5G economical impact can be relative modest (albeit momentarily painful) to brutal (i.e., little chance of financial return on investment). As discussed in the Barclays “5G – A new dawn” paper.

Furthermore, if the relative cost of delivering a 5G Byte is 13 – 14 times lower than an LTE Byte, and the 5G capacity demand is 50 times higher than LTE, the economics doesn’t work out very well. So if I can produce a 5G Byte at 1/14th of an LTE Byte, but my 5G Byte demand is 50x higher than in LTE, I could (simplistically) end up with more than 3x more absolute cost for 5G. That’s really Ugly! Although if Barclays are correct in the factor 10 higher number of 5G sites, then a (relevant) cost increase of factor 3 doesn’t seem completely unrealistic. Of course Barclays could be wrong! Unfortunately, an assessment of the incremental revenue potential has yet to be provided. If the price for a 5G Byte could be in excess of a factor 3 of an LTE Byte … all would be cool!

If there is something to be worried about, I would worry much more about the Barclays 5G analysis than the challenges of William Webb (although certainly somehow intertwined).

What is the 5G market potential in terms of connections?

At this moment very few 5G market uptake forecasts have yet made it out in the open. However, taking the Strategy Analytics August 2016 5G FC of ca. 690 million global 5G connections by year 2025 we can get an impression of how 5G uptake might look like;

Caution! Above global mobile connection forecast is likely to change many time as we approaches commercial launch and get much better impression of the 5G launch strategies of the various important players in the Telco Industry. In my own opinion, if 5G will be launched primarily in the mm-wave bands around and above 30 GHz, I would not expect to see a very aggressive 5G uptake. Possible a lot less than the above (with the danger of putting myself in the category of badly wrong forecasts of the future). If 5G would be deployed as an overlay to existing macro-cellular networks … hmmm who knows! maybe above would be a very pessimistic view of 5G uptake?

THE 5G PROMISES (WHAT OTHERS MIGHT CALL A VISION).

Let’s start with the 5G technology vision as being presented by NGMN and GSMA.

GSMA (Groupe Speciale Mobile Association) 2014 paper entitled ‘Understanding 5G: Perspective on future technology advancements in mobile’ have identified 8 main requirements; 

1.    1 to 10 Gbps actual speed per connection at a max. of 10 millisecond E2E latency.

Note 1: This is foreseen in the NGMN whitepaper only to be supported in dense urban areas including indoor environments.

Note 2: Throughput figures are as experienced by the user in at least 95% of locations for 95% of the time.

Note 3: In 1 ms speed the of light travels ca. 200 km in optical fiber.

2.    A Minimum of 50 Mbps per connection everywhere.

Note 1: this should be consistent user experience outdoor as well as indoor across a given cell including at the cell edge.

Note 2: Another sub-target under this promise was ultra-low cost Networks where throughput might be as low as 10 Mbps.

3.    1,000 x bandwidth per unit area.

Note: notice the term per unit area & think mm-wave frequencies; very small cells, & 100s of MHz frequency bandwidth. This goal is not challenging in my opinion.

4.    1 millisecond E2E round trip delay (tactile internet).

Note: The “NGMN 5G White Paper” does have most 5G use cases at 10 ms allowing for some slack for air-interface latency and reasonable distanced transport to core and/or aggregation points.

5.    Massive device scale with 10 – 100 x number of today’s connected devices.

Note: Actually, if one believes in the 1 Million Internet of Things connections per km2 target this should be aimed close to 1,000+ x rather than the 100 x for an urban cell site comparison.

6.    Perception of 99.999% service availability.

Note: ca. 5 minutes of service unavailability per year. If counted on active usage hours this would be less than 2.5 minutes per year per customer or less than 1/2 second per day per customer.

7.    Perception of 100% coverage.

Note: In 2015 report from European Commission, “Broadband Coverage in Europe 2015”, for EU28, 86% of households had access to LTE overall. However, only 36% of EU28 rural households had access to LTE in 2015.

8.    90% energy reduction of current network-related energy consumption.

Note: Approx. 1% of a European Mobile Operator’s total Opex.

9.    Up-to 10 years battery life for low-power Internet of Things 5G devices. 

The 5G whitepaper also discusses new business models and business opportunities for the Telco industry. However, there is little clarity on what would be the relevant 5G business targets. In other words, what would 5G as a technology bring, in additional Revenues, in Churn reduction, Capex & Opex (absolute) Efficiencies, etc…

More concrete and tangible economical requirements are badly required in the 5G discussion. Without it, is difficult to see how Technology can ensure that the 5G system that will be developed is also will be relevant for the business challenges in 2020 and beyond.

Today an average European Mobile operator spends approx. 40 Euro in Total Cost of Ownership (TCO) per customer per anno on network technology (and slightly less on average per connection). Assuming a capital annualization rate of 5 years and about 15% of its Opex relates to Technology (excluding personnel cost).

The 40 Euro TCO per customer per anno sustains today an average LTE EU28 customer experience of 31±9 Mbps downlink speed @ 41±9 ms (i.e., based on OpenSignal database with data as of 23 December 2016). Of course this also provides for 3G/HSPA network sustenance and what remains of the 2G network.

Thus, we might have a 5G TCO ceiling at least without additional revenue. The maximum 5G technology cost per average speed (in downlink) of 1 – 10 Gbps @ 10 ms should not be more than 40 Euro TCO per customer per anno (i.e, and preferably a lot less at the time we eventually will launch 5G in 2020).

 

Thus, our mantra when developing the 5G system should be:

5G should not add additional absolute cost burden to the Telecom P&L.

and also begs the question of proposing some economical requirements to partner up with the technology goals.

 

5G ECONOMIC REQUIREMENTS (TO BE CONSIDERED).

  • 5G should provide new revenue opportunities in excess of 20% of access based revenue (e.g., Europe mobile access based revenue streams by 2021 expected to be in the order of 160±20 Billion Euro; thus the 5G target for Europe should be to add an opportunity of ca. 30±5 Billion in new non-access based revenues).
  • 5G should not add to Technology  TCO while delivering up-to 10 Gbps @ 10 ms (with a floor level of 1 Gbps) in urban areas.
  • 5G focus on delivering macro-cellular customer experience at minimum 50 Mbps @ maximum 10 ms.
  • 5G should target 20% reduction of Technology TCO while delivering up-to 10 Gbps @ 10 ms (min. 1 Gbps).
  • 5G should keep pursuing better spectral efficiency (i.e., Mbps/MHz/cell) not only through means antennas designs, e.g., n-order MiMo and Massive-MiMo, that are largely independent of the air-interface (i.e., works as well with LTE).
  • Target at least 20% 5G device penetration within first 2 years of commercial launch (note: only after 20% penetration does the technology efficiency become noticeable).

In order not to increment the total technology TCO, we would at the very least need to avoid adding additional physical assets or infrastructure to the existing network infrastructure. Unless such addition provide a net removal of other physical assets and thus associated cost. This is in the current high frequency, and resulting demand for huge amount of small cells, going to be very challenging but would be less so by focusing more on macro cellular exploitation of 5G.

Thus, there need to be a goal to also overlay 5G on our existing macro-cellular network. Rather than primarily focus on small, smaller and smallest cells. Similar to what have been done for LT and was a much more challenge with UMTS (i.e., due to optimum cellular grid mismatch between the 2G voice-based and the 3G more data-centric higher frequency network).

What is the cost reference that should be kept in mind?

As shown below, the pre-5G technology cost is largely driven by access cost related to the number of deployed sites in a given network and the backhaul transmission.

Adding more sites, macro-cellular or a high number of small cells, will increase Opex and add not only a higher momentary Capex demand, but also burden future cash requirements. Unless equivalent cost can removed by the 5G addition.

Obviously, if adding additional physical assets leads to verifiable incremental margin, then accepting incremental technology cost might be perfectly okay (let”s avoid being radical financial controllers).

Though its always wise to remember;

Cost committed is a certainty, incremental revenue is not.

NAUGHTY … IMAGINE A 5G MACRO CELLULAR NETWORK (OHH JE!).

From the NGMN whitepaper, it is clear that 5G is supposed to be served everywhere (albeit at very different quality levels) and not only in dense urban areas. Given the economical constraints (considered very lightly in the NGMN whitepaper) it is obvious that 5G would be available across operators existing macro-cellular networks and thus also in the existing macro cellular spectrum regime. Not that this gets a lot of attention.

In the following, I am proposing a 5G macro cellular overlay network providing a 1 Gbps persistent connection enabled by massive MiMo antenna systems. This though experiment is somewhat at odds with the NGMN whitepaper where their 50 Mbps promise might be more appropriate. Due to the relative high frequency range in this example, massive MiMo might still be practical as a deployment option.

If you follow all the 5G news, particular on 5G trials in US and Europe, you easily could get the impression that mm-wave frequencies (e.g., 30 GHz up-to 300 GHz) are the new black.

There is the notion that;

“Extremely high frequencies means extremely fast 5G speeds”

which is baloney! It is the extremely large bandwidth, readily available in the extremely high frequency bands, that make for extremely fast 5G (and LTE of course) speeds.

We can have GHz bandwidths instead of MHz (i.e, 1,000x) to play with! … How extremely cool is that not? We totally can suck at fundamental spectral efficiency and still get out extremely high throughputs for the consumers data consumption.

While this mm-wave frequency range is very cool, from an engineering perspective and for sure academically as well, it is also extremely non-matching our existing macro-cellular infrastructure with its 700 to 2.6 GHz working frequency range. Most mobile networks in Europe have been build on a 900 or 1800 MHz fundamental grid, with fill in from UMTS 2100 MHz coverage and capacity requirements.

Being a bit of a party pooper, I asked whether it wouldn’t be cool (maybe not to the extreme … but still) to deploy 5G as an overlay on our existing (macro) cellular network? Would it not be economically more relevant to boost the customer experience across our macro-cellular networks, that actually serves our customers today? As opposed to augment the existing LTE network with ultra hot zones of extreme speeds and possible also an extreme number of small cells.

If 5G would remain an above 3 GHz technology, it would be largely irrelevant to the mass market and most use cases.

A 5G MACRO CELLULAR THOUGHT EXAMPLE.

So let’s be (a bit) naughty and assume we can free up 20MHz @ 1800 MHz. After all, mobile operators tend to have a lot of this particular spectrum anyway. They might also re-purpose 3G/LTE 2.1 GHz spectrum (possibly easier than 1800 MHz pending overall LTE demand).

In the following, I am ignoring that whatever benefits I get out of deploying higher-order MiMo or massive MiMo (mMiMo) antenna systems, will work (almost) equally well for LTE as it will for 5G (all other things being equal).

Remember we are after

  • A lot more speed. At least 1 Gbps sustainable user throughput (in the downlink).
  • Ultra-responsiveness with latencies from 10 ms and down (E2E).
  • No worse 5G coverage than with LTE (at same frequency).

Of course if you happen to be a NGMN whitepaper purist, you will now tell me that I my ambition should only be to provide sustainable 50 Mbps per user connection. It is nevertheless an interesting thought exercise to explore whether residential areas could be served, by the existing macro cellular network, with a much higher consistent throughput than 50 Mbps that might ultimately be covered by LTE rather than needing to go to 5G. Anywhere both Rachid El Hattachi and Jarvan Erfenian knew well enough to hedge their 5G speed vision against the reality of economics and statistical fluctuation.

and I really don’t care about the 1,000x (LTE) bandwidth per unit area promise!

Why? The 1,000x promise It is fairly trivial promise. To achieve it, I simply need a high enough frequency and a large enough bandwidth (and those two as pointed out goes nicely hand in hand). Take a 100 meter 5G-cell range versus a 1 km LTE-cell range. The 5G-cell is 100 times smaller in coverage area and with 10x more 5G spectral bandwidth than for LTE (e.g., 200 MHz 5G vs 20 MHz LTE), I would have the factor 1,000 in throughput bandwidth per unit area. This without having to assume mMiMo that I could also choose to use for LTE with pretty much same effect.

Detour to the cool world of Academia: University of Bristol published recently (March 2016) a 5G spectral efficiency of ca. 80 Mbps/MHz in a 20 MHz channel. This is about 12 times higher than state of art LTE spectral efficiency. Their base station antenna system was based on so-called massive MiMo (mMiMo) with 128 antenna elements, supporting 12 users in the cell as approx. 1.6 Gbps (i.e., 20 MHz x 80 Mbps/MHz). The proof of concept system operated 3.5 GHz and in TDD mode (note: mMiMo does not scale as well for FDD and pose in general more challenges in terms of spectral efficiency). National Instruments provides a very nice overview of 5G MMiMo systems in their whitepaper “5G Massive MiMo Testbed: From Theory to Reality”.

A picture of the antenna system is shown below;

Figure above: One of the World’s First Real-Time massive MIMO Testbeds–Created at Lund University. Source: “5G Massive MiMo (mMiMo) Testbed: From Theory to Reality” (June 2016).

For a good read and background on advanced MiMo antenna systems I recommend Chockalingam & Sundar Rajan’s book on “Large MiMo Systems” (Cambridge University Press, 2014). Though there are many excellent accounts of simple MiMo, higher-order MiMo, massive MiMo, Multi-user MiMo antenna systems and the fundamentals thereof.

Back to naughty (i.e., my 5G macro cellular network);

So let’s just assume that the above mMiMO system, for our 5G macro-cellular network,

  • Ignoring that such systems originally were designed and works best for TDD based systems.
  • and keeping in mind that FDD mMiMo performance tends to be lower than TDD all else being equal.

will, in due time, be available for 5G with a channel of at least 20 MHz @ 1800MHz. And at a form factor that can be integrated well with existing macro cellular design without incremental TCO.

This is a very (VERY!) big assumption. Requirements of substantially more antenna space for massive MiMo systems, at normal cellular frequency ranges, are likely to result. Structural integrity of site designs would have to be checked and possibly be re-enforced to allow for the advanced antenna system, contributing to both additional capital cost and possible incremental tower/site lease.

So we have (in theory) a 5G macro-cellular overlay network with at least cell speeds of 1+Gbps, which is ca. 10 – 20 times that of today’s LTE networks cell performance (not utilizing massive MiMo!). If I have more 5G spectrum available, the performance would increase linearly (and a bit) accordingly.

The observant reader will know that I have largely ignored the following challenges of massive MiMo (see also Larsson et al’s “Massive MiMo for Next Generation Wireless Systems” 2014 paper);

  1. mMiMo designed for TDD, but works at some performance penalty for FDD.
  2. mMiMo will really be deployable at low total cost of ownership (i.e., it is not enough that the antenna system itself is low cost!).
  3. mMiMo performance leap frog comes at the price of high computational complexity (e.g., should be factored into the deployment cost).
  4. mMiMo relies on distributed processing algorithms which at this scale is relative un-exploited territory (i.e., should be factored into the deployment cost).

But wait a minute! I might (naively) theorize away additional operational cost of the active electronics and antenna systems on the 5G cell site (overlaid on legacy already present!). I might further assume that the Capex of the 5G radio & antenna system can be financed within the regular modernization budget (assuming such a budget exists). But … But surely our access and core transport networks have not been scaled for a factor 10 – 20 (and possibly a lot more than that) in crease in throughput per active customer?

No it has not! Really Not!

Though some modernized converged Telcos might be a lot better positioned for thefixed broadband transformation required to sustain the 5G speed promise.

For most mobile operators, it is highly likely that substantial re-design and investments of transport networks will have to be made in order to support the 5G target performance increase above and beyond LTE.

Definitely a lot more on this topic in a subsequent Blog.

ON THE 5G PROMISES.

Lets briefly examine the 8 above 5G promises or visionary statements and how these impact the underlying economics. As this is an introductory chapter, the deeper dive and analysis will be referred to subsequent chapters.

NEED FOR SPEED.

PROMISE 1: From 1 to 10 Gbps in actual experienced 5G speed per connected device (at a max. of 10 ms round-trip time).

PROMISE 2: Minimum of 50 Mbps per user connection everywhere (at a max. of 10 ms round-trip time).

PROMISE 3: Thousand times more bandwidth per unit area (compared to LTE).

Before anything else, it would be appropriate to ask a couple of questions;

“Do I need this speed?” (The expert answer if you are living inside the Telecom bubble is obvious! Yes Yes Yes ….Customer will not know they need it until they have it! …).

“that kind of sustainable speed for what?” (Telekom bubble answer would be! Lots of useful things! … much better video experience, 4K, 8K, 32K –> fully emerged holographic VR experience … Lots!)

“am I willing to pay extra for this vast improvement in my experience?” (Telekom bubble answer would be … ahem … that’s really a business model question and lets just have marketing deal with that later).

What is true however is:

My objective measurable 5G customer experience, assuming the speed-coverage-reliability promise is delivered, will quantum leap to un-imaginable levels (in terms of objectively measured performance increase).

Maybe more importantly, will the 5G customer experience from the very high speed and very low latency really be noticeable to the customer? (i.e, the subjective or perceived customer experience dimension).

Let’s ponder on this!

In Europe end of 2016, the urban LTE speed and latency user experience per connection would of course depend on which network the customer would be (not all being equal);

In 2016 on average in Europe an urban LTE user, experienced a DL speed of 31±9 Mbps, UL speed of 9±2 Mbps and latency around 41±9 milliseconds. Keep in mind that OpenSignal is likely to be closer to the real user’s smartphone OTT experience, as it pings a server external to the MNOs network. It should also be noted that although the OpenSignal measure might be closer to the real customer experience, it still does not provide the full experience from for example page load or video stream initialization and start.

The 31 Mbps urban LTE user experience throughput provides for a very good video streaming experience at 1080p (e.g., full high definition video) even on a large TV screen. Even a 4K video stream (15 – 32 Mbps) might work well, provided the connection stability is good and that you have the screen to appreciate the higher resolution (i.e., a lot bigger than your 5” iPhone 7 Plus). You are unlikely to see the slightest difference on your mobile device between the 1080p (9 Mbps) and 480p (1.0 – 2.3 Mbps) unless you are healthy young and/or with a high visual acuity which is usually reserved for the healthy & young.

With 5G, the DL speed is targeted to be at least 1 Gbps and could be as high as 10 Gbps, all delivered within a round trip delay of maximum 10 milliseconds.

5G target by launch (in 2020) is to deliver at least 30+ times more real experienced bandwidth (in the DL) compared to what an average LTE user would experience in Europe 2016. The end-2-end round trip delay, or responsiveness, of 5G is aimed to be at least 4 times better than the average experienced responsiveness of LTE in 2016. The actual experience gain between LTE and 3G has been between 5 – 10 times in DL speed, approx. 3 –5 times in UL and between 2 to 3 times in latency (i.e., pinging the same server exterior to the mobile network operator).

According with Sandvine’s 2015 report on “Global Internet Phenomena Report for APAC & Europe”, in Europe approx. 46% of the downstream fixed peak aggregate traffic comes from real-time entertainment services (e.g., video & audio streamed or buffered content such as Netflix, YouTube and IPTV in general). The same report also identifies that for Mobile (in Europe) approx. 36% of the mobile peak aggregate traffic comes from real-time entertainment. It is likely that the real share of real-time entertainment is higher, as video content embedded in social media might not be counted in the category but rather in Social Media. Particular for mobile, this would bring up the share with between 10% to 15% (more in line with what is actually measured inside mobile networks). Real-time entertainment and real-time services in general is the single most important and impacting traffic category for both fixed and mobile networks.

Video viewing experience … more throughput is maybe not better, more could be useless.

Video consumption is a very important component of real-time entertainment. It amounts to more than 90% of the bandwidth consumption in the category. The Table below provides an overview of video formats, number of pixels, and their network throughput requirements. The tabulated screen size is what is required (at a reasonable viewing distance) to detect the benefit of a given video format in comparison with the previous. So in order to really appreciate 4K UHD (ultra high definition) over 1080p FHD (full high definition), you would as a rule of thumb need double the screen size (note there are also other ways to improved the perceived viewing experience). Also for comparison, the Table below includes data for mobile devices, which obviously have a higher screen resolution in terms of pixels per inch (PPI) or dots per inch (DPI). Apart from 4K (~8 MP) and to some extend  8K (~33 MP), the 16K (~132 MP) and 32K (~528 MP) are still very yet exotic standards with limited mass market appeal (at least as of now).

We should keep in mind that there are limits to the human vision with the young and healthy having a substantial better visual acuity than what can be regarded as normal 20/20 vision. Most magazines are printed at 300 DPI and most modern smartphone displays seek to design for 300 DPI (or PPI) or more. Even Steve Jobs has addressed this topic;

However, it is fair to point out that  this assumed human vision limitation is debatable (and have been debated a lot). There is little consensus on this, maybe with the exception that the ultimate limit (at a distance of 4 inch or 10 cm) is 876 DPI or approx. 300 DPI (at 11.5 inch / 30 cm).

Anyway, what really matters is the customers experience and what they perceive while using their device (e.g., smartphone, tablet, laptop, TV, etc…).

So lets do the visual acuity math for smartphone like displays;

We see (from the above chart) that for an iPhone 6/7 Plus (5.5” display) any viewing distance above approx. 50 cm, a normal eye (i.e., 20/20 vision) would become insensitive to video formats better than 480p (1 – 2.3 Mbps). In my case, my typical viewing distance is ca. 30+ cm and I might get some benefits from 720p (2.3 – 4.5 Mbps) as opposed to 480p. Sadly my sight is worse than the norm of 20/20 (i.e., old! and let’s just leave it at that!) and thus I remain insensitive to the resolution improvements 720p would provide. If you have a device with at or below 4” display (e.g., iPhone 5 & 4) the viewing distance where normal eyes become insensitive is ca. 30+ cm.

All in all, it would appear that unless cellular user equipment, and the way these are being used, changes very fundamentally the 480p to 720p range might be more than sufficient.

If this is true, it also implies that a cellular 5G user on a reliable good network connection would need no more than 4 – 5 Mbps to get an optimum viewing (and streaming) experience (i.e., 720p resolution).

The 5 Mbps streaming speed, for optimal viewing experience, is very far away from our 5G 1-Gbps promise (x200 times less)!

Assuming instead of streaming we want to download movies, assuming we lots of memory available on our device … hmmm … then a typical 480p movie could be download in ca. 10 – 20 seconds at 1Gbps, a 720p movie between 30 and 40 seconds, and a 1080p would take 40 to 50 seconds (and likely a waste due to limitations to your vision).

However with a 5G promise of super reliable ubiquitous coverage, I really should not need to download and store content locally on storage that might be pretty limited.

Downloads to cellular devices or home storage media appears somewhat archaic. But would benefit from the promised 5G speeds.

I could share my 5G-Gbps with other users in my surrounding. A typical Western European household in 2020 (i.e., about the time when 5G will launch) would have 2.17 inhabitants (2.45 in Central Eastern Europe), watching individual / different real-time content would require multiples of the bandwidth of the optimum video resolution. I could have multiple video streams running in parallel, to likely the many display devices that will be present in the consumer’s home, etc… Still even at fairly high video streaming codecs, a consumer would be far away from consuming the 1-Gbps (imagine if it was 10 Gbps!).

Okay … so video consumption, independent of mobile or fixed devices, does not seem to warrant anywhere near the 1 – 10 Gbps per connection.

Surely EU Commission wants it!

EU Member States have their specific broadband coverage objectives – namely: ‘Universal Broadband Coverage with speeds at least 30 Mbps by 2020’ (i.e, will be met by LTE!) and ‘Broadband Coverage of 50% of households with speeds at least 100 Mbps by 2020 (also likely to be met with LTE and fixed broadband means’.

The European Commission’s “Broadband Coverage in Europe 2015” reports that 49.2% of EU28 Households (HH) have access to 100 Mbps (i.e., 50.8% of all HH have access to less than 100 Mbps) or more and 68.2% to broadband speeds above 30 Mbps (i.e., 32.8% of all HH with access to less than 30 Mbps). No more than 20.9% of HH within EU28 have FTTP (e.g., DE 6.6%, UK UK 1.4%, FR 15.5%, DK 57%).

The EU28 average is pretty good and in line with the target. However, on an individual member state level, there are big differences. Also within each of the EU member states great geographic variation is observed in broadband coverage.

Interesting, the 5G promises to per user connection speed (1 – 10 Gbps), coverage (user perceived 100%) and reliability (user perceived 100%) is far more ambitious that the broadband coverage objectives of the EU member states.

So maybe indeed we could make the EU Commission and Member States happy with the 5G Throughput promise. (this point should not be underestimated).

Web browsing experience … more throughput and all will be okay myth!

So … Surely, the Gbps speeds can help provide a much faster web browsing / surfing experience than what is experienced today for LTE and for the fixed broadband? (if there ever was a real Myth!).

In other words the higher the bandwidth, the better the user’s web surfing experience should become.

While bandwidth (of course) is a factor in customers browsing experience, it is but a factor out of several that also governs the customers real & perceived internet experience; e.g., DNS Lookups (this can really mess up user experience), TCP, SSL/TLS negotiation, HTTP(S) requests, VPN, RTT/Latency, etc…

An excellent account of these various effects is given by Jim Getty’s “Traditional AQM is not enough” (i.e., AQM: Active Queue Management). Measurements (see Jim Getty’s blog) strongly indicates that at a given relative modest bandwidth (>6+ Mbps) there is no longer any noticeable difference in page load time. In my opinion there are a lot of low hanging fruits in network optimization that provides large relative improvements in customer experience than network speed alone..

Thus one might carefully conclude that, above a given throughput threshold it is unlikely that more throughput would have a significant effect on the consumers browsing experience.

More work needs to be done in order to better understand the experience threshold after which more connection bandwidth has diminishing returns on the customer’s browsing experience. However, it would appear that 1-Gbps 5G connection speed would be far above that threshold. An average web page in 2016 was 2.2 MB which from an LTE speed perspective would take 568 ms to load fully provided connection speed was the only limitation (which is not the case). For 5G the same page would download within 18 ms assuming that connection speed was the only limitation.

Downloading content (e.g., FTTP). 

Now we surely are talking. If I wanted to download the whole Library of the US Congress (I like digital books!), I am surely in need for speed!?

The US Congress have estimated that the whole print collection (i.e., 26 million books) adds up to 208 terabytes.Thus assuming I have 208+ TB of storage, I could within 20+ (at 1 Gbps) to 2+ (at 20 Gbps) days download the complete library of the US Congress.

In fact, at 1 Gbps would allow me to download 15+ books per second (assuming 1 book is on average 3oo pages and formatted at 600 DPI TIFF which is equivalent to ca. 8 Mega Byte).

So clearly, for massive file sharing (music, videos, games, books, documents, etc…), the 5G speed promise is pretty cool.

Though, it does assume that consumers would continue to see a value in storing information locally on their personally devices or storage medias. The idea remains archaic, but I guess there will always be renaissance folks around.

What about 50 Mbps everywhere (at a 10 ms latency level)?

Firstly, providing a customers with a maximum latency of 10 ms with LTE is extremely challenging. It would be highly unlikely to be achieved within existing LTE networks, particular if transmission retrials are considered. From OpenSignal December 2016 measurements shown in the chart below, for urban areas across Europe, the LTE latency is on average around 41±9 milliseconds. Considering the LTE latency variation we are still 3 – 4 times away from the 5G promise. The country average would be higher than this. Clearly this is one of the reasons why the NGMN whitepaper proposes a new air-interface. As well as some heavy optimization and redesigns in general across our Telco networks.

The urban LTE persistent experience level is very reasonable but remains lower than the 5G promise of 50 Mbps, as can be seen from the chart below;

The LTE challenge however is not the customer experience level in urban areas but on average across a given geography or country. Here LTE performs substantially worse (also on throughput) than what the NGMN whitepaper’s ambition is. Let us have a look at the current LTE experience level in terms of LTE coverage and in terms of (average) speed.

Based on European Commission “Broadband Coverage in Europe 2015” we observe that on average the total LTE household coverage is pretty good on an EU28 level. However, the rural households are in general underserved with LTE. Many of the EU28 countries still lack LTE consistent coverage in rural areas. As lower frequencies (e.g., 700 – 900 MHz) becomes available and can be overlaid on the existing rural networks, often based on 900 MHz grid, LTE rural coverage can be improved greatly. This economically should be synchronized with the normal modernization cycles. However, with the current state of LTE (and rural network deployments) it might be challenging to reach a persistent level of 50 Mbps per connection everywhere. Furthermore, the maximum 10 millisecond latency target is highly unlikely to be feasible with LTE.

In my opinion, 5G would be important in order to uplift the persistent throughput experience to at least 50 Mbps everywhere (including cell edge). A target that would be very challenging to reach with LTE in the network topologies deployed in most countries (i.e., particular outside urban/dense urban areas).

The customer experience value to the general consumer of a maximum 10 millisecond latency is in my opinion difficult to assess. At a 20 ms response time would most experiences appear instantaneous. The LTE performance of ca. 40 ms E2E external server response time, should satisfy most customer experience use case requirements beside maybe VR/AR.

Nevertheless, if the 10 ms 5G latency target can be designed into the 5G standard without negative economical consequences then that might be very fine as well.

Another aspect that should be considered is the additional 5G market potential of providing a persistent 50 Mbps service (at a good enough & low variance latency). Approximately 70% of EU28 households have at least a 30 Mbps broadband speed coverage. If we look at EU28 households with at least 50 Mbps that drops to around 55% household coverage. With the 100% (perceived)coverage & reliability target of 5G as well as 50 Mbps everywhere, one might ponder the 30% to 45% potential of households that are likely underserved in term of reliable good quality broadband. Pending the economics, 5G might be able to deliver good enough service at a substantial lower cost compared more fixed centric means.

Finally, following our expose on video streaming quality, clearly a 50 Mbps persistent 5G connectivity would be more than sufficient to deliver a good viewing experience. Latency would be less of an issue in the viewing experience as longs as the variation in the latency can be kept reasonable low.

 

Acknowledgement

I greatly acknowledge my wife Eva Varadi for her support, patience and understanding during the creative process of creating this Blog.

 

WORTHY 5G & RELATED READS.

  1. “NGMN 5G White Paper” by R.El Hattachi & J. Erfanian (NGMN Alliance, February 2015).
  2. “Understanding 5G: Perspectives on future technological advancement in mobile” by D. Warran & C. Dewar (GSMA Intelligence December 2014).
  3. “Fundamentals of 5G Mobile Networks” by J. Rodriguez (Wiley 2015).
  4.  “The 5G Myth: And why consistent connectivity is a better future” by William Webb (2016).
  5. “Software Networks: Virtualization, SDN, 5G and Security”by G. Pujolle (Wile 2015).
  6. “Large MiMo Systems” by A. Chockalingam & B. Sundar Rajan (Cambridge University Press 2014).
  7. “Millimeter Wave Wireless Communications” by T.S. Rappaport, R.W. Heath Jr., R.C. Daniels, J.N. Murdock (Prentis Hall 2015).
  8. “The Limits of Human Vision” by Michael F. Deering (Sun Microsystems).
  9. “Quad HD vs 1080p vs 720p comparison: here’s what’s the difference” by Victor H. (May 2014).
  10. “Broadband Coverage in Europe 2015: Mapping progress towards the coverage objectives of the Digital Agenda” by European Commission, DG Communications Networks, Content and Technology (2016).

Mobile Data Consumption, the Average Truth? the Average Lie?

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“Figures often beguile me” leading to the statement that “There are three kinds of lies: lies, damned lies, and statistics.” (Mark Twain, 1906).

We are so used to averages … Read any blog or newspaper article trying to capture a complex issue and its more than likely that you are being told a story of averages … Adding to Mark Twain’s quote on Lies, in our data intense world ” The Average is often enough the road to an un-intentional Lie” .. or just about “The Average Lie” .

Imagine this! Having (at the same time) your feet in the oven at 80C and you head in the freezer at -6C … You would be perfectly OK! On average! as your average temperature would equal 80C + (-6C) divided by 2 which is 37C, i.e., the normal and recommended body temperature for an adult human being. However both your feet and your head is likely to suffer from such an experiment (and therefore really should not be tried out … or left to Finns used to Sauna and Icy water … though even the Finns seldom enjoyed this simultaneously).

Try this! Add together the age of the members your household and divide by the number of members. This would give you the average age of your household … does the average age you calculated have any meaning? … if you have young children or grandparents living with you, I think that there is a fairly high chance that the answers to that question is NO! …  The average age of my family”s household is 28 years. However, this number is a meaningless average representation of my household. It is 20 times higher than my sons age and about 40% lower than my own age.

Most numbers, most conclusions, most stories, most (average) analysis are based on an average representation of one or another Reality …. and as such can easily lead to Reality Distortion.

When we are presented with averages (or mean values as it is also called in statistics), we tend to substitute Average with Normal and believe that the story represents most of us (i.e., statistically this means about 68% of us all). More often than not we sit back with the funny feeling that if what we just read is “normal” then maybe we are not.

On mobile data consumption (I ll come back to Smartphone data consumption a bit later) … There is one (non-average) truth about mobile data consumption that has widely (and correctly) been communicated …

Very few mobile customers (10%) consumes the very most of the mobile data traffic (90%).

(see for example: http://www.nytimes.com/2012/01/06/technology/top-1-of-mobile-users-use-half-of-worlds-wireless-bandwidth.html/).

Lets just assume that a mobile operator make claim to an average 200MB monthly consumption (source: http://gigaom.com/broadband/despite-critics-cisco-stands-by-its-data-deluge/). Lets assume that 10% of customer base generating 90% of the traffic. It follows that the high usage segment has an average  volumetric usage of 1,800MB and the low usage segment an average volumetric usage of only 22MB.  In other words 10% of the customer base have 80+ times higher consumption than the remaining 90%. The initial average consumption (taken across the whole customer base) of 200MB communicated is actually 9 times higher than the average consumption of 90% of the customer base. It follows (with some use case exceptions) that the 10% high usage segment spends a lot more Network Resources and Time. The time the high usage segment spend actively with their device are likely to be a lot higher than the 90% low usage segment.

The 200MB is hardly normal! It is one of many averages that can be calculated. Obviously 200MB is a lot more “sexy” than to state that 90% of the customer base consumes typically 22MB.

Created using PiktoChart http://app.piktochart.com.

Do Care about Measurement and Data Processing!

What further complicates consumptive values being quoted is how the underlying data have been measured, processed and calculated!

  1. Is the averaging done over the whole customer base?,
  2. Is the averaging done over active customers?, or
  3. A subset of active customers (i.e., 2G vs 3G, 3G vs HSPA+ vs LTE vs WiFi, smartphone  vs basic phone, iPad vs iPhone vs Laptop, prepaid vs postpaid, etc..) or
  4. A smaller subset based on particular sample criteria (i.e., iOS, Android, iPad, iPhone, Galaxy, price plan, etc..) or availability (mobile Apps installed, customer approval, etc..).  or …

Without knowing the basis of a given average number any bright analysis or cool conclusion might be little more than Conjecture or Clever Spin.

On Smartphone Usage

One the most recent publicized studies on Smartphone usage comes from O2/Telefonica UK (Source: http://mediacentre.o2.co.uk/Press-Releases/Making-calls-has-become-fifth-most-frequent-use-for-a-Smartphone-for-newly-networked-generation-of-users-390.aspx). The O2 data provides an overview of average daily Smartphone usage across 10 use case categories.

The O2’s Smartphone statistics have been broken down in detail by one of our industry”s brightest Tomi Ahonen (A Must Read http://www.communities-dominate.blogs.com/ though it is drowning in his Nokia/Mr. Elop “Howler Letters”). Tomi points out the Smartphone’s disruptive replacement potential of many legacy consumer products (e.g., think: watch, alarm clock, camera,  etc..).

The O2 Smartphone data is intuitive and exactly what one would expect! Boring really! Possible with the exception of Tomi’s story telling (see above reference)! The data was so boring that The Telegraph (source: http://www.telegraph.co.uk/technology/mobile-phones/9365085/Smartphones-hardly-used-for-calls.html) had to conclude that “Smartphones Hardly Used for Calls”. Relative to other uses of course not really an untruth.

Though The Telegraph did miss 9or did not care) the fact that both Calls and SMS appeared to be what one would expect (and why would a Smartphone generate more Voice and SMS than Normal? … hmmmm). Obviously, the Smartphone is used for a lot of other stuff than calling and SMSing! The data tells us that an average Smartphone user (whatever that means) spend ca. 42 minutes on web browsing and social networking while “only” 22 minutes on Calls and SMS (i.e., actually 9 minutes of SMS sounds more like a teenager than a high-end smartphone user … but never mind that!). There are lots of other stuff going on with that Smartphone. In fact out of the total daily usage of 128 minutes only 17% of the time (i.e., 22 minutes) is used for Plain Old Mobile Telephony Services (The POMTS). We do however find that both voice minutes and legacy messaging consumption are declining faster in the Smartphone segment than for Basic Phones (which are declining rapidly as well) as OTT Mobile Apps alternatives substitute POMTS (see inserted chart from http://www.slideshare.net/KimKyllesbechLarsen/de-risking-the-broadband-business-model-kkl2411201108x).

I have no doubt that the O2 data represents an averaging across a given Smartphone sample, the question is how does this data help us to understand the Real Smartphone User and his behavior.

So how did O2 measure this data?

(1) To be reliable and reasonable, data collection should be done by an App residing in the O2 customer’s smartphone. An alternative (2) would be deep packet inspection (dpi) but this would only capture network usage which can (and in most cases will be) very different from the time the customer actively uses his Smartphone. (3) Obviously the data could also be collected by old fashion Questionnaires being filled in. This would be notoriously unreliable and I cannot imagine this being the source.

Thus, I am making the reasonable guess that the Smartphone Data Collection is mobile App based.

“Thousand and 1 Questions”: Does the data collected represents a normal O2 Smartphone user? or a particular segment that don’t mind having a Software Sniffer (i.e., The Sniffer) on the used device reporting his behavior? Is “The Sniffer” a standard already installed (and activated?) App on all Smartphone devices?, only on a certain segment? or is it downloadable? (i..e, which would require a certain effort from the customer), is the collection done for both prepaid & contract customers, both old and new smartphones (i.e., usage patterns depends on OS version/type, device capabilities such as air interface speed DL & UL, CPU, memory management, etc..) … is WiFi included or excluded?, what about Apps running in the background (are these included), etc…

I should point out that it is always much easier to poke at somebody else data analysis than it often is to collect, analyse and present such data. Though, depending on the answer to the above “1,000 + 1” questions the O2 data either becomes a fair representation of an O2 Smartphone customer or “just” an interesting data point for one of their segments.

If the average Smartphone cellular (i.e., no WiFi blend) monthly consumption in UK is ca. 450MB (+/-50MB) and if the consumer had on average cellular speed of 0.5Mbps (i.e., likely conservative with exception of streaming services which could be lower), one would expect that Time spend consuming Network Resources would be no more than 120 minutes per month or 5 minutes per day (@ R99 384kbps this would be ca. 6 min per day). If I would chose a more sophisticated QoS distribution, the Network Consumption Time would anyway not change with an order of magnitude or more.

So we have 5 minutes of Mobile Data Network Time Consumption daily versus O2’s Smartphone usage time of 106 minutes (wo Calls & SMS) … A factor 22 in difference!

For every minutes of mobile data network consumption the customer spends 20+ minutes actively with his device (i.e., reading, writing, playing, etc..).

So …. Can we trust the O2 Smartphone data?

Trend wise the data certainly appear reasonable! Whether the data represents a majority of the O2 smartphone users or not … I doubt somewhat. However, without having a more detailed explanation of data collection, sampling, and analysis it’s difficult to conclude how representable the O2 Smartphone data really is for their Smartphone customers.

Alas this is the problem with most of the mobile data user and usage statistics being presented to the public as an average (i.e., have had my share of this challenge as well).

Clearly we spend a lot more time with our device than the device spends actively at the mobile network. This trend has been known for a long time from the fixed internet. O2 points out that the Smartphone, with its mobile applications, has become the digital equivalent to a “Swiss Army Knife” and as a consequence (as Tomi also points out in his Blog) already in the process of replacing a host of legacy consumer devices, such as the watch, alarm clock, camera (both still pictures and video), books, music radios, and of course last but not least substituting The POMTS.

I have made argued and shown examples that Average Numbers we are presented with are notorious by character. What other choices do we have?  Would it be better to report the Median? rather than the Average (or  Mean)? The Median divides a given consumptive distribution in half (i.e., 50% of customers have a consumption below the Median and 50% above). Alternative we could report the Mode which would give us the most frequent consumption across our consumer distribution.

Of course if consumer usage was distributed normally (i.e., symmetric bell shaped) Mean, Median and Mode would be one and the same (and we would all be happy and bored). Not so much luck!

Most consumptive behaviors tends to be much more skewed and asymmetric (i.e., “the few takes the most”) than the normal distribution (that most of us instinctively uses when we are presented with figures). Most people are not likely to spend much thought on how a given number is calculated. However, it might be constructive to provide a %tage of the customers for which their usage is below the reported average. The reader should however note that in case the percentage figure is different from 50%, the consumptive distribution is skewed and

onset of Reality Distortion has occurred.

Wireless Broadband Access (BWA) Greenfield Ambition… (from March 2008)

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In case you are contemplating starting a wireless broadband, maybe even mobile broadband, greenfield operation in Europe there will be plenty of opportunity the next 1 to 2 years.Will it be a great business in Western Europes mature market? – probably not – but it still might be worth pursuing. The mobile incumbants will have a huge edge when it comes to spectrum and capacity for growth which will be very difficult to compete against for a Greenfield with comparable limited spectrum.Upcoming 2.50 GHz to 2.69 GHz spectrum (i.e., 2.6 GHz for short) auctions, often refered to as the UMTS extension band spectrum, are being innitiated in several European countries (United Kingdom, The Netherlands, Sweden, etc..). Thus, we are talking about 190 MHz of bandwidth up for sale to the highest bidder(s). Compared this with the UMTS auction at the 2.1 GHz band which was 140 Mhz. The European Commission has recommended to split up the 190 MHz into 2×70 MHz for FDD operations (basically known as UMTS extension band in some countries) and a (minimum ) 1×50 MHz part for TDD operation.

In general it is expected that incumbent mobile operators (e.g., Vodafone, T-Mobile, KPN, Orange, Telefonica/O2, etc..) will bid for the 2.6 GHz FDD spectrum, supplementing their existing UMTS 2.10 GHz spectrum mitigating possible growth limitation they might foresee in the future. The TDD spectrum is in particular expected to be contended by new companies, greenfield operations as well as fixed-line operators (i.e, BT) with the ambition to launch broadband wireless access BWA (i..e, WiMAX) networks. Thus, new companies which intend to compete with today’s mobile operators and their mobile broadband data proporsitions. Furthermore, just as mobile operators with broadband data competes with fixed broadband business (i.e., DSL & cable); so is it expected that the new players would likewise compete with both existing fixed and mobile broadband data proporsitions. Obviously, new business might not limit their business models to broadband data but also provide voice offerings.

Thus, the competive climate would become stronger as more players contend for the same customers and those customer’s wallet.

Let’s analyse the Greenfields possible business model as the economical value of starting up a broadband data business in mature markets of Western Europe. The analysis will be done on a fairly high level which would give us an indication of the value of the Greenfield Business model as well as what options a new business would have to optimize that value.

FDD vs TDD Spectrum

The 2.6 GHz auction is in its principles assymetric, allocating more bandwidth to FDD based operation than to TDD-based Broadband Wireless Access (BWA) deployment; 2×70 MHz vs 1×50 MHz. It appears fair to assuming that most incumbent operators will target 2×20 MHz FDD which coincide with the minimum bandwidth target for the Next-Generation Mobile Network (NGMN)/Long-Term Evolution (LTE) Network vision (ref: 3GPP LTE).

For the entrant interested in the part of the 1×50 MHz TDD spectrum would in worst case need 3x the FDD spectrum to get an equivalent per sector capacity as an FDD player, i.e., 2×20 MHz FDD equivalent to 1×60 MHz TDD with a frequency re-use of 3 used by the TDD operator. Thus, in a like-for-like a TDD player would have difficulty matching the incumbants spectrum position at 2.6 GHz (ignoring the incumbant having a significantly stronger spectrum position from the beginning).

Of course better antenna systems (moving to re-use 1), improved radio resource management, higher spectral efficiency (i.e., Mbps/MHz) as well as improved overall link budgets might mitigate possible disadvantage in spectral assymmetry benefiting the TDD player. However, those advantages are more a matter of time before competing access technologies bridge an existing performance gab (technology equivalent tit-for-tat).

Comparing actual network performance of FDD-based UMTS/HSPA (High-Speed Packet Access) with WiMAX 802.16e-2005 the performance is roughly equivalent in terms of spectral efficiency. However, in general in Europe there has been allocated far more FDD-based spectrum than TDD-based which overall does result in a considerable capacity and growth issues for TDD-based business models. Long-Term Evolution (LTE) path is likely to be developed both for FDD and TDD based access and equivalent performance might be expected in terms of bits-per-second to Hz performance.

Thus, it is likely that a TDD-based network would become capacity limited sooner than a mobile operator having a full portfolio of FDD-based spectrum (i.e., 900 MHz (GSM), 1800 MHz (GSM), 2,100 MHz (FDD UMTS) and 2,500 MHz (FDD – UMTS/LTE) to its disposition. Therefore, a TDD based business model could be expected to look differently than an incumbants mobile operators existing business model.

The Greenfield BWA Business Case

Assume that Greenfield BWA intends to start-up its BWA business in a market with 17 million inhabitants, 7.4 million households, and a surface area of 34,000 km2. The Greenfield’s business model is based on house-hold coverage with focus on Urban and Sub-Urban areas covering 80% of the population and 60% of the surface area.

It is worth mentioning that the valuation approach presented here is high-level and should not replace proper financial modelling and due dilligence. This said, the following approach does provide a good guidance to the attractiveness of a business proporsition.

Greenfield BWA – The Technology Part

The first exercise the business modeller is facing is to size the network needed consistent with the business requirements and vision. How many radio nodes would be required to provide coverage and support the projected demand – is the question to ask! Given frequency and radio technology it is relative straightforward to provide a business model estimate of the site numbers needed.

Using standard radio engineering framework (e.g., Cost231 Walfish-Ikegami cell range model (Ref.:Cost321)) a reasonable estimate for a typical maximum cell range which can be expected subject to the radio environment (i.e, dense-city, urban, sub-urban and rural). Greenfield BWA intends to deploy (mobile) WiMAX at 2.6 GHz. Using the standard radio engineering formula a 1.5 km @ 2.6 GHz Uplink limited cell range is estimated. Uplink limited implies that the range between the Customer Premise Equipment (CPE) and the Basestation (BS) is shorter than the other direction from BS to CPE. This is a normal situation as the CPE equipment often is the limiting factor in network deployment considerations.

The 1.5-km cell range we have estimated above should be compared with typical cell ranges observed in actual mobile networks (e.g., GSM900, GSM1800 and UMTS2100). Typically in dense-city (i.e., Top-3 cities) areas, the cell range is between 0.5 and 0.7 km depending on load. In urban/metropolitan radio environment we often find an average between 2.0 – 2.5 km cell range depending on deployed frequency, cell load and radio environment. In sub-urban and rural areas one should expect an average cell range between 2.0 – 3.5 km depending on frequency and radio environment. Typically cell load would be more important in city and urban areas (i.e., less frequency dependence) while the frequency will be most important in sub-urban and rural areas (i.e., low-frequency => higher cell range => fewer sites; higher frequency => lower cell range => higher number of sites).The cell range (i.e., 1.5 km) and effective surface area targeted for network deployment (i.e., 20,000 km2) provides an estimate for the number of coverage driven sites of ca. 3,300 BWA nodes. Whether more sites would be needed due to capacity limitations can be assessed once the market and user models have been defined.

Using typical infrastructure pricing and site-build cost the investment level for Western Europe (i.e., Capital expenses, Capex) should not exceed 350 million Euro for the network deployment all included. Assuming that the related network operational expense can be limited to 10%(excluding personnel cost) of the cumulated Capex, we have a yearly Network related opex of 35 million Euro (after rollout target has been reached). After the the final deployment target has been reached the Greenfield should assume a capital expense level of minimum 10% of their service revenue.

It should not take Greenfield BWA more than 4 years to reach their rollout target. This can further be accelerated if Greenfield BWA can share existing incumbant network infrastructure (i.e., site sharing) or use independent tower companies services. In the following assume that the BWA site rollout can be done within 3 years of launch.

Greenfield BWA the Market & Finance Part

Greenfield BWA will target primarily the house-hold market with broadband wireless access services based on the WiMAX (i.e., 802.16e standard). Voice over IP will be supported and offered with the subscription.

Furthermore, the Greenfield BWA intends to provide stationary as well as normadic services to the house-hold segment. In addition Greenfield BWA also will provide some mobility in the areas they provide coverage. However, this would not be their primary concern and thus national roaming would not be offered (reducing roaming charges/cost).

Greenfield BWA reaches a steady-state (i.e., after final site rollout) customer market-share of 20% of the Household base; ca. 1.1 million household subscriptions on which they have a blended revenue per household €20 per month can be expected. Thus, a yearly service revenue of ca. 265 million Euro. From year 4 and onwards a maintenance Capex level of 25 million Euro is kept (i.e., ca. 10% of revenue).

Greenfield BWA manage its cost strictly and achieve an EBITDA margin of 40% from year 4 onwards (i.e, total annual operational cost of 160 million Euro).

Depreciation & Amortisation (D&A) level is kept at a level of $40 million annually (steady-state). Furthermore, Greenfield Inc has an effective tax rate of 30%.

Now we can actually estimate the free cash flow (FCF) Greenfield Inc would generate from the 4th year forward:

(all in million Euro)
Revenue €265
-Opex €158
=EBITDA €106
– D&A €40 (ignoring spectrum amortization)
– Tax €20 (i.e., 30%)
+ D&A €40
=Gross Cash Flow €86
-Capex €25
=FCF €61

assuming zero percent FCF growth rate and operating with a 10% (i.e., this could be largely optimistic for a pure Greenfield operation. Having 15% – 25% is not unheard off to reflect the high risks) Weighted Average Cost of Capital (i.e., WACC) the perpetuity value from year 4 onwards would be €610 million. In Present Value this is €416 million, net €288 million for the initial 3 years discounted capital investment (for network deployment) and considering the first 3 years cumulated discounted EBITDA 12 million provides

a rather weak business case of ca. 140 million (upper) valuation prior to spectrum investment where-of bulk valuation arises from the continuation value (i.e., 4 year onwards).

Alternative valuation would be to take a multiple of the EBITDA (4th year) as a sales price valuation equivalent; typically one would expect between 6x and 10x the (steady-state) EBITDA and thus €636 mio (6x) to €1,000 mio (10x).

The above valuation assumptions are optimistic and it is worthwhile to note the following;

1. €20 per month per household customer should be seen as optimistic upper value; lower and more realistic might not be much more than €15 per month.
2. 20% market share is ambitious particular after 3 years operation.
3. 40% margin with 15% customer share and 3,300 radio nodes is optimistic but might be possible if Greenfield BWA can make use of Network Sharing and other cost synergies in relation to for example outsourcing.
4. 10% WACC is assumed. This is rather low given start-up scenario. Would not be surprised that this could be estimated to be as high as 15% to 20%.If point 1 to 4 lower boundaries would be applied to above valuation logic the business case would very quickly turn in red (i.e., negative); leading to the conclusion of a significant business risk given the scope of above business model.Our hypothetical Greenfield BWA should target paying minimum license fee for the TDD spectrum; upper boundary should not exceed €50 million to mitigate too optimistic business assumptions.The City-based Operation Model

Greenfield BWA could choose to focus their business model on the top-10 cities and their metropolitan areas. Lets assume that by this 50% of population or house-holds are captured as well as 15% of the surface area. This should be compared with the above assumptions 80% population and 60% surface area coverage.

The key business drivers would look as follows (in paranthesis the previous values have been shown for reference).

Sites 850 (3,300) rollout within 1 to 2 years (3 years).
Capex €100 mio (€350) for initial deployment; afterwhich €18 mio (€25).

Customer 0.74 mio (1.1)
Revenue €178 mio (€264)
EBITDA €72 mio (€106)
Opex €108 mio (€160)
FCF €38 mio (€61)
Value €210 mio (€140)

The city-based network strategy is about 50% more valuable than a more extensive coverage strategy would be.

Alternative valuation would be to take a multiple of the EBITDA (3rd year) as the sales price valuation equivalent; typically one would expect between 6x and 10x the (steady-state) EBITDA and thus €432 mio (6x) to €720 mio (10x).

Interestingly (but not surprising!) Greenfield BWA would be better of focusing on smaller network but in areas of high population density is financially more attractive. Greenfield BWA should avoid coverage based rollout strategy known from the mobile operator business model.

The question is how important is it for the Greenfield BWA to provide coverage everywhere? if their target is primarily households based customers with normadic and static mobility requirements then such a “coverage where the customer is” business model might actually work?

Source: http://harryshell.blogspot.de/2008/03/wireless-broadband-access-bwa.html

Did you know? Did you consider? (from March 2008)

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In 2007 the European average mobile revenue per user (ARPU per month) was €28+/-€6; a drop of ca. 4% compared to 2006 (the EU inflation level in 2007 was ca. 2.3%).

of the €28 ARPU, ca. 16% could be attributed to non-voice usage (i.e,. €4.5).

of the €4.5 Non-Voice ARPU, ca. 65% could be attributed to SMS usage (i.e, €3.0).

Thus, leaving €1.5 for non-voice (mobile) data service (i.e., 5.4% of total ARPU).

The increase that most European countries have seen in their mobile Non-Voice Revenue has by far not been able to compensate for the drop in ARPU across most countries over the last 5 to 6 years.

Adding advanced data (e.g., UMTS and HSPA) capabilities to the mobile networks around Europe has not resulted in getting more money out of the mobile customer (but absolute revenue has grown due to customer intake).

Although most European UMTS/HSPA operators report a huge uptake (in relative terms) of Bytes generated by the customers, this is not reflected in the ARPU development.

Maybe it really does not matter as long as the mobile operators overall financial performance remains excelent (i.e., Revenues, Customers, EBITDA, Cash, ….)?

Is it possible to keep healthy financial indicators with decreasing ARPU, huge data usage growth and investments into brand-new radio access technologies targeting the €1.5 per month per user?

Source: http://harryshell.blogspot.de/2008_03_01_archive.html

Winner of the 700-MHz Auction is … Google! (from April 2008)

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The United States has recently ended (March 2008) the auction of 5 blocks (see details below) of the analog TV spectrum band of 700-MHz. More specifically the band between 698 – 763 MHz (UL) and 728 – 793 MHZ (DL), with a total bandwidth of 2×28 MHz. In addition a single band 1×6 MHz in 722 – 728 MHz range was likewise auctioned. The analog TV band is expected to be completely vacated by Q1 2009.

The USA 700 MHz auction result was an impressive total of $19.12 billion, spend buying the following spectrum blocks: A (2×6 MHz), B (2×6 MHz), C (2×11 MHz) and E (1×6 MHz) blocks. The D (2×5 Mhz) block did not reach the minimum level. A total of 52 MHz (i.e, 2×23 + 1×6 MHz) bandwidth was auctioned off.

Looking with European eyes on the available spectrum allocated per block it is not very impressive (which is similar to other US Frequency Blocks per Operator, e.g., AWS & PCS). The 700 MHz frequency is clearly very economical for radio network coverage deployment in particular compared the high-frequency AWS spectrum used by T-Mobile, Verizon and Sprint. However, the 6 to 11 MHz (UL/DL) is not very impressive from a capacity sustainance perspective. It is quiet likely that this spectrum would be exhausted and rapidly leading to a significant additional financial commitment to cell splits / capacity extensions.

This $19.12 billion for 52 MHz translates to $1.22 per MHz spectrum per Population @ 700 MHz.

This should be compared to following historical auctions
* $0.56/MHz/Pop @ 1,700 MHz in 2006 US AWS auction
* $0.15/MHz/Pop (USA Auction 22 @ 1999) to $4.74/MHz/Pop (NYC, Verizon).
* $1.23/MHz/Pop Canadian 2000 PCS1900 Auction of 40MHz.
* $5.94/MHz/Pop UK UMTS auction (2001) in UK auctioning a total of 2×60 MHz FDD spectrum (TDD not considered).
* $7.84/MHz/Pop German UMTS auction in 2001 (2×60 MHz FDD, TDD not considered).

(Note: the excesses of the European UMTS auctions clearly illustrates a different time and place).

What is particular interesting is that Verizon “knocked-out” Google by paying $4.74 billion for the nationwide C-block of 2×11 MHz. “Beating” Google’s offer of $4.6 billion.

However, Google does not appear too sadened of the outcome and …. why should they! Google has to a great extend influenced the spectrum conditions allowing for open access (although it remains to be seen what this really means) to the C spectrum block; The USA Federal Communications Commission (FCC) has proposed to apply “open access” requirements for devices and applications on a the nation wide spectrum block C (2×11 MHz). 

Clearly Google should be regarded as the winner of the 700 MHz auction. They have avoided committing a huge amount of cash for the spectrum and on-top having to deploy even more cash to build and operate a wireless network (i.e., which is really their core business anyway).

Googling the Business Case
Google was willing to put down $4.6 billion for the 2×11 MHz @ 700 MHz. Let’s stop up an ask how their business case possible could have looked like.

At 700 MHz, with not too ambitious bandwidth per user requirements, Google might achieve a typical cell range between 2.5 and 4 km (Uplink limited, i.e., user equipment connection to base station). Although in “broadcast/downlink” mode, the cell range could be significantly larger (and downlink is all you really need for advertisement and broadcast;-).

Assume Google’s ambition was top-100 cities and 1-2% of the USA surface area they would need at least 30 thousand nodes. Financially (all included) this would likely result in $3 to $5 billion network capital expense (Capex) and a technology driven annual operational expense (Opex) of $300 to $500 million (in steady-state). On top of the spectrum price.

Using above rough technology indicators Google (if driven by sound financial principles) must have had a positive business case for a cash-out of minimum $8 billion over 10 years, incl. spectrum and discounted with WACC of 8% (all in all being very generous) and annual Technology Opex of minimum $300 million. On top of this comes customer acquisition, sales & marketing, building a wireless business operations (obviously they might choose to outsource all that jazz).

… and then dont forget the customer device that needs to be developed for the 700 MHz band (note GSM 750 MHz falls inside the C-band). Typically takes between 3 to 5 years to get a critical customer mass and then only if the market is stimulated.

It would appear to be a better business proporsition to let somebody else pay for spectrum, infrastructure, operation, etc… and just do what Google does best … selling advertisments and deliver search results … for mobile devices … maybe even agnostic to the frequency (seems better than wait until critical mass has been reached at the 700 MHz).

But then again … Google reported for full year 2007 a $16.4 billion in advertising revenues (up 56% compared to the previous year).(see refs Google Investor Relations). Imagine what this could be if extended to wireless / mobile market. Still lower than Verizon’s 2007 full year revnue of $23.8B (up 5.5% from 2006) but not that much lower considering the difference in growth rate.

The “successfull” proud owners (Verizon, AT&T Mobility, etc….) of the 700 MHz spectrum might want to keep in mind that Google’s business case for entering wireless must have been far beyond the their proposed $4.6 billion.

Appendix:
The former analog TV spectrum auction has been divided UHF spectrum into 5 blocks:
Block A: 2×6 MHz bandwidth (698–704 and 728–734 MHz); $3.96 billion
Block B: 2×6 MHz bandwidth (704–710 and 734–740 MHz); $9.14 billion dominated by AT&T Mobility.
Block C: 2×11 MHz bandwidth (746–757 and 776–787 MHz) Verizon $4.74 billion
Block D: 2×5 MHz bandwidth (758–763 and 788–793 MHz) No bids above the minimum.
Block E: 1×6 MHz bandwidth (722–728 MHz)Frontier Wireless LCC $1.26 billion

Source: http://harryshell.blogspot.de/2008/04/winner-of-700-mhz-auction-is-google.html

Backhaul Pains (from April 2008)

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Backhaul, which is the connection between a radio node and the core network, is providing mobile-wireless operators possible with the biggest headache ever (apart from keeping a healthy revenue growth in mature markets 😉 … it can be difficult to come by in the right quantities and can be rather costly with conventional transmission cost-structures … Backhaul is expected to have delayed the Sprint WiMAX rollout of their Xohm branded wireless internet service. A Sprint representative is supposed to have said: “You need a lot of backhaul capacity to do what’s required for WiMax.” (see forexample WiMax.com blog)

What’s a lot?

Well … looking at the expected WiMAX speed per Base Station (BS) of up-to 50 Mbps (i.e., 12 – 24x typical backhaul supporting voice demand), it is clear that finding suitable and low-cost bachaul solutions might be challenging. Conventional leased lines would be grossly un-economical at least if priced conventionally; xDSL and Fiber-to-the-Premises (FTTP) infrastructure that could support (economically?) such bandwidth demand is not widely deployed yet.

Is this a Sprint issue only? Nope! …. Sprint cannot be the only mobile-wireless operator with this problem – for UMTS/HSPA mobile operators the story should be pretty much the same (unless an operator has a good and modern microwave backhaul network supporting the BS speed).

Backhaul Pains – Scalability Issues
The backhaul connection can be either via a Leased Line (LL) or a Microwave (MW) radio link. Sometimes a MW link can be leased as well and might even be called a leased line.

With microwave (MW) links one can easily deliver multiples of 2.048 Mbps (i.e., 10 – 100 Mbps) on the same connection for relative low capital cost (€500 – €1,000 per 2.048 Mbps) and low operational expense. However planning and deployment experience and spectrum is required.

In many markets network operators have been using conventional (fixed) leased lines, leased from incumbent fixed-line providers. The pricing model is typically based on an upfront installation fee (might be capitalized) and a re-occurring monthly lease. On a yearly basis this operational expense can be in the order of €5,000 per 2.048 Mbps, i.e., 5x to 10 x the amount of a MW connection. Some price-models trade-off the 1-off installation fee with a lower lease cost.

Voice was the Good for Backhaul; Before looking at the broadband wireless data bandwidth demand its worth noticing that in the good old Voice days (i.e., GSM, IS95, ..) 1x to 2x 2.048 Mbps was more than sufficient to support most demands on a radio base station (BS).

Mobile-Wireless Broadband data enablers are the Bad and quickly becoming the Very Ugly for Backhaul; With the deployment of High Speed Packet Access (HSPA) on-top of UMTS and with WiMAX (a la Sprint) a BS can easily provide between 7.2 to 14.4 Mbps or higher per sector depending on available bandwidth. With 3 sectors per BS the total supplied data capacity could (in theory … ) be in excess of 21 Mbps per radio Base Station.

From the perspective of backhaul connectivity one would need at least an equivalent bandwidth of 10x 2.048 Mbps connections. Assuming such backhaul lease bandwidth is available in the first instance, with conventional leased line pricing structure, such capacity would be very expensive, i.e., €50,000 per backhaul connection per year. Thus, for 1,000 radio nodes an operator would pay on an annual basis 50 million Euro (Opex directly hitting the EBITDA). This operational expense could be 8 times more than a voice-based operational leased-line expense.

Now that’s alot!

Looking a little ahead (i.e., next couple of years) our UMTS and WiMAX based mobile networks will undergo the so-called Long-Term Evolution (LTE; FDD and TDD based) with expected radio node downlink (i.e., base station to user equipment) capacity between 173 Mbps and 326 Mbps depending on antenna system and available bandwidth (i.e., minimum 20 Mhz spectrum per sector). Thus over a 3-sectored BS (theoretical) speeds in excess of 520 Mbps might be dreamed of (i.e., 253x 2.048 Mbps – and this is HUGE!:-). Alas across a practical real-life deployed base station (on average) no more than 1/3 of the theoretical speed should be expected.

“Houston we have a problem” … should be ringing in any CFO / CTO’s ears – a. Financially near-future developments could significantly strain the Technology Opex budgets and b.Technically providing cost-efficient backhaul capacity that can sustain the promised land.

A lot of that above possible cost can and should be avoided; looking at possible remedies we have several options;

1. High capacity microwave backhaul can prevent the severe increase in leased line cost; provided spectrum and expertise is available. Financially microwave deployment has the advantage of being mainly capital-investment driven with resulting little additional operational expense per connection. It is expected that microwave solutions will be available in the next couple of years which can provide connection capacity of 100 Mbps and above.

Microwave backhaul solutions are clearly economical. However, it is doubtful that LTE speed requirements can be met even with most efficient microwave backhaul solutions?

2. Move to different leased line (LL) pricing mechanisms such as flat pricing (eat all you can for x-Euro). Changing the LL pricing structure is not sufficient. At the same time providers of leased-line infrastructure will be “forced” (i.e., by economics and bandwidth demand) to move to new types of leased bandwidth solutions and architectures in order to sustain the radio network capabilities; ADSL is expected to develop from 8(DL)/1(UL) Mbps to 25(DL)/3.5(UL) Mbps with ADSL2+; VDSL (UL/DL symmetric) from ca. 100 Mbps to 250 Mbps with VDSL2 (ITU-T G.993.2 standard).

Clearly a VDSL2-based infrastructure could support today’s HSPA/WiMAX requirements, as well as the initial bandwidth requirements of LTE. Although VDSL2-based networks are being deployed around Europe (and the world) it is not not widely available.

Another promising mean of supporting the radio-access bandwidth requirements is Fiber to the Premises (FTTP), such as for example offered by Verizon in certain areas of USA (Verizon FiOS Service). With Gigabit Passive Optical Network (GPON, ITU-T G.984 standard) maximum speeds of 2,400 Mbps (DL) and 1,200 Mbps (UL) can be expected. If available FTTP to the base station would be ideal – provided that the connection is priced no higher than a standard 2.048 Mbps leased line to day (i.e., €5,000 benchmark). Note that for a mobile operator it could be acceptable to pay a large 1-off installation fee which could partly finance the FTTP connection to the base station.

Cost & Pricing Expectations
It is in general accepted by industry analysts that broadband wireless services are not going to add much to mobile operators total service revenue growth. In optimistic revenue scenarios data revenue compensates for stagnating/falling voice revenues. EBITDA margins will (actually are!) under pressure and the operational expenses will be violently scrutinized.

Thus, mobile operators deploying UMTS/HSPA, WiMAX and eventually (in the short-term) LTE cannot afford to have its absolute Opex increase. Therefore, if a mobile-wireless operator has a certain backhaul Opex, it would try to keep it at the existing level or reduce it over time (to mitigate possible revenue decline).

For the backhaul leased-capacity providers this is sort of bad news (or good? as it forces them to become economically more efficient) …. as they would have to finance their new fixed higher-bandwidth infrastructures (i.e., VDSL or FTTP) with little additional revenue from the mobile-wireless operators.

Economically it is not clear whether mobile-wireless cost-structure expectations will meet the leased-capacity providers total-cost of deploying networks supporting the mobile-wireless bandwidth demand.

However, for the provider of leased fixed-bandwith, providing VDSL2 and/or FTTP to the residential market should finance their deployment model.

With more than 90% of all data traffic being consumed in-house/in-door and with VDSL2/Fiber-to-the-Home (FTTH) solutions being readily available to the Homes (in urban environments at least) of business as well as residential customers, will mobile-wireless LTE base stations be loaded to the extend that very-high capacity (i.e., beyond 50 Mbps) backhaul connections would be needed?

Source: http://harryshell.blogspot.de/2008/04/backhaul-pains.html