# RAN Unleashed … Strategies for being the best (or the worst) cellular network (Part III).

I have been spending my holiday break this year (December 2021) updating my dataset on Western Europe Mobile Operators, comprising 58+ mobile operators in 16 major Western European markets, focusing on spectrum positions, market dynamics, technology diffusion (i.e., customer migration to 5G), advanced antenna strategies, (modeled) investment levels and last but not least answering the question: what makes a cellular network the best in a given market or the world. What are the critical ingredients for an award-winning mobile network?

An award-winning cellular network, the best network, also provides its customers with a superior experience, the best network experience possible in a given market.

I am fascinated by the many reasons and stories we tell ourselves (and others) why this or that cellular network is the best. The story may differ whether you are an operator, a network supplier, or an analyst covering the industry. I have had the privileged to lead a mobile network (T-Mobile Netherlands) that won the Umlaut best mobile network award in The Netherlands since 2016 (5 consecutive times) and even scored the highest amount of points in the world in 2019 and 2020/2021. So, I guess it would make me a sort of “authority” on winning best network awards? (=sarcasm).

In my opinion and experience, a cellular operator has a much better than fair chance at having the best mobile network, compared to its competition, with access to the most extensive active spectrum portfolio, across all relevant cellular bands, implemented on a better (or best) antenna technology (on average) situated on a superior network footprint (e.g., more sites).

For T-Mobile Netherlands, firstly, we have the largest spectrum portfolio (260 MHz) compared to KPN (205 MHz) and Vodafone (215 MHz). The spectrum advantage of T-Mobile, as shown above, is both in low-band (< 1800 MHz) as well as mid-band range (> 1500 MHz). Secondly, as we started out back in 1998, our cell site grid was based on 1800 MHz, requiring a denser cell site grid (thus, more sites required) than the networks based on 900 MHz of the two Dutch incumbent operators, KPN and Vodafone. Therefore, T-Mobile ended up with more cell sites than our competition. We maintained the site advantage even after the industry’s cell grid densification needs of UMTS at 2100 MHz (back in the early 2000s). Our two very successful mergers have also helped our site portfolio, back in 2007 acquiring and merging with Orange NL and in 2019 merging with Tele2 NL.

The number of sites (or cells) matter for coverage, capacity, and overall customer experience. Thirdly, T-Mobile was also first in deploying advanced antenna systems in the Dutch market (e.g., aggressive use of higher-order MiMo antennas) across many of our frequency bands and cell sites. Our antenna strategy has allowed for a high effective spectral efficiency (across our network). Thus, we could (and can) handle more bits per second in our network than our competition.

Moreover, over the last 3 years, T-Mobile has undergone (passive) site modernization that has improved coverage and quality for our customers. This last point is not surprising since the original network was built based on a single 1800 MHz frequency, and since 1998 we have added 7 additional bands (from 700 MHz to 2.5 GHz) that need to be considered in the passive site optimization. Of course, as site modernization is ongoing, an operator (like T-Mobile) also should consider the impact of future bands that may be required (e.g., 3.x GHz). Optimize subject to the past as well as the future spectrum outlook. Last but not least, we at T-Mobile have been blessed with a world-class engineering team that has been instrumental in squeezing out continuous improvements of our cellular network over the last 6 years.

So, suppose you have 25% less spectrum than a competitor. In that case, you either need to compensate by building 25% more cells (very costly & time-consuming), deploying better antennas with a 25% better effective spectral efficiency (limited, costly & relatively easy to copy/match), or a combination of both (expensive & time-consuming). The most challenging driver to copy for network superiority is the amount of spectrum. A competitor only compensates by building more sites, deploying better antenna technology, and over decades to try to equalize spectrum position is subsequent spectrum auctions (e.g., valid for Europe, not so for the USA where acquired spectrum usually is owned in perpetuity).

T-Mobile has consistently won the best mobile network award over the last 6 years (and 5 consecutive times) due to these 3 multiplying core dimensions (i.e., spectrum × antenna technology × sites) and our world-class leading engineering team.

### THE MAGIC RECIPE FOR CELLULAR PERFORMANCE.

We can formalize the above network heuristics in the following key (very beautiful IMO) formula for cellular network capacity measured in throughput (bits per second);

It is actually that simple. Cellular capacity is made as simple as possible, dependent on three basic elements, but not more straightforward. Maybe, super clear, though only active spectrum counts. Any spectrum not deployed is an opportunity for a competitor to gain network leadership on you.

If an operator has a superior spectrum position and everything else is equal (i.e., antenna technology & the number of sites), that operator should be unbeatable in its market.

There are some caveats, though. In an overloaded (congested) cellular network, performance would decrease, and superior network performance would be unlikely to be ensured compared to competitors not experiencing such congestion. Furthermore, spectrum superiority must be across the depth of the market-relevant cellular frequencies (i.e., 600 MHz – 3.x GHz and higher). In other words, if a cellular operator “only” has to work with, for example, 100 MHz @ 3.5GHz, it is unlikely that this would guarantee a superior network performance across a market (country) compared to a much better balance spectrum portfolio.

The option space any operator has is to consider the following across the three key network quality dimensions;

Let us look at the hypothetical Western European country Mediana. Mediana, with a population of 25 million, has 3 mobile operators each have 8 cellular frequency bands, incumbent Winky has a total cellular bandwidth of 270 MHz, Dipsy has 220 MHz, and Po has 320 MHz (top their initial weaker spectrum position through acquisitions). Apart from having the most robust spectrum portfolio, Po also has more cell sites than any other in the market (10,000) and keeps winning the best network award. Winky, being the incumbent, is not happy about this situation. No new spectrum opportunities will become available in the next 10 years. Winky’s cellular network, based initially on 900MHz but densified over time, has about 20% fewer sites than Po. Po and Winky’s deployed state of antenna technology is comparable.

What can Winky do to gain network leadership? Winky has assessed that Po has ca. 20% stronger spectrum position than they, state of antenna technology is comparable, and they (Po) have ca. 20% more sites. Using the above formula, Winky estimates that Po’s have 44% more raw cellular network quality available compared to their own capability. Winky’s commenced a network modernization program that adds another 500 new sites and significantly improves their antenna technology. After this modernization program, Winky has decreased its site deficit to having 10% fewer sites than Po and almost 60% better antenna technology capability than Po. Overall, using the above network quality formula, Winky has changed their network position to a lead over Po with ca. 18%. In theory, it should have an excellent chance to capture the best network award.

Of course, Po could simply follow and deploy the same antenna technology as Winky and would easily overtake Winky’s position due to its superior spectrum position (that Winky cannot beat the next 10 to 15 years at least).

In economic terms, it may be tempting to conclude that Winky has avoided 625 Million Euro in spectrum fees by possessing 50 MHz less than Po (i.e., median spectrum fee in Mediana is 0.50 Euro per MHz per pop times the avoided 50 MHz times the population of Mediana 25 Million pops) and that for sure should allow Winky to make a lot of network (and market) investments to gain network leadership. By adding more sites, assuming it is possible to do where they are needed and invest in better antenna technology. However, do the math with realistic prices and costs incurred over a 10 to 15 year period (i.e., until the next spectrum opportunity). You may be more likely to find a higher total cost for Winky than the spectrum fee avoidance. Also, the strategy of Winky is easy to copy and overtake in the next modernization cycle of Po.

Is there any value for operators engaging in such the best network equivalent of a “nuclear arms” race? That interesting question is for another article. Though the answer (spoiler alert) is (maybe) not so black and white as one may think.

An operator can compensate for a weaker spectrum position by adding more cell sites and deploying better antenna technologies.

A superior spectrum portfolio is not an entitlement. Still, an opportunity to become the sustainable best network in a given market (for the duration that spectrum is available to the operator, e.g., 10 – 15 years in Europe at least).

### WESTERN EUROPE SPECTRUM POSITIONS.

A cellular operator’s spectrum position is an important prerequisite for superior performance and customer experience. If an operator has the highest amount of spectrum (well balanced over low, mid, and high-frequency bands), it will have a powerful position to become the best network in that given market. Using Spectrum Monitor’s Global Mobile Frequency database (last updated May 2021), I analyzed the spectrum position of a total of 58 cellular operators in 16 Western European markets. The result is shown below as (a) Total spectrum position, (b) Low-band spectrum position covering spectrum below and including 1500 MHz (SDL band), and (c) Mid-band spectrum covering the spectrum above 1500 MHz (SDL band). For clarity, I include the 3.X GHz (C-band) as mid-band and do not include any mmWave (n257 band) positions (anyway would be high band, obviously).

4 operators are in a category by themselves with 400+ MHz of total cellular bandwidth in their spectrum portfolios; A1 (Austria), TDC (Denmark), Cosmote (Greece), and Swisscom (Switzerland). TDC and Swisscom have incredibly strong low-band and mid-band positions compared to their competition. Magenta in Austria has a 20 MHz advantage to A1 in low-band (very good) but trails A1 with 92 MHz in mid-band (not so good). Cosmote slightly follows behind on low-band compared to Vodafone (+10 MHz in their favor), and they head the Greek race with +50 MHz (over Vodafone) in mid-band. All 4 operators should be far ahead of their competitors in network quality. At least if they used their spectrum resources wisely in combination with good (or superior) antenna technologies and a sufficient cellular network footprint. In all else being equal, these 4 operators should be sustainable unbeatable based on their incredible strong spectrum positions. Within Western Europe, I would, over the next few years, expect to see all round best networks with very high best network benchmark scores in Denmark (TDC), Switzerland (Swisscom), Austria (A1), and Greece (Cosmote). Western European countries with relatively more minor surface areas (e.g., <100,000 square km) should outperform much larger countries.

In fact, 3 of the 4 top spectrum-holding operators also have the best cellular networks in their markets. The only exception is A1 in Austria, which lost to Magenta in the most recent Umlaut best network benchmark. Magenta has the best low-band position in the Austrian market, providing for above and beyond cellular indoor-quality coverage that the low-band provides.

There are so many more interesting insights in my collected data. Alas for another article at another time (e.g., topics like the economic value of being the best and winning awards, industry investment levels vs. performance, infrastructure strategies, incumbent vs. later stages operator dynamics, 3.X GHz and mmWave positions in WEU, etc…).

The MNO rank within a country will depend on the relative spectrum position between 1st and 2nd operator. If below 10% (i.e., dark red in chart below), I assess that it will be relative easy for number 2 to match or beat number 1 with improved antenna technology. As the relative strength of the spectrum position of number 1 relative to number 2 is increased, it will become increasingly difficult (assuming number 1 uses an optimal deployment strategy).

The Stars (e.g., #TDCNet / #Nuuday#Swisscom and #EE) have more than a 30% relative spectrum strength compared to the 2nd ranked MNO in a given market. They will have to severely mess up, not to take (or have!) the best cellular network position in their relevant markets. Moreover, network economically, the Stars should have a substantial better Capex position compared to their competitors (although 1 of the Stars seem a “bit” out-of-whack in their sustainable Capex spend, but may be due to fixed broadband focus as well?). As a “cherry on the pie” both Nuuday/TDCNet and Swisscom have some of the strongest spectral overhead positions (i.e., MHz per pop) in Western Europe (relative small populations to very strong spectrum portfolios), which is obviously should enable superior customer experience.

### HOW AND HOW NOT TO WIN BEST NETWORK AWARDS.

Out of the 16 cellular operators having the best networks (i.e., rank 1), 12 (75%) also had the strongest (in market) spectrum positions. 3 Operators having the second-best spectrum position ended up taking the best network position, and 1 operator (WindTre, Italy) with the 3rd best spectrum position took the pole network position. The incumbent TIM (Italy) has the strongest spectrum position both in low- (+40 MHz vs. WindTre) and mid-band (+52 MHz vs. WindTre). Clearly, it is not a given that having a superior spectrum position also leads to a superior network position. Though 12 out of 16 operators leverage their spectrum superiority compared to their respective competitors.

For operators with the 2nd largest spectrum position, more variation is observed. 7 out of 16 operators end up with the 2nd position as best network (using Umlaut scoring). 3 ended up as best network, and the rest either in 3rd or 4th position. The reason is that often the difference between 2nd and 3rd spectrum rank position is not per see considerable and therefor, other effects, such as several sites, better antenna technologies, and/or better engineering team, are more likely to be decisive factors.

Nevertheless, the total spectrum is a strong predictor for having the best cellular network and winning the best network award (by Umlaut).

As I have collected quite a rich dataset for mobile operators in Western Europe, it may also be possible to model the expected ranking of operators in a given market. Maybe even reasonably predict an Umlaut score (Hakan, don’t worry, I am not quite there … yet!). This said, while the dataset comprises 58+ operators across 16 markets, more data would be required to increase the confidence in benchmark predictions (if that is what one would like to do). Particular to predict absolute benchmark scores (e.g., voice, data, and crowd) as compiled by Umlaut. Speed benchmarks, ala what Ookla’s provides, are (much) easier to predict with much less sophistication (IMO).

Here I will just show my little toy model using the following rank data (using Jupyter R);

The rank dataset set has 64 rows representing rank data and 5 columns containing (1) performance rank (perf_rank, the response), (2) total spectrum rank (spec_rank, predictor), (3) low-band spectrum rank (lo_spec_rank, predictor), (4) high-band spectrum rank (hi_spec_rank, predictor) and (5) Hz-per-customer rank (hz_cust_rank, predictor).

Concerning the predictor (or feature) Hz-per-customer, I am tracking all cellular operators’ so-called spectrum-overhead, which indicates how much Hz can be assigned to a customer (obviously an over-simplification but nevertheless an indicator). Rank 1 means that there is a significant overhead. That is, we have a lot of spectral capacity per customer. Rank 4 has the opposite meaning: the spectral overhead is small, and we have less spectral capacity per customer. It is good to remember that this particular feature is usually dynamic unless the spectrum situation changes for a given cellular operator (e.g., like traffic and customers may grow).

A (very) simple illustration of the “toy model” is shown below, choosing only low-band and high-band ranks as relevant predictors. Almost 60% of the network-benchmark rank can be explained by the low- and high-band ranks.

The model can, of course, be enriched by including more features, such as effective antenna-capability, Hz-per-Customer, Hz-per-Byte, Coverage KPI, Incident rates, Equipment Aging, Supplier, investment level (over last 2 – 3 years), etc… Given the ongoing debate of the importance of supplier to best networks (and their associated awards), I do not find a particularly strong correlation between RAN (incl. antenna) supplier, network performance, and benchmark rank. The total amount of deployed spectrum is a more important predictor. Of course, given the network performance formula above, if an antenna deployment delivers more effective spectral efficiency (or antenna “boost”) than competitors, it will increase the overall network quality for that operator. However, such an operator would still need to overcompensate the potential lack of spectrum compared to a spectrum-superior competitor.

### END THOUGHTS.

Having the best cellular network in a market is something to be very proud of. Winning best network awards is obviously great for an operator and its employees. However, it should really mean that the customers of that best network operator also get the best cellular experience compared to any other operator in that market. A superior customer experience is key.

Firstly, the essential driver (enabler) for best network or network leadership is having a superior spectrum position. In low-band, mid-band, and longer-term also in high-band (e.g., mmWave spectrum). The second is having a good coverage footprint across your market. Compared to competitors, a superior spectrum portfolio could even be with fewer cell sites than a competitor with an inferior spectrum position (forced to densify earlier due to spectral capacity limitations as traffic increases). For a spectrum laggard, building more cell sites is costly (i.e., Capex, Opex, and Time) to attempt to improve or match a superior spectrum competitor. Thirdly, having superior antenna technology deployed is essential. It is also a relatively “easy” way to catch up with a superior competitor, at least in the case of relative minor spectrum position differences. Compared to buying additional spectrum (assuming such is available when you need it) or building out a substantial amount of new cell sites to equalize a cellular performance difference, investing into the best (or better or good-enough-to-win) antenna technology, particular for a spectrum laggard, seems to be the best strategy. Economically, relative to the other two options, and operationally, as time-to-catch-up can be relatively short.

After all, this has been said and done, a superior cellular spectrum portfolio is one of the best predictors for having the best network and even winning the best network award.

Economically, it could imply that a spectrum-superior operator, depending on the spectrum distance to the next-best spectrum position in a given market, may not need to invest in the same level of antenna technology as an inferior operator or could delay such investments to a more opportune moment. This could be important, particularly as advanced antenna development is still at its “toddler” state, and more innovative, powerful (and economical) solutions are expected over the next few years. Though, for operators with relatively minor spectrum differences, the battle will be via the advancement of antenna technology and further cell site sectorization (as opposed to building new sites).

### ACKNOWLEDGEMENT.

I greatly acknowledge my wife, Eva Varadi, for her support, patience, and understanding during the creative process of writing this Blog. Also, many of my Deutsche Telekom AG and Industry colleagues, in general, have in countless ways contributed to my thinking and ideas leading to this little Blog. Again, I would like to draw attention to Petr Ledl and his super-competent team in Deutsche Telekom’s Group Research & Trials. Thank you so much for being a constant inspiration and always being available to talk antennas and cellular tech in general.

Spectrum Monitoring, “Global Mobile Frequencies Database”, the last update on the database was May 2021. You have a limited amount of free inquiries before you will have to pay an affordable fee for access.

Umlaut, “Umlaut Benchmarking” is an important resources for mobile (and fixed) network benchmarks across the world. The umlaut benchmarking methodology is the de-facto industry standard today and applied in more than 120 countries measuring over 200 mobile networks worldwide. I have also made use of the associated Connect Testlab resouce; www.connect-testlab.com. Most network benchmark data goes back to at least 2017. The Umlaut benchmark is based on in-country drive test for voice and data as well as crowd sourced data. It is by a very big margin The cellular network benchmark to use for ranking cellular operators (imo).

Speedtest (Ookla), “Global Index”, most recent data is Q3, 2021. There are three Western European markets that I have not found any Umlaut (or P3 prior to 2020) benchmarks for; Denmark, France and Norway. For those markets I have (regrettably) had to use Ookla data which is clearly not as rich as Umlaut (at least for public domain data).

# 5G Standalone – Network Slicing, a Bigger Slice of the Value Pie (Part II)

Full disclosure … when I was first introduced to the concept of Network Slicing, from one of the 5G fathers that I respect immensely (Rachid, it must have been back at the end of 2014), I thought that it was one of the most useless concepts that I had heard of. I did simply not see (or get) the point of introducing this level of complexity. It did not feel right. My thoughts were that taking the slicing concept to the limit might actually not make any difference to not having it, except for a tremendous amount of orchestration and management overhead (and, of course, besides the technological fun of developing it and getting it to work).

It felt a bit (a lot, actually) as a “let’s do it because we can” thinking. With the “We can” rationale based on the maturity of cloudification and softwarization frameworks, such as cloud-native, public-cloud scale, cloud computing (e.g., edge), software-defined networks (SDN), network-function virtualization (NFV), and the-one-that-is-always-named Artificial Intelligence (AI). I believed there could be other ways to offer the same variety of service experiences without this additional (what I perceived as an unnecessary) complexity. At the time, I had reservations about its impact on network planning, operations, and network efficiency. Not at all sure, it would be a development in the right economic direction.

Since then, I have softened to the concept of Network Slicing. Not (of course) that I have much choice, as slicing is an integral part of 5G standalone (5G) implementation that will be implemented and launched over the next couple of years across our industry. Who knows, I may very likely be proven very wrong, and then I learn something.

What is a network slice? We can see a network slice as an on-user-demand logical separated network partitioning, software-defined on-top of our common physical network infrastructure (wam … what a mouthful … test me out on this one next time you see me), slicing through our network technology stack and its layers. Thinking of a virtual private network (VPN) tunnel through a transport network is a reasonably good analogy. The network slice’s logical partitioning is isolated from other traffic streams (and slices) flowing through the 5G network. Apart from the slice logical isolation, it can have many different customizations, e.g., throughput, latency, scale, Quality of Service, availability, redundancy, security, etc… The user equipment initiates the slice request from a list of pre-defined slice categories. Assuming the network is capable of supporting its requirements, the chosen slice category is then created, orchestrated, and managed through the underlying physical infrastructure that makes up the network stack. The pre-defined slice categories are designed to match what our industry believe is the most essential use-cases, e.g., (a) enhanced mobile broadband use cases (eMBB), (b) ultra-reliable low-latency communications (uRLLC) use cases, (c) massive machine-type communication (MMTC) use cases, (d) Vehicular-to-anything (V2X) use-cases, etc… While the initial (early day) applications of network slicing are expected to be fairly static and configurationally relatively simple, infrastructure suppliers (e.g., Ericsson, Huawei, Nokia, …)expect network slices to become increasingly dynamic and rich in their configuration possibilities. While slicing is typically evoked for B2B and B2B2X, there is not really a reason why consumers could not benefit from network slicing as well (e.g., gaming/VR/AR, consumer smart homes, consumer vehicular applications, etc..).

### Show me the money!

Ericsson and Arthur D. Little (ADL) have recently investigated the network slicing opportunities for communications service providers (CSP). Ericsson and ADL have analyzed more than 70 external market reports on the global digitalization of industries and critically reviewed more than 400 5G / digital use cases (see references in Further Readings below). They conclude that the demand from digitalization cannot be served by CSPs without Network Slicing, e.g., “Current network resources cannot match the increasing diversity of demands over time” and “Use cases will not function” (in a conventional mobile network). Thus, according to Ericsson and ADL, the industry can not “live” without Network Slicing (I guess it is good that it comes with 5G SA then). In fact, from their study, they conclude that 30% of the 5G use cases explored would require network slicing (oh joy and good luck that it will be in our networks soon).

Ericsson and ADL find globally a network slicing business potential of 200 Billion US dollars by 2030 for CSPs. With a robust CAGR (i.e., the potential will keep growing) between 23% to 36% by 2030 (i.e., CAGR estimate for period 2025 to 2030). They find that 6 Industries segments take 90+% of the slicing potential(1) Healthcare (23%), (2) Government (17%), (3) Transportation (15%), (4) Energy & Utilities (14%), (5) Manufacturing (12%) and (6) Media & Entertainment (11%). For the keen observer, we see that the verticals are making up for most of the slicing opportunities, with only a relatively small part being related to the consumers. It should, of course, be noted that not all CSPs are necessarily also mobile network operators (MNOs), and there are also outside the strict domain of MNOs revenue potential for non-MNO CSPs (I assume).

Let us compare this slicing opportunity to global mobile industry revenue projections from 2020 to 2030. GSMA has issued a forecast for mobile revenues until 2025, expecting a total turnover of 1,140 Billion US$in 2025 at a CAGR (2020 – 2025) of 1.26%. Assuming this compounded annual growth rate would continue to apply, we would expect a global mobile industry revenue of 1,213 Bn US$ by 2030. Our 5G deployments will contribute in the order of 621 Bn US$(or 51% of the total). The incremental total mobile revenue between 2020 and 2030 would be ca. 140 Bn US$ (i.e., 13% over period). If we say that roughly 20% is attributed to mobile B2B business globally, we have that by 2030 we would expect a B2B turnover of 240+ Bn US$(an increase of ca. 30 Bn US$ over 2020). So, Ericsson & ADL’s 200 Bn US$network slicing potential is then ca. 16% of the total 2030 global mobile industry turnover or 30+% of the 5G 2030 turnover. Of course, this assumes that somehow the slicing business potential is simply embedded in the existing mobile turnover or attributed to non-MNO CSPs (monetizing the capabilities of the MNO 5G SA slicing enablers). Of course, the Ericsson-ADL potential could also be an actual new revenue stream untapped by today’s network infrastructures due to the lack of slicing capabilities that 5G SA will bring in the following years. If so, we can look forward to a boost of the total turnover of 16% over the GSMA-based 2030 projection. Given ca. 90% of the slicing potential is related to B2B business, it may imply that B2B mobile business would almost double due to network slicing opportunities (hmmm). Another recent study assessed that the global 5G network slicing market will reach approximately 18 Bn US$ by 2030 with a CAGR of ca. 41% over 2020-2030.

Irrespective of the slicing turnover quantum, it is unlikely that the new capabilities of 5G SA (including network slicing and much richer granular quality of service framework) will lead to new business opportunities and enable unexplored use cases. That, in turn, may indeed lead to enhanced monetization opportunities and new revenue streams between now (2022) and 2030 for our industry.

Most Western European markets will see 5G SA being launched over the next 2 to 3 years; as 5G penetration rapidly approaches 50% penetration, I expect network slicing use cases being to be tried out with CSP/MNOs, industry partners, and governmental institutions soon after 5G SA has been launched. It should be pointed out that already for some years, slicing concepts have been trialed out in various settings. Both in 4G as well as 5G NSA networks.

### Prologue to Network Slicing.

5G comes with a lot of fundamental capabilities as shown in the picture below,

5G allows for (1) enhanced mobile broadband, (2) very low latency, (3) massive increase in device density handling, i.e., massive device scale-up, (4) ultra-higher network reliability and service availability, and (5) enhanced security (not shown in the above diagram) compared to previous Gs.

The service (and thus network) requirement combinations are very high. The illustration below shows two examples of mapped-out sub-set of service (and therefore also eventually slice) requirements mapped onto the major 5G capabilities. In addition, it is quite likely that businesses would have additional requirements related to slicing performance monitoring, for example, in real-time across the network stack.

and with all the various industrial or vertical use cases (see below) one could imagine (noting that there may be many many more outside our imagination), the “fathers” of 5G became (very) concerned with how such business-critical services could be orchestrated and managed within a traditional mobile network architecture as well as across various public land mobile networks (PLMN). Much of this also comes out of the wish that 5G should “conquer” (take a slice of) next-generation industries (i.e., Industry 4.0), providing additional value above and beyond “the dumb bit pipe.” Moreover, I do believe that in parallel with the wish of becoming much more relevant to Industry 4.0 (and the next generation of verticals requirements), what also played a role in the conception of network slicing is the deeply rooted engineering concept of “control being better than trust” and that “centralized control is better than decentralized” (I lost count on this debate of centralized control vs. distributed management a long time ago).

So, yes … The 5G world is about to get a lot more complex in terms of Industrial use cases that 5G should support. And yes, our consumers will expect much higher download speeds, real-time (whatever that will mean) gaming capabilities, and “autonomous” driving …

“… it’s clear that the one shared public network cannot meet the needs of emerging and advanced mobile connectivity use cases, which have a diverse array of technical operations and security requirements.” (quote from Ericsson and Arthur D. Little study, 2021).

“The diversity of requirements will only grow more disparate between use cases — the one-size-fits-all approach to wireless connectivity will no longer suffice.” (quote from Ericsson and Arthur D. Little study, 2021).

Being a naturalist (yes, I like “naked” networks), it does seem somewhat odd (to me) to say that next generation (e.g., 5G) networks cannot support all the industrious use cases that we may throw at it in its native form. Particular after having invested billions in such networks. By partitioning a network up in limiting (logically isolated), slice instances can all be supported (allegedly). I am still in the thinking phase on that one (but I don’t think the math adds up).

Now, whether one agrees (entirely) with the economic sentiment expressed by Ericsson and ADL or not. We need a richer granular way of orchestrating and managing all those diverse use-cases we expect our 5G network to support.

### Network Slicing.

So, we have (or will get) network slicing with our 5G SA Core deployment. As a reminder, when we talk about a network slice, we mean;

“An on-user-demand logical separated network partitioning, software-defined, on-top of a common physical network infrastructure.”

So, the customer requested the network slice, typically via a predefined menu of slicing categories that may also have been pre-validated by the relevant network. Requested slices can also be Customized, by the requester, within the underlying 5G infrastructure capabilities and functionalities. If the network can provide the requested slicing requirements, the slice is (in theory) granted. The core network then orchestrates a logically separated network partitioning throughout the relevant infrastructure resources to comply with the requested requirements (e.g., speed, latency, device scale, coverage, security, etc…). The requested partitioning (i.e., the slice) is isolated from other slices to enable (at least on a logical level) independence of other live slices. Slice Isolation is an essential concept to network slicing. Slice Elasticity ensures that resources can be scaled up and down to ensure individual slice efficiency and an overall efficient operation of all operating slices. It is possible to have a single individual network slice or partition a slice into sub-slices with their individual requirements (that does not breach the overarching slice requirements). GSMA has issued roaming and inter-PLMN guidelines to ensure 5G network slicing inter-operability when a customer’s application finds itself outside its home -PLMN.

Today, and thanks to GSMA and ITU, there are some standard network slice services pre-defined, such as (a) eMBB – Enhanced Mobile Broadband, (b) mMTC – Massive machine-type communications, (c) URLLC – Ultra-reliable low-latency communications, (d) V2X – Vehicular-to-anything communications. These identified standard network slices are called Slice Service Types (SST). SSTs are not only limited to above mentioned 4 pre-defined slice service types. The SSTs are matched to what is called a Generic Slice Template (GST) that currently, we have 37 slicing attributes, allowing for quite a big span of combinations of requirements to be specified and validated against network capabilities and functionalities (maybe there is room for some AI/ML guidance here).

The user-requested network slice that has been set up end-2-end across the network stack, between the 5G Core and the user equipment, is called the network slice instance. The whole slice setup procedure is very well described in Chapter 12 of “5G NR and enhancements, from R15 to R16. The below illustration provides a high-level illustration of various network slices,

The 5G control function Access and Mobility management Function (AMF) is the focal point for the network slicing instances. This particular architectural choice does allow for other slicing control possibilities with a higher or lower degree of core network functionality sharing between slice instances. Again the technical details are explained well in some of the reading resources provided below. The takeaway from the above illustration is that the slice instance specifications are defined for each layer and respective physical infrastructure (e.g., routers, switches, gateways, transport device in general, etc…) of the network stack (e.g., Telco Core Cloud, Backbone, Edge Cloud, Fronthaul, New Radio, and its respective air-interface). Each telco stack layer that is part of a given network slice instance is supposed to adhere strictly to the slice requirements, enabling an End-2-End, from Core to New Radio through to the user equipment, slice of a given quality (e.g., speed, latency, jitter, security, availability, etc..).

And it may be good to keep in mind that although complex industrial use cases get a lot of attention, voice and mobile broadband could easily be set up with their own slice instances and respective quality-of-services.

### Network slicing examples.

All the technical network slicing “stuff” is pretty much-taken care of by standardization and provided by the 5G infrastructure solution providers (e.g., Mavenir, Huawei, Ericsson, Nokia, etc..). Figuring the technical details of how these works require an engineering or technical background and a lot of reading.

As I see it, the challenge will be in figuring out, given a use-case, the slicing requirements and whether a single slice instance suffice or multiple are required to provide the appropriate operations and fulfillment. This, I expect, will be a challenge for both the mobile network operator as well as the business partner with the use case. This assumes that the economics will come out right for more complex (e.g., dynamic) and granular slice-instance use cases. For the operator as well as for businesses and public institutions.

The illustration below provides examples of a few (out of the 37) slicing attributes for different use cases, (a) Factories with time-critical, non-time-critical, and connected goods sub-use cases (e.g., sub-slice instances, QoS differentiated), (b) Automotive with autonomous, assisted and shared view sub-use cases, (c) Health use cases, and (d) Energy use cases.

One case that I have been studying is Networked Robotics use cases for the industrial segment. Think here about ad-hoc robotic swarms (for agricultural or security use cases) or industrial production or logistics sorting lines; below are some reflections around that.

### End thoughts.

With the emergence of the 5G Core, we will also get the possibility to apply Network slicing to many diverse use cases. That there are interesting business opportunities with network slicing, I think, is clear. Whether it will add 16% to the global mobile topline by 2030, I don’t know and maybe also somewhat skeptical about (but hey, if it does … fantastic).

Today, the type of business opportunities that network slicing brings in the vertical segments is not a very big part of a mobile operator’s core competence. Mobile operators with 5G network slicing capabilities ultimately will need to build up such competence or (and!) team up with companies that have it.

That is, if the future use cases of network slicing, as envisioned by many suppliers, ultimately will get off the ground economically as well as operationally. I remain concerned that network slicing will not make operators’ operations less complex and thus will add cost (and possible failures) to their balance sheets. The “funny” thing (IMO) is that when our 5G networks are relatively unloaded, we would not have a problem delivering the use cases (obviously). Once our 5G networks are loaded, network slicing may not be the right remedy to manage traffic pressure situations or would make the quality we are providing to consumers progressively worse (and I am not sure that business and value-wise, this is a great thing to do). Of course, 6G may solve all those concerns 😉

### Acknowledgement.

I greatly acknowledge my wife, Eva Varadi, for her support, patience, and understanding during the creative process of writing this Blog. Also, many of my Deutsche Telekom AG and Industry colleagues, in general, have in countless ways contributed to my thinking and ideas leading to this little Blog. Thank you!

Kim Kyllesbech Larsen, “5G Standalone – European Demand & Expectations (Part I).”, LinkedIn article, (December 2021).

Kim Kyllesbech Larsen, “5G Economics – The Numbers (Appendix X).”, Techneconomyblog.com, (July 2017).

Kim Kyllesbech Larsen, “5G Economics – The Tactile Internet (Chapter 2)”, Techneconomyblog.com, (January 2017).

Henrik Bailier, Jan Lemark, Angelo Centonza, and Thomas Aasberg, “Applied network slicing scenarios in 5G”, Ericsson Technology Review, (February 2021).

Ericsson and Arthur D. Little, “Network slicing: A go-to-market guide to capture the high revenue potential”, Ericsson.com, (2021). The study concludes that network slicing is a 200 Bn. US\$ opportunity for CSPs by 2030. It is 1 out of 4 reports on network slicing. See also “Network slicing: Top 10 use cases to target”, “The essential building blocks of E2E network slicing” and “The network slicing transformation journey“.

S. O’Dea, “Global mobile industry revenue from 2016 to 2025″, (March, 2021).

S. M. Ahsan Kazmi, Latif U.Khan, Nguyen H. Tran, and Choong Seon Hong, “Network Slicing for 5G and Beyond Networks”, Springer International Publishing, (2019).

Jia Shen, Zhongda Du, & Zhi Zhang, “5G NR and enhancements, from R15 to R16”, Elsevier Science, (2021). Provides a really good overview of what to expect from 5G standalone. Chapter 12 provides a good explanation of (and in detail account for) how 5G Network Slicing works in detail. Definitely one of my favorite books on 5G, it is not “just” an ANRA.

GSMA Association, “An Introduction to Network Slicing”, (2017). A very good introduction to Network slicing.

ITU-T, “Network slice orchestration and management for providing network services to 3rd party in the IMT-2020 network”, Recommendation ITU-T Y.3153 (2019). Describing high-level customer slice request for instantiation, changes and ultimately the termination.

Claudia Campolo, Antonella Molinaro, Antonio Lera, and Francesco Menichella, “5G Network Slicing for Vehicle-to-Everything Services”, IEEE Wireless Communications 24, (December 2017). Great account of how network slicing should work for V2X services.

GSMA, “Securing the 5G Era” (2021). A good overview of security principles in 5G and how previous vulnerabilities in previous cellular generations are being addressed in 5G. This includes some explanation on why slicing further enhances security.

# 5G Standalone – European Demand & Expectations (Part I).

By the end of 2020, according with Ericsson, it was estimated that there where ca. 7.6 million 5G subscriptions in Western Europe (~ 1%). Compare this to North America’s ca. 14 million (~4%) and 190 million (~11%) North East Asia (e.g, China, South Korea, Japan, …).

Maybe Western Europe is not doing that great, when it comes to 5G penetration, in comparison with other big regional markets around the world. To some extend the reason may be that 4G network’s across most of Western Europe are performing very well and to an extend more than servicing consumers demand. For example, in The Netherlands, consumers on T-Mobile’s 4G gets, on average, a download speed of 100+ Mbps. About 5× the speed you on average would get in USA with 4G.

From the October 2021 statistics of the Global mobile Suppliers Association (GSA), 180 operators worldwide (across 72 countries) have already launched 5G. With 37% of those operators actively marketing 5G-based Fixed Wireless Access (FWA) to consumers and businesses. There are two main 5G deployment flavors; (a) non-standalone (NSA) deployment piggybacking on top of 4G. This is currently the most common deployment model, and (b) as standalone (SA) deployment, independently from legacy 4G. The 5G SA deployment model is to be expected to become the most common over the next couple of years. As of October 2021, 15 operators have launched 5G SA. It should be noted that, operators with 5G SA launched are also likely to support 5G in NSA mode as well, to provide 5G to all customers with a 5G capable handset (e.g., at the moment only 58% of commercial 5G devices supports 5G SA). Only reason for not supporting both NSA and SA would be for a greenfield operator or that the operator don’t have any 4G network (none of that type comes to my mind tbh). Another 25 operators globally are expected to be near launching standalone 5G.

It should be evident, also from the illustration below, that mobile customers globally got or will get a lot of additional download speed with the introduction of 5G. As operators introduce 5G, in their mobile networks, they will leapfrog their available capacity, speed and quality for their customers. For Europe in 2021 you would, with 5G, get an average downlink (DL) speed of 154 ± 90 Mbps compared to 2019 4G DL speed of 26 ± 8 Mbps. Thus, with 5G, in Europe, we have gained a whooping 6× in DL speed transitioning from 4G to 5G. In Asia Pacific, the quality gain is even more impressive with a 10× in DL speed and somewhat less in North America with 4× in DL speed. In general, for 5G speeds exceeding 200 Mbps on average may imply that operators have deployed 5G in the C-band band (e.g., with the C-band covering 3.3 to 5.0 GHz).

The above DL speed benchmark (by Opensignal) gives a good teaser for what to come and to expect from 5G download speed, once a 5G network is near you. There is of course much more to 5G than downlink (and uplink) speed. Some caution should be taken in the above comparison between 4G (2019) and 5G (2021) speed measurements. There are still a fair amount of networks around the world without 5G or only started upgrading their networks to 5G. I would expect the 5G average speed to reduce a bit and the speed variance to narrow as well (i.e., performance becoming more consistent).

In a previous blog I describe what to realistically expect from 5G and criticized some of the visionary aspects of the the original 5G white paper paper published back in February 2015. Of course, the tech-world doesn’t stand still and since the original 5G visionary paper by El Hattachi and Erfanian. 5G has become a lot more tangible as operators deploy it or is near deployment. More and more operators have launched 5G on-top of their 4G networks and in the configuration we define as non-standalone (i.e., 5G NSA). Within the next couple of years, coinciding with the access to higher frequencies (>2.1 GHz) with substantial (unused or underutilized) spectrum bandwidths of 50+ MHz, 5G standalone (SA) will be launched. Already today many high-end handsets support 5G SA ensuring a leapfrog in customer experience above and beyond shear mobile broadband speeds.

The below chart illustrates what to expect from 5G SA, what we already have in the “pocket” with 5G NSA, and how that may compare to existing 4G network capabilities.

There cannot be much doubt that with the introduction of the 5G Core (5GC) enabling 5G SA, we will enrich our capability and service-enabler landscape. Whether all of this cool new-ish “stuff” we get with 5G SA will make much top-line sense for operators and convenience for consumers at large is a different story for a near-future blog (so stay tuned). Also, there should not be too much doubt that 5G NSA already provide most of what the majority of our consumers are looking for (more speed).

Overall, 5G SA brings benefits, above and beyond NSA, on (a) round-trip delay (latency) which will be substantially lower in SA, as 5G does not piggyback on the slower 4G, enabling the low latency in ultra-reliable low latency communications (uRLLC), (b) a factor of 250× improvement device density (1 Million devices per km2) that can be handled supporting massive machine type communication scenarios (mMTC), (c) supports communications services at higher vehicular speeds, (d) in theory should result in low device power consumption than 5G NSA, and (e) enables new and possible less costly ways to achieve higher network (and connection) availability (e.g., with uRLLC).

Compared to 4G, 5G SA brings with it a more flexible, scalable and richer set of quality of service enablers. A 5G user equipment (UE) can have up to 1,024 so called QoS flows versus a 4G UE that can support up to 8 QoS classes (tied into the evolved packet core bearer). The advantage of moving to 5G SA is a significant reduction of QoS driven signaling load and management processing overhead, in comparison to what is the case in a 4G network. In 4G, it has been clear that the QoS enablers did not really match the requirements of many present day applications (i.e., brutal truth maybe is that the 4G QoS was outdated before it went live). This changes with the introduction of 5G SA.

So, when is it a good idea to implement 5G Standalone for mobile operators?

There are maybe three main events that should trigger operators to prepare for and launch 5G SA;

1. Economical demand for what 5G SA offers.
2. Critical mass of 5G consumers.
3. Want to claim being the first to offer 5G SA.

with the 3rd point being the least serious but certainly not an unlikely factor in deploying 5G SA. Apart from potentially enriching consumers experience, there are several operational advantages of transitioning to a 5GC, such as more mature IT-like cloudification of our telecommunications networks (i.e., going telco-cloud native) leading to (if designed properly) a higher degree of automation and autonomous network operations. Further, it may also allow the braver parts of telco-land to move a larger part of its network infrastructure capabilities into the public-cloud domain operated by hyperscalers or network-cloud consortia’s (if such entities will appear). Another element of the 5G SA cloud nativification (a new word?) that is frequently not well considered, is that it will allow operators to start out (very) small and scale up as business and consumer demand increases. I would expect that particular with hyperscalers and of course the-not-so-unusual-telco-supplier-suspects (e.g., Ericsson, Nokia, Huawei, Samsung, etc…), operators could launch fairly economical minimum viable products based on a minimum set of 5G SA capabilities sufficient to provide new and cost-efficient services. This will allow early entry for business-to-business new types of QoS and (or) slice-based services based on our new 5G SA capabilities.

### Western Europe mobile market expectations – 5G technology share.

By end of 2021, it is expected that Western Europe would have in the order of 36 Million 5G connections, around a 5% 5G penetration. Increasing to 80 Million (11%) by end of 2022. By 2024 to 2025, it is expected that 50% of all mobile connections would be 5G based. As of October 2021 ca. 58% of commercial available mobile devices supports already 5G SA. This SA share is anticipated to grow rapidly over the next couple of years making 5G NSA increasingly unimportant.

Approaching 50% of all connections being 5G appears a very good time to aim having 5G standalone implemented and launched for operators. Also as this may coincide with substantial efforts to re-farming existing frequency spectrum from 4G to 5G as 5G data traffic exceeds that of 4G.

For Western Europe 2021, ca. 18% of the total mobile connections are business related. This number is expected to steadily increase to about 22% by 2030. With the introduction of new 5G SA capabilities, as briefly summarized above, it is to be expected that the 5G business connection share quickly will increase to the current level and that business would be able to directly monetize uRLLC, mMTC and the underlying QoS and network slicing enablers. For consumers 5G SA will bring some additional benefits but maybe less obvious new monetization possibilities, beyond the proportion of consumers caring about latency (e.g., gamers). Though, it appears likely that the new capabilities could bring operators efficiency opportunities leading to improved margin earned on consumers (for another article).

Recommendation:

• Learn as much as possible from recent IT cloudification journeys (e.g., from monolithic to cloud, understand pros and cons with lift-and-shift strategies and the intricacies of operating cloud-native environments in public cloud domains).
• Aim to have 5GC available for 5G SA launch latest by 2024.
• Run 5GC minimum viable product poc’s with friendly (business) users prior to bigger launch.
• As 5G is launched on C-band / 3.x GHz it may likewise be a good point in time to have 5G SA available. At least for B2B customers that may benefit from uRLLC, lower latency in general, mMTC, a much richer set of QoS, network slicing, etc…
• Having a solid 4G to 5G spectrum re-farming strategy ready between now and 2024 (too late imo). This should map out 4G+NSA and SA supply dynamics as increasingly customers get 5G SA capabilities in their devices.

### Western Europe mobile market expectations – traffic growth.

With the growth of 5G connections and the expectation that 5G would further boost the mobile data consumption, it is expected that by 2023 – 2024, 50% of all mobile data traffic in Western Europe would be attributed to 5G. This is particular driven by increased rollout of 3.x GHz across the Western European footprint and associated massive MiMo (mMiMo) antenna deployments with 32×32 seems to be the telco-lands choice. In blended mobile data consumption a CAGR of around 34% is expected between 2020 and 2030, with 2030 having about 26× more mobile data traffic than that of 2020. Though, I suspect that in Western Europe, aggressive fiberization of telecommunications consumer and business markets, over the same period, may ultimately slow the growth (and demand) on mobile networks.

A typical Western European operator would have between 80 – 100+ MHz of bandwidth available for 4G its downlink services. The bandwidth variation being determined by how much is required of residual 3G and 2G services and whether the operator have acquired 1500MHz SDL (supplementary downlink) spectrum. With an average 4G antenna configuration of 4×4 MiMo and effective spectral efficiency of 2.25 Mbps/MHz/sector one would expect an average 4G downlink speed of 300+ Mbps per sector (@ 90 MHz committed to 4G). For 5G SA scenario with 100 MHz of 3.x GHz and 2×10 MHz @ 700 MHz, we should expect an average downlink speed of 500+ Mbps per sector for a 32×32 massive MiMo deployment at same effective spectral efficiency as 4G. In this example, although naïve, quality of coverage is ignored. With 5G, we more than double the available throughput and capacity available to the operator. So the question is whether we remain naïve and don’t care too much about the coverage aspects of 3.x GHz, as beam-forming will save the day and all will remain cheesy for our customers (if something sounds too good to be true, it rarely is true).

In an urban environment it is anticipated that with beam-forming available in our mMiMo antenna solutions downlink coverage will be reasonably fine (i.e., on average) with 3.x GHz antennas over-layed on operators existing macro-cellular footprint with minor densification required (initially). In the situation that 3.x GHz uplink cannot reach the on-macro-site antenna, the uplink can be closed by 5G @ 700 MHz, or other lower cellular frequencies available to the operator and assigned to 5G (if in standalone mode). Some concerns have been expressed in literature that present advanced higher order antenna’s (e.g., 16×16 and above ) will on average provide a poorer average coverage quality over a macro cellular area than what consumers would be used to with lower order antennas (e.g., 4×4 or lower) and that the only practical (at least with today’s state of antennas) solution would be sectorization to make up for beam forming shortfalls. In rural and sub-urban areas advanced antennas would be more suitable although the demand would be a lot less than in a busy urban environment. Of course closing the 3.x GHz with existing rural macro-cellular footprint may be a bigger challenge than in an urban clutter. Thus, massive MiMo deployments in rural areas may be much less economical and business case friendly to deploy. As more and more operators deploy 3.x GHz higher-order mMiMo more field experience will become available. So stay tuned to this topic. Although I would reserve a lot more CapEx in my near-future budget plans for substantial more sectorization in urban clutter than what I am sure is currently in most operators plans. Maybe in rural and suburban areas the need for sectorizations would be much smaller but then densification may be needed in order to provide a decent 3.x GHz coverage in general.

### Western Europe mobile market expectations – 5G RAN Capex.

That brings us to another important aspect of 5G deployment, the Radio Access Network (RAN) capital expenditures (CapEx). Using my own high-level (EU-based) forecast model based on technology deployment scenario per Western European country that in general considers 1 – 3% growth in new sites per anno until 2024, then from 2025 onwards, I assuming 2 – 5% growth due to densifications needs of 5G, driven by traffic growth and before mentioned coverage limitations of 3.x GHz. Exact timing and growth percentages depends on initial 5G commercial launch, timing of 3.x GHz deployment, traffic density (per site), and site density considering a country’s surface area.

According with Statista, Western Europe had in 2018 a cellular site base of 421 thousands. Further, Statista expected this base will grow with 2% per anno in the years after 2018. This gives an estimated number of cellular sites of 438k in 2020 that has been assumed as a starting point for 2020. The model estimates that by 2030, over the next 10 years, an additional 185k (+42%) sites will have been built in Western Europe to support 5G demand. 65% (120+k) of the site growth, over the next 10 years, will be in Germany, France, Italy, Spain and UK. All countries with relative larger geographical areas that are underserved with mobile broadband services today. Countries with incumbent mobile networks, originally based on 900 MHz GSM grids (of course densified since the good old GSM days), and thus having coarser cellular grids with higher degree of mismatching the higher 5G cellular frequencies (i.e., ≥ 2.5 GHz). In the model, I have not accounted for an increased demand of sectorizations to keep coverage quality upon higher order mMiMO deployments. This, may introduce some uncertainty in the Capex assessment. However, I anticipate that sectorization uncertainty may be covered in the accelerated site demand the last 5 years of the period.

In the illustration above, the RAN capital investment assumes all sites will eventually be fiberized by 2025. That may however be an optimistic assumption and for some countries, even in Western Europe, unrealistic and possibly highly uneconomical. New sites, in my model, are always fiberized (again possibly too optimistic). Miscellaneous (Misc.) accounts for any investments needed to support the RAN and Fiber investments (e.g., Core, Transport, Cap. Labor, etc..).

In the economical estimation price erosion has been taken into account. This erosion is a blended figure accounting for annual price reduction on equipment and increases in labor cost. I am assuming a 5-year replacement cycle with an associated 10% average price increase every 5 years (on the previous year’s eroded unit price). This accounts for higher capability equipment being deployed to support the increased traffic and service demand. The economical justification for the increase unit price being that otherwise even more new sites would be required than assumed in this model. In my RAN CapEx projection model, I am assuming rational deployment, that is demand driven deployment. Thus, operators investments are primarily demand driven, e.g., only deploying infrastructure required within a given financial recovery period (e.g., depreciation period). Thus, if an operator’s demand model indicate that it will need a given antenna configuration within the financial recovery period, it deploys that. Not a smaller configuration. Not a bigger configuration. Only the one required by demand within the financial recovery period. Of course, there may be operators with other deployment incentives than pure demand driven. Though on average I suspect this would have a neglectable effect on the scale of Western Europe (i.e., on average Western Europe Telco-land is assumed to be reasonable economically rational).

All in all, demand over the next 8 years leads to an 80+ Billion Euro RAN capital expenditure, required between 2022 and 2030. This, equivalent to a annual RAN investment level of a bit under 10 Billion Euro. The average RAN CapEx to Mobile Revenue over this period would be ca. 6.3%, which is not a shockingly high level (tbh), over a period that will see an intense rollout of 5G at increasingly higher frequencies and increasingly capable antenna configurations as demand picks up. Biggest threat to capital expenditures is poor demand models (or no demand models) and planning processes investing too much too early, ultimately resulting in buyers regret and cycled in-efficient investment levels over the next 10 years. And for the reader still awake and sharp, please do note that I have not mentioned the huge elephant in the room … The associated incremental operational expense (OpEx) that such investments will incur.

As mobile revenues are not expected to increase over the period 2022 to 2030, this leaves 5G investments main purpose to maintaining current business level dominated by consumer demand. I hope this scenario will not materialize. Given how much extra quality and service potential 5G will deliver over the next 10 years, it seems rather pessimistic to assume that our customers would not be willing to pay more for that service enhancement that 5G will brings with it. Alas, time will show.

### Acknowledgement.

I greatly acknowledge my wife Eva Varadi for her support, patience and understanding during the creative process of writing this Blog. Petr Ledl, head of DTAG’s Research & Trials, and his team’s work has been a continuous inspiration to me (thank you so much for always picking up on that phone call Petr!). Also many of my Deutsche Telekom AG, T-Mobile NL & Industry colleagues in general have in countless of ways contributed to my thinking and ideas leading to this little Blog. Thank you!

Kim Kyllesbech Larsen, “5G Standalone Will Deliver! – But What?”, Keynote presentation at Day 2 Telecoms Europe 5G Conference, (November 2021). A YouTube voice over is given here on the presentation.

Kim Kyllesbech Larsen, “5G Economics – The Numbers (Appendix X).”, Techneconomyblog.com, (July 2017).

Kim Kyllesbech Larsen, “5G Economics – An Introduction (Chapter 1)”, Techneconomyblog.com, (December 2016).

Peter Boyland, “The State of Mobile Network Experience – Benchmarking mobile on the eve of the 5G revolution”, OpenSignal, (May 2019).

Ian Fogg, “Benchmarking the Global 5G Experience”, OpenSignal, (November 2021).

Rachid El Hattachi & Javan Erfanian , “5G White Paper”, NGMN Alliance, (February 2015). See also “5G White Paper 2” by Nick Sampson (Orange), Javan Erfanian (Bell Canada) and Nan Hu (China Mobile).

Global Mobile Frequencies Database. (last update, 25 May 2021). I recommend very much to subscribe to this database (€595,. single user license). Provides a wealth of information on spectrum portfolios across the world.

Thomas Alsop, “Number of telecom tower sites in Europe by country in 2018 (in 1,000s)”, Statista Telecommunications, (July 2020).

Jia Shen, Zhongda Du, & Zhi Zhang, “5G NR and enhancements, from R15 to R16”, Elsevier Science, (2021). Provides a really good overview of what to expect from 5G standalone. Particular, very good comparison with what is provided with 4G and the differences with 5G (SA and NSA).

Ali Zaidi, Fredrik Athley, Jonas Medbo, Ulf Gustavsson, Giuseppe Durisi, & Xiaoming Chen, “5G Physical Layer Principles, Models and Technology Components”, Elsevier Science, (2018). The physical layer will always pose a performance limitation on a wireless network. Fundamentally, the amount of information that can be transferred between two locations will be limited by the availability of spectrum, the laws of electromagnetic propagation, and the principles of information theory. This book provides a good description of the 5G NR physical layer including its benefits and limitations. It provides a good foundation for modelling and simulation of 5G NR.

Thomas L. Marzetta, Erik G. Larsson, Hong Yang, Hien Quoc Ngo, “Fundamentals of Massive MIMO”, Cambridge University Press, (2016). Excellent account of the workings of advanced antenna systems such as massive MiMo.

Western Europe: Western Europe has a bit of a fluid definition (I have found), here Western Europe includes the following countries comprising a population of ca. 425 Million people (in 2021); Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland United Kingdom, Andorra, Cyprus, Faeroe Islands, Greenland, Guernsey, Jersey, Malta, Luxembourg, Monaco, Liechtenstein, San Marino, Gibraltar.