Telco energy consumption – a path to a greener future?

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!


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.

\frac{E_{4G}}{bit} \; = \; \frac {\; P_{4G} \;} {\; B_{4G} \; \cdot \; \eta_{4G,eff} \; \cdot N \;\;\;} and \;\;\; \frac{E_{5G}}{bit} \; = \; \frac {\; P_{5G} \;} {\; B_{5G} \; \cdot \; \eta_{5G,eff} \; \cdot N \;}

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

\frac{E_{4G}/bit}{E_{5G}/bit} \; = \; \frac{\; P_{4G} \;}{\; P_{5G}} \; \cdot \; \frac{\; B_{5G} \;}{\; B_{4G}} \; \cdot \; \frac{\; \eta_{5G,eff} \;}{\; \eta_{4G,eff}}

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

\frac{P_{4G}}{P_{5G}} \; \lesssim \; 1

\frac{B_{5G}}{B_{4G}} \; > \;2

\frac{\; \eta_{5G,eff} \;}{\; \eta_{4G,eff}} \; \approx \; 10

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

\frac{E_{4G}/bit}{E_{5G}/bit} \; \approx \; \frac{\; \eta_{5G,eff} \;}{\; \eta_{4G,eff}} \; \gtrsim \; 10

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,

E_{RAT} \; = \; P_{RAT} \; \cdot \; t \; \approx \; E_{idle} \; + \; P_{BB, RAT} \; \cdot \; t \; +\sum_{freq}P_{freq,\; antenna\; type}\; \cdot \; t_{freq} \;

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.


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).

\frac{E_{4G}/bit}{E_{5G}/bit} \; = \; \frac{\; P_{4G} \;}{\; P_{5G}} \; \cdot \; \frac{\; B_{5G} \;}{\; B_{4G}} \; \cdot \; \frac{\; \eta_{5G,eff} \;}{\; \eta_{4G,eff}} \; \geq \; 2,000


\frac{\; P_{4G} \;}{\; P_{5G}} \; \cdot \; \frac{\; B_{5G} \;}{\; B_{4G}} \; \geq \; 200


\frac{\; \eta_{5G,eff} \;}{\; \eta_{4G,eff}} \; \approx \; 10

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

\frac{E_{5G}}{E_{4G}} \; = \; \frac{\; P_{5G} \; \cdot \; t\;}{\; P_{4G} \; \cdot \; t}\; \approx \; \frac{\; P_{5G} \;}{\; P_{4G} \; } \; \leq \; \frac{1}{2}

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.


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.


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.


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.


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.