Book Review: The 5G Myth

The 5G Myth is the provocative title of a recent book by William Webb, CEO of Weightless SIG, a standard body for IoT/M2M technology. In this book, the author tells a compelling story of a stagnating market for cellular communications, where the customers are generally satisfied with the data rates delivered by the 4G networks. The revenue growth for the mobile network operators (MNOs) is relatively low and also in decay, since the current services are so good that the customers are unwilling to pay more for improved service quality. Although many new wireless services have materialized over the past decade (e.g., video streaming, social networks, video calls, mobile payment, and location-based services), the MNOs have failed to take the leading role in any of them. Instead, the customers make use of external services (e.g., Youtube, Facebook, Skype, Apple Pay, and Google Maps) and only pay the MNOs to deliver the data bits.

The author argues that, under these circumstances, the MNOs have little to gain from investing in 5G technology. Most customers are not asking for any of the envisaged 5G services and will not be inclined to pay extra for them. Webb even compares the situation with the prisoner’s dilemma: the MNOs would benefit the most from not investing in 5G, but they will anyway make investments to avoid a situation where customers switch to a competitor that has invested in 5G. The picture that Webb paints of 5G is rather pessimistic compared to a recent McKinsey report, where the more cost-efficient network operation is described as a key reason for MNOs to invest in 5G.

The author provides a refreshing description of the market for cellular communications, which is important in a time when the research community focuses more on broad 5G visions than on the customers’ actual needs. The book is thus a recommended read for 5G researchers, since we should all ask ourselves if we are developing a technology that tackles the right unsolved problems.

Webb does not only criticize the economic incentives for 5G deployment, but also the 5G visions and technologies in general. The claims are in many cases reasonable; for example, Webb accurately points out that most of the 5G performance goals are overly optimistic and probably only required by a tiny fraction of the user base. He also accurately points out that some “5G applications” already have a wireless solution (e.g., indoor IoT devices connected over WiFi) or should preferably be wired (e.g., ultra-reliable low-latency applications such as remote surgery).

However, it is also in this part of the book that the argumentation sometimes falls short. For example, Webb extrapolates a recent drop in traffic growth to claim that the global traffic volume will reach a plateau in 2027. It is plausible that the traffic growth rate will reduce as a larger and larger fraction of the global population gets access to wireless high-speed connections. But one should bear in mind that we have witnessed an exponential growth in wireless communication traffic for the past century (known as Cooper’s law), so this trend can just as well continue for a few more decades, potentially at a lower growth rate than in the past decade.

Webb also provides a misleading description of multiuser MIMO by claiming that 1) the antenna arrays would be unreasonable large at cellular frequencies and 2) the beamforming requires complicated angular beam-steering. These are two of the myths that we dispelled in the paper “Massive MIMO: Ten myths and one grand question” last year. In fact, testbeds have demonstrated that massive multiuser MIMO is feasible in lower frequency bands, and particularly useful to improve the spectral efficiency through coherent beamforming and spatial multiplexing of users. Reciprocity-based beamforming is a solution for mobile and cell-edge users, for which angular beam-steering indeed is inefficient.

The book is not as pessimistic about the future as it might seem from this review. Webb provides an alternative vision for future wireless communications, where consistent connectivity rather than higher peak rates is the main focus. This coincides with one of the 5G performance goals (i.e., 50 Mbit/s everywhere), but Webb advocates an extensive government-supported deployment of WiFi instead of 5G technology. The use WiFi is not a bad idea; I personally consume relatively little cellular data since WiFi is available at home, at work, and at many public locations in Sweden. However, the cellular services are necessary to realize the dream of consistent connectivity, particularly outdoors and when in motion. This is where a 5G cellular technology that delivers better coverage and higher data rates at the cell edge is highly desirable. Reciprocity-based Massive MIMO seems to be the solution that can deliver this, thus Webb would have had a stronger case if this technology was properly integrated into his vision.

In summary, the combination of 5G Massive MIMO for wide-area coverage and WiFi for local-area coverage might be the way to truly deliver consistent connectivity.

Real-Time Massive MIMO DSP at 50 milliWatt

Colleagues at Lund University presented last month a working circuit that performs, in real time, zero-forcing decoding and precoding of 8 simultaneous terminals with 128 base station antennas, over a 20 MHz bandwidth at a power consumption of about 50 milliWatt.

Impressive, and important.

Granted, this number does not include the complexity of FFTs, sampling rate conversions, and several other (non-insignificant) tasks; however, it does include the bulk of the “Massive-MIMO”-specific digital processing. The design exploits a number of tricks and Massive-MIMO specific properties: diagonal dominance of the channel Gramian, in particular, in sufficiently favorable propagation.

When I started work on Massive MIMO in 2009, the common view held was that the technology would be infeasible because of computational complexity. Particularly, the sheer idea of performing zero-forcing processing in real time was met with, if not ridicule, extreme skepticism. We quickly realized, however, that a reasonable DSP implementation would require no more than some ten Watt. While that is a small number in itself, it turned out to be an overestimate by orders of magnitude!

I spoke with some of the lead inventors of the chip, to learn more about its design. First, the architectures for decoding and for precoding differ a bit. While there is no fundamental reason for why this has to be so, one motivation is the possible use of nonlinear detectors on uplink. (The need for such detectors, for most “typical” cellular Massive MIMO deployments, is not clear – but that is another story.)

Second, and more importantly, the scalability of the design is not clear. While the complexity of the matrix operations themselves scale fast with the dimension, the precision in the arithmetics may have to be increased as well – resulting in a much-faster-than-cubically overall complexity scaling. Since Massive MIMO operates at its best when multiplexing to many tens of terminals (or even thousands, in some applications), significant challenges remain for the future. That is good news for circuit engineers, algorithm designers, and communications theoreticians alike. The next ten years will be exciting.

How Much Performance is Lost by FDD Operation?

There has been a long-standing debate on the relative performance between reciprocity-based (TDD) Massive MIMO and that of FDD solutions based on grid-of-beams, or hybrid beamforming architectures. The matter was, for example, the subject of a heated debate in the 2015 Globecom industry panel “Massive MIMO vs FD-MIMO: Defining the next generation of MIMO in 5G” where on the one hand, the commercial arguments for grid-of-beams solutions were clear, but on the other hand, their real potential for high-performance spatial multiplexing was strongly contested.

While it is known that grid-of-beams solutions perform poorly in isotropic scattering, no prior experimental results are known. This new paper:

Massive MIMO Performance—TDD Versus FDD: What Do Measurements Say?

answers this performance question through the analysis of real Massive MIMO channel measurement data obtained at the 2.6 GHz band. Except for in certain line-of-sight (LOS) environments, the original reciprocity-based TDD Massive MIMO represents the only effective implementation of Massive MIMO at the frequency bands under consideration.

Teaching the Principles of Massive MIMO

In January this year, the IEEE Signal Processing Magazine contained an article by Erik G. Larsson, Danyo Danev, Mikael Olofsson, and Simon Sörman on “Teaching the Principles of Massive MIMO: Exploring reciprocity-based multiuser MIMO beamforming using acoustic waves“. It describes an exciting approach to teach the basics of Massive MIMO communication by implementing the system acoustically, using loudspeaker elements instead of antennas. The fifth-year engineering students at Linköping University have performed such implementations in 2014, 2015, and 2016, in the form of a conceive-design-implement-operate (CDIO) project.

The article details the teaching principles and experiences that the teachers and students had from the 2015 edition of the CDIO-project. This was also described in a previous blog post. In the following video, the students describe and demonstrate the end-result of the 2016 edition of the project. The acoustic testbed is now truly massive, since 64 loudspeakers were used.

Relative Value of Spectrum

What is more worth? 1 MHz bandwidth at 100 MHz carrier frequency, or 10 MHz bandwidth at 1 GHz carrier? Conventional wisdom has it that higher carrier frequencies are more valuable because “there is more bandwidth there”. In this post, I will explain why that is not entirely correct.

The basic presumption of TDD/reciprocity-based Massive MIMO is that all activity, comprising the transmission of uplink pilots, uplink data and downlink data, takes place inside of a coherence interval:

At fixed mobility, in meter/second, the dimensionality of the coherence interval is proportional to the wavelength, because the Doppler spread is proportional to the carrier frequency.

In a single cell, with max-min fairness power control (for uniform quality-of-service provision), the sum-throughput of Massive MIMO can be computed analytically and is given by the following formula:

In this formula,

  • $B$ = bandwidth in Hertz (split equally between uplink and downlink)
  • $M$ = number of base station antennas
  • $K$ = number of multiplexed terminals
  • $B_c$ = coherence bandwidth in Hertz (independent of carrier frequency)
  • $T_c$ = coherence time in seconds (inversely proportional to carrier frequency)
  • SNR = signal-to-noise ratio (“normalized transmit power”)
  • $\beta_k$ = path loss for the k:th terminal
  • $\gamma_k$ = constant, close to $\beta_k$ with sufficient pilot power

This formula assumes independent Rayleigh fading, but the general conclusions remain under other models.

The factor that pre-multiplies the logarithm depends on $K$.
The pre-log factor is maximized when $K=B_c T_c/2$. The maximal value is $B B_c T_c/8$, which is proportional to $T_c$, and therefore proportional to the wavelength. Due to the multiplication $B T_c$, one can get same pre-log factor using a smaller bandwidth by instead increasing the wavelength, i.e., reducing the carrier frequency. At the same time, assuming appropriate scaling of the number of antennas, $M$, with the number of terminals, $K$, the quantity inside of the logarithm is a constant.

Concluding, the sum spectral efficiency (in b/s/Hz) easily can double for every doubling of the wavelength: a megahertz of bandwidth at 100 MHz carrier is ten times more worth than a megahertz of bandwidth at a 1 GHz carrier. So while there is more bandwidth available at higher carriers, the potential multiplexing gains are correspondingly smaller.

In this example,

all three setups give the same sum-throughput, however, the throughput per terminal is vastly different.

More Demanding Massive MIMO Trials Using the Bristol Testbed

Last year, the 128-antenna Massive MIMO testbed at University of Bristol was used to set world records in per-cell spectral efficiency. Those measurements were conducted in a controlled indoor environment, but demonstrated that the theoretical gains of the technology are also practically achievable—at least in simple propagation scenarios.

The Bristol team has now worked with British Telecom and conducted trials at their site in Adastral Park, Suffolk, in more demanding user scenarios. In the indoor exhibition hall trial,  24 user streams were multiplexed over a 20 MHz bandwidth, resulting in a sum rate of 2 Gbit/s or a spectral efficiency of 100 bit/s/Hz/cell.

Several outdoor experiments were also conducted, which included user mobility. We are looking forward to see more details on these experiments, but in the meantime one can have a look at the following video:

Update: We have corrected the bandwidth number in this post.

Massive MIMO at the Mobile World Congress 2017

The Mobile World Congress (MWC) was held in Barcelona last week. Several major telecom companies took the opportunity to showcase and describe their pre-5G solutions based on Massive MIMO technology.

Huawei and Optus carried out an infield trial on February 26, where a sum rate of 655 Mbit/s was obtained over a 20 MHz channel by spatial multiplexing of 16 users. This corresponds to 33 bit/s/Hz or 2 bit/s/Hz/user, which are typical spectral efficiencies to expect from Massive MIMO. The base station was equipped with 128 antenna ports, but the press release provides no details on whether uplink or downlink transmission was considered.

ZTE demonstrated their TDD Massive MIMO solution, which we have described earlier on the blog. The company claimed to set a new record for single-site peak sum rate at their MWC demonstration. Spatial multiplexing of 16 data streams was considered with 256-QAM and the sum rate was 2.1 Gbit/s. Further details are found in their press release.

Nokia and Sprint demonstrated TDD-based Massive MIMO technology for LTE networks, using 64 antenna ports at the base station. Spatial multiplexing of eight commercial LTE terminals was considered. Communication theory predicts that the sum rate should grow proportionally to the number of terminals, which is consistent with the 8x improvement in uplink rates and 5x improvement in downlink rates that were reported. Further details are found in their press release or in the following video:

Ericsson and Sprint are also planning Massive MIMO tests in LTE TDD in the second half of 2017, according to another press release.

Did we miss any Massive MIMO related announcement from MWC? Please tell us in the comment field below!

News – commentary – mythbusting