Category Archives: News

New book: Introduction to Multiple Antenna Communications and Reconfigurable Surfaces

The way that mobile communication networks are designed changed dramatically with the advent of 5G. In the past, it was all about utilizing large bandwidths and deploying many base stations. Nowadays, we are instead equipping each base station and smartphone with multiple antennas, which enables us to use signal processing algorithms to improve signal strength, enhance reliability, and send more data of the same spectrum by controlling the spatial direction of each signal layer. In essence, we refine the hardware and algorithms instead of deploying more infrastructure and requiring more signal resources.

Further dramatic changes are envisioned in the 6G era, where the use of even larger antenna arrays uncovers near-field effects, conventional frequency bands will be complemented with millimeter and sub-terahertz spectrum, optimized reflections from reconfigurable surfaces might improve propagation conditions, and communication networks can provide new localization and sensing services.

These extraordinary changes will affect not only the wireless technology but also the required knowledge and skills among the engineers and researchers who will implement it. Hence, it is essential to revise the curriculum in basic wireless communication courses to shift focus onto these new aspects of the physical layer.

When I realized the need for a new basic textbook, I joined forces with Özlem Tuğfe Demir to write “Introduction to Multiple Antenna Communications and Reconfigurable Surfaces”, NowOpen (2024). The book provides a gentle introduction to multiple antenna communications with a focus on system modeling, channel capacity theory, algorithms, and practical implications. The reader is expected to be familiar with basic signals and systems, linear algebra, probability theory, and digital communications, but a comprehensive recap is provided in the book. Once the fundamental point-to-point and multi-user MIMO theory and its practical implications have been covered, we also demonstrate how similar methodologies are used for wireless localization, radar sensing, and optimization of reconfigurable intelligent surfaces.

The first draft of the book was written for the first-year Master course TSKS14 Multiple Antenna Communications at Linköping University. You might have seen the YouTube video series that I produced while teaching that course during the pandemic. The book covers the same things and much more, and it contains numerous new examples and exercises.

The writing process focused on pinpointing all the technical and practical know-how that we believe the next-generation wireless engineers must have within this topic. We then wrote the text as a story that leads to these points. The writing has taken a long time: four years of progressive course material development followed by two years of intense writing with the goal of completing a book.

Our ambition has not been to write the one-and-only textbook on the topic, but the book that one should read first to build a deep knowledge foundation. After that, one can continue reading books such as “Fundamentals of Massive MIMO,” “Massive MIMO Networks,” or “Foundations of User-Centric Cell-Free Massive MIMO,” depending on personal preference.

The book is published with open access and accompanying MATLAB code that reproduces all the simulation results. You can access the PDF from the publisher’s website, where you can also buy printed copies. We are extremely proud of the book and hope you will like it too!

Episode 38: Things We Learned at the 6G Symposium

We have now released the 38th episode of the podcast Wireless Future. It has the following abstract:

Many topics are studied within the 6G research community, from hardware design to algorithms, protocols, and services. Erik G. Larsson and Emil Björnson recently attended the ELLIIT 6G Symposium in Lund, Sweden. In this episode, they discuss ten things that they learned from listening to the keynote speeches. The topics span from integrated sensing, positioning, and localization via machine-learning applications in communications to fundamental communication theory, such as circuits for universal channel decoding and jamming protection. The expected 6G spectrum ranges, energy efficiency in base stations, and new use cases for electromagnetic materials are also covered. You can find slides from the symposium here.

Ten things we learned

3:22 Integrated sensing and communication 12:45 Positioning using phase-coherent access points 20:42 Experimental work on positioning from ELLIIT Focus period 24:02 Trained activation functions in machine learning 30:25 Learning to operate a reconfigurable intelligent surface 37:15 Guessing Random Additive Noise Decoding (GRAND) 44:30 Protecting digital beamforming against jamming 53:02 6G frequency spectrum 1:01:50 Energy efficiency in base stations 1:08:47 New use cases for electromagnetic materials

You can watch the video podcast on YouTube:

You can listen to the audio-only podcast at the following places:

The Golden Frequencies

The golden frequencies for wireless access are in the band below 6 GHz. Why are these frequencies so valuable? The reasons, of course, are rooted in the physics. First, the wavelength is short enough that a (numerically) large array has an attractive form factor, enabling spatial multiplexing even from a single antenna panel. At the same time, the wavelength is large enough that a sufficiently large aperture can be obtained with a reasonable number of antennas – which, in turn, directly translates into a favorable link budget and high coverage. Second, below 6 GHz, Doppler is low enough, even at high mobility, that reciprocity-based beamforming based on uplink pilots for channel estimation works without relying on prior assumptions on the propagation environment, let alone on the fading statistics. This directly translates into robustness, simplicity of implementation, and scalability with respect to the number of service antennas. Third, these frequencies are not hindered so much by blockage, and strong multipath components can guarantee connectivity even when there is no line-of-sight, while in contrast, for mmWave a human blocking the line-of-sight path can suffice to break the link. Finally, analog microelectronics for the golden bands is mature, and very energy-efficient.

Distributed MIMO (D-MIMO) with reciprocity-based beamforming is the natural way of best exploiting the golden frequencies. This technology naturally operates in the [geometric] near-field of the “super-array” collectively constituted by all antenna panels together. In fact, the actual antenna deployment hardly matters at all! With reciprocity-based beamforming, the physical shape of the actual beams, and grating lobe phenomena in particular, become irrelevant. If anything, given a set of antennas, it is advantageous to spread them out over as large aperture as possible. The only definite no-no is to place antennas closer than half a wavelength together: such dense packing of antennas is almost never meaningful, as sampling points lambda/2-spaced apart captures essentially all the degrees of freedom of the field; putting the antennas closer results in coupling effects that are usually of more harm than benefit.

REINDEER is the European project that develops and demonstrates D-MIMO for the golden frequencies. What are the most important technical challenges? One is, down-to-earth, to handle the vast amounts of baseband data, and process them in real time. Another is time and phase synchronization of distributed MIMO arrays: antenna panels driven by independent local oscillators must be re-calibrated for joint reciprocity every time the oscillators have drifted apart. Locking the clocks using cabling is possible in principle, but considered very expensive to deploy. A third is initial access, covering space uniformly with system information signals, and waking up sleeping devices. A fourth is energy-efficiency, at all levels in the network. A fifth is the integration of service of energy-neutral devices that communicate via backscattering. D-MIMO naturally offers the infrastructure for that, permitting simultaneous transmission and reception from different panels in a bistatic setup; however, these activities break the TDD flow and must be carefully integrated into the workings of the system.

If sub-6 GHz are gold, then what is silver? Perhaps right above: the 7-15 GHz band, that is intended in 6G to extend the “main capacity” layer. It appears that these bands can still be suitable mobile applications, and that higher carriers (28 GHz, 38 GHz) are appropriate for fixed wireless access mostly. But the sub-6 GHz bands will remain golden and the first choice for the most challenging situations: high mobility, area coverage, and outdoor-to-indoor.

Erik G. Larsson
Liesbet Van der Perre

Episode 36: 6G from an Operator Perspective

We have now released the 36th episode of the podcast Wireless Future. It has the following abstract:

It is easy to get carried away by futuristic 6G visions, but what matters in the end is what technology and services the telecom operators will deploy. In this episode, Erik G. Larsson and Emil Björnson discuss a new white paper from SK Telecom that describes the lessons learned from 5G and how these experiences can be utilized to make 6G more successful. The paper and conversation cover network evolution, commercial use cases, virtualization, artificial intelligence, and frequency spectrum. The latest developments in defining official 6G requirements are also discussed. The white paper can be found here. The following news article about mmWave licenses is mentioned. The IMT-2030 Framework for 6G can be found here.

You can watch the video podcast on YouTube:

You can listen to the audio-only podcast at the following places:

25 Years of Signal Processing Advances for Multiantenna Communications

Multiantenna communications have a long and winding history, starting with how Guglielmo Marconi used an array of phase-aligned antennas to communicate over the Atlantic and Karl Ferdinand Braun used a triangular array to transmit phase-shifted signal copies to beamform in a controlled direction. The use of antenna arrays for spatial diversity and multiplexing has since appeared. The cellular network pioneer Martin Cooper tried to launch multi-user MIMO in the 1990s but concluded in 1996 that “computers weren’t powerful enough to operate it”.

During the last 25 years, multiantenna communications have changed from being a technology only used for beamforming and diversity, to becoming a mainstream enabler of high-capacity communication in 5G. It is used for both single-user and multi-user MIMO when connecting any modern mobile phone to the Internet, in both the 3 GHz and mmWave bands.

The IEEE Signal Processing Society is celebrating its 75 years anniversary and, therefore, the Signal Processing Magazine publishes a special issue focusing on the last 25 years of research developments. I have written a paper for this issue called “25 Years of Signal Processing Advances for Multiantenna Communications“. It is now available on arXiv, and it is co-authored by Yonina Eldar, Erik G. Larsson, Angel Lozano, and H. Vincent Poor. I hope you will like it!

Episode 34: How to Achieve 1 Terabit/s over Wireless?

We have now released the 34th episode of the podcast Wireless Future. It has the following abstract:

The speed of wired optical fiber technology is soon reaching 1 million megabits per second, also known as 1 terabit/s. Wireless technology is improving at the same pace but is 10 years behind in speed, thus we can expect to reach 1 terabit/s over wireless during the next decade. In this episode, Erik G. Larsson and Emil Björnson discuss these expected developments with a focus on the potential use cases and how to reach these immense speeds in different frequency bands – from 1 GHz to 200 GHz. Their own thoughts are mixed with insights gathered at a recent workshop at TU Berlin. Major research challenges remain, particularly related to algorithms, transceiver hardware, and decoding complexity.

You can watch the video podcast on YouTube:

You can listen to the audio-only podcast at the following places:

Making Cell-Free Massive MIMO Competitive

The paper “Making Cell-Free Massive MIMO Competitive with MMSE Processing and Centralized Implementation” that I’ve authored together with Luca Sanguinetti has been awarded the 2022 IEEE Marconi Prize Paper Award in Wireless Communications. This is a great honor that places the paper on the same list as many seminal papers published in the IEEE Transactions on Wireless Communications.

I will take this opportunity to elaborate on five things that I learned while writing the paper. The basic premise is that we analyze the uplink of a system with many distributed access points (APs) that serve a collection of user devices at the same time and frequency. We compared the data rates that can be achieved depending on how deeply the APs are collaborating, from Level 1 (cellular network with no cooperation) to Level 4 (cell-free network with centralized computations based on complete signal knowledge). We also compared maximum ratio (MR) processing of the received signals with local and centralized forms of minimum mean-squared error (MMSE) processing.

I learned the following five things:

  1. MMSE processing always outperforms MR processing. This might seem obvious, since the former scheme can suppress interference, but the really surprising thing was that the performance difference is large even for single-antenna APs that operate distributively. The reason is that MMSE processing provides much more channel hardening.
  2. Distributed MR processing is the worst-case scenario. Many of the early works on cell-free massive MIMO assumed distributed MR processing and focused on developing advanced power control algorithms. We demonstrated that one can achieve better performance with MMSE processing and rudimentary power control; thus, when designing a cell-free system, the choice of processing scheme is of primary importance, while the choice of power control is secondary.
  3. Linear uplink processing is nearly optimal. In a fully centralized implementation, it is possible to implement non-linear processing schemes for signal detection; in particular, successive interference cancellation could be used. We showed that this approach only increases the sum rate by a few percent, which isn’t enough to motivate the increased complexity. The reason is that we seldom have any strong interfering signals, just many weakly interfering signals.
  4. Distributed processing increases fronthaul signaling. Since the received signals are distributed over the APs, it might seem logical that one can reduce the fronthaul signaling by also doing parts of the processing distributively. This is not the case in the intended operating regime of cell-free massive MIMO, where each AP serves more or equally many users than it has antennas. In this case, fewer parameters need to be sent over the fronthaul when making a centralized implementation!
  5. Max-min fairness is a terrible performance goal. While a key motivation behind cell-free massive MIMO is to even out the performance variations in the system, compared to cellular networks, we shouldn’t strive for exact uniformity. To put it differently, the user with the worst channel conditions in the country shouldn’t dictate the performance of everyone else! Several early works on the topic focused on max-min fairness optimization and showed very promising simulation results, but when I attempted to reproduce these results, I noticed that they were obtained by terminating the optimization algorithms long before the max-min fairness solution was found. This indicates that we need a performance goal based on relative fairness (proportional fairness?) instead of the overly strict max-min fairness goal.

Since the paper was written in 2019, I have treated centralized MMSE processing as the golden standard for cell-free massive MIMO. I have continued looking for ways to reduce the fronthaul signaling while making use of distributed computational resources (that likely will be available in practice). I will mention two recent papers in this direction. The first is “MMSE-Optimal Sequential Processing for Cell-Free Massive MIMO With Radio Stripes“, which shows that one can implement centralized MMSE processing in a distributed/sequential manner, if the fronthaul is sequential. The paper “Team MMSE Precoding with Applications to Cell-free Massive MIMO” develops a methodology for dealing with the corresponding downlink problem, which is more challenging due to power and causality constraints.

Finally, let me thank IEEE ComSoc for not only giving us the Marconi Prize Paper Award but also producing the following nice video about the paper: