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.
We have now released the 37th episode of the podcast Wireless Future. It has the following abstract:
We celebrate the three-year anniversary of the podcast with a live recording from the Wireless Future Symposium that was held in September 2023. A panel of experts answered questions that we received on social media. Liesbet Van der Perre (KU Leuven) discusses the future of wireless Internet-of-Things, Fredrik Tufvesson (Lund University) explains new channel properties at higher frequencies, Jakob Hoydis (NVIDIA) describes differentiable ray-tracing and its connection to machine learning, Deniz Gündüz (Imperial College London) presents his vision for how artificial intelligence will affect future wireless networks, Henk Wymeersch (Chalmers University of Technology) elaborates on the similarities and differences between communication and positioning, and Luca Sanguinetti (University of Pisa) demystifies holographic MIMO and its relation to near-field communications.
You can watch the video podcast on YouTube:
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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:
We have now released the 35th episode of the podcast Wireless Future. It has the following abstract:
The main directions for 6G research have been established and include pushing the communication to higher frequency bands, creating smart radio environments, and removing the conventional cell structure. There are many engineering issues to address on the way to realizing these visions. In this episode, Emil Björnson and Erik G. Larsson discuss the article “The Road to 6G: Ten Physical Layer Challenges for Communications Engineers” from 2021. What specific research challenges did the authors identify, and what remains to be done? The conversation covers system modeling complexity, hardware implementation issues, and signal processing scalability. The article can be found here: https://arxiv.org/pdf/2004.07130 The following papers were also mentioned: https://arxiv.org/pdf/2111.15568 and https://arxiv.org/pdf/2104.15027
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You can listen to the audio-only podcast at the following places:
When I first heard Tom Marzetta describe Massive MIMO with an infinite number of antennas, I felt uncomfortable since it challenged my way of thinking about MIMO. His results and conclusions seemed too good to be true and were obtained using a surprisingly simple channel model. I was a Ph.D. student then and couldn’t pinpoint specific errors, but I sensed something was wrong with the asymptotic analysis.
I’ve later grown to understand that Massive MIMO has all the fantastic features that Marzetta envisioned in his seminal paper. Even the conclusions from his asymptotic analysis are correct, even if the choice of model overemphasizes the impact of pilot contamination. The only issue is that one cannot reach all the way to the asymptotic limit, where the number of antennas is infinite.
Assuming that the universe is infinite, we could indeed build an infinitely large antenna array. The issue is that the uncorrelated and correlated fading models that were used for asymptotic Massive MIMO analysis during the last decade will, as the number of antennas increases, eventually deliver more signal power to the receiver than was transmitted. This breaches a fundamental physical principle: the law of conservation of energy. Hence, the conventional channel models cannot predict the actual performance limits.
In 2019, Luca Sanguinetti and I finally figured out how to study the actual asymptotic performance limits. As the number of antennas and array size grow, the receiver will eventually be in the radiative near-field of the transmitter. This basically means that the outermost antennas contribute less to the channel gain than the innermost antennas, and this effect becomes dominant as the number of antennas goes to infinity. We published the analytical results in the article “Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces“ in the IEEE Open Journal of the Communications Society. In particular, we highlighted the implications for both MIMO receivers, MIMO relays, and intelligent reflecting surfaces. I have explained our main insights in a previous blog post, so I will not repeat it here.
I am proud to announce that this article has received the 2023 IEEE Communications Society Outstanding Paper Award. We wrote this article to quench our curiosity without knowing that the analysis of near-field propagation would later become one of the leading 6G research directions. From our perspective, we just found an answer to a fundamental issue that had been bugging us for years and published it in case others would be interested. Another journal first rejected the paper; thus, this is also a story of how one can reach success with hard work, even when other researchers are initially skeptical of your results and their practical utility.
The following 5-minute video summarizes the paper neatly:
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.
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Authors: William Tärneberg, Gilles Callebaut and Liesbet Van der Perre
What’s in a name? ‘The spoken newspaper’ is the term grandma1 used to call the news broadcasted on the radio. The curious name became a witness to how news media changed rapidly. In the same way, the term ‘Access Point (AP)’ literally becomes a somewhat crooked term in the context of 6G networks: nor will the infrastructure provide only access, nor will services be delivered via one point. This blog post clarifies why 6G applications and sustainability targets require, on the infrastructure side, a compute-connectivity platform, consisting of interconnected distributed resources. We introduce new essential terminology to enable a clear discussion in developing novel technologies, originating from lively academic-industrial interactions in the REINDEER project and illustrated in the figure below (spoiler alert!).
We, and the devices we use, rely more and more on information from other devices and sources, accessed wirelessly, and progressively dispersed around us and the globe. The vast population of devices generating all this data are generally referred to as Internet-of-Things (IoT) devices. They often inhabit the capillaries of the network, where they sense and report data, enabling us to make more granular and complex decisions. Therefore, in the past decade, the information centre-of-gravity has and is shifting from data centres at the heart of the network, to the edge of the network. Consequently, traditional cloud data centres are dispersing towards the edge, offering seamless computational capacity throughout the network, in the form of edge and fog computing. The potential number and types of devices that want to reliably connect, wirelessly, at low latency, and high throughput presents a huge challenge to wireless networks. Imagine, a throughput-hungry AR headset, that shares a space with a few thousand connected sensors, whilst being driven around in an autonomous vehicle. Satisfying the needs for that scenario, and many more like it is the precursor to the 6th generation wireless networks (6G).
Researchers are in the midst of shaping the 6th generation of wireless networks, capable of supporting divergent applications and especially services that go far beyond what the 5th generation can offer. That effort includes addressing challenges in achieving remarkably high data rates, imperceptibly low latency, unrivalled dependability, and ultra-low power consumption [1,2]. Also, and with increasing urgency, the above should be accomplished with a negligible carbon footprint. Our vision for 6G is focused on realising large intelligent surface (LIS) [3]. LIS is an extension of massive MIMO, where the number of antennas is increased several orders of magnitude and distributed throughout a three-dimensional space, rather than co-located on a plane. Accompanying the antennas are radio and computational resources. This spatial and computational diversity is the singular most significant distinction between the 6th generation wireless networks and their predecessors.
With such diversity, the potential for 6G is monumental, but therein lies its greatest challenge. To seamlessly serve users with LIS, shared computational and radio resources will have to be dynamically allocated and orchestrated at a previously unseen scale and speed. As there are no discrete base stations, all decisions will have to be distributed, which is referred to as a cell-free network.
In cell-free networking [4,5], all resources in the network can be used to offer a given service. It provides an interesting concept to fully use the available resource capacity. Although the theoretical potential of cell-free networking has been identified, many questions remain concerning how these systems can be designed to be practically feasible. For example, how can such a great pool of resources get coordinated and allocated efficiently? And how can both the infrastructure and the services provided in 6G be scalable?
Our incarnation of 6G is called RadioWeaves (RW) [6]. Cell-free networking and embedded edge computing are central components in RW. Further, as a means to begin to address the above challenges, in RW, we analogously group resources dynamically in both the temporal and spatial domains. In RW, we use the term federation(s) to denote such a group of resources, that jointly serve an application. In distinction to current wireless networks, the envisioned RW system, will also support precise positioning, wireless energy transfer and energy-neutral IoT devices [7]. Following this paradigm shift, a new terminology for the conventional AP is introduced, i.e., the contact service point (CSP). It provides a first contact point into the network from the perspective of the user equipment (UE) and supports more than just wireless communication, as mentioned above. To do this, CSPs can host a variety of hardware such as radio, charging, processing, data storage and other sensing elements.
The figure above illustrates the abstract notion of a massive number of spatially distributed CSPs, and their grouping in relation to users and applications, i.e., federations. Concretely, the figure shows an example deployment of RW in a smart factory, with four federations, shown in different colours. Before we proceed, we need to take note of the RW terminology used in the figure. RW CSPs are deployed throughout the production hall on the walls and ceiling and are dynamically assigned to federations to serve the devices and their running applications. The constellation of CSPs assigned to each federation is tailored to the particular application’s requirements. The video below goes into more detail about how we address this challenge.
Implementing RW is the next analogous step in bringing the benefits of 6G to society. We are therefore implementing two test beds, one located at KU Leuven, Belgium, and the other at Lund University, Sweden. The testbed at KU Leuven, Techtile [8], was inaugurated in October 2021 and already has the physical infrastructure in place, but work is ongoing on the software to manage and run the testbed. Techtile consists of a 4-by-8-by-2-meter room built with 140 modular panels, each of which contains software-defined radios, edge computing units, and sensors. The testbed is specifically designed to study scalable and low-cost RW systems. It, therefore, uses Ethernet for power, data, and synchronisation. Complementary, the Lund University testbed2 is designed to assess high-throughput and latency-critical applications. The testbed consists of 16 panels, having 4-by-4 RF chains, equating to a total of 256 antenna elements.
More information regarding the concept and terminology can be found here: G. Callebaut, W. T ̈arneberg, L. Van der Perre, and E. Fitzgerald, “Dynamic federations for 6G cell-free networking: Concepts and terminology,” in 2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC), 2022, pp. 1–5. doi: 10.1109/SPAWC51304.2022.9833918 [9].
The authors would like to thank the REINDEER team, and especially Emma Fitzgerald, Erik G. Larsson, Pål Frenger, Ove Edfors and Liang Liu, for the rich discussions that have strengthened the definition of the new terminology and realisation of the test beds.
[1] EU H2020 REINDEER project. “REsilient INteractive applications through hyper Diversity in Energy Efficient RadioWeaves technology (REINDEER) project – Deliverable 1.1: Use case-driven specifications and technical requirements and initial channel model.” Visited on 2021-07-26. (2021), [Online]. Available: https://reindeer-project.eu/D1.1(visited on 2021).
[2] Ericsson AB, Joint communication and sensing in 6G networks, https://www.ericsson.com/en/6g, 2021.
[3] S. Hu, F. Rusek, and O. Edfors, “Beyond massive MIMO: The potential of positioning with large intelligent surfaces,” IEEE Transactions on Signal Processing, 2018.
[4] G. Interdonato, E. Björnson, H. Q. Ngo, P. Frenger, and E. G. Larsson, “Ubiquitous cell-free massive MIMO communications,” EURASIP Journal on Wireless Communications and Networking, 2019.
[5] H. Q. Ngo, A. Ashikhmin, H. Yang, E. G. Larsson, and T. L. Marzetta, “Cell-Free Massive MIMO Versus Small Cells,” IEEE Transactions on Wireless Communications, vol. 16, no. 3, pp. 1834–1850, 2017. doi: 10.1109/TWC.2017.2655515.
[6] L. Van der Perre, E. G. Larsson, F. Tufvesson, L. De Strycker, E. Bjornson, and O. Edfors, “RadioWeaves for efficient connectivity: analysis and impact of constraints in actual deployments,” Matthews, MB, IEEE, 2019, pp. 15–22.
[7] B. J. B. Deutschmann, T. Wilding, E. G. Larsson, and K. Witrisal, “Location-based Initial Access for Wireless Power Transfer with Physically Large Arrays,” in WS08 IEEEICC 2022 Workshop on Synergies of communication, localization, and sensing towards 6G (WS08 ICC’22 Workshop – ComLS-6G), Seoul, Korea (South), May 2022.
[8] G. Callebaut, J. Van Mulders, G. Ottoy, et al., “Techtile – Open 6G R&D Testbed for Communication, Positioning, Sensing, WPT and Federated Learning,” in 2022 Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6GSummit): Operational & Experimental Insights (OPE) (2022 EuCNC & 6G Summit -OPE), Grenoble, France, Jun. 2022.
[9] G. Callebaut, W. T ̈arneberg, L. Van der Perre, and E. Fitzgerald, “Dynamic federations for 6g cell-free networking: Concepts and terminology,” in 2022 IEEE 23rd International Workshop on Signal Processing Advances in Wireless Communication (SPAWC), 2022, pp. 1–5. doi: 10.1109/SPAWC51304.2022.9833918.4
1Livine Cleemput, mormor of L. Van der Perre, original term ‘Gesproken dagblad’ 2 www.eit.lth.se/index.php?gpuid=325&L=1
The project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101013425.
