A new EU-funded 6G initiative, the REINDEER project, joins forces from academia and industry to develop and build a new type of multi-antenna-based smart connectivity platform integral to future 6G systems. From Ericsson’s new site:
The project’s name is derived from REsilient INteractive applications through hyper Diversity in Energy-Efficient RadioWeaves technology, and the development of “RadioWeaves” technology will be a key deliverable of the project. This new wireless access infrastructure consists of a fabric of distributed radio, compute and storage. It will advance the ideas of large-scale intelligent surfaces and cell-free wireless access to offer capabilities far beyond future 5G networks. This is expected to offer capacity scalable to quasi-infinite, and perceived zero latency and interaction with a large number of embedded devices.
In my latest magazine paper, I identified real-time reconfigurability as the key technical research challenge: we need fast algorithms for over-the-air channel estimation that can handle large surfaces and complex propagation environments. In other words, we need hardware that can be reconfigured and algorithms to find the right configuration.
The literature contains several theoretical algorithms but it is a very different thing to demonstrate real-time reconfigurability in lab experiments. I was therefore impressed when finding the following video from the team of Dr. Mohsen Khalily at the University of Surrey:
The video shows how a metasurface is used to reflect a signal from a transmitter to a receiver. In the second half of the video, they move the receiver out of the reflected beam from the metasurface and then press a button to reconfigure the surface to change the direction of the beam.
I asked Dr. Khalily to tell me more about the setup:
“The metasurface consists of several conductive printed patches (scatterers), and the size of each scatterer is a small proportion of the wavelength of the operating frequency. The macroscopic effect of these scatterers defines a specific surface impedance and by controlling this surface impedance, the reflected wave from the metasurface sheet can be manipulated. Each individual scatterer or a cluster of them can be tuned in such a way that the whole surface can reconstruct radio waves with desired characteristics without emitting any additional waves.”
The surface shown in the video contains 2490 patches that are printed on a copper ground plane. The patches are made of a new micro-dispersed ceramic PTFE composite and designed to support a wide range of phase variations along with a low reflection loss for signals in the 3.5 GHz band. The design of the surface was the main challenge according to Dr. Khalily:
“Fabrication was very difficult due to the size of the surface, so we had to divide the surface into six tiles then attach them together.Our surface material has a higher dielectric constant than the traditional PTFE copper-clad laminates to meet the design and manufacturing of circuit miniaturization. This material also possesses high thermal conductivity, which gives an added advantage for heat dissipation of the apparatus.”
The transmitter and receiver were in the far-field of the metasurface in the considered experimental setup. Since there is an unobstructed line-of-sight path, it was sufficient to estimate the angular difference between the receiver and the main reflection angle, and then adjust the surface impedance to compensate for the difference. When this was properly done, the metasurface improved the signal-to-noise ratio (SNR) by almost 15 dB. I cannot judge how close this number is to the theoretical maximum. In the considered in-room setup with highly directional horn antennas at the transmitter and receiver, it might be enough that the reflected beam points in roughly the right direction to achieve a great SNR gain. I’m looking forward to learning more about this experiment when there is a technical paper that describes it.
This is not the first experiment of this kind, but I think it constitutes the state-of-the-art when it comes to bringing the concept of reconfigurable intelligent surfaces from theory to practice.
I am giving a tutorial on “Beyond Massive MIMO: User-Centric Cell-Free Massive MIMO” at Globecom 2020, together with my colleagues Luca Sanguinetti and Özlem Tuğfe Demir. It is a prerecorded 3-hour tutorial that can be viewed online at any time during the conference and there will be a live Q/A session on December 11 where we are available for questions.
The tutorial is based on our upcoming book on the topic: Foundations on User-Centric Cell-free Massive MIMO.
Until December 11 (the last day of the tutorial), we are offering a free preprint of the book, which can be downloaded by creating an account at the NOW publishers’ website. By doing so, I think you will also get notified when the final version of the book is available early next year, so you can gain access to the final PDF and an offer to buy printed copies.
If you download the book and have any feedback that we can take into account when preparing the final version, we will highly appreciate to receive it! Please email me your feedback by December 15. You find the address in the PDF.
The abstract of the tutorial is as follows:
Massive MIMO (multiple-input multiple-output) is no longer a promising concept for cellular networks-in 2019 5G it became a reality, with 64-antenna fully digital base stations being commercially deployed in many countries. However, this is not the final destination in a world where ubiquitous wireless access is in demand by an increasing population. It is, therefore, time for MIMO and mmWave communication researchers to consider new multi-antenna technologies that might lay the foundations for beyond 5G networks. In particular, we need to focus on improving the uniformity of the service quality.
Suppose all the base station antennas are distributed over the coverage area instead of co-located in arrays at a few elevated locations, so that the mobile terminals are surrounded by antennas instead of having a few base stations surrounded by mobile terminals. How can we operate such a network? The ideal solution is to let each mobile terminal be served by coherent joint transmission and reception from all the antennas that can make a non-negligible impact on their performance. That effectively leads to a user-centric post-cellular network architecture, called “User-Centric Cell-Free Massive MIMO”. Recent papers have developed innovative signal processing and radio resource allocation algorithms to make this new technology possible, and the industry has taken steps towards implementation. Substantial performance gains compared to small-cell networks (where each distributed antenna operates autonomously) and cellular Massive MIMO have been demonstrated in numerical studies, particularly, when it comes to the uniformity of the achievable data rates over the coverage area.
5G used to be described as synonymous with millimeter-wave communications, but now when 5G networks are being rolled out all around the world, the focus is instead on Massive MIMO in the 3 GHz band. Moreover, millimeter-wave communications used to be synonymous with hybrid beamforming (e.g., using multiple analog phased arrays), often described as a necessary compromise between performance and hardware complexity. However, digital implementations are already on the way.
Last year, I wrote about experiments by NEC with a 24-antenna base station that carries out digital beamforming in the 28 GHz band. The same convergence towards digital solutions is happening for the chips that can be used in 5G terminals. The University of Michigan published experimental results at the 2020 IEEE Radio Frequency Integrated Circuits Symposium (RFIC) regarding a 16-element prototype for the 28 GHz band. The university calls it the “first digital single-chip millimeter-wave beamformer“. It is manufactured as a single chip using 40 nm CMOS technology and has a dimension of around 3 x 3 mm. The chip doesn’t include the 16 antenna elements (which are connected to it, see the image below and click on it to find larger images) but transceiver chains with low-noise amplifiers, phase-locked loops, analog-to-digital converters (ADCs), etc. While each antenna element has a separate ADC, groups of four adjacent ADCs are summing up their digital signals before they reach the baseband processor. Hence, from a MIMO perspective, this is essentially a digital four-antenna receiver.
One reason to call this a prototype rather than a full-fleshed solution is that the chip can only function as a receiver, but this doesn’t take away the fact that this is an important step forward. In an interview with the Michigan Engineering News Center, Professor Michael P. Flynn (who lead the research) is explaining that “With analog beamforming, you can only listen to one thing at a time” and “This chip represents more than seven years of work by multiple generations of graduate students”.
Needless to say, the first 5G base stations and cell phones that support millimeter-wave bands will make use of hybrid beamforming architectures. For example, the Ericsson Street Macro 6701 (that Verizon is utilizing in their network) contains multiple phased arrays, which can take 4 inputs and thereby produce up to 4 simultaneous beams. However, while the early adopters are making use of hybrid architectures, it becomes increasingly likely that fully digital architectures will be available when millimeter-wave technology becomes more widely adopted around the world.
I have written several posts about Massive MIMO field trials during this year. A question that I often get in the comment field is: Have the industry built “real” reciprocity-based Massive MIMO systems, similar to what is described in my textbook, or is something different under the hood? My answer used to be “I don’t know” since the press releases are not providing such technical details.
The 5G standard supports many different modes of operation. When it comes to spatially multiplexing of users in the downlink, the way to configure the multi-user beamforming is of critical importance to control the inter-user interference. There are two main ways of doing that.
The first option is to let the users transmit pilot signals in the uplink and exploit the reciprocity between uplink and downlink to identify good downlink beams. This is the preferred operation from a theoretical perspective; if the base station has 64 transceivers, a single uplink pilot is enough to estimate the entire 64-dimensional channel. In 5G, the pilot signals that can be used for this purpose are called Sounding Reference Signals (SRS). The base station uses the uplink pilots from multiple users to select the downlink beamforming. This is the option that resembles what the textbooks on Massive MIMO are describing as the canonical form of the technology.
The second option is to let the base station transmit a set of downlink signals using different beams. The user device then reports back some measurement values describing how good the different downlink beams were. In 5G, the corresponding downlink signals are called Channel State Information Reference Signal(CSI-RS). The base station uses the feedback to select the downlink beamforming. The drawback of this approach is that 64 downlink signals must be transmitted to explore all 64 dimensions, so one might have to neglect many dimensions to limit the signaling overhead. Moreover, the resolution of the feedback from the users is limited.
In practice, the CSI-RS operation might be easier to implement, but the lower resolution in the beamforming selection will increase the interference between the users and ultimately limit how many users and layers per user that can be spatially multiplexed to increase the throughput.
New field trial based on SRS
The Signal Research Group has carried out a new field trial in Plano, Texas. The unique thing is that they confirm that the SRS operation was used. They utilized hardware and software from Ericsson, Accuver Americas, Rohde & Schwarz, and Gemtek. A 100 MHz channel bandwidth in the 3.5 GHz band was considered, the downlink power was 120 W, and a peak throughput of 5.45 Gbps was achieved. 8 user devices received two layers each, thus, the equipment performed spatial multiplexing of 16 layers. The setup was a suburban outdoor cell with inter-cell interference and a one-kilometer range. The average throughput per device was around 650 Mbps and was not much affected when the number of users increased from one to eight, which demonstrates that the beamforming could effectively deal with the interference.
It is great to see that “real” reciprocity-based Massive MIMO provides such great performance in practice. In the report that describes the measurements, the Signal Research Group states that not all 5G devices support the SRS-based mode. They had to look for the right equipment to carry out the experiments. Moreover, they point out that:
“Operators with mid-band 5G NR spectrum (2.5 GHz and higher) will start deploying MU-MIMO, based on CSI-RS, later this year to increase spectral efficiency as their networks become loaded. The SRS variant of MU-MIMO will follow in the next six to twelve months, depending on market requirements and vendor support.“
The following video describes the measurements in further detail:
There are basically two approaches to achieve high data rates in 5G: One can make use of huge bandwidths in mmWave bands or use Massive MIMO to spatially multiplex many users in the conventional sub-6 GHz bands.
As I wrote back in June, I am more impressed by the latter approach since it is more spectrally efficient and requires more technically advanced signal processing. I was comparing the 4.7 Gbps that Nokia had demonstrated over an 840 MHz mmWave band with the 3.7 Gbps that Huawei had demonstrated over 100 MHz of the sub-6 GHz spectrum. The former example achieves a spectral efficiency of 5.6 bps/Hz while the latter achieves 37 bps/Hz.
T-Mobile and Ericsson recently described a new field trial with even more impressive results. They made use of 100 MHz in the 2.5 GHz band and achieved 5.6 Gbps, corresponding to a spectral efficiency of 56 bps/Hz; an order-of-magnitude more than one can expect in mmWave bands!
The press release describes that the high data rate was achieved using a 64-antenna base station, similar to the product that I described earlier. Eight smartphones were served by spatially multiplexing and each received two parallel data streams (so-called layers). Hence, each user device obtained around 700 Mbps. On average, each of the 16 layers had a spectral efficiency of 3.5 bps/Hz, thus 16-QAM was probably utilized in the transmission.
I think these numbers are representative of what 5G can deliver in good coverage conditions. Hopefully, Massive MIMO based 5G networks will soon be commercially available in your country as well.
Since the pandemic made it hard to travel over the world, several open online seminar series have appeared with focus on different research topics. The idea seems to be to give researchers a platform to attend talks by international experts and enable open discussions.
There is a “One World Signal Processing Seminar Series” series, which has partially considered topics on multi-antenna communications. I want to highlight one such seminar. Professor Wei Yu (University of Toronto) is talking about Machine Learning for Massive MIMO Communications. The video contains a 45 minute long presentation plus another 30 minutes where questions are being answered.