Category Archives: News

“Computers Weren’t Powerful Enough to Operate It”

Image from Wikipedia

I found an interesting news article by  where he is interviewing Martin Cooper, who is considered the father of the handheld cell phone. Cooper is talking about spatial division multiple access, the early name of the multi-user MIMO technology, and how “computers weren’t powerful enough to operate it” at the time it was invented at his startup-company ArrayComm.

Cooper points out that “Today we spray energy in all directions. Why not aim it directly?” He then provides three examples of why multi-user MIMO solves important practical problems:

First, deploying cellular and derivative technologies is costly. Second, the quality of wireless communicating must be comparable or better than that of wireline in order to compete with wireline, said Cooper. And as spectrum is finite, technology must work toward greater efficiency.

Furthermore, he says that ArrayComm’s multi-user MIMO solution “requires fewer base stations, which cuts costs. The technology also is adaptive, which simplifies network design and reduces site acquisition and installation costs.”

By the way, did I forgot to say that this interview is from 1996…?

I explained in a previous blog post why the efforts to commercialize multi-user MIMO in the nineties were not as successful as Cooper and others might have hoped for. Now, more than 20 years later, we are about to witness a large-scale deployment of 5G technology, in which MIMO is a key component. The industry has hopefully learned from the negative past experiences when Massive MIMO is now being deployed in commercial networks. One thing we know for sure is that computational complexity is not a problem anymore.

Open Science and Massive MIMO

Open science is just science done right” is a quote from Prof. Jon Tennant in a recent podcast. He is referring to the movement away from the conventionally closed science community where you need to pay to gain access to research results and everyone treats data and simulation code as confidential. Since many funding agencies are requiring open access publishing and open data nowadays, we are definitely moving in the open science direction. But different research fields are at different positions on the scale between fully open and entirely closed science. The machine learning community has embraced open science to a large extent, maybe because the research requires common data sets. When the Nature Machine Intelligence journal was founded, more 3000 researchers signed a petition against its closed access and author fees and promised to not publish in that journal. However, research fields that for decades have been dominated by a few high-impact journals (such as Nature) have not reached as far.

IEEE is the main publisher of Massive MIMO research and has, fortunately, been quite liberal in terms of allowing for parallel publishing. At the time of writing this blog post, the IEEE policy is that an author is allowed to upload the accepted version of their paper on the personal website, the author’s employer’s website, and on arXiv.org. It is more questionable if it is allowed to upload papers in other popular repositories such as ResearchGate – can the ResearchGate profile pages count as personal websites?

It is we as researchers that need to take the steps towards open science. The publishers will only help us under the constraint that they can sustain their profits. For example, IEEE Access was created to have an open access alternative to the traditional IEEE journals, but its quality is no better than non-IEEE journals that have offered open access for a long time. I have published several papers in IEEE Access and although I’m sure that these papers are of good quality, I’ve been quite embarrassed by the poor review processes.

Personally, I try to make all my papers available on arXiv.org and also publish simulation code and data on my GitHub whenever I can, in an effort to support research reproducibility. My reasons for doing this are explained in the following video:

Outdoor Massive MIMO Demonstrations in Bristol

The University of Bristol continues to be one of the driving forces in demonstrating reciprocity-based Massive MIMO in time-division duplex. The two videos below are from an outdoor demo that was carried out in Bristol in March 2018.  A 128-antenna testbed with a rectangular array of 4 rows and 32 single-polarized antennas per row were used. The demo was carried out with a carrier frequency of 3.5 GHz and featured spatial multiplexing of video streaming to 12 users.

Prof. Mark Beach, who is leading the effort, believes that Massive MIMO in sub-6 GHz bands will be the key technology for serving the users in hotspots and sport arenas. Interestingly, Prof. Beach is also an author of one of the first paper on multiuser MIMO from 1990: “The performance enhancement of multibeam adaptive base-station antennas for cellular land mobile radio systems“.

Joint Massive MIMO Deployment for LTE and 5G

The American telecom operator Sprint is keen on mentioning Massive MIMO in the marketing of its 5G network deployments, as I wrote about a year ago. You can find their new video below and it gives new insights into the deployment strategy of their new 64-antenna BSs. Initially, the base station will be divided between LTE and 5G operation. According to CTO Dr. John Saw, the left half of the array will be used for LTE and the right half for 5G. This will lead to a 3 dB loss in SNR and also a reduced multiplexing capability, but I suppose that Sprint is only doing this temporarily until the number of 5G users is sufficiently large to motivate a 5G-only base station. Another thing that one can infer from the video is that the LTE/5G splitting is software-defined so physical changes to the base station hardware are not needed to change it.

Massive MIMO for Maritime Communications

The Norwegian startup company Super Radio has during the past year made several channel measurement campaigns for Massive MIMO for land-to-sea communications, within a project called MAMIME (LTE, WIFI and 5G Massive MIMO Communications in Maritime Propagation Environments). There are several other companies and universities involved in the project.

The maritime propagation environment is clearly different from the urban and suburban propagation environments that are normally modeled in wireless communications. For example, the ground plane consists of water, and the sea waves are likely to reflect the radio waves in a different way than the hard surface on land. Except for islands, there won’t be many other objects that can create multipath propagation in the sea. Hence, a strong line-of-sight path is key in these use cases.

The MAMIME project is using a 128-antenna horizontal array, which is claimed to be the largest in the world. Such an array can provide narrow horizontal beams, but no elevation beamforming – which is probably not needed since the receivers will all be at the sea level. The array consists of 4 subarrays which each has a dimension of 1070 x 630 mm. Frequencies relevant for LTE and WiFi have been considered so far. The goal of the project is to provide “extremely high throughputs, stability and long coverage” for maritime communications. I suppose that range extension and spatial multiplexing of multiple ships is what this type of Massive MIMO system can achieve, as compared to a conventional system.

A first video about the project was published in December 2017:

Now a second video has been released, see below. Both videos have been recorded outside Trondheim, but Kan Yang at Super Radio told me that further measurements outside Oslo will soon be conducted, with focus on LTE Massive MIMO.

A Look at an LTE-TDD Massive MIMO Product

I wrote earlier about the Ericsson AIR 6468 that was deployed in Russian in preparation for the 2018 World Cup in football. If you are curious to know more about this Massive MIMO product, among the first of its kind, you can read the public documents that were submitted to FCC for approval. For example, if you click on the link above and then select “Conf Exhibit 9 Internal photos” you will see how the product looks at the inside.

I will now summarize some of the key properties of this LTE TDD product. AIR stands for Antenna Integrated Radio, and Ericsson AIR 6468 is a unit with 64 antennas connected to 64 transmitter/receiver branches. This allows for fully digital beamforming, but the baseband processing is taking place in a separate unit that is connected to AIR 6468 with an optical cable. Hence, the processing unit can be updated to support future LTE releases and more advanced signal processing.

There are different versions of AIR 6468 that are targeting different LTE bands, for example, 2496-2690 MHz and 3400–3600 MHz. These units weight 60.4 kg and are 988 x 520 x 187 mm, which clearly demonstrates that Massive MIMO does not require physically large arrays; the height is typical for an LTE antenna, while the width is slightly larger. This can be seen in the image below, where the AIR 6468 is in the middle.

 

The array can be mounted on a wall or a pole, and tilted in various ways. As far as I understand, the 64 antennas consist of 32 dual-polarized antennas, which are arranged on a rectangular grid with 4 antennas in the vertical dimension and 8 antennas in the horizontal dimension. The reason that the array is still physically larger in the vertical dimension is the larger vertical antenna spacing, which is the common practice to achieve a narrower vertical beamwidth since most users are concentrated around the same elevation angles in practical deployments (see Section 7.3-7.4 in Massive MIMO Networks for a more detailed explanation).

QPSK, 16-QAM, 64-QAM, and 256-QAM are the supported modulation types. AIR 6468 can perform carrier aggregation of up to three carriers of 15 or 20 MHz each. The maximum radiated transmit power is 1.875 W per antenna, which corresponds to 120 W in total for the array. I suppose this means 40 W in total in each 15-20 MHz carrier (and 0.625 W per antenna), but it is of course the spectrum licenses that determine the actual numbers.

64 or 128 Antennas?

After some successful trials, the first deployments of TDD-LTE with Massive MIMO functionality were unveiled earlier this year. For example, the telecom operator Sprint turned on Massive MIMO base stations in Chicago, Dallas, and Los Angeles last April.

If you read the press release from Sprint, it is easy to get confused regarding the number of antennas being used:

Sprint will deploy 64T64R (64 transmit, 64 receive) Massive MIMO radios using 128 antennas working with technology leaders Ericsson, Nokia, and Samsung Electronics.

From reading this quote, I get the impression that the Massive MIMO arrays contain 128 antennas, whereof 64 are used for the transmission and another 64 for the reception. That would be a poor system design, since channel reciprocity can only be exploited in TDD if the same antennas are used for both transmission and reception!

Fortunately, this is not what Sprint and other operators have actually deployed. According to my sources, the arrays contain 64 dual-polarized elements, so there are indeed 128 radiating elements. However, as I explained in a previous blog post, an antenna consists of a collection of radiating elements that are connected to the same RF chain. The number of antennas is equal to the number of RF chains, which is 64 in this case. The reason that Sprint points out that there are 64 transmit antennas and 64 receive antennas is because different RF chains are used for transmission and reception. The system switches between them according to the TDD protocol. In principle, one could design an array that has a different number of RF chains in the uplink than in the downlink, but that is not the case here.

So how are the 128 elements mapped to 64 antennas (RF chains)? This is done by taking pairs of vertically adjacent elements, which have the same polarization, and connecting them to the same RF chain.  This is illustrated in the figure to the right (see this blog post for pictures of how the actual arrays look like). As compared to having 128 RF chains (and antennas), this design choice results in lower flexibility in elevation beamforming, but the losses in data rates and multiplexing capability are supposed to be small since there are much larger variations in azimuth angles between the users in a cellular network than in the elevation angles. (This is explained in detail in Section 7.3-7.4 of my book). The advantage is that the implementation is more compact and less expensive when having 64 instead of 128 antennas.