Recently Björnson and Marzetta in their publication on Antenna Arrays [1] discussed five possible future research directions. In their opinion Massive MIMO is no longer a theoretical concept and it is already being adopted in the industry. It is not uncommon to find 64 element antenna arrays being deployed in wireless communication systems. So we now need to look beyond Massive MIMO or MaMIMO as it is popularly referred to. Here are three possible future research directions that we find most interesting.
Extremely Large Aperture Array
It is well known that spatial resolution of an array depends upon the aperture of the array or in simple terms the size of the array. So in future wireless communication systems we may see thousands of antennas deployed at a Base Station spread over a large geographical area. As discussed in [1] one possibility is to deploy these antennas on the facade of buildings located in urban city centers. But a problem faced in such a configuration is that inter-element spacing may be greater than half the wavelength causing spatial aliasing. This is similar to the concept of aliasing when an undersampled signal is transformed from time domain to frequency domain. Also note that the frequency resolution is dependent on the time domain window size and not sampling frequency as is popularly believed.
One solution to the problem of spatial aliasing is to have an aperture so large that the beam pattern is like a fine ray pointing in the direction of interest. Rays that may exist in other directions are so narrow that the chance of interfering with unwanted user is very low. Another problem is that Far Field assumption would not hold true as the Mobile Station distance from the Base Station (a building in this case) would be comparable to the size of the array (or even lesser). To be exact the Far Field distance of an antenna array is given as FF > 2D2/λ. So as the signal wavelength λ decreases (especially as we move to millimeter wave) and as the antenna dimension D increases the antenna Far Field distance increases. Lastly we would like to point out that in all our discussions so far on Antenna Arrays we have considered a Uniform Linear Array but non-uniform geometries can provide better spatial resolution in some cases.
3D Spatial Location
Earlier wireless communication systems had very coarse spatial location (50m – 200m) which was based on Cell ID and inaccurate timing measurements. But over the years the accuracy has been improved greatly with current systems achieving accuracy of about 10m. This has been made possible by using GPS signals and more accurate Time Difference of Arrival (TDoA) techniques. Remember that GPS signals alone are not sufficient as they do not work indoors and in urban canyons. In future wireless communication systems location accuracy would be improved to less than 10m and we would be able to define position along X, Y and Z. It is expected that it would also be possible to measure the roll, pitch and yaw of a mobile device (referred to as 6D Spatial Location). This would be made possible by large antenna arrays.
Large Scale MIMO Radar
Radar or Radio Detection and Ranging was first discovered when an aircraft accidentally interfered in the signal transmission between a radio transmitter and a radio receiver. Eight countries started working on it at more or less the same time and had it ready before World War-II. But MIMO Radar is a relatively newer concept and first paper that most researchers like to cite is by E. Fishler from 2004 [2]. The concept of MIMO Radar is to use multiple antennas at the transmitter and receiver to improve the detection of signals. These transmitters or receivers may or may not be collocated. The number of targets that a MIMO Radar can detect is usually much higher than a typical Radar. A Large Aperture MIMO Radar can provide much better spatial resolution and improved interference rejection capabilities. Another important concept that researchers have worked on is that of Waveform Diversity which allows multiple waveforms to be transmitted simultaneously from the transmitters and distinctly detected at the receivers.
Full Duplex: A Bonus Inclusion
Full Duplex (FD) was not a part of the original article but is now included due to its promise of doubling the capacity of wireless systems. It was originally thought that it would make it to 5G but the challenge of implementing it in real world scenarios still remains and it will most likely get included in 6G or whatever the next generation of wireless systems is called. In simple terms most wireless communication systems work by transmitting at one frequency and receiving at another frequency, this is called FDD. Some wireless communication systems work by transmitting and receiving at the same frequency but having different time slots for each, this is called TDD. In Full Duplex (FD) the transmission and reception happens at the same frequency and within the same time slot. The challenge here is that the transmitted signal feeds back into the receive chain and the received signal is drowned in the transmitted signal.
Several techniques have been proposed in the literature to cancel this echo as it is sometimes called. They can be broadly classified into antenna based techniques, RF techniques and digital techniques. Antenna techniques are the simplest as they propose to place the transmit antennas (usually 2) at an appropriate distance from the receive antenna so that the echos cancel out on arrival. Another technique simply inverts the phase of the transmitted signal and then adds it to the echo after adjusting the power level appropriately. Lastly are digital techniques that also apply some form of echo cancellation to recover the received signal. All these techniques are simple in theory but much harder to implement in practice where the wanted signal is drowned in 60-90 dB more powerful unwanted signal.
[1] E. Bjornson, L. Sanguinetti, H. Wymeersch, J. Hoydis, and T. L. Marzetta, “Massive MIMO is a reality – what is next? Five promising research directions for antenna arrays,” arXiv e-prints, p. arXiv:1902.07678, Feb 2019.
[2] E. Fishler, A. Haimovich, R. Blum, D. Chizhik, L. Cimini, and R. Valenzuela, “MIMO radar: an idea whose time has come,” in IEEE Radar Conference, 2004, pp. 71–78
Hi dear John!
You have mentioned and discussed briefly on MIMO but you have not given any MATLAB implementation of it just like other stuff. Can you share a MATLAB code that estimates the DOA and DOD of channel per user in a MU-MIMO system?
Regards,