Massive MIMO

The radio spectrum has become an increasingly precious and rare resource and much work has been dedicated on ways to improve the capacity of mobile communication systems without actually increasing the spectrum utilized. In this sense, multiple-input multiple-output (MIMO) provides undoubtedly the best solution. Indeed, in MIMO systems the effective available communication resources are increased in the spatial domain, by adding extra antennas at the transmitter side and, often, at the receiver side. In this respect, massive MIMO has recently gained much attention in the scientific community, as a scalable version of Multiuser MIMO technology to dramatically increase the spectral efficiency of future mobile communication systems, such as 5G.

Massive MIMO is a multi-user technology that is able to provide high quality communication to a large number of user equipments (UEs) K, even in high mobility scenarios. If the complex matrix   models the massive MIMO channel, where M is the number of BS antennas and N is the number of antennas at the UE, M is increased dramatically with respect to conventional MIMO, i.e., in massive MIMO we have that  and . In essence, the benefits of massive MIMO lie in the possibility to better focus the energy of the transmit signal to a relatively large set of receiving UEs (i.e., spatial multiplexing). Hence, the interference between different UE transmissions is cancelled spatially by the base-station (BS), thus allowing the network to support a large set of simple receiving UEs, such as single-antenna terminals. This is possible thanks to the excess spatial degrees of freedom at the BS-side.

Beamforming to several tens of UEs simultaneously, within the same time-frequency resources, results in orders of magnitude higher system throughput with respect to state-of-the-art MIMO systems. Remarkably, this can be achieved via simple linear signal processing techniques (e.g., matched filter or zero-forcing) at the BS-side. Indeed, thanks to such combining of the transmit signals, the channel variations due to the small-scale fading are averaged-out over the antenna array, i.e., the channel variance decreases with M. This is known as channel hardening and is a consequence of the law of large numbers. Thanks to this effect, the randomness in the channel gains is negligible after coherent precoding/combining.

Moreover, thanks to focused transmit beams, the received power at the UEs is considered to be proportional to the number of transmit antennas M and hence much higher than conventional MIMO systems. For this reason, massive MIMO is probably the best candidate to reach, in future mobile networks, not only the expected spectral efficiencies, but also enhanced energy efficiency. Indeed, in a network ecosystem that is evolving towards denser and smaller cells, a massive MIMO system operating in a small cell could significantly scale down its transmit power without excessive losses in performance.

While the benefits of massive MIMO are many, there are also some downsides which are mostly related to the overhead of channel acquisition and the interference produced by pilot contamination, which has a greater impact on performance with respect to conventional MIMO systems. Indeed, many MIMO systems are based on Frequency Division Duplexing (FDD), where the frequency bands used for transmission on the uplink and downlink are different. This means that the channel on the two links is different, as opposed to Time Division Duplexing (TDD) where transmission on both links takes place within the same frequency band, but in different time slots. In FDD the channel state is acquired by the UEs on the downlink ad it is fed back to the BS via a separate communication link. Thus, the number of pilot symbols scales with the number of BS antennas M, which results in a significant system overhead in massive MIMO. On the other hand, in TDD the BS acquires the channel state on the uplink and uses it to beamform on the downlink thanks to channel reciprocity. In this case the number of pilot symbols is independent of the number of BS antennas.

Finally, another significant limitation to practical massive MIMO systems might be represented by pilot contamination. This refers to the interference produced by UEs that share the same pilot sequence and attempt to transmit it to the BS within the same time-frequency resources. The quality of the channel estimates produced is inevitably severely interference-limited, which in turn results in poor downlink beamforming. Such effect is believed to ultimately limit the performance of massive MIMO, in the context of systems employing pilot-based channel estimation, although some studies demonstrate how this is not true when the channel statistics of interfering UEs exhibit some special spatial properties. Whether such properties are realistic or not is yet to be discovered.