Reflect- and Transmit-Array Antennas for Scalable and Energy-Efficient mmWave Massive MIMO

Hybrid analog-digital architectures are promising candidates for implementing millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems since they enable a considerable reduction of the required number of costly radio frequency (RF) chains by moving some of the signal processing operations into the analog domain. Nevertheless, the analog feed network, comprising RF dividers, combiners, phase shifters, and line connections, of hybrid MIMO architectures is not scalable due to its prohibitively high power consumption for large numbers of transmit antennas. In this paper, we study novel massive MIMO architectures, namely reflect-array (RA) and transmit-array (TA) antennas, which consist of few active antennas (i.e., RF chains) and large numbers of passive antennas. We show that the constraints that the precoders for RA and TA antennas have to meet, differ from those of conventional MIMO architectures. Taking these constraints into account and exploiting the sparsity of mmWave channels, we design two efficient precoders for RA and TA antennas; one based on maximizing the mutual information and one based on approximating the optimal unconstrained digital precoder via the orthogonal matching pursuit algorithm. Furthermore, in order to fairly compare the performance of RA and TA antennas against conventional fully-digital and hybrid MIMO architectures, we develop a unified power consumption model. Our simulation results show that unlike conventional MIMO architectures, RA and TA antennas are highly energy efficient and fully scalable in terms of the number of transmit antennas. Therefore, RA and TA antennas are candidates for realizing the potential of \textit{massive} MIMO in practice.