Transceiver Design for Energy-Efficiency Maximization in mmWave MIMO IoT Networks

Abstract

Millimeter wave (mmWave) communications have been regarded as a fundamental enabling technology for future 5G Internet of Things (IoT) networks. This paper studies a hybrid transceiver design problem considering both perfect and imperfect channel state information to maximize the energy-efficiency (EE) of a mmWave multiple-input multiple-output (MIMO) interference channel involving multiple hardware impaired IoT devices. Since the original hybrid transceiver design problem is intractable, we propose a low-complexity two-stage algorithm, both of which are proven to converge. In the first stage, we transform the multivariate problems into their univariate equivalents and exploit the well-known relationship between rate and mean squared error to solve them in an alternating fashion. In the second stage, using the results from stage one, we separate the joint transceiver optimization problems into hybrid precoders and combiners sub-problems and apply orthogonal matching pursuit algorithm to obtain the optimal solution for each sub-problem. Finally, through numerical simulations it is shown that the proposed hybrid algorithms achieve near-optimal EE performance to support power constrained IoT devices with lower complexity than univariate designs.