Joint Transceiver and Intelligent Reflecting Surface Design for mmWave Massive MIMO Systems

Abstract

This article aims to maximize the spectral efficiency of an intelligent reflecting surface (IRS)-assisted hybrid millimeter-wave massive multiple-input–multiple-output system by jointly optimizing the hybrid precoding at the base station, hybrid combining at the user equipment, and reflecting beamforming at the IRS, where the reflecting beamforming and analog precoding/combining are implemented with finite-resolution phase shifters. This joint design problem can be decoupled into reflecting beamforming and hybrid precoding/combining design problems. However, such a decoupled approach experiences difficulties in solving the reflecting beamforming design problem. A known solution further reformulates the reflecting beamforming design problem into a more tractable problem addressed by a Riemannian manifold optimization (RMO)-based algorithm. However, the application of the RMO-based algorithm to solve the reformulated problem may lead to performance degradation given that the reformulated problem differs from the original one. Moreover, the RMO-based algorithm is tailored for the IRS with infinite-resolution phase shifters rather than practical finite-resolution phase shifters. Furthermore, the complexity of the RMO-based algorithm remains high. Therefore, we propose two coordinate descent method-based algorithms to tackle these issues. Simulation results demonstrate the effectiveness of the proposed algorithms compared with the state-of-the-art RMO-based algorithm.