A Low Complexity Algorithm for Achievable Rate Maximization in mmWave Systems Aided by IRS

Abstract

This letter investigates the weighted sum-rate maximization in a multi-user millimeter wave (mmWave) wideband downlink system aided by double intelligent reflecting surfaces (IRS). We formulate a joint optimization problem of digital beamforming (BF) matrix, analog BF matrix, and IRS phase shifts matrix, which is non-convex. To solve this problem, we propose an alternating optimization (AO) algorithm based on the projection gradient method (PGM). PGM is used to deal with non-convex element-wise constant-modulus constraints for analog BF matrix and IRS phase shifts. Furthermore, the performance loss caused by using discrete phase shift is studied by the proposed algorithm and quantization method. Simulation results show that the proposed AO algorithm based on PGM achieves the same achievable rate with a lower complexity compared to existing methods.