Hybrid Beamforming for Distributed Intelligent Reflecting Surfaces-Aided Systems

Abstract

In this paper, a distributed multiple-intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) system is studied. Since IRS is operated in a passive manner, only imperfect channel information is considered in our model. Our aim is to maximize the achievable sum rate of the system by adopting a hybrid construction where we jointly optimize the active transmit beamforming at the base station (BS) and the passive beamforming at the IRS. To solve this problem, utilizing successive convex approximation (SCA), an iterative algorithm is proposed via alternatively optimizing transmit beamforming and passive beamforming. Simulation results show the proposed iterative algorithm outperforms the conventional semi-definite programming (SDP)-based algorithm. Moreover, the proposed algorithm is able to significantly compensate for the channel estimation error.