Intelligent Reflecting Surface Aided Wireless Communication Systems: Joint Location and Passive Beamforming Design

Intelligent Reflecting Surface (IRS) technology has attracted significant attention as a novel approach to enhance wireless communication systems in recent years. By intelligently configuring its reflective elements, IRS can manipulate signal propagation, thereby improving desired signals while mitigating interference among users. In this paper, we study an IRS-aided multi-user wireless communication scenario, where the base station (BS) transmits various signals and each user receives their desired signals. To ensure fairness in wireless communications, the objective is to maximize the minimum user rates, considering the power constraint of the BS and the phase constraint of the IRS. Unlike prior works focusing mainly on optimizing BS and IRS beamforming, this study also addresses IRS location optimization. Since the problem is non-convex, it is decomposed into two subproblems and transformed into lower bound problems. Alternating optimization (AO) and successive convex approximation (SCA) methods are employed to solve these subproblems iteratively, aiming to converge the objective function within an acceptable range. Simulation results validate the convergence of the proposed algorithm and demonstrate performance improvements compared to benchmark schemes in wireless communication systems.