Low Complexity User Selection, Beamforming and IRS Phase Optimization in the Downlink

Joint beamforming and Intelligent Reflecting Surface (IRS) phase optimization for the Multiuser Multiple-Input Single-Output (MU-MISO) downlink has been studied recently. Two such optimization problems are: Weighted sum rate maximization under a transmit power constraint, and transmit power minimization under rate constraints. Since these multiuser problems are non-convex, existing solutions are based on iterative algorithms like block coordinate descent (BCD). The complexity of these algorithms is high and convergence is also an issue. In this paper, we propose low complexity methods based on dynamic user selection combined with linear beamforming and single-user RIS phase optimization for one of the selected users. Using simulations, we demonstrate that the proposed methods can perform close to the solution provided by algorithms like BCD for both the above optimization problems.