Robust Resource Alloctation for RIS-Assisted Downlink MISO System with Imperfect CSI

In this paper, we study the robust beamforming problem in reconfigurable intelligent surface (RIS)-assisted downlink multiple-input-single-output (MISO) systems in the presence of channel state information (CSI) uncertainty, and construct a nonconvex optimization model with the objective of minimizing the transmit power, satisfying the signal-to-interference-noise ratio (SINR) and the unit-mode constraints of the RIS unit, through the joint optimization of the base station (BS) precoding vectors and the RIS phase-shift matrices. For solving highly coupled variables and infinitely many quadratic constraints, an efficient alternating optimization (AO) algorithm based on S-procedure, Schur complement, penalized convex-concave process (CCP) and successive convex approximation (SCA) is proposed. Comparing with the benchmark scheme proposed in this paper, the simulation results verify the effectiveness and robustness of the proposed algorithm.