摘要
This paper investigates a millimeter-wave (mmWave) multiuser multiple-input single-output (MU-MISO) transceiver system assisted by a reconfigurable intelligent surface (RIS). Furthermore, potential hardware impairments (HWI) and imperfect channel state information (CSI) are considered in the system model, reflecting realistic implementation constraints. The objective is to achieve user fairness, and thus reduce inequality among users, by jointly optimizing the transceiver beamforming and discrete RIS phase shifts to minimize the worst-case mean square error (MSE) across all users, thereby strictly ensuring user fairness. To solve this non-convex min-max problem, we develop an alternating optimization (AO)-based algorithm that iteratively decouples the coupled variables, enabling tractable and efficient subproblem solutions. Simulations demonstrate rapid convergence within 31 iterations and up to 15% worst-case MSE reduction compared to benchmarks.