On the Sum Rate and User Fairness of STAR-RIS Aided Communications

TL;DR

This paper investigates a STAR-RIS aided communication system, proposing a robust joint beamforming algorithm to optimize sum rate and user fairness under imperfect CSI, demonstrating improved trade-offs and resilience compared to conventional RIS.

Contribution

It introduces a novel robust beamforming design for STAR-RIS systems under imperfect CSI, balancing sum rate and fairness with an efficient optimization algorithm.

Findings

STAR-RIS outperforms conventional RIS in trade-off regions.

The proposed algorithm achieves less than 7% performance degradation under imperfect CSI.

Various trade-offs between sum rate and fairness are achievable with the method.

Abstract

A simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided communication system is investigated. A robust joint beamforming design problem under the imperfect channel state information (CSI) is formulated to maximize the weighted sum of the Jain's fairness index and the normalized system sum rate. To solve this non-convex problem, an alternating optimization (AO) algorithm is proposed, which leverages the S-Procedure, successive convex approximation (SCA), and semidefinite relaxation (SDR). Simulation results demonstrate that with proposed algorithm: 1) various trade-offs between sum rate and user fairness can be achieved; 2) a larger trade-off region can be achieved by adopting STAR-RIS compared to conventional RIS; and 3) the performance degradation caused by imperfect CSI is less than 7% with our proposed robust beamforming approach.