Max-Min Energy-Efficiency Fair Optimization in STAR-RIS Assisted System

TL;DR

This paper proposes an optimization framework for STAR-RIS systems to maximize the minimum user energy efficiency, demonstrating improved fairness and performance over traditional RIS through an alternating optimization algorithm.

Contribution

It introduces a joint optimization method for active beamforming and STAR-RIS phase shifts to enhance energy efficiency fairness in STAR-RIS aided systems.

Findings

STAR-RIS outperforms traditional reflecting-only RIS.

The proposed AO algorithm efficiently maximizes minimum user EE.

Numerical results confirm improved user fairness and system performance.

Abstract

In this paper, we investigate simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS), which enables to communicate with users both sides by transmitting signals to users forward and reflecting signals to users backward simultaneously. We consider a communicatio system with a STAR-RIS, a base station (BS) and many users to maximize the minimum user energy efficiency (EE) by jointly optimizing the active beamforming, transmission and reflection coefficients with BS power consumption limited. To solve this optimization problem efficiently, we divide it into two sub-problems to optimize the transmitting beamforming matrix and phase shifts of STAR-RIS seperately. With the two subproblems fixed, an Alternating Optimization (AO) method is proposed to solve the maximize minmum user EE fair optimization problem. Numerical results can demonstrate that STAR-RIS behaves better than traditional reflecting-only RIS, and the algorithm we desigend can maximize the minum EE problem efficienty to ensure user fairness.