Max-Min Fairness in Stacked Intelligent Metasurface-Aided Rate Splitting Networks

TL;DR

This paper presents a novel wave-domain beamforming approach using stacked intelligent metasurfaces combined with rate-splitting multiple access to enhance fairness in multiuser wireless networks.

Contribution

It introduces a fairness-focused SIM-RSMA design with a max-min rate optimization framework and develops an alternating optimization method for joint beamforming and power control.

Findings

SIM-RSMA outperforms space division and non-orthogonal multiple access in max-min fairness.

The proposed optimization framework effectively balances resource allocation among users.

Simulation results demonstrate significant fairness improvements with the proposed system.

Abstract

This paper investigates a downlink multiuser multiple-input single-output system that integrates rate-splitting multiple access (RSMA) with a stacked intelligent metasurface (SIM) to enable wave-domain beamforming. Unlike conventional digital beamforming, the proposed system leverages the programmable phase shifts of the SIM to perform beamforming entirely in the wave domain. In contrast to existing literature, this work introduces a fairness-centric SIM-RSMA design that shifts the emphasis from maximizing sum-rate to ensuring fair allocation of resources. In particular, we formulate a max-min rate optimization problem that jointly optimizes transmit power coefficients at the base station and SIM phase shifts. Given the non-convex nature of this problem, we develop an alternating optimization framework, where the power allocation is optimized through successive convex approximation and SIM beamforming is optimized using the Riemannian conjugate gradient method. Simulation results indicate that combining SIM with RSMA yields superior max-min performance compared to its integration with space division multiple access or non-orthogonal multiple access.