Sum Rate Maximization for Movable Antenna-Aided Downlink RSMA Systems

TL;DR

This paper introduces a movable antenna scheme for RSMA systems, jointly optimizing antenna positions and beamforming to significantly enhance sum rate performance over traditional fixed antennas.

Contribution

It proposes a novel movable antenna-assisted RSMA framework with a joint optimization method, improving system sum rate and reliability.

Findings

Movable antennas significantly improve RSMA sum rate.

The proposed optimization algorithm effectively enhances system performance.

Numerical results confirm substantial gains over fixed-position antenna systems.

Abstract

Rate splitting multiple access (RSMA) is regarded as a crucial and powerful physical layer (PHY) paradigm for next-generation communication systems. Particularly, users employ successive interference cancellation (SIC) to decode part of the interference while treating the remainder as noise. However, conventional RSMA systems rely on fixed-position antenna arrays, limiting their ability to fully exploit spatial diversity. This constraint reduces beamforming gain and significantly impairs RSMA performance. To address this problem, we propose a movable antenna (MA)-aided RSMA scheme that allows the antennas at the base station (BS) to dynamically adjust their positions. Our objective is to maximize the system sum rate of common and private messages by jointly optimizing the MA positions, beamforming matrix, and common rate allocation. To tackle the formulated non-convex problem, we apply fractional programming (FP) and develop an efficient two-stage, coarse-to-fine-grained searching (CFGS) algorithm to obtain high-quality solutions. Numerical results demonstrate that, with optimized antenna adjustments, the MA-enabled system achieves substantial performance and reliability improvements in RSMA over fixed-position antenna setups.