Sum Rate Maximization for Movable Antenna-Aided Downlink RSMA Systems

Rate splitting multiple access (RSMA) is regarded as an essential and powerful physical-layer (PHY) paradigm for next generation communication systems. Under such a system, users employ successive interference cancellation (SIC), allowing them to decode a portion of the interference and treat the remainder as noise. However, a problem is that current RSMA systems rely on fixed-position antenna arrays, limiting their capacity to fully exploit spatial freedom. This constraint restricts beamforming gain, which substantially degrades RSMA performance. To address this problem, we propose an movable antenna (MA)-aided RSMA scheme that allows the antennas at the base station (BS) to adjust their positions dynamically. Our target is to maximize the system's sum rate of both common and private messages by jointly optimizing the MA positions, beamforming matrix, and common rate allocation. To tackle the formulated non-convex problem, we employ fractional programming (FP) and develop a two-stage, coarse-to-fine-grained search algorithm to obtain suboptimal solutions. Numerical results demonstrate that, with appropriate antenna adjustments, the MA-enabled system significantly enhances the overall performance and reliability of RSMA when employing the proposed algorithm compared to fixed-position antenna configurations.