The Optimization of UAV-Assisted Downlink Transmission Based on RSMA

Abstract

Unmanned Aerial Vehicles (UAVs) provide exceptional flexibility, making them ideal for mitigating communication disruptions in disaster-affected or high-demand areas. When functioning as communication base stations, UAVs can adopt either orthogonal or non-orthogonal multiple access schemes. However, traditional Orthogonal Multiple Access (OMA) techniques are constrained by limited user access capacity and system throughput, necessitating the study of non-orthogonal access mechanisms for UAV-assisted communication systems. While much of the research on non-orthogonal multiple access focuses on Non-Orthogonal Multiple Access (NOMA), Rate-Splitting Multiple Access (RSMA), a novel non-orthogonal technique, offers superior throughput performance compared to NOMA. This paper, therefore, investigates the optimization of UAV-assisted downlink communication systems based on RSMA. We first develop a mathematical model of the system and decompose the primary optimization problem into multiple subproblems according to parameter types. To solve these subproblems, we propose an optimization algorithm that combines the Augmented Lagrange Method (ALM) with the Artificial Fish Swarm Algorithm (AFSA). The optimization algorithm is further enhanced by incorporating dynamic step size and visual strategies, as well as memory behaviors to improve convergence speed and optimization accuracy. To address linear equality constraints, we introduce a correction factor to modify the behavior of the artificial fish. The final optimization is achieved through cross-iterative solutions. Simulation results show that the system throughput under the RSMA strategy can be improved by 13.30% compared with NOMA, validating the effectiveness and superiority of RSMA in UAV-assisted communication systems.