Resource Optimization and AAV Deployment for RSMA-RIS Enabled Secure Communication

This paper investigates a downlink multi-user communication network enabled by an autonomous aerial vehicle (AAV) integrated with the reconfigurable intelligent surface (RIS). The proposed network introduces rate-splitting multiple access (RSMA) to provide high-quality services to various ground users and leverages the RIS-mounted AAV to reconstruct wireless channels, thereby enhancing resistance to potential eavesdropping threats. To promote green communication, we formulate an optimization problem aimed at maximizing the sum secrecy rate. For the non-convex problem, we propose an iterative framework for joint optimization. Specifically, the simulated annealing (SA) algorithm is employed to achieve power allocation, the semi-definite relaxation (SDR) method is applied to obtain the RIS phase shifts, and the deep deterministic policy gradient (DDPG) algorithm is proposed to optimize the AAV trajectory. Numerical results demonstrate the superiority of the proposed scheme in improving physical layer security and supporting efficient multi-user access.