Secure Sum-Rate Optimization in RIS-Assisted RSMA HAP Systems With Untrusted Users

Nonterrestrial networks leveraging high-altitude platforms (HAPs) are pivotal for bridging coverage gaps in remote regions and ensuring service continuity when terrestrial infrastructure fails (e.g., during disasters) or becomes congested (e.g., mass events). While integrating rate-splitting multiple access (RSMA) and reconfigurable intelligent surfaces (RISs) enhances spectral efficiency, securing transmissions against unknown eavesdroppers with imperfect channel state information remains a critical challenge. We propose a secure multiuser, multicluster RIS-assisted RSMA system for HAPs, jointly optimizing precoding, RIS beamforming, and cluster time allocation to maximize sum-rate under secrecy rate constraints. The nonconvex problem is transformed into a tractable semidefinite program via successive convex approximation, auxiliary variable bounding, and a rank-1 penalty method. Simulations demonstrate significant performance gains over benchmarks, robustness to practical RIS phase quantization, and scalability across varying numbers of users per cluster, validating the framework's efficacy.