Max–Min Rate Optimization for Active RIS-Aided Rate-Splitting Multiple Access Systems With Integrated Sensing and Communication

This paper investigates active reconfigurable intelligent surface (RIS)-aided rate-splitting multiple access (RSMA) systems with integrated sensing and communication (ISAC). A multiple-antenna dual-functional base station (DFBS) simultaneously communicates with multiple-antenna users and detects multiple targets. We aim to optimize the transmit precoders (TPs) at the DFBS, common rate allocation in RSMA, and the reflection coefficients (RCs) at the RIS to maximize communication performance in terms of the minimum achievable rate while guaranteeing beampattern performance for radar sensing. The underlying design optimization problem is mathematically intractable due to the intricate coupling of design variables, the nonconcave nature of the objective function and the nonconvexity of the constraints. To address this, we invoke alternating optimization (AO) and minorization-maximization (MiMa) approaches to recast the design problem into convex optimization one by deriving surrogate functions. The numerical results demonstrate the superiority of the RIS-aided ISAC systems with RSMA over the counterparts with conventional space division multiple access (SDMA) and non-orthogonal multiple access (NOMA), as well as provide valuable insights into the achievable performance across various system settings.