Multi-STAR-RIS NOMA: Clustering, RIS Assignment and Power Optimization

Abstract

Reconfigurable intelligent surfaces (RISs) represent a breakthrough technology capable of dynamically modifying wireless signals' amplitude and/or phase via numerous reflecting units, thereby reconfiguring the radio propagation environment. This paper investigates the performance of multi-simultaneously transmitting and reflecting RIS (STAR-RIS)-enabled non-orthogonal multiple access (NOMA) networks under the collective impact of transceiver hardware impairments (HIs) and RIS phase error. Unlike existing studies that often focus on two-user scenarios with ideal hardware assumptions, we propose a network-centric approach that clusters users and associates multiple STAR-RIS units with these clusters, while accounting for practical hardware constraints. Specifically, we formulate an optimization problem aimed at maximizing the network sum rate by optimally clustering users, assigning STAR-RIS units, and optimizing power allocation among NOMA user pairs. The proposed solution decouples this problem into more tractable subproblems to facilitate real-time application. Subsequently, we derive closed-form expressions for the ergodic rates and their upper bounds to evaluate the system performance. The numerical results highlight the effectiveness of the proposed multi-STAR-RIS NOMA scheme compared to benchmark schemes, emphasizing its relevance for evaluating the performance of future wireless systems under practical conditions.