Resource Allocation Scheme in STAR-RIS-Assisted NOMA Systems Based on UAV Energy Supply

In this paper, we introduce a novel simultaneous transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted non-orthogonal multiple access (NOMA) model designed for non-line-of-sight (NLoS) scenarios. To ensure energy self-sustainability, an unmanned aerial vehicle (UAV) is introduced for wireless energy transfer. In the proposed model, ground users (GUs) situated in communication-obstructed environments are supported by STAR-RIS to connect with the base station (BS). Energy harvested from the UAV is utilized to enable prolonged communication with 360° full spatial coverage. An optimization problem is formulated to maximize the system’s sum-rate and is decomposed into three subproblems: phase-shift optimization, power allocation, and time allocation. These subproblems are solved using semidefinite relaxation (SDR), Dinkelbach’s method, and game theory, respectively. A joint resource allocation algorithm based on the block coordinate descent (BCD) method is then proposed. Simulation results show that the proposed UAV-assisted STAR-RIS-NOMA scheme, combined with the BCD algorithm, achieves a 43.64% improvement in system capacity compared to existing approaches.