STAR-RIS-Aided AAV-NOMA Networks: Joint Resource Allocation and Trajectory Optimization

Unmanned aerial vehicle (UAV) assisted wireless communication has great practical significance for enhancing the coverage of networks. However, achieving the seamless coverage for the whole network is still facing critical challenges due to the complex propagation environment. A novel outdoor-to-indoor (O2I) framework for simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted the UAV based on nonorthogonal multiple access (NOMA) scheme is proposed in this paper, referred to as STARS-UAV-NOMA. The users are divided into transmission users (TUs) and reflection users (RUs), and a TU is paired with a RU, i.e, RU-TU pair. In each time slot, the UAV associates with a RU-TU pair and delivers the superposed signals through the NOMA scheme. In this paper, we jointly optimize RU-TU pair scheduling, active beamforming of UAV, passive beamforming of STAR-RIS, and trajectory of UAV to maximize the average weighted sum-rate (AWSR) of users. In order to solve the highly complex non-convex problem, we propose an efficient double-layer penalty-based algorithm. Specifically, the algorithm invokes the block coordinate descent (BCD) framework to decompose the proposed problem into three subproblems, in which, the CCCP technique is adopted to deal with the non-convex constraints, and the penalized method is exploited to handle the rank-one constraints and 0-1 constraint. Numerical results demonstrate that: 1) the STAR-RIS achieves significant superiority over the transmission/reflection-only RIS; 2) the applied NOMA scheme outperforms the orthogonal multiple access (OMA) scheme in terms of enhancing the communication rate; and 3) the proposed algorithm can effectively improve network performance compared to other benchmark scheme while satisfying the constraints well.