Joint Trajectory and Resource Optimization for RIS Assisted UAV Cognitive Radio

Unmanned ariel vehicle (UAV) can be used in cognitive radio (CR) due to its high mobility and line-of-sight (LoS) transmission. However, the throughput of secondary user (SU) may decrease because of interference arising from spectrum sharing. Reconfigurable intelligent surface (RIS) may overcome the interference by reconstructing the propagation links. Our aim is to maximize the throughput of SU subject to the interference constraint of primary user (PU) through the joint optimization of the UAV's trajectory, RIS's passive beamforming and UAV's power allocation. We divide the formulated non-convex optimization problem into three subproblems: passive beamforming optimization, power allocation optimization and trajectory design, and then propose an alternating iterative optimization algorithm of the subproblems to get the suboptimal solutions. Numerical results show the proposed algorithm can achieve remarkable throughput gain.