IRS辅助无人机安全通信的波束成形与联合轨迹优化OA

To address the strong coupling and non-convex intractability of joint beamforming and trajectory optimization in Intelli-gent Reflecting Surface(IRS)-assisted secure Unmanned Aerial Vehicle(UAV)communications,this paper focuses on a single-user Multiple-Input Single-Output(MISO)scenario and proposes to adopt a joint optimization approach based on alternating optimization and Successive Convex Approximation(SCA).In the proposed approach,alternating optimization and convex approximation strategies are employed to decouple the original problem into three subproblems,namely transmit beamforming,IRS phase-shift design,and UAV trajectory optimization.Specifically,the transmit beamformer is obtained by solving a generalized eigenvector problem at the transmitter,the IRS phase shifts are optimized via fractional programming,and the UAV trajectory is refined through convex optimization,thereby achieving a significant improvement in the system secrecy rate.Numerical simulation results demonstrate that jointly optimizing active and passive beamforming together with the UAV trajectory can effectively enhance the secrecy performance of the system.Moreover,an appropriate design of the number of transmit antennas,the number of IRS reflecting elements,and the UAV flight duration can further improve the reliability and robustness of the proposed algorithm.