无人机机载可见光通信网络协同部署与节能优化方法研究OA

Visible light communication(VLC)-assisted unmanned aerial vehicle(UAV)technology pro-vides flexible communication and illumination for various applications,e.g.,transportation,cultural tour-ism and emergency.However,the high mobility of UAVs and the limited onboard resources pose signifi-cant challenges to system deployment and energy efficiency optimization.This paper proposes a dual-stage sequential optimization scheme for the cooperative deployment and resource allocation of UAV-VLC networks.The scheme jointly optimizes user association,UAV trajectory planning and power allocation to construct a system energy consumption minimization model.An enhanced K-means algorithm is employed for user clustering and initial association,and a deep reinforcement learning algorithm is developed to dy-namically optimize the trajectory and power control.Under the constraints of ensuring communication and illumination quality for all ground users,simulation results demonstrate that the proposed scheme re-duces total transmission power consumption by at least 67.62%compared to conventional approaches.