无人机辅助传感器网络中吞吐量与节点能量优化方法OA北大核心CSTPCD

With its high mobility,unmanned aerial vehicles(UAVs)can perform wireless data acquisition and wireless power transmission to sensor nodes,but wireless data acquisition and wireless power transmission are coupled to each other,and how to optimize their resource allocation and the flight trajectory is the key to improve the UAV-assisted wireless powered sensor network performance.Therefore,a joint optimization scheme is proposed,which maximizes the minimum node utility by alternately optimizing node access,UAV three-dimensional flight trajectory,energy and data transmission time allocation respectively.A joint optimization scheme is proposed for maximizing the minimum node utility in the wireless powered sensor networks(WPCN)model.Since the problem is non-convex,a maximized the minimum node utility algorithm(MMNUA)is proposed,which uses the block coordinate descent method to transform the original problem into four subproblems,and uses successive convex approximation(SCA)technology to optimize the four subproblems in each iteration,so that the maximized minimum node utility gradually converges.Compared with the basic UAV scheme,the MMNUA scheme improves the system performance by 14.1%,567.5%and 177.0%,respectively,which effectively improves the work efficiency of the UAV,and the proposed algorithm has good convergence and less complexity.