Research On Deployment Optimization And Resource Allocation For UAV-enabled Wireless Powered Communication Networks

The UAV-enabled wireless powered communication networks(U-WPCN)can transmit radio frequency energy to the target terminal and realize information interaction by using the line of sight(LOS)channel.In order to provide efficient energy supply and communication services for wireless sensor networks,serve the major strategic needs of environmental monitoring,disaster early warning,territorial security maintenance,this dissertation conducts basic research work on the U-WPCN.The dissertation focuses on the key technical issues such as the efficient deployment and coverage of multiple UAVs,the optimal allocation of UAV cruise trajectory and resources,and the physical layer security of UAV air-to-ground information transmission.Specifically includes the following contents:(1)This dissertation studies the deployment optimization of U-WPCN.The model of multi UAV group coverage communication network is established,and the UAV deployment optimization algorithm is proposed.The closed form solution of UAV hovering position in each group is given by adjustable relaxation variables,and the global deployment optimization scheme of UAV is obtained by greedy algorithm.In order to optimize the coverage efficiency of UAV,the deployment optimization strategy under dynamic communication requirements is proposed.By adjusting the type and number of UAV platforms,when the number of available UAV platforms is limited,the information transmission rate of sensor terminals is improved;when the minimum information transmission rate threshold of sensor terminals is guaranteed,the deployment sorties of UAVs are reduced.Simulation results show that the proposed algorithm can achieve efficient coverage and rapid deployment of the target area while improving the information transmission rate of terminal equipment.(2)This dissertation studies the efficient cruise problem of UAV-enabled wireless powered relay network.In order to maximize the information collection efficiency of UAV in the target area under the limited flight period,a joint optimization algorithm of trajectory and resource allocation is proposed.Using successive convex approximation(SCA)theory and block coordinate descent(BCD)algorithm,the flight trajectory,energy broadcast power,information relay power,slot resource allocation scheme and terminal information transmission power of UAV are optimized.The communication mode adaptive switching mechanism of terminal equipment is given,which enables UAV to provide relay service for terminals with difficult information transmission,so as to improve cruise efficiency.Simulation results show that the proposed algorithm can effectively improve the information collection throughput of UAV in cruise cycle,and ensure the fairness of information transmission of the target terminal.On the basis of theoretical methods and technical research,a visual flight path and information collection interface software are designed,and relevant experiments are carried out to verify the reliability of UAV cruise information collection system.(3)This dissertation studies the information security transmission problem of UWPCN.The participation probability model of air-to-ground cooperative interference is established,and the optimization algorithm of information physical layer security transmission is proposed.Through the way of energy compensation,the interference nodes are encouraged to participate in the cooperation and interfere with the eavesdropping nodes,so as to improve the information security transmission rate of the system.On the premise of ensuring the expected air-to-ground cooperation probability,the flight trajectory and energy compensation scheme of UAV are jointly optimized,which not only optimizes the system energy efficiency and improves the safe transmission rate of UAV information collection,but also provides decision-making basis for air ground cooperation interference.When the location of eavesdropping nodes is fuzzy,the robust optimal location of eavesdropping nodes is given,which improves the robustness of the joint optimization algorithm.Simulation results show that the proposed algorithm can effectively improve the physical layer security transmission rate of UAV information collection process.