Research On Resource Management Algorithm In UAV-Assisted Energy Harvesting Communication System

Energy harvesting communication assisted by unmanned aerial vehicle(UAV)is an emerging green communication method.The key of improving the communication system performance is how to make full use of UAV and optimize the system resources to efficiently use the harvested energy.Aiming at difference of number of users in different time periods(i.e.,more users in busy time and fewer users in spare time)for the femto base station,the resource management strategy are investigated in this thesis to improve the information and energy efficiency of the energy harvesting communication system.The main contributions are presented as follows:(1)A resource management strategy is investigated to maximize the downlink total information assisted by UAV base station.By deploying a UAV base station with radio frequency energy harvesting capability.It can serve for a small number of users when the numbers of users in multiple femto base stations are small.The energy consumption and transmitting power should satisfy the constraint conditions in order to maximize the downlink information of the femto base station and the UAV base station.By introducing the augmented Lagrange multiplier method to obtain the optimal solution.The simulation results show that compared with the equal power method and partial fixed power method with UAV base station,the proposed method has an increase in terms of total information to different degrees.(2)A resource management strategy is investigated to maximize the energy efficiency in a single cycle with UAV relay assistance.A UAV relay with energy harvesting capability is deployed.It can take over multiple femto base stations to provide communication services for users when the number of users is small.The goal of resource management is to maximize single cycle energy efficiency through the combined optimization of the transmitting power of the femto base station and the UAV relay.The suboptimal solution is obtained by introducing particle swarm optimization(PSO)algorithm.The simulation results show that compared with the average power method with UAV relay participation and the partial fixed power method,the proposed method can improve the energy efficiency greatly.(3)A multi period energy efficiency maximization strategy for UAV relay assistance with joint trajectory optimization is investigated.A UAV relay is introduced.It can assist multiple femto base stations when the number of users is large.And it will replace multiple femto base stations to provide communication services for users when the number of users is small.The problem should meet the user minimum throughput,UAV relay and femto base station energy consumption and transmitting power limits.The multi-period energy efficiency is maximized through the joint optimization of the transmitting power of the femto base station and UAV relay,UAV flight radius coefficient and UAV downlink communication time ratio.The quantum behavior particle swarm optimization(QPSO)algorithm is applied to solve the problem and get the suboptimal solution.The simulation results show that compared with the busy and spare time fixed power allocation method and the PSO algorithm with UAV trajectory optimization,the energy efficiency of the proposed method is improved to a certain extent.