Performance Optimization Of Uav Cooperative Communication Network Based On Wireless Power Transfer Technique

With the development of the wireless communication network,non-terrestrial network(NTN)will become the next hot spot of future research.And unmanned aerial vehicles(UAVs)play an important role in NTN communication due to their advantages,such as flexible deployment,fast networking and low cost.However,the energy constraint of UAVs also leads to many challenges to the communication system.In order to solve this problem,wireless power transfer technique is applied to UAV communication network.Besides,UAV system models are established based on the actual communication scenario requirements,and optimization algorithms are also proposed to improve the information transmission rate and energy efficiency of UAV communication network.The main contents and innovations of this thesis are listed as follows:A multiple-UAV enabled wireless powered communication network(WPCN)is constructed first.The ground micro base station(mBS)is deployed as a hybrid access point to transmit energy signals and receive information for monitoring UAVs.The target is to maximize the achievable sum rate of all UAVs over each time slot by optimizing the mBSs’ transmit power allocation.To solve the non-convex problem,a successive alternate optimization(SAO)algorithm is proposed to approximate the problem to a convex form.Simulation results show that the optimal power allocation scheme achieves significant system throughput gain.An effective deployment of millimeter wave(mmWave)in UAV-enabled wireless powered communication network is investigated.The channel model and antenna model in millimeter wave communication scenario are considered,and the influence of energy transmission time is further considered.In order to maximize the network throughput,a two-stage iterative optimization algorithm is proposed.The energy transmission time and base transmit power are optimized alternately through the proposed algorithm,and the convergence of the algorithm is proved.In addition,the effectiveness of the proposed algorithm is verified by simulation.The proposed algorithm achieves significant performance from the aspects of iterations and throughput gains,compared with Q-learning algorithm and other benchmark schemes.A multi-type UAV aided Internet of things(IoT)network is constructed,where the energy UAV is cooperated with the base station UAV.In order to maximize the energy efficiency of UAV network,a joint optimization algorithm is proposed to optimize the flight trajectory of base station UAV,system time resource allocation,transmit power.Besides,the complexity of the proposed algorithm is analyzed.Simulation results show the effectiveness of the proposed algorithm.