Research On UAV Based Energy Efficient&Long-term Communication Coverage

Due to the flexibility,controllability and strong coverage ability of Unmanned Aerial Vehicle(UAV),UAV based communication coverage can meet the communication requirements in some specific situations,such as earthquake area and hotspots.Then,the research and applications of UAV based communication grow rapidly,and UAV based communication coverage will be one of the important directions of academic research in the future networks.Recently,UAV-aided coverage,UAV-aided relaying and UAV-aided data collection and distribution have gained more interests in the literature.However,the biggest bottleneck of civil UAV is its limit flight duration,which seriously limits the application of UAV in communications.Hence,the research of improving the energy efficiency of UAV as well as taking a group of UAV with limit flight duration to provide long-term coverage is essential for UAV based communications.In this paper,we analyze the main power aspects of UAV that relative to the energy efficiency and service duration of UAV based communication systems,such as the relationship between the position and altitude of UAV with the energy efficiency based on the air-to-ground channel model,the relationship between the flight trajectory and flight speed with the propulsion power of UAV according to the propulsion power model.Then,some remote charging technologies that can improve the flight duration of UAV are introduced.Based on above analyses,we study the cooperative strategy for UAV in order to realize seamless long-term services in the context of static coverage,dynamic coverage and coverage in heterogeneous cellular networks.Then,in order to maximize the energy efficiency,we investigate the optimization method for the long-term cooperative strategies.Firstly,in the research of multi-UAV based coverage in urban environment,a UAV power model and a cyclic recharging and reshuffling strategy for rechargeable UAVs are proposed in order to achieve seamless long-term coverage for ground users.For the sake of maximizing the energy efficiency of the multi-UAV system,a two-stage joint optimization algorithm based on particle swarm optimization(PSO)is proposed to optimize the deployment strategy for target points and the cyclic recharging and reshuffling strategy.Simulation results show that the proposed method improves the energy efficiency of the proposed multi-UAV system when guaranteeing seamless long-term communication coverage.Moreover,the proposed algorithm has faster convergence rate and better convergence results than both genetic algorithm and greedy algorithm.Secondly,aiming at the limit flight duration of UAVs,a dynamic cooperative architecture for seamless long-term coverage with multiple UAVs is proposed.Considering the multi-UAV scenario,the interference among the UAVs and the cooperative constraints of multiple UAVs are discussed.In order to improve the energy efficiency of the system,a joint optimization algorithm is proposed for optimizing the user assignment,UAV flight trajectories and UAV transmit power control.Simulation results show that the proposed method can optimize the energy efficiency of the long-term coverage system by optimizing the cooperative strategy of multiple UAVs,while the optimality of the proposed algorithm is verified by comparing with ergodic search method.Thirdly,in the scenario of UAV asisted cellular heterogeneous network,a cooperative architecture with UAV and ground base stations is proposed,where the limit flight energy of UAV is concerned.Based on the interference model between UAV and ground base stations as well as the propulsion power model of UAV,a convex optimization theory based successive approximation algorithm is proposed.Simulation results show that the proposed strategy of UAV with limit flight energy can improve the quality-of-services of ground users,while the UAV can increase the minimum user throughput by more than 60% and average user throughput by more than 300%,respectively.Finally,we conclude our paper,and propose some future prospection on the research of the energy efficiency of UAV based communication coverage.