Power Allocation and Trajectory Design for Unmanned Aerial Vehicle Relay Network with Mobile Users
In Unmanned Aerial Vehicle(UAV)relay networks,communication resource allocation and motion planning of UAV are the key problems that should be solved.In order to improve the communication efficiency of UAV relay communication system,a joint planning method of UAV relay power allocation and trajectory design is proposed based on proximal policy optimization algorithm.The joint planning problem of UAV relay power allocation and trajectory design in the user movement scenario is modelled as a Markov decision-making process.Considering the inaccurate acquisition of user location information,the reward function is set with the maximum throughput of the relay communication system as the optimization goal under the premise of satisfying the user interruption probability constraint.Then,a deep reinforcement learning algorithm with high convergence speed——the Proximal Policy Optimization(PPO)algorithm,is used to solve the problem and realized the flight trajectory optimization of relay UAV and the reasonable and effective allocation of relay transmission power.The simulation experimental results show that for the scenario of UAV relay communication with random users movement,the proposed method improves system throughput by 22% and 15%,respectively,compared to the methods based on random strategy and traditional Deep Deterministic Policy Gradient(DDPG).The results show that the proposed method can effectively improve the communication efficiency of the system.
万方数据
维普
