认知无人机辅助边缘通信的能效优化

针对无人机辅助边缘通信中的频谱资源紧缺与无人机能量受限问题,研究了最大化该场景下无人机认知通信的能量效率问题。首先,构建了无人机辅助边缘节点的认知通信网络模型;其次,提出了一种最大化无人机能效的算法,通过联合优化无人机的认知通信感知时间、飞行速度和通信距离阈值,显著提升了无人机认知通信过程中的能效;最后,通过仿真实验对所提算法进行验证,结果表明:同时存在最优的感知时间、无人机飞行速度和通信距离阈值使得能效最大化,且用户对吞吐量要求的大小会影响最大化的能效;该算法在提升能效方面优于现有的方案,有效地提高了认知无人机辅助通信网络的能效。

Optimization of Energy Efficiency for Cognitive UAV-assisted Edge Communication

In order to overcome the shortage of spectral resources and the limitation of unmanned aerial vehicle(UAV)energy in the UAV-assisted edge communication network,this paper studies the problem of maximizing the energy efficiency of UAV cognitive communication in this scenario.First,the cognitive network model of the UAV assisted edge nodes communication is established.Second,an algorithm to maximize the energy efficiency of UAV communication is presented.By jointly optimizing the sensing time of UAV sensors,flight speed and communication coverage of UAV,the energy efficiency of the UAV cognitive communication is significantly improved.Next,an algorithm to maximize the energy efficiency of UAV is presented.By jointly optimizing the sensing time,flying speed and communication distance thresholds of the UAV,the energy efficiency is significantly improved.Finally,the proposed algorithm is validated through simulations.The results show that optimal sensing time,UAV flying speed and communication coverage radius can simultaneously exist to maximize the energy efficiency.And the maximum energy efficiency can be affected by the users’QoS for throughput.The proposed algorithm is superior to the benchmark scheme in terms of improving energy efficiency,which proves that the algorithm effectively improves the energy efficiency of cognitive UAV-assisted edge communication.