基于MCR⁃WPT的无人机协助WPCN的资源分配策略  

Resource allocation strategy for UAV⁃aided WPCN based on MCR⁃WPT

作　　者：徐志红 赵宜升[1,2] 贺喜梅 陈勇 XU Zhihong;ZHAO Yisheng;HE Ximei;CHEN Yong(College of Physics and Information Engineering,Fuzhou University,Fuzhou 350116,China;Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information,Fuzhou University,Fuzhou 350116,China)

机构地区：[1]福州大学物理与信息工程学院,福建福州350116 [2]福州大学福建省媒体信息智能处理与无线传输重点实验室,福建福州350116

出　　处：《南京邮电大学学报（自然科学版）》2022年第6期61-69,共9页Journal of Nanjing University of Posts and Telecommunications：Natural Science Edition

基　　金：国家自然科学基金(61871133);福建省自然科学基金(2021J01587)资助项目

摘　　要：针对无人机(Unmanned Aerial Vehicle,UAV)协助的无线供电通信网络中采用射频能量收集方式出现的地面终端能量不足的问题,研究基于磁耦合谐振无线能量传输的最小吞吐量最大化资源分配策略。通过引入一个搭载磁耦合谐振装置的能量传输UAV,依次为地面终端提供足够的能量。为了使所有地面终端的最小吞吐量最大化,联合优化信息接收UAV轨迹、地面终端发射功率和时隙分配比例。由于该问题是非凸优化问题,难以直接求解。通过引入一些辅助变量,将一些非凸约束条件通过适当的数学推导转换成凸约束条件。对于难以转化的非凸约束条件,采用凹凸过程将非凸函数线性化成两个凸函数相减的形式。最后通过迭代求解原非凸逼近问题的凸逼近问题,得到原始问题的次优解。仿真结果表明,与固定UAV轨迹、固定时隙分配比例、量子行为粒子群优化算法和标准粒子群优化算法相比,所提方法在最小吞吐量方面有一定程度的提高。Since insufficient ground terminal energy in unmanned aerial vehicle(UAV)aided wireless powered communication networks(WPCNs)use the radio frequency to harvest energy,ground terminals usually suffer from insufficient energy.This paper proposes the minimum throughput maximization resource allocation strategy based on magnetic coupling resonant wireless power transfer(WPT)is studied in this paper.By introducing a power transfer UAV equipped with a magnetic coupling resonance(MCR)device,sufficient energy is provided for ground terminals in turn.In order to maximize the minimum throughput of all the ground terminals,the UAV trajectory for receiving information,the ground terminal transmission power and the timeslot allocation proportion are jointly optimized.Since this problem is a non⁃convex optimization problem and hard to obtain solutions directly.By introducing some auxiliary variables,some non⁃convex constraints are converted into convex constraints through the appropriate mathematical derivation.For the non⁃convex constraint conditions that are difficult to convert,the concave⁃convex process is used to linearize the non⁃convex function into the subtraction form of two convex functions.Finally,the sub⁃optimal solution of the original problem is obtained by iteratively solving the convex approximation problem of the original non⁃convex approximation problem.The simulation results show that the proposed method achieves a certain degree of improvement in the minimum throughput,compared with the method with fixed UAV trajectory,the method with fixed timeslot allocation ratio,the quantum behavior particle swarm optimization algorithm and the standard particle swarm optimization algorithm.

关 键 词：磁耦合谐振 无人机 无线供电通信网络 资源分配 

分 类 号：TN915[电子电信—通信与信息系统]