无人机能耗与数据传输速率部署优化  

Optimization of UAVs deployment based on energy consumption and data transmission rate

作　　者：高睿 王霄[1] 徐凌桦[1] GAO Rui;WANG Xiao;XU Linghua(School of Electrical Engineering,Guizhou University,Guiyang 550025,China)

机构地区：[1]贵州大学电气工程学院,贵州贵阳550025

出　　处：《现代电子技术》2024年第11期6-12,共7页Modern Electronics Technique

基　　金：国家自然科学基金项目(61861007);国家自然科学基金项目(61640014);贵州省科技计划项目(黔科合基础-ZK[2021]一般303);贵州省科技支撑计划(黔科合支撑[2022]一般017,黔科合支撑[2023]一般096,黔科合支撑[2022]一般264);贵州省教育厅创新群体项目(黔教合KY字[2021]012);贵大人基合字(2014)08号。

摘　　要：针对灾害场景下的多无人机协同部署问题,提出一种基于遗传-拟牛顿算法的无人机节能部署与数据传输优化方法。首先提取无人机信道、路径损耗、连通率和覆盖率特征,将多无人机协同部署问题抽象为连通率、覆盖率问题。然后,使用排序组选择操作、随机权重交叉操作以及非一致性变异算子改进遗传算法,结合改进搜索方向和迭代步长的BFGS算法,进一步提出IGA-BFGS算法,该算法在全局和局部上都能得到较好的优化效果,提高求解效率和精度。最后,根据不同环境下需要救援的地面用户的信道特性和离散系数,动态调整无人机基站的发射功率和高度,提高了无人机基站的功耗效率,增加了无人机基站的使用时间,实现了无人机基站的节能部署。仿真结果表明,设计的方法能够有效实现无人机节能部署与数据传输优化。ed as connectivity rate and coverage rate.The genetic algorithm(GA)is improved by the sorting group selection operation,the random weight crossover operation and the inconsistent mutation operator.In combination with the BFGS(Broyden-Fletcher-Goldfarb-Shanno)algorithm which improves the search direction and the iteration step length,the IGA-BFGS algorithm is proposed.This algorithm can get better optimization effect both globally and locally,and also can improve the efficiency and precision of the solution.The transmitting power and height of UAV base station are dynamically adjusted according to the channel characteristics and discrete coefficients of ground users needing rescue in different environments,which improves the power consumption efficiency of UAV base station,increases the working time of UAV base station,and realizes the energy-saving deployment of UAV base station.The simulation results show that the designed method can effectively realize the energy-saving deployment and data transmission optimization of UAV.

关 键 词：节能部署 异构无人机 应急通信 遗传算法 多无人机 任务分配 数据传输 拟牛顿法 

分 类 号：TN919-34[电子电信—通信与信息系统]