Scheduling optimization for UAV communication coverage using virtual force-based PSO model  

作　　者：Jianguo Sun Wenshan Wang Sizhao Li Qingan Da Lei Chen 

机构地区：[1]College of Computer Science and Technology,Harbin Engineering University,Harbin,Heilongjiang,150001,China [2]College of Engineering and Computing,Georgia Southern University,Statesboro,GA,30458,USA

出　　处：《Digital Communications and Networks》2024年第4期1103-1112,共10页数字通信与网络（英文版）

基　　金：supported by National Key R&D Program of China under Grants No.2022YFB4400703;National Natural Science Foundation of Heilongjiang Province of China(Outstanding Youth Foundation)under Grants No.JJ2019YX0922 and NSFC under Grants No.F2018006.

摘　　要：When the ground communication base stations in the target area are severely destroyed,the deployment of Unmanned Aerial Vehicle(UAV)ad hoc networks can provide people with temporary communication services.Therefore,it is necessary to design a multi-UAVs cooperative control strategy to achieve better communication coverage and lower energy consumption.In this paper,we propose a multi-UAVs coverage model based on Adaptive Virtual Force-directed Particle Swarm Optimization(AVF-PSO)strategy.In particular,we first introduce the gravity model into the traditional Particle Swarm Optimization(PSO)algorithm so as to increase the probability of full coverage.Then,the energy consumption is included in the calculation of the fitness function so that maximum coverage and energy consumption can be balanced.Finally,in order to reduce the communication interference between UAVs,we design an adaptive lift control strategy based on the repulsion model to reduce the repeated coverage of multi-UAVs.Experimental results show that the proposed coverage strategy based on gravity model outperforms the existing state-of-the-art approaches.For example,in the target area of any size,the coverage rate and the repeated coverage rate of the proposed multi-UAVs scheduling are improved by 6.9–29.1%,and 2.0–56.1%,respectively.Moreover,the proposed scheduling algorithm is high adaptable to diverse execution environments.©2022 Published by Elsevier Ltd.

关 键 词：Multi-UAVs Ad hoc network Area collaborative coverage Gravity model Swarm optimization algorithm Random topology 

分 类 号：V279[航空宇航科学与技术—飞行器设计] TP18[自动化与计算机技术—控制理论与控制工程] TN929.5[自动化与计算机技术—控制科学与工程]