Deployment Optimization Based on Hybrid Intelligent Algorithms for UAV Communications

被引:3
|
作者
Li, Xujie [1 ,2 ]
Zhou, Lingjie [1 ]
Zhou, Siyuan [1 ]
Xu, Yanli [3 ]
机构
[1] Hohai Univ, Coll Comp & Informat, Nanjing, Peoples R China
[2] Chinese Acad Sci, Shanghai Inst Microsyst & Informat Technol, Key Lab Wireless Sensor Network & Commun, Shanghai, Peoples R China
[3] Shanghai Maritime Univ, Coll Informat Engn, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
UAV communication; deployment optimization; hybrid algorithm; GENETIC ALGORITHM; PLACEMENT;
D O I
10.1109/gcwkshps45667.2019.9024701
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Using unmanned aerial vehicles (UAV) as the aerial wireless base station is effective to provide wireless service to ground users (GU) compared to conventional communications. In this paper, an efficient algorithm is proposed for deployment optimization that improves the throughput for UAV communication. First, UAV communication system model is presented that includes a certain number of uniformly distributed GUs and some UAVs and the problem of deployment of UAV to get the larger throughput is described. Second, the details of the proposed optimal beetle antennae search (BAS) algorithm are presented. Third, to overcome the problem that BAS algorithm trapped in the local optimal solution easily, a hybrid intelligent algorithm combining beetle antennae search algorithm and genetic algorithm is proposed. Finally, simulation results are presented that show the performance of proposed hybrid algorithm outperforms than that of the BAS algorithm and random algorithm. This result can provide an effective optimization for deployment for UAV communications.
引用
收藏
页数:6
相关论文
共 50 条
  • [31] Multi-agent based optimal UAV deployment for throughput maximization in 5 G communications
    Baghnoi, Farjam Mohammadi
    Jamali, Jasem
    Taghizadeh, Mehdi
    Fatehi, Mohammah Hossein
    WIRELESS NETWORKS, 2024, 30 (04) : 2285 - 2296
  • [32] Age of Information Aware UAV Deployment for Intelligent Transportation Systems
    Han, Rui
    Wen, Yongqing
    Bai, Lin
    Liu, Jianwei
    Choi, Jinho
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (03) : 2705 - 2715
  • [33] Intelligent UAV Deployment for a Disaster-Resilient Wireless Network
    Hydher, Hassaan
    Jayakody, Dushantha Nalin K.
    Hemachandra, Kasun T.
    Samarasinghe, Tharaka
    SENSORS, 2020, 20 (21) : 1 - 18
  • [34] UAV POSITION DEPLOYMENT AND POWER OPTIMIZATION BASED ON USER CLUSTERING IN IOT NETWORK
    Shi, Xiaoye
    Su, Xiangcheng
    Cai, Shu
    Zhang, Zhaowei
    Dai, Haibo
    2024 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING WORKSHOPS, ICASSPW 2024, 2024, : 625 - 629
  • [35] Editorial: Hybrid intelligent algorithms based learning, optimization, and application to autonomic control systems, volume II
    Zhu, Yanzheng
    Zhong, Zhixiong
    FRONTIERS IN NEUROROBOTICS, 2023, 17
  • [36] Study on optimization of economic dispatching of electric power system based on Hybrid Intelligent Algorithms (PSO and AFSA)
    Yuan, Guanghui
    Yang, Weixin
    ENERGY, 2019, 183 : 926 - 935
  • [37] Hybrid intelligent algorithms and applications
    Corchado, Emilio
    Abraham, Ajith
    de Carvalho, Andre
    INFORMATION SCIENCES, 2010, 180 (14) : 2633 - 2634
  • [38] Resource Allocation Schemes Based on Intelligent Optimization Algorithms for D2D Communications Underlaying Cellular Networks
    Li, Xujie
    Zhou, Lingjie
    Chen, Xing
    Qi, Ailin
    Li, Chenming
    Xu, Yanli
    MOBILE INFORMATION SYSTEMS, 2018, 2018
  • [39] 3D Deployment of Multiple UAV-Mounted Base Stations for UAV Communications
    Zhang, Chen
    Zhang, Leyi
    Zhu, Lipeng
    Zhang, Tao
    Xiao, Zhenyu
    Xia, Xiang-Gen
    IEEE TRANSACTIONS ON COMMUNICATIONS, 2021, 69 (04) : 2473 - 2488
  • [40] Research on route planning for solar UAV based on the intelligent optimization algorithm
    Hu, Zhonghua
    Liu, Shihao
    SCIENCE PROGRESS, 2023, 106 (03)