Robust Multi-UAV Cooperative Trajectory Planning and Power Control for Reliable Communication in the Presence of Uncertain Jammers

被引:0
作者
Wang, Fan [1 ,2 ]
Zhang, Zhiqiang [3 ]
Zhou, Lingyun [4 ]
Shang, Tao [5 ]
Zhang, Rongqing [6 ]
机构
[1] Xidian Univ, Sch Telecommun Engn, Xian 710071, Peoples R China
[2] China Res Inst Radiowave Propagat, Qingdao 266107, Peoples R China
[3] Henan Polytech Univ, Hebi Inst Engn & Technol, Hebi 458030, Peoples R China
[4] South Cent Minzu Univ, Coll Elect & Informat Engn, Wuhan 430074, Peoples R China
[5] Xidian Univ, State Key Lab Integrated Serv Networks, Xian 710071, Peoples R China
[6] Tongji Univ, Sch Comp Sci & Technol, Shanghai 201804, Peoples R China
基金
中国国家自然科学基金;
关键词
multi-UAV; nonconvex optimization; trajectory planning; power allocation; RESOURCE-ALLOCATION; DESIGN; SKY; LTE;
D O I
10.3390/drones8100558
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Unmanned aerial vehicles (UAVs) have become a promising application for future communication and spectrum awareness due to their favorable features such as low cost, high mobility, and ease of deployment. Nevertheless, the jamming resistance appears to be a new challenge in multi-UAV cooperative communication scenarios. This paper focuses on designing trajectory planning and power allocation for efficient control and reliable communication in a ground control unit (GCU)-controlled UAV network, where the GCU coordinates multi-UAV systems to execute tasks amidst multiple jammers with imperfect location and power information. Specifically, this paper formulates a nonconvex semi-infinite optimization problem to maximize the average worst-case signal-to-interference-plus-noise ratio (SINR) among multiple UAVs by designing robust flight paths and power control strategy under stringent energy and mobility constraints. To efficiently address this issue, this paper proposes a powerful iterative algorithm utilizing the S-procedure and the successive convex approximation (SCA) method. Extensive simulations validate the effectiveness of the proposed strategy.
引用
收藏
页数:20
相关论文
共 32 条
  • [1] Boyd S., 2004, Convex Optimization, DOI 10.1017/CBO9780511804441
  • [2] Joint Trajectory and Resource Allocation Design for Energy-Efficient Secure UAV Communication Systems
    Cai, Yuanxin
    Wei, Zhiqiang
    Li, Ruide
    Ng, Derrick Wing Kwan
    Yuan, Jinhong
    [J]. IEEE TRANSACTIONS ON COMMUNICATIONS, 2020, 68 (07) : 4536 - 4553
  • [3] Chen XM, 2018, CHINA COMMUN, V15, P89
  • [4] Robust Trajectory and Transmit Power Design for Secure UAV Communications
    Cui, Miao
    Zhang, Guangchi
    Wu, Qingqing
    Ng, Derrick Wing Kwan
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2018, 67 (09) : 9042 - 9046
  • [5] Optimal Node Placement and Resource Allocation for UAV Relaying Network
    Fan, Rongfei
    Cui, Jiannan
    Jin, Song
    Yang, Kai
    An, Jianping
    [J]. IEEE COMMUNICATIONS LETTERS, 2018, 22 (04) : 808 - 811
  • [6] Fu X., 2016, P 2016 IEEE INT C SI
  • [7] Robust Trajectory and Power Control for Cognitive UAV Secrecy Communication
    Gao, Ying
    Tang, Hongying
    Li, Baoqing
    Yuan, Xiaobing
    [J]. IEEE ACCESS, 2020, 8 (08): : 49338 - 49352
  • [8] Gong J., 2018, P 2018 11 INT S COMM
  • [9] Survey of Important Issues in UAV Communication Networks
    Gupta, Lav
    Jain, Raj
    Vaszkun, Gabor
    [J]. IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2016, 18 (02): : 1123 - 1152
  • [10] Deployment of Heterogeneous UAV Base Stations for Optimal Quality of Coverage
    Huang, Hailong
    Savkin, Andrey, V
    [J]. IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (17) : 16429 - 16437