Energy Efficiency Optimization of IRS-Assisted UAV Networks Based on Statistical Channels

被引:16
|
作者
Zhao, Chen [1 ]
Pang, Xiaowei [1 ]
Lu, Weidang [2 ]
Chen, Yunfei [3 ]
Zhao, Nan [1 ]
Nallanathan, Arumugam [4 ]
机构
[1] Dalian Univ Technol, Sch Informat & Commun Engn, Dalian 116024, Peoples R China
[2] Zhejiang Univ Technol, Coll Informat Engn, Hangzhou 310023, Peoples R China
[3] Univ Durham, Dept Engn, Durham DH1 3LE, England
[4] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London E1 4NS, England
基金
中国国家自然科学基金;
关键词
Energy efficiency; intelligent reflecting surface; statistical channel state information; unmanned aerial vehicle; COMMUNICATION;
D O I
10.1109/LWC.2023.3276910
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this letter, intelligent reflecting surface (IRS) is adopted to assist unmanned aerial vehicle (UAV) to achieve energy-efficient transmission. Specifically, the energy efficiency is maximized by jointly optimizing the UAV trajectory, transmit power and IRS phase shifts based on the statistical channel state information (CSI), since the instantaneous CSI is difficult to obtain due to the mobility of UAV and the passive structure of IRS. The non-convex problem is decomposed into two sub-problems of the trajectory and transmit power optimization, and the phase-shift optimization. To deal with the non-convexity of the first one, the successive convex approximation and Dinkelbach's algorithm are utilized. For the second one, a closed-form solution is derived directly through equivalent transformations. Then, the two sub-problems are solved iteratively to obtain an effective solution to the original problem. Simulation results are presented to validate the effectiveness of the proposed scheme.
引用
收藏
页码:1419 / 1423
页数:5
相关论文
共 50 条
  • [41] Energy Efficiency and Spectral Efficiency Tradeoff in IRS-Assisted Downlink MmWave NOMA Systems
    Xu, Fuyuan
    Zhang, Hailin
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2022, 11 (07) : 1433 - 1437
  • [42] IRS-Assisted Cognitive UAV Networks: Joint Sensing Duration, Passive Beamforming, and 3-D Location Optimization
    Deng, Qian
    Yu, Guangcheng
    Liang, Xiaopeng
    Shu, Feng
    Wang, Jiangzhou
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (02) : 2767 - 2782
  • [43] Spectral efficiency maximization for IRS-assisted wireless communication in cognitive radio networks
    Wang, Jianling
    PHYSICAL COMMUNICATION, 2022, 50
  • [44] Deep reinforcement learning for IRS-assisted UAV covert communications
    Bi, Songjiao
    Hu, Langtao
    Liu, Quanjin
    Wu, Jianlan
    Yang, Rui
    Wu, Lei
    CHINA COMMUNICATIONS, 2023, 20 (12) : 131 - 141
  • [45] Deep Reinforcement Learning for Deception in IRS-assisted UAV Communications
    Olowononi, Felix O.
    Rawat, Danda B.
    Kamhoua, Charles A.
    Sadler, Brian M.
    2022 IEEE MILITARY COMMUNICATIONS CONFERENCE (MILCOM), 2022,
  • [46] Online deep learning based energy efficient optimization for IRS-assisted eMBB and URLLC services
    Liu, Wanxian
    He, Xiuli
    Xu, Hongbo
    Wang, Ze
    Zhou, Aizhi
    PHYSICAL COMMUNICATION, 2023, 61
  • [47] Deep Reinforcement Learning for IRS-Assisted UAV Covert Communications
    Songjiao Bi
    Langtao Hu
    Quanjin Liu
    Jianlan Wu
    Rui Yang
    Lei Wu
    ChinaCommunications, 2023, 20 (12) : 131 - 141
  • [48] Deep Reinforcement Learning for Deception in IRS-assisted UAV Communications
    Olowononi, Felix O.
    Rawat, Danda B.
    Kamhoua, Charles A.
    Sadler, Brian M.
    Proceedings - IEEE Military Communications Conference MILCOM, 2022, 2022-November : 763 - 768
  • [49] Aerial IRS-Assisted Secure SWIPT System With UAV Jitter
    Cheng, Tianhao
    Wang, Buhong
    Cao, Kunrui
    Zheng, Beixiong
    Tian, Jiwei
    Dong, Runze
    Diao, Danyu
    Chen, Jingyu
    IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING, 2024, 8 (04): : 1530 - 1544
  • [50] Energy Efficiency Maximization in Mobile Edge Computing Networks via IRS assisted UAV Communications
    Zhang, Ying
    Niu, Weiming
    Xiu, Supu
    Mu, Guangchen
    CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES, 2024, 138 (02): : 1865 - 1884