Advanced Search
Volume 46 Issue 5
May  2024
Turn off MathJax
Article Contents
YAN Zhi, LU Yuanyuan, DING Cong, HE Daiyu, OUYANG Bo, YANG Liang, WANG Yaonan. Power Allocation and Trajectory Design for Unmanned Aerial Vehicle Relay Network with Mobile Users[J]. Journal of Electronics & Information Technology, 2024, 46(5): 1896-1907. doi: 10.11999/JEIT231337
Citation: YAN Zhi, LU Yuanyuan, DING Cong, HE Daiyu, OUYANG Bo, YANG Liang, WANG Yaonan. Power Allocation and Trajectory Design for Unmanned Aerial Vehicle Relay Network with Mobile Users[J]. Journal of Electronics & Information Technology, 2024, 46(5): 1896-1907. doi: 10.11999/JEIT231337

Power Allocation and Trajectory Design for Unmanned Aerial Vehicle Relay Network with Mobile Users

doi: 10.11999/JEIT231337
Funds:  The National Key Research and Development Program of China (2021YFC1910402), Hunan Provincial Natural Science Foundation General Project (2024JJ5090)
  • Received Date: 2023-12-04
  • Rev Recd Date: 2024-05-09
  • Available Online: 2024-05-18
  • Publish Date: 2024-05-10
  • In Unmanned Aerial Vehicle (UAV) relay networks, communication resource allocation and motion planning of UAV are the key problems that should be solved. In order to improve the communication efficiency of UAV relay communication system, a joint planning method of UAV relay power allocation and trajectory design is proposed based on proximal policy optimization algorithm. The joint planning problem of UAV relay power allocation and trajectory design in the user movement scenario is modelled as a Markov decision-making process. Considering the inaccurate acquisition of user location information, the reward function is set with the maximum throughput of the relay communication system as the optimization goal under the premise of satisfying the user interruption probability constraint. Then, a deep reinforcement learning algorithm with high convergence speed—the Proximal Policy Optimization (PPO) algorithm, is used to solve the problem and realized the flight trajectory optimization of relay UAV and the reasonable and effective allocation of relay transmission power. The simulation experimental results show that for the scenario of UAV relay communication with random users movement, the proposed method improves system throughput by 22% and 15%, respectively, compared to the methods based on random strategy and traditional Deep Deterministic Policy Gradient (DDPG). The results show that the proposed method can effectively improve the communication efficiency of the system.
  • loading
  • [1]
    胡钰林, 文玄, 原晓鹏, 等. 面向无线能量传输的三维无人机轨迹设计[J]. 电子与信息学报, 2022, 44(3): 852–859. doi: 10.11999/JEIT211280.

    HU Yulin, WEN Xuan, YUAN Xiaopeng, et al. 3D unmanned aerial vehicle trajectory design for wireless power transfer[J]. Journal of Electronics & Information Technology, 2022, 44(3): 852–859. doi: 10.11999/JEIT211280.
    [2]
    张天魁, 陈超, 王子端, 等. 无人机辅助蜂窝网络中的无人机与用户协同缓存算法[J]. 通信学报, 2020, 41(9): 130–138. doi: 10.11959/j.issn.1000-436x.2020029.

    ZHANG Tiankui, CHEN Chao, WANG Ziduan, et al. Cooperative caching algorithm of UAV and user in UAV-assisted cellular network[J]. Journal on Communications, 2020, 41(9): 130–138. doi: 10.11959/j.issn.1000-436x.2020029.
    [3]
    GHANAVI R, KALANTARI E, SABBAGHIAN M, et al. Efficient 3D aerial base station placement considering users mobility by reinforcement learning[C]. 2018 IEEE Wireless Communications and Networking Conference (WCNC), Barcelona, Spain, 2018: 1–6. doi: 10.1109/WCNC.2018.8377340.
    [4]
    ZHANG Shuo, SHI Shuo, GU Shushi, et al. Power control and trajectory planning based interference management for UAV-assisted wireless sensor networks[J]. IEEE Access, 2020, 8: 3453–3464. doi: 10.1109/ACCESS.2019.2962547.
    [5]
    ZHONG Xijian, GUO Yan, LI Ning, et al. Joint optimization of relay deployment, channel allocation, and relay assignment for UAVs-aided D2D networks[J]. IEEE/ACM Transactions on Networking, 2020, 28(2): 804–817. doi: 10.1109/TNET.2020.2970744.
    [6]
    LI Lei, CHANG T H, and CAI Shu. UAV positioning and power control for two-way wireless relaying[J]. IEEE Transactions on Wireless Communications, 2020, 19(2): 1008–1024. doi: 10.1109/TWC.2019.2950301.
    [7]
    LIANG Fengzhu, ZHANG Jun, LI Bin, et al. The optimal placement for caching UAV-assisted mobile relay communication[C]. 2019 IEEE 19th International Conference on Communication Technology (ICCT), Xi’an, China, 2019: 540–544. doi: 10.1109/ICCT46805.2019.8947051.
    [8]
    CHEN Yunfei, ZHAO Nan, DING Zhiguo, et al. Multiple UAVs as relays: Multi-hop single link versus multiple dual-hop links[J]. IEEE Transactions on Wireless Communications, 2018, 17(9): 6348–6359. doi: 10.1109/TWC.2018.2859394.
    [9]
    WEI Wei, CHEN Shukang, YAN Jun, et al. Optimal relay placement for UAV-assisted wireless regenerative communication system[C]. 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), Guilin, China, 2017: 2850–2854. doi: 10.1109/FSKD.2017.8393232.
    [10]
    PAN Cunhua, REN Hong, DENG Yansha, et al. Joint blocklength and location optimization for URLLC-enabled UAV relay systems[J]. IEEE Communications Letters, 2019, 23(3): 498–501. doi: 10.1109/LCOMM.2019.2894696.
    [11]
    REN Hong, PAN Cunhua, WANG Kezhi, et al. Joint transmit power and placement optimization for URLLC-enabled UAV relay systems[J]. IEEE Transactions on Vehicular Technology, 2020, 69(7): 8003–8007. doi: 10.1109/TVT.2020.2992736.
    [12]
    ZENG Yong, ZHANG Rui, and LIM T J. Throughput maximization for UAV-enabled mobile relaying systems[J]. IEEE Transactions on Communications, 2016, 64(12): 4983–4996. doi: 10.1109/TCOMM.2016.2611512.
    [13]
    WANG Haichao, WANG Jinlong, DING Guoru, et al. Spectrum sharing planning for full-duplex UAV relaying systems with Underlaid D2D communications[J]. IEEE Journal on Selected Areas in Communications, 2018, 36(9): 1986–1999. doi: 10.1109/JSAC.2018.2864375.
    [14]
    WANG Lei, HU Bo, CHEN Shanzhi, et al. UAV-enabled reliable mobile relaying based on downlink NOMA[J]. IEEE Access, 2020, 8: 25237–25248. doi: 10.1109/ACCESS.2020.2970206.
    [15]
    ZENG Yong and ZHANG Rui. Energy-efficient UAV communication with trajectory optimization[J]. IEEE Transactions on Wireless Communications, 2017, 16(6): 3747–3760. doi: 10.1109/TWC.2017.2688328.
    [16]
    XIAO Lin, XU Yu, YANG Dingcheng, et al. Secrecy energy efficiency maximization for UAV-enabled mobile relaying[J]. IEEE Transactions on Green Communications and Networking, 2020, 4(1): 180–193. doi: 10.1109/TGCN.2019.2949802.
    [17]
    GU Jiangchun, DING Guoru, XU Yitao, et al. Proactive optimization of transmission power and 3D trajectory in UAV-assisted relay systems with mobile ground users[J]. Chinese Journal of Aeronautics, 2021, 34(3): 129–144. doi: 10.1016/j.cja.2020.09.028.
    [18]
    ZENG Shuhao, ZHANG Hongliang, DI Boya, et al. Trajectory optimization and resource allocation for OFDMA UAV relay networks[J]. IEEE Transactions on Wireless Communications, 2021, 20(10): 6634–6647. doi: 10.1109/TWC.2021.3075594.
    [19]
    SUN Zhongxiang, YANG Dingcheng, XIAO Lin, et al. Joint energy and trajectory optimization for UAV-enabled relaying network with multi-pair users[J]. IEEE Transactions on Cognitive Communications and Networking, 2021, 7(3): 939–954. doi: 10.1109/TCCN.2020.3048392.
    [20]
    XU Yongjun, LIU Zijian, HUANG Chongwen, et al. Robust resource allocation algorithm for energy-harvesting-based D2D communication underlaying UAV-assisted networks[J]. IEEE Internet of Things Journal, 2021, 8(23): 17161–17171. doi: 10.1109/JIOT.2021.3078264.
    [21]
    XU Yongjun, GUI Guan, GACANIN H, et al. A survey on resource allocation for 5G heterogeneous networks: Current research, future trends, and challenges[J]. IEEE Communications Surveys & Tutorials, 2021, 23(2): 668–695. doi: 10.1109/COMST.2021.3059896.
    [22]
    李国权, 林金朝, 徐勇军, 等. 无人机辅助的NOMA网络用户分组与功率分配算法[J]. 通信学报, 2020, 41(9): 21–28. doi: 10.11959/j.issn.1000-436x.2020194.

    LI Guoquan, LIN Jinzhao, XU Yongjun, et al. User grouping and power allocation algorithm for UAV-aided NOMA network[J]. Journal on Communications, 2020, 41(9): 21–28. doi: 10.11959/j.issn.1000-436x.2020194.
    [23]
    WU Qingqing, ZENG Yong, and ZHANG Rui. Joint trajectory and communication design for multi-UAV enabled wireless networks[J]. IEEE Transactions on Wireless Communications, 2018, 17(3): 2109–2121. doi: 10.1109/TWC.2017.2789293.
    [24]
    ZHANG Guangchi, OU Xiaoqi, CUI Miao, et al. Cooperative UAV enabled relaying systems: Joint trajectory and transmit power optimization[J]. IEEE Transactions on Green Communications and Networking, 2022, 6(1): 543–557. doi: 10.1109/TGCN.2021.3108147.
    [25]
    WANG Zhen, ZHOU Fuhui, WANG Yuhao, et al. Joint 3D trajectory and resource optimization for a UAV relay-assisted cognitive radio network[J]. China Communications, 2021, 18(6): 184–200. doi: 10.23919/JCC.2021.06.015.
    [26]
    WANG Liang, WANG Kezhi, PAN Cunhua, et al. Deep Q-network based dynamic trajectory design for UAV-aided emergency communications[J]. Journal of Communications and Information Networks, 2020, 5(4): 393–402. doi: 10.23919/JCIN.2020.9306013.
    [27]
    CHANG Zheng, DENG Hengwei, YOU Li, et al. Trajectory design and resource allocation for multi-UAV networks: Deep reinforcement learning approaches[J]. IEEE Transactions on Network Science and Engineering, 2023, 10(5): 2940–2951. doi: 10.1109/TNSE.2022.3171600.
    [28]
    ZHAO Nan, CHENG Yiqiang, PEI Yiyang, et al. Deep reinforcement learning for trajectory design and power allocation in UAV networks[C]. ICC 2020 - 2020 IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020: 1–6. doi: 10.1109/ICC40277.2020.9149196.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(9)  / Tables(3)

    Article Metrics

    Article views (140) PDF downloads(38) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return