高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

支持无线采能及簇间负载均衡的无人机辅助数据调度及轨迹优化算法

柴蓉 李沛欣 梁承超 陈前斌

柴蓉, 李沛欣, 梁承超, 陈前斌. 支持无线采能及簇间负载均衡的无人机辅助数据调度及轨迹优化算法[J]. 电子与信息学报, 2024, 46(10): 4009-4016. doi: 10.11999/JEIT240048
引用本文: 柴蓉, 李沛欣, 梁承超, 陈前斌. 支持无线采能及簇间负载均衡的无人机辅助数据调度及轨迹优化算法[J]. 电子与信息学报, 2024, 46(10): 4009-4016. doi: 10.11999/JEIT240048
CHAI Rong, LI Peixin, LIANG Chengchao, CHEN Qianbin. Wireless Energy Harvest and Inter-Cluster Load Balancing-Enabled UAV-Assisted Data Scheduling and Trajectory Optimization Algorithms[J]. Journal of Electronics & Information Technology, 2024, 46(10): 4009-4016. doi: 10.11999/JEIT240048
Citation: CHAI Rong, LI Peixin, LIANG Chengchao, CHEN Qianbin. Wireless Energy Harvest and Inter-Cluster Load Balancing-Enabled UAV-Assisted Data Scheduling and Trajectory Optimization Algorithms[J]. Journal of Electronics & Information Technology, 2024, 46(10): 4009-4016. doi: 10.11999/JEIT240048

支持无线采能及簇间负载均衡的无人机辅助数据调度及轨迹优化算法

doi: 10.11999/JEIT240048
基金项目: 国家自然科学基金(62271097)
详细信息
    作者简介:

    柴蓉:女,教授,研究方向为空天地一体化网络架构及关键技术、无线资源管理及移动性管理技术等

    李沛欣:女,硕士生,研究方向为无线通信、无线资源管理等

    梁承超:男,教授,研究方向为卫星通信系统架构及关键技术、无线资源管理等

    陈前斌:男,教授,研究方向为无线通信关键技术、无线资源管理等

    通讯作者:

    梁承超 liangcc@cqupt.edu.cn

  • 中图分类号: TN926.2

Wireless Energy Harvest and Inter-Cluster Load Balancing-Enabled UAV-Assisted Data Scheduling and Trajectory Optimization Algorithms

Funds: The National Natural Science Foundation of China(62271097)
  • 摘要: 该文研究了无人机(UAV)辅助无线传感器网络的数据收集问题。首先提出基于均值漂移算法的传感器节点(SN)初始分簇策略,进而以簇间负载均衡为目标,设计SN切换算法。基于所得成簇策略,将UAV数据收集及轨迹规划问题建模为系统能耗最小化问题。由于该问题是一个非凸问题,难以直接求解,将其分为两个子问题,即数据调度子问题及UAV轨迹规划子问题。针对数据调度子问题,提出一种基于多时隙库恩-蒙克雷斯算法的时频资源调度策略。针对UAV轨迹规划子问题,将其建模为马尔可夫决策过程,并提出一种基于深度Q网络的UAV轨迹规划算法。仿真结果验证了所提算法的有效性。
  • 图  1  系统模型图

    图  2  各簇数据量比较图

    图  3  UAV总悬停时隙与节点数量关系图

    图  4  系统能耗与SN发射功率关系图

    图  5  累计奖励与迭代次数关系图

    表  1  仿真参数设置

    仿真参数 数值
    SN数据量$ {\varphi _k} $ [0, 1024] MB
    载波频率Cf [1, 3] GHz
    节点可用带宽B 1 MHz
    SN发射功率pc 0.1 W
    UAV飞行高度H 70 m
    UAV飞行速度v 10 m/s
    UAV平均转子诱导速度v0 4.03 m/s
    空气密度ρ 1.225 km/m3
    转子盘面积Sr 0.503 m2
    下载: 导出CSV
  • [1] 孙利民, 张书钦, 李志, 等. 无线传感器网络: 理论及应用[M]. 北京: 清华大学出版社, 2018: 5–18.

    SUN Limin, ZHANG Shuqin, LI Zhi, et al. Wireless Sensor Networks: Theory and Applications[M]. Beijing: Tsinghua University Press, 2018: 5–18.
    [2] ZENG Yong, ZHANG Rui, and LIM T J. Wireless communications with unmanned aerial vehicles: Opportunities and challenges[J]. IEEE Communications Magazine, 2016, 54(5): 36–42. doi: 10.1109/MCOM.2016.7470933.
    [3] WEI Zhiqing, ZHU Mingyue, ZHANG Ning, et al. UAV-assisted data collection for Internet of things: A survey[J]. IEEE Internet of Things Journal, 2022, 9(17): 15460–15483. doi: 10.1109/JIOT.2022.3176903.
    [4] AHANI G, YUAN Di, and ZHAO Yixin. Age-optimal UAV scheduling for data collection with battery recharging[J]. IEEE Communications Letters, 2021, 25(4): 1254–1258. doi: 10.1109/LCOMM.2020.3047909.
    [5] SAMIR M, ASSI C, SHARAFEDDINE S, et al. Online altitude control and scheduling policy for minimizing AoI in UAV-assisted IoT wireless networks[J]. IEEE Transactions on Mobile Computing, 2022, 21(7): 2493–2505. doi: 10.1109/TMC.2020.3042925.
    [6] LUAN Qiuji, CUI Hongyan, ZHANG Lifeng, et al. A hierarchical hybrid subtask scheduling algorithm in UAV-assisted MEC emergency network[J]. IEEE Internet of Things Journal, 2022, 9(14): 12737–12753. doi: 10.1109/JIOT.2021.3138263.
    [7] ZHU Botao, BEDEER E, NGUYEN H H, et al. UAV trajectory planning for AoI-minimal data collection in UAV-aided IoT networks by transformer[J]. IEEE Transactions on Wireless Communications, 2023, 22(2): 1343–1358. doi: 10.1109/TWC.2022.3204438.
    [8] INDU, SINGH R P, CHOUDHARY H R, et al. Trajectory design for UAV-to-ground communication with energy optimization using genetic algorithm for agriculture application[J]. IEEE Sensors Journal, 2021, 21(16): 17548–17555. doi: 10.1109/JSEN.2020.3046463.
    [9] CHEN Jinchao, DU Chenglie, ZHANG Ying, et al. A clustering-based coverage path planning method for autonomous heterogeneous UAVs[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(12): 25546–25556. doi: 10.1109/TITS.2021.3066240.
    [10] SHEN Kun, SHIVGAN R, MEDINA J, et al. Multidepot drone path planning with collision avoidance[J]. IEEE Internet of Things Journal, 2022, 9(17): 16297–16307. doi: 10.1109/JIOT.2022.3151791.
    [11] MA Ting, ZHOU Haibo, QIAN Bo, et al. UAV-LEO integrated backbone: A ubiquitous data collection approach for B5G internet of remote things networks[J]. IEEE Journal on Selected Areas in Communications, 2021, 39(11): 3491–3505. doi: 10.1109/JSAC.2021.3088626.
    [12] YUAN Xiaopeng, HU Yulin, ZHANG Jian, et al. Joint user scheduling and UAV trajectory design on completion time minimization for UAV-aided data collection[J]. IEEE Transactions on Wireless Communications, 2023, 22(6): 3884–3898. doi: 10.1109/TWC.2022.3222067.
    [13] LIU Wentao, LI Dong, LIANG Tianhao, et al. Joint trajectory and scheduling optimization for age of synchronization minimization in UAV-assisted networks with random updates[J]. IEEE Transactions on Communications, 2023, 71(11): 6633–6646. doi: 10.1109/TCOMM.2023.3297198.
    [14] CHAI Shuqi and LAU V K N. Multi-UAV trajectory and power optimization for cached UAV wireless networks with energy and content recharging-demand driven deep learning approach[J]. IEEE Journal on Selected Areas in Communications, 2021, 39(10): 3208–3224. doi: 10.1109/JSAC.2021.3088694.
    [15] WANG Jun, NA Zhenyu, and LIU Xin. Collaborative design of multi-UAV trajectory and resource scheduling for 6G-enabled Internet of things[J]. IEEE Internet of Things Journal, 2021, 8(20): 15096–15106. doi: 10.1109/JIOT.2020.3031622.
  • 加载中
图(5) / 表(1)
计量
  • 文章访问数:  164
  • HTML全文浏览量:  43
  • PDF下载量:  27
  • 被引次数: 0
出版历程
  • 收稿日期:  2024-01-24
  • 修回日期:  2024-08-27
  • 网络出版日期:  2024-09-01
  • 刊出日期:  2024-10-30

目录

    /

    返回文章
    返回