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智能反射面辅助的无人机无线携能通信网络吞吐量最大化算法研究

刘志新 赵松晗 杨毅 袁亚洲

刘志新, 赵松晗, 杨毅, 袁亚洲. 智能反射面辅助的无人机无线携能通信网络吞吐量最大化算法研究[J]. 电子与信息学报, 2022, 44(7): 2325-2331. doi: 10.11999/JEIT220195
引用本文: 刘志新, 赵松晗, 杨毅, 袁亚洲. 智能反射面辅助的无人机无线携能通信网络吞吐量最大化算法研究[J]. 电子与信息学报, 2022, 44(7): 2325-2331. doi: 10.11999/JEIT220195
LIU Zhixin, ZHAO Songhan, YANG Yi, YUAN Yazhou. Throughput Maximization Algorithm for Intelligent Reflecting Surface-aided Unmanned Aerial Vehicle Communication Networks with Wireless Energy Transfer[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2325-2331. doi: 10.11999/JEIT220195
Citation: LIU Zhixin, ZHAO Songhan, YANG Yi, YUAN Yazhou. Throughput Maximization Algorithm for Intelligent Reflecting Surface-aided Unmanned Aerial Vehicle Communication Networks with Wireless Energy Transfer[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2325-2331. doi: 10.11999/JEIT220195

智能反射面辅助的无人机无线携能通信网络吞吐量最大化算法研究

doi: 10.11999/JEIT220195
基金项目: 国家自然科学基金(61873223)
详细信息
    作者简介:

    刘志新:男,1976年生,教授,研究方向为无线通信网络资源优化分配与协同控制

    赵松晗:男,1996年生,博士生,研究方向为智能反射面通信系统

    杨毅:女,1983年生,助理研究员,研究方向为无线资源优化管理

    袁亚洲:男,1985年生,副教授,研究方向为物联网技术与应用

    通讯作者:

    刘志新 lzxauto@ysu.edu.cn

  • 中图分类号: TN92

Throughput Maximization Algorithm for Intelligent Reflecting Surface-aided Unmanned Aerial Vehicle Communication Networks with Wireless Energy Transfer

Funds: The National Natural Science Foundation of China (61873223)
  • 摘要: 为了解决城市场景中无人机(UAV)与地面终端设备(GUs)间易受到障碍物阻挡的问题,该文提出一种基于智能反射面(IRS)辅助的UAV供能通信网络吞吐量最大化算法。首先,在满足能量因果、IRS相移、UAV移动性等约束条件下,建立了一个联合IRS相移设计、GU无线资源分配、UAV飞行轨迹设计的多变量耦合优化模型。其次,通过快坐标下降法(BCD)将原非凸问题转换为3个易于处理的子问题,并通过三角不等式、引入松弛变量、连续凸近似(SCA)等方法,对子问题进行转化求解。仿真结果表明,该文所提算法具有较好的收敛性,同时可有效提高系统总吞吐量。
  • 图  1  IRS辅助的UAV供能通信网络

    图  2  时隙分配

    图  3  不同参数下UAV轨迹

    图  4  算法收敛性验证

    图  5  SCA逼近程度验证图

    图  6  总吞吐量与IRS元件数量的关系

    表  1  基于BCD的资源分配算法

     初始化系统参数:$ {{\boldsymbol{\varTheta }}^{(0)}} $, $ {{\boldsymbol{P}}^{(0)}} $, $ {\boldsymbol{t}}_{\text{E}}^{(0)} $, $ {\boldsymbol{t}}_m^{(0)} $, $ {{\boldsymbol{q}}^{(0)}} $, $ {\psi ^{(0)}} $;设置最大迭代次数$ {L_{{\text{max}}}} $;设置收敛精度$ \varepsilon \gt 0 $;迭代次数$ l = 0 $;
     (1) Repeat
     (2) 设置迭代次数$ l = l + 1 $;
     (3) 根据给定的$ {{\boldsymbol{P}}^{(l - 1)}} $, $ {\boldsymbol{t}}_{\text{E}}^{(l - 1)} $, $ {\boldsymbol{t}}_m^{(l - 1)} $, $ {{\boldsymbol{q}}^{(l - 1)}} $,通过式(11)更新$ {{\boldsymbol{\varTheta }}^{(l)}} $;
     (4) 根据给定的$ {{\boldsymbol{\varTheta }}^{(l)}} $和$ {{\boldsymbol{q}}^{(l - 1)}} $,通过求解问题式(13)得到$ {{\boldsymbol{P}}^{(l)}} $, $ {\boldsymbol{t}}_{\text{E}}^{(l)} $和$ {\boldsymbol{t}}_m^{(l)} $;
     (5) 根据给定的$ {{\boldsymbol{P}}^{(l)}} $, $ {\boldsymbol{t}}_{\text{E}}^{(l)} $, $ {\boldsymbol{t}}_m^{(l)} $和$ {{\boldsymbol{\varTheta }}^{(l)}} $,通过求解问题式(20)得到$ {{\boldsymbol{q}}^{(l)}} $;
     (6) Until $ |{\psi ^{(l)}} - {\psi ^{(l - 1)}}| \le \varepsilon $或者$ l \ge {L_{{\text{max}}}} $;
     (7) 结束并输出结果。
    下载: 导出CSV
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    XU Yongjun, GAO Zhengnian, WANG Qianzhu, et al. Robust energy efficiency maximization algorithm for intelligent reflecting surface-aided wireless powered-communication networks[J]. Journal of Electronics & Information Technology, To be published.
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出版历程
  • 收稿日期:  2022-02-28
  • 修回日期:  2022-04-05
  • 网络出版日期:  2022-04-15
  • 刊出日期:  2022-07-25

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