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基于智能反射面辅助的无线供电通信网络鲁棒能效最大化算法

徐勇军 高正念 王茜竹 周继华 黄东

徐勇军, 高正念, 王茜竹, 周继华, 黄东. 基于智能反射面辅助的无线供电通信网络鲁棒能效最大化算法[J]. 电子与信息学报, 2022, 44(7): 2317-2324. doi: 10.11999/JEIT210714
引用本文: 徐勇军, 高正念, 王茜竹, 周继华, 黄东. 基于智能反射面辅助的无线供电通信网络鲁棒能效最大化算法[J]. 电子与信息学报, 2022, 44(7): 2317-2324. doi: 10.11999/JEIT210714
XU Yongjun, GAO Zhengnian, WANG Qianzhu, ZHOU Jihua, HUANG Dong. Robust Energy Efficiency Maximization Algorithm for Intelligent Reflecting Surface-aided Wireless Powered-communication Networks[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2317-2324. doi: 10.11999/JEIT210714
Citation: XU Yongjun, GAO Zhengnian, WANG Qianzhu, ZHOU Jihua, HUANG Dong. Robust Energy Efficiency Maximization Algorithm for Intelligent Reflecting Surface-aided Wireless Powered-communication Networks[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2317-2324. doi: 10.11999/JEIT210714

基于智能反射面辅助的无线供电通信网络鲁棒能效最大化算法

doi: 10.11999/JEIT210714
基金项目: 国家自然科学基金(61601071, 62071078),国家重点研发计划(2019YFC1511300),重庆市自然科学基金(cstc2019jcyj-xfkxX0002),重庆市研究生科研创新项目(CYS21292,C YS21294)
详细信息
    作者简介:

    徐勇军:男,1986年生,副教授,硕士生导师,研究方向为异构无线网络、智能反射面、鲁棒资源分配等

    高正念:女,1994年生,硕士生,研究方向为智能反射面、资源分配

    王茜竹:女,1975年生,正高级工程师,硕士生导师,研究方向为智能反射面、资源分配

    周继华:男,1979年生,研究员,博士生导师,研究方向为移动网络、无线通信、5G/6G等

    黄东:男,1981年生,教授,博士生导师,研究方向为智慧网络、移动通信系统等

    通讯作者:

    周继华 jhzhou@ict.ac.cn

  • 中图分类号: TN929.5

Robust Energy Efficiency Maximization Algorithm for Intelligent Reflecting Surface-aided Wireless Powered-communication Networks

Funds: The National Natural Science Foundation of China (61601071, 62071078), The National Key Research and Development Program of China (2019YFC1511300), The Natural Science Foundation of Chongqing (cstc2019jcyj-xfkxX0002), The Graduate Scientific Research Innovation Project of Chongqing (CYS21292, CYS21294)
  • 摘要: 为了解决能量收集效率易受到障碍物阻挡和信道不确定性影响的问题,该文提出一种基于智能反射面(IRS)辅助的无线供电通信网络鲁棒能效(EE)最大化算法。首先,考虑最小收集能量、IRS相移、最小吞吐量等约束,基于有界信道不确定性,建立一个联合优化能量波束、相移、传输时间的多变量耦合非线性资源分配模型。然后,利用最坏准则、变量替换和S-Procedure等方法,将原非凸问题转换为确定性凸优化问题,同时,提出一种基于迭代的鲁棒能效最大化算法进行求解。仿真结果表明,与现有算法比较,该文算法具有较好的能效和鲁棒性。
  • 图  1  IRS辅助多用户WPCN

    图  2  系统能效收敛图

    图  3  系统能效与能量站最大发射功率在不同用户数下的关系

    图  4  系统能效与能量站最大发射功率在不同算法下的关系

    图  5  系统能效与吞吐量门限在不同算法下的关系

    图  6  系统能效与信道不确定性在不同算法下的关系

    图  7  中断概率与信道不确定性在不同算法下的关系

    表  1  基于迭代的鲁棒能效最大化算法

     初始化系统参数:$ M $, $ N $, $ K $, $ T $, $ P_{\text{B}}^{\text{C}} $, $ P_{\text{e}}^{\text{C}} $, $ p_k^{\text{C}} $, $ P_{\text{D}}^{\text{C}} $, $ {\bar {\boldsymbol{G}}_k} $, $ {\bar g_k} $, $ {\omega _k} $, $ {\sigma _k} $, $ R_k^{\min } $, $ \eta $, $ {P^{\max }} $, $ {q^{(0)}} $, $ {{\boldsymbol{v}}^{(0)}} $;设置收敛精度$ \varepsilon \ge 0 $,最大迭代次数$ {L_{\max }} $,
     初始化$ l \ge 0 $;
     (1) While $ \left| {{q^{(l)}} - {q^{(l - 1)}}} \right| \ge \varepsilon $或$l \le {L_{\max } }$ do
     (2) 设置迭代次数$ l = l + 1 $;
     (3) 固定$ {{\boldsymbol{v}}^{(l - 1)}} $,根据式(18)计算$ \left\{ {{{\boldsymbol{W}}^{(l)}},t_0^{(l)},t_k^{(l)},p_k^{(l)}} \right\} $;
     (4) 固定$ \left\{ {{{\boldsymbol{W}}^{(l)}},t_0^{(l)},t_k^{(l)},p_k^{(l)}} \right\} $,根据式(20)计算$ {{\boldsymbol{V}}^{(l)}} $;
     (5) 特征值分解$ {{\boldsymbol{V}}^{(l)}} = {\boldsymbol{U}}{\boldsymbol{\varLambda}} {\boldsymbol{U}} $, $ {{\boldsymbol{v}}^{(l)}} = {\boldsymbol{U}}{{\boldsymbol{\varLambda}} ^{(1/2)}}{\boldsymbol{r}} $;
     (6) 更新能效$ {q^{(l)}} = \frac{{\displaystyle\sum\limits_{k = 1}^K {{t_k}{{\log }_2}} \left( {1 + \frac{{{p_k}{{\tilde g}_k}}}{{{\delta ^2}}}} \right)}}{{{t_0}(P_{\text{B}}^{\text{C}} + NP_{\text{e}}^{\text{C}}) + \displaystyle\sum\limits_{k = 1}^K {({t_0} + {t_k})} p_k^{\text{C}} + {t_0}{\text{Tr(}}{\boldsymbol{W}}{\text{)}} - \displaystyle\sum\limits_{k = 1}^K {{\chi _k}} + \displaystyle\sum\limits_{k = 1}^K {{t_k}{p_k}} + \displaystyle\sum\limits_{k = 1}^K {{t_k}P_{\text{D}}^{\text{C}}} }} $;
     (7) End While
    下载: 导出CSV
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    XU Yongjun, LIU Zijian, LI Guoquan, et al. Robust energy efficiency optimization algorithm for NOMA-based D2D communication with simultaneous wireless information and power transfer[J]. Journal of Electronics &Information Technology, 2021, 43(5): 1289–1297. doi: 10.11999/JEIT200175
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出版历程
  • 收稿日期:  2021-07-15
  • 修回日期:  2021-09-11
  • 网络出版日期:  2021-09-26
  • 刊出日期:  2022-07-25

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