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智能反射面辅助的多天线通信系统鲁棒安全资源分配算法

徐勇军 符加劲 黄琼 黄东

徐勇军, 符加劲, 黄琼, 黄东. 智能反射面辅助的多天线通信系统鲁棒安全资源分配算法[J]. 电子与信息学报, 2024, 46(1): 165-174. doi: 10.11999/JEIT221554
引用本文: 徐勇军, 符加劲, 黄琼, 黄东. 智能反射面辅助的多天线通信系统鲁棒安全资源分配算法[J]. 电子与信息学报, 2024, 46(1): 165-174. doi: 10.11999/JEIT221554
XU Yongjun, FU Jiajin, HUANG Qiong, HUANG Dong. Robust Secure Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Multi-antenna Communication Systems[J]. Journal of Electronics & Information Technology, 2024, 46(1): 165-174. doi: 10.11999/JEIT221554
Citation: XU Yongjun, FU Jiajin, HUANG Qiong, HUANG Dong. Robust Secure Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Multi-antenna Communication Systems[J]. Journal of Electronics & Information Technology, 2024, 46(1): 165-174. doi: 10.11999/JEIT221554

智能反射面辅助的多天线通信系统鲁棒安全资源分配算法

doi: 10.11999/JEIT221554
基金项目: 国家自然科学基金(62271094),重庆市教委科学技术研究项目(KJZD-K202200601),重庆市博士后研究项目特别资助(2021XM3082)
详细信息
    作者简介:

    徐勇军:男,副教授,博士生导师,研究方向智能反射面、鲁棒安全资源分配

    符加劲:男,硕士生,研究方向为智能反射面、鲁棒安全资源分配

    黄琼:女,教授,硕士生导师,研究方向智能反射面、鲁棒安全资源分配

    黄东:男,正高级工程师,博士生导师,研究方向为智能反射面、鲁棒安全资源分配、5G/6G等

    通讯作者:

    黄东 huangd@gzu.edu.cn

  • 中图分类号: TN929.5

Robust Secure Resource Allocation Algorithm for Intelligent Reflecting Surface-assisted Multi-antenna Communication Systems

Funds: The National Natural Science Foundation of China (62271094), The Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJZD-K202200601), Special support for Chongqing Postdoctoral Research Project (2021XM3082)
  • 摘要: 为了解决蜂窝通信系统中因窃听者、障碍物阻挡和信道不确定性导致安全性低和传输质量差的问题,该文提出一种智能反射面(IRS)辅助的多天线通信系统鲁棒安全资源分配算法。首先,考虑合法用户的安全速率约束、最大发射功率约束和IRS相移约束,基于有界信道不确定性,建立了一个联合优化基站主动波束、IRS被动波束的鲁棒资源分配问题。然后,利用S-程序、连续凸近似、交替优化和罚函数等方法对含参数摄动的原非凸问题进行转换,得到可直接求解的确定性凸优化问题。最后,提出一种基于迭代的鲁棒能效最大化算法。仿真结果表明,该文算法具有较好的能效和较强的鲁棒性。
  • 图  1  系统模型

    图  2  仿真场景

    图  3  系统能效收敛图

    图  4  系统能效与${P^{\max }}$的关系

    图  5  不同算法与$R_k^{\min }$的关系

    图  6  保密中断概率与不同算法的关系

    图  7  不同算法与信道误差上界的关系

    图  8  系统能效与用户直接信道误差上界的关系

    算法1 基于迭代的鲁棒能效最大化算法
     初始化系统参数:$ N,L,M,K,\mu ,{P^{\text{c}}},{P^{\max }},R_k^{\min },{{\boldsymbol{\bar H}}_k},{{\boldsymbol{\bar h}}_k},{{\boldsymbol{\bar G}}_m},{{\boldsymbol{\bar g}}_m},\xi _k^{\text{h}},\xi _k^{\text{H}},\xi _m^{\text{g}},\xi _m^{\text{G}},{\tau ^{(0)}},{\kern 1pt} {\rho ^{(0)}},r_k^{(0)},\beta _k^{(0),{\text{U}}},\phi _k^{(0)},\beta _{k,m}^{(0),{\text{E}}},{{\boldsymbol{w}}^{(0)}},{\kern 1pt} {{\boldsymbol{v}}^{(0)}},{\kern 1pt} {\lambda _{\max }} $,
     能效${\varepsilon ^{(0)}}$;设置收敛精度$ \psi \ge 0 $,$ \vartheta \ge 1 $,最大迭代次数${T_{\max }}$,初始化$t \ge 1$,迭代停止条件${\vartheta _1},{\vartheta _2}$;
     (1) 重复
     (2) 通过给的$\{ {{\boldsymbol{v}}^{(t - 1)}},{\tau ^{(t - 1)}},{\rho ^{(t - 1)}},r_k^{(t - 1)},\beta _k^{(t - 1),{\text{U}}},\phi _k^{(t - 1)},\beta _{k,m}^{(t - 1),{\text{E}}}\} $,求解问题式(20)获得$\{ {{\boldsymbol{w}}^{(t)}},{\tau ^{(t)}},{\rho ^{(t)}},r_k^{(t)},\beta _k^{(t),{\text{U}}},\phi _k^{(t)},\beta _{k,m}^{(t),{\text{E}}}\} $;
     (3) 重复
     (4) 通过$\{ {{\boldsymbol{w}}^{(t)}},{\tau ^{(t)}},{\rho ^{(t)}},r_k^{(t)},\beta _k^{(t),{\text{U}}},\phi _k^{(t)},\beta _{k,m}^{(t),{\text{E}}}\} $,求解问题式(22)获得$\{ {{\boldsymbol{v}}^{(t + 1)}},{\tau ^{(t + 1)}},{\rho ^{(t + 1)}},r_k^{(t + 1)},\beta _k^{(t + 1),{\text{U}}},\phi _k^{(t + 1)},\beta _{k,m}^{(t + 1),{\text{E}}}\} $;
     (5) 更新${\lambda ^{(t)}} = \min \{ \vartheta {\lambda ^{(t - 1)}},{\lambda _{\max }}\} $, ${\tau ^{(t)}} = {\tau ^{(t + 1)}}$, ${\rho ^{(t)}} = {\rho ^{(t + 1)}}$, $r_k^{(t)} = r_k^{(t + 1)}$, $\beta _k^{(t),{\text{U}}} = \beta _k^{(t + 1),{\text{U}}}$;
     (6) 直到$\phi _k^{(t)} = \phi _k^{(t + 1)}$, $\beta _{k,m}^{(t),{\text{E}}} = \beta _{k,m}^{(t + 1),{\text{E}}}$
     (7) 更新$ ||{\boldsymbol{z}}|{|_1} \le {\vartheta _1} $和$||{{\boldsymbol{v}}^{(t)}} - {{\boldsymbol{v}}^{(t - 1)}}|{|_1} \le {\vartheta _2}$;
     (8) 更新${\varepsilon ^{(t + 1)}} = {\varepsilon ^{(t)}}$, $t = t + 1$;
     (9) 直到$\left| {{\varepsilon ^{(t)}} - {\varepsilon ^{(t - 1)}}} \right| \ge \psi $或$t \le {T_{\max }}$
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-12-16
  • 修回日期:  2023-01-15
  • 网络出版日期:  2023-02-04
  • 刊出日期:  2024-01-17

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