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智能反射面辅助的多入单出共生无线电鲁棒安全资源分配算法

吴翠先 周春宇 徐勇军 陈前斌

吴翠先, 周春宇, 徐勇军, 陈前斌. 智能反射面辅助的多入单出共生无线电鲁棒安全资源分配算法[J]. 电子与信息学报, 2024, 46(4): 1203-1211. doi: 10.11999/JEIT230426
引用本文: 吴翠先, 周春宇, 徐勇军, 陈前斌. 智能反射面辅助的多入单出共生无线电鲁棒安全资源分配算法[J]. 电子与信息学报, 2024, 46(4): 1203-1211. doi: 10.11999/JEIT230426
WU Cuixian, ZHOU Chunyu, XU Yongjun, CHEN Qianbin. Robust Secure Resource Allocation Algorithm for Multiple Input Single Output Symbiotic Radio with Reconfigurable Intelligent Surface Assistance[J]. Journal of Electronics & Information Technology, 2024, 46(4): 1203-1211. doi: 10.11999/JEIT230426
Citation: WU Cuixian, ZHOU Chunyu, XU Yongjun, CHEN Qianbin. Robust Secure Resource Allocation Algorithm for Multiple Input Single Output Symbiotic Radio with Reconfigurable Intelligent Surface Assistance[J]. Journal of Electronics & Information Technology, 2024, 46(4): 1203-1211. doi: 10.11999/JEIT230426

智能反射面辅助的多入单出共生无线电鲁棒安全资源分配算法

doi: 10.11999/JEIT230426
基金项目: 国家自然科学基金(62271094),重庆市自然科学基金创新发展联合基金(CSTB2022NSCQ-LZX0009),重庆市教委科学技术研究项目(KJZD-K202200601)
详细信息
    作者简介:

    吴翠先:女,正高级工程师,硕士生导师,研究方向为共生无线电、资源分配等

    周春宇:女,硕士生,研究方向为共生无线电、智能反射面

    徐勇军:男,副教授,博士生导师,研究方向为共生无线电、智能反射面、鲁棒资源分配等

    陈前斌:男,教授,博士生导师,研究方向为共生无线电、智能反射面、资源分配等

    通讯作者:

    徐勇军 xuyj@cqupt.edu.cn

  • 11) 通过基站与RIS的协同控制使得共生接收机传输性能满足设计要求,从而实现共生环境下的优化。优化过程与传递首先从基站侧发起,基站将波束信息传输给接收端,接收端根据接收到的信息计算其当下的实际速率,判定是否满足优化问题的约束条件,并将判定结果反馈给基站侧,基站通过反馈的结果来调整波束。与此同时,FPGA控制器也接收到相应的反馈,通过对RIS的相移进行调整来辅助基站,直至参数稳定下来。
  • 22) 本系统可以扩展到多用户系统,且本文侧重于克服CSI不确定性带来的影响并解决窃听用户引起的物理层安全问题,不同于文献[6,7]仅仅将RIS用来协助传输,本文中RIS不仅可以作为中继来反射入射信号,也可以传输其自身的信息给接收机,并且实现能量自供给。
  • 33)对于本系统物联网节点而言,获得CSI的代价并不高,且在实际系统中是可行的。因为CSI的获取可以通过以下两种方式获得:(1)网关通过信道估计获取[17],常见的方法包括最小均方误差估计、最大似然估计、导频辅助估计、能量检测估计;(2)通过信道的有限反馈来获取[18],其间接收端会周期性地评估信道的状态,并将这些信息以有限的比特数的形式发送回发送端,发送端收到反馈信息后,可以根据这些信息进行自适应调整。
  • 中图分类号: TN929.5

Robust Secure Resource Allocation Algorithm for Multiple Input Single Output Symbiotic Radio with Reconfigurable Intelligent Surface Assistance

Funds: The National Natural Science Foundation of China (62271094), The Key Fund of Natural Science Foundation of Chongqing (CSTB2022NSCQ-LZX0009), The Scientific and Technological Research Program of Chongqing Municipal Education Commission (KJZD-K202200601)
  • 摘要: 针对信道不确定性影响、无线信息泄露和障碍物阻挡导致通信质量下降等问题,该文提出一种基于智能反射面(RIS)辅助的多输入单输出(MISO)共生无线电(SR)鲁棒安全资源分配算法。考虑主用户的安全速率约束、次用户的最小速率约束、RIS最小能量收集约束,基于有界信道不确定性,建立了一个联合主被动波束赋形优化的资源分配问题。利用半正定松弛、S-procedure和变量替换法将含参数摄动的非凸问题转化为确定性的凸优化问题,并提出一种基于半正定松弛的鲁棒资源分配算法。仿真结果表明,与现有算法相比,该文算法具有较好的收敛性和鲁棒性。
  • 图  1  系统模型

    图  2  迭代收敛图

    图  3  最小发射功率与信道不确定性$ {\delta _{\boldsymbol{v}}} $的关系

    图  4  最小发射功率与最小保空速率门限值$ R_{\text{p}}^{{\text{min}}} $的关系

    图  5  最小发射功率与信道不确定性$ {\delta _{\boldsymbol{F}}} $的关系

    图  6  最小发射功率与最小保密速率门限值$ R_{\text{p}}^{{\text{min}}} $的关系

    图  7  实际保密速率$ R_{\text{p}} $与信道不确定性$ {\delta _{\boldsymbol{F}}} $的关系

    算法1 基于半正定松弛的鲁棒资源分配算法
     初始化系统参数:$ N,{\text{ }}L,{\text{ }}Q,{\text{ }}R_{\text{s}}^{{\text{min}}},{\text{ }}R_{\text{p}}^{{\text{min}}},{\text{ }}\rho ,{\text{ }}\eta ,{\text{ }}{\sigma ^2},{\text{ }}{\delta _{\boldsymbol{F}}},{\text{ }}{\delta _{\boldsymbol{H}}} $,
     ${\delta _{\boldsymbol{G}}},{\text{ }}{\delta _{\boldsymbol{h}}},{\text{ }}{\delta _{\boldsymbol{v}}},{\text{ }}e,{\text{ }}{{\boldsymbol{\varPsi}} ^{(0)}},{{\boldsymbol{W}}^{(0)}} $;设置收敛精度$ \varepsilon \ge {\text{0}} $,最大迭代
     次数$ {K_{\max }} $,初始化$ k = 0 $;
     (1) While $ {\text{|Tr(}}{{\boldsymbol{W}}^{(k + 1)}}{{) - {\mathrm{Tr}}(}}{{\boldsymbol{W}}^{(k)}}{\text{)|}} \ge \varepsilon $或$ k \le {K_{\max }} $ do
     (2) 给定$ {{\boldsymbol{\varPsi}} ^{(k)}} $,通过求解式(36)获得$ {{\boldsymbol{W}}^{(k + 1)}} $;
     (3) 给定$ {{\boldsymbol{W}}^{(k + 1)}} $,通过求解式(38)获得$ {\tilde{\boldsymbol{ \varPsi }}^{(k + 1)}} $;
     (4) $ {{\boldsymbol{W}}^{(k + 1)}} = {e^{(k + 1)}}{{\boldsymbol{W}}^{(k + 1)}} $, $ {{\boldsymbol{\varPsi}} ^{(k + 1)}} = \frac{{\text{1}}}{{{e^{(k + 1)}}}}{\tilde {\boldsymbol{\varPsi}} ^{(k + 1)}} $;
     (5) 计算$ {\text{Tr(}}{{\boldsymbol{W}}^{(k + 1)}}) $;
     (6) 设置迭代次数$ k = k + 1 $;
     (7) End While
    下载: 导出CSV
  • [1] 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.
    [2] LIANG Yingchang, ZHANG Qianqian, LARSSON E G, et al. Symbiotic radio: Cognitive backscattering communications for future wireless networks[J]. IEEE Transactions on Cognitive Communications and Networking, 2020, 6(4): 1242–1255. doi: 10.1109/TCCN.2020.3023139.
    [3] WU Qingqing and ZHANG Rui. Towards smart and reconfigurable environment: Intelligent reflecting surface aided wireless network[J]. IEEE Communications Magazine, 2020, 58(1): 106–112. doi: 10.1109/MCOM.001.1900107.
    [4] 徐勇军, 徐然, 周继华, 等. 面向窃听用户的RIS-MISO系统鲁棒资源分配算法[J]. 电子与信息学报, 2022, 44(7): 2253–2263. doi: 10.11999/JEIT211537.

    XU Yongjun, XU Ran, ZHOU Jihua, et al. Robust resource allocation algorithm for RIS-assisted MISO systems with eavesdroppers[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2253–2263. doi: 10.11999/JEIT211537.
    [5] ZHANG Qianqian, LIANG Yingchang, and POOR H V. Reconfigurable intelligent surface assisted MIMO symbiotic radio networks[J]. IEEE Transactions on Communications, 2021, 69(7): 4832–4846. doi: 10.1109/TCOMM.2021.3070043.
    [6] CHEN Hao, YANG Gang, and LIANG Yingchang. Joint active and passive beamforming for reconfigurable intelligent surface enhanced symbiotic radio system[J]. IEEE Wireless Communications Letters, 2021, 10(5): 1056–1060. doi: 10.1109/LWC.2021.3056874.
    [7] XU Xinyue, LIANG Yingchang, YANG Gang, et al. Reconfigurable intelligent surface empowered symbiotic radio over broadcasting signals[C]. IEEE Global Communications Conference (GLOBECOM), Taipei, China, 2020: 1–6. doi: 10.1109/GLOBECOM42002.2020.9348236.
    [8] HU Jinlin, LIANG Yingchang, and PEI Yiyang. Reconfigurable intelligent surface enhanced multi-user MISO symbiotic radio system[J]. IEEE Transactions on Communications, 2021, 69(4): 2359–2371. doi: 10.1109/TCOMM.2020.3047444.
    [9] ZHOU Hu, KANG Xin, LIANG Yingchang, et al. Cooperative beamforming for reconfigurable intelligent surface-assisted symbiotic radios[J]. IEEE Transactions on Vehicular Technology, 2022, 71(11): 11677–11692. doi: 10.1109/TVT.2022.3190515.
    [10] HU Jinlin, LIANG Yingchang, PEI Yiyang, et al. Reconfigurable intelligent surface based uplink MU-MIMO symbiotic radio system[J]. IEEE Transactions on Wireless Communications, 2023, 22(1): 423–438. doi: 10.1109/TWC.2022.3194910.
    [11] NGUYEN V D, DUONG T Q, and SHIN O S. Physical layer security for primary system: A symbiotic approach in cooperative cognitive radio networks[C]. IEEE Global Communications Conference (GLOBECOM), San Diego, USA, 2015: 1–6. doi: 10.1109/GLOCOM.2015.7417101.
    [12] YOU Li, XIONG Jiayuan, NG D W K, et al. Energy efficiency and spectral efficiency tradeoff in RIS-aided multiuser MIMO uplink transmission[J]. IEEE Transactions on Signal Processing, 2021, 69: 1407–1421. doi: 10.1109/TSP.2020.3047474.
    [13] ZOU Yuze, LONG Yusi, GONG Shimin, et al. Robust beamforming optimization for self-sustainable intelligent reflecting surface assisted wireless networks[J]. IEEE Transactions on Cognitive Communications and Networking, 2022, 8(2): 856–870. doi: 10.1109/TCCN.2021.3133839.
    [14] NASIR A A, ZHOU Xiangyun, DURRANI S, et al. Relaying protocols for wireless energy harvesting and information processing[J]. IEEE Transactions on Wireless Communications, 2013, 12(7): 3622–3636. doi: 10.1109/TWC.2013.062413.122042.
    [15] LYU Bin, RAMEZANI P, HOANG D T, et al. Optimized energy and information relaying in self-sustainable IRS-empowered WPCN[J]. IEEE Transactions on Communications, 2021, 69(1): 619–633. doi: 10.1109/TCOMM.2020.3028875.
    [16] XU Yongjun, XIE Hao, WU Qingqing, et al. Robust max-min energy efficiency for RIS-aided HetNets with distortion noises[J]. IEEE Transactions on Communications, 2022, 70(2): 1457–1471. doi: 10.1109/TCOMM.2022.3141798.
    [17] MAO Zhendong, PENG Mugen, and LIU Xiqing. Channel estimation for reconfigurable intelligent surface assisted wireless communication systems in mobility scenarios[J]. China Communications, 2021, 18(3): 29–38. doi: 10.23919/JCC.2021.03.003.
    [18] BONSU K A, ZHOU Weiwei, PAN Su, et al. Optimal power allocation with limited feedback of channel state information in multi-user MIMO systems[J]. China Communications, 2020, 17(2): 163–175. doi: 10.23919/JCC.2020.02.014.
    [19] WU Qingqing, ZHOU Xiaobo, and SCHOBER R. IRS-assisted wireless powered NOMA: Do we really need different phase shifts in DL and UL?[J]. IEEE Wireless Communications Letters, 2021, 10(7): 1493–1497. doi: 10.1109/LWC.2021.3072502.
    [20] ZHOU Gui, PAN Cunhua, REN Hong, et al. A framework of robust transmission design for IRS-aided MISO communications with imperfect cascaded channels[J]. IEEE Transactions on Signal Processing, 2020, 68: 5092–5106. doi: 10.1109/TSP.2020.3019666.
    [21] BOYD S and VANDENBERGHE L. Convex Optimization[M]. Cambridge, UK: Cambridge University Press, 2004: 61–102.
    [22] WANG Jun, LIANG Yingchang, HAN Shiying, et al. Robust beamforming and phase shift design for IRS-enhanced multi-user MISO downlink communication[C]. IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020: 1–6. doi: 10.1109/ICC40277.2020.9148947.
    [23] YE Yinghui, SHI Liqin, HU R Q, et al. Energy-efficient resource allocation for wirelessly powered backscatter communications[J]. IEEE Communications Letters, 2019, 23(8): 1418–1422. doi: 10.1109/LCOMM.2019.2920834.
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出版历程
  • 收稿日期:  2023-05-17
  • 修回日期:  2023-11-08
  • 网络出版日期:  2023-11-14
  • 刊出日期:  2024-04-24

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