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基于IRS辅助的异构网络中超可靠低时延通信波束成形算法设计

罗佳俊 代海波 王保云 李春国

罗佳俊, 代海波, 王保云, 李春国. 基于IRS辅助的异构网络中超可靠低时延通信波束成形算法设计[J]. 电子与信息学报, 2022, 44(7): 2289-2298. doi: 10.11999/JEIT220397
引用本文: 罗佳俊, 代海波, 王保云, 李春国. 基于IRS辅助的异构网络中超可靠低时延通信波束成形算法设计[J]. 电子与信息学报, 2022, 44(7): 2289-2298. doi: 10.11999/JEIT220397
LUO Jiajun, DAI Haibo, WANG Baoyun, LI Chunguo. Design of Beamforming Algorithm for Ultra-reliable and Low-latency Communication in Heterogeneous Networks Based on IRS Assistance[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2289-2298. doi: 10.11999/JEIT220397
Citation: LUO Jiajun, DAI Haibo, WANG Baoyun, LI Chunguo. Design of Beamforming Algorithm for Ultra-reliable and Low-latency Communication in Heterogeneous Networks Based on IRS Assistance[J]. Journal of Electronics & Information Technology, 2022, 44(7): 2289-2298. doi: 10.11999/JEIT220397

基于IRS辅助的异构网络中超可靠低时延通信波束成形算法设计

doi: 10.11999/JEIT220397
基金项目: 国家铁路智能运输系统工程技术研究中心开放课题(RITS2021KF02),江苏省重点研发计划(BE2021013-3),国家自然科学基金(61971238)
详细信息
    作者简介:

    罗佳俊:男,1996年生,硕士,研究方向为可重构智能表面

    代海波:男,1988年生,讲师,硕士生导师,研究方向为异构网络 资源分配等

    王保云:男,1967年生,教授,博士生导师,研究方向为信息论、 物理层安全通信等

    李春国:男,1983年生,教授,研究方向为多天线中继传输技术、短距离宽带及高速无线传输技术等

    通讯作者:

    代海波 hbdai@njupt.edu.cn

  • 中图分类号: TN92

Design of Beamforming Algorithm for Ultra-reliable and Low-latency Communication in Heterogeneous Networks Based on IRS Assistance

Funds: Open Foundation of National Railway Intelligence Transportation System Engineering Technology Research Center (RITS2021KF02), Key Research and Development Plan of Jiangsu Province (BE2021013-3), The National Natural Science Foundation of China (61971238)
  • 摘要: 为了增强微小区内超可靠低时延通信(URLLC)业务在异构网络场景下的传输性能,该文提出一种基于智能超表面(IRS)辅助通信网络下最大化用户和速率的波束成形算法。异构网络中微小区采用短包通信技术,在保证宏小区用户通信质量的前提下,使用IRS提高微小区用户在一定解码错误概率下的短数据包传输性能,建立一个联合优化波束向量和IRS相移向量的微小区用户和速率最大化问题模型。通过交替固定优化变量的方式,将该非凸优化问题拆分为两个子问题,利用逐次凸逼近(SCA)的方法将原问题转换成凸优化问题,并利用交替优化算法对该问题进行求解。仿真结果表明,该算法通过部署IRS可以有效减弱异构场景下对于微小区用户的干扰,同时由于IRS的部署能够有效优化波束成形向量进而提高微小区用户的短包传输性能,并且IRS的通信增强效果与微小区用户的解码错误概率以及IRS反射单元的数量有直接关系。
  • 图  1  IRS辅助异构网络系统模型

    图  2  迭代次数与系统平均和速率关系, $N = 16,36,64$,${P_{\max }} = 30\;{\text{dBm}}$

    图  3  小蜂窝SC的${P_{\max }}$与系统平均和速率,$K = 2,N = 16$

    图  4  IRS反射单元与系统平均和速率,$K = 2$,${P_{\max }} = 40\;{\text{dBm}}$

    图  5  宏蜂窝MC最大传输功率${P_{{\rm{MC}}}}$与系统平均和速率, $K = 2,N = 16,{P_{\max }} = 40\;{\text{dBm}}$

    图  6  本文算法SC最大传输功率与系统平均和速率

    表  1  基于SCA的迭代主动预编码波束向量算法设计(算法1)

     初始化最大迭代次数$t_1^{\max }$,迭代序号为${t_1}$以及变量$ \{ {\mathbf{W}}_k^{{t_1}}\} $,固定
     优化变量$ {\mathbf{u}} = {[{u_1},{u_2}, \cdots ,{u_N}]^{\text{H}}} $为常量;
     (1) ${\text{for }}i = 1,2, \cdots ,{\text{do}}$
     (2) 在给定变量$ {\mathbf{W}}_k^{{t_1}} $,$ {\mathbf{u}} $的条件下,求解问题式(16),从而获取
       $ {\mathbf{W}}_k^{{t_1} + 1} $;
     (3) 令${t_1} = {t_1} + 1$$ ; $
     (4) 循环直到收敛或者${t_1} = t_1^{\max }$;
     (5) ${\text{end for}}$
    下载: 导出CSV

    表  2  基于SCA迭代优化反射相移算法设计(算法2)

     初始化最大迭代次数$t_2^{\max }$,迭代序号为${t_2} = 0$,在给定$ {\mathbf{W}}_k^{{t_1}} $,初
     始化变量$ {{\mathbf{\bar U}}^{{t_2}}} $,
     (1) ${\text{for }}i = 1,2, \cdots ,{\text{do}}$
     (2) 在给定$ {\mathbf{W}}_k^{{t_1}} $的情况下,通过求解问题(25),从而获取$ {{\mathbf{\bar U}}^{{t_2} + 1}} $
     (3) 令${t_2} = {t_2} + 1$
     (4) 循环直到收敛或者$ {t_2} = t_2^{\max } $
     (5) ${\text{end for}}$
    下载: 导出CSV

    表  3  基于交替迭代优化主动波束和反射相移算法设计(算法3)

     初始化最大迭代次数$t_3^{\max }$,初始化迭代序列号${t_3} = 0$,变量
     $ {\mathbf{W}}_k^{{t_3}} $以及$ {{\mathbf{\bar U}}^{{t_3}}} $
     (1) ${\text{for }}i = 1,2, \cdots ,{\text{do}}$
     (2) 通过表1的算法在给定$ {\mathbf{W}}_k^{{t_3}} $以及$ {{\mathbf{\bar U}}^{{t_3}}} $的情况下获取$ {\mathbf{W}}_k^{{t_3} + 1} $
     (3) 通过表2在给定$ {\mathbf{W}}_k^{{t_3} + 1} $的情况下获取$ {{\mathbf{\bar U}}^{{t_3} + 1}} $
     (4)  令${t_3} = {t_3} + 1$
     (5) 循环直到收敛或者$ {t_3} = t_3^{\max } $
     (6) ${\text{end for}}$
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-04-06
  • 修回日期:  2022-06-21
  • 网络出版日期:  2022-06-24
  • 刊出日期:  2022-07-25

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