IRS-assisted millimeter-wave channel estimation based on parallel factorization

YANG Qingqing; LI Xuewen; PENG Yi; WANG Jianming

doi:10.13471/j.cnki.acta.snus.ZR20230019

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IRS-assisted millimeter-wave channel estimation based on parallel factorization

Research articles | 更新时间：2024-09-29

- IRS-assisted millimeter-wave channel estimation based on parallel factorization
- Acta Scientiarum Naturalium Universitatis Sunyatseni Vol. 63, Issue 4, Pages: 124-131(2024)
- 作者机构：
  
  1.昆明理工大学信息工程与自动化学院，云南昆明 650500
  2.云南省计算机技术应用重点实验室，云南昆明 650500
- 作者简介：
- 基金信息：
- DOI：10.13471/j.cnki.acta.snus.ZR20230019
  CLC： TN929.5
- Published：25 July 2024，
  
  Published Online：01 April 2024，
  
  Received：21 November 2023，
  
  Accepted：04 January 2024
- 稿件说明：
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杨青青,李学文,彭艺等.基于平行因子分解的IRS辅助毫米波信道估计[J].中山大学学报(自然科学版)(中英文),2024,63(04):124-131.

YANG Qingqing,LI Xuewen,PENG Yi,et al.IRS-assisted millimeter-wave channel estimation based on parallel factorization[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2024,63(04):124-131.
杨青青,李学文,彭艺等.基于平行因子分解的IRS辅助毫米波信道估计[J].中山大学学报(自然科学版)(中英文),2024,63(04):124-131. DOI： 10.13471/j.cnki.acta.snus.ZR20230019.

YANG Qingqing,LI Xuewen,PENG Yi,et al.IRS-assisted millimeter-wave channel estimation based on parallel factorization[J].Acta Scientiarum Naturalium Universitatis Sunyatseni,2024,63(04):124-131. DOI： 10.13471/j.cnki.acta.snus.ZR20230019.

摘要

提出了一种基于平行因子分解的信道估计算法。首先，根据毫米波信道固有的稀疏特性对信道进行建模，利用块衰落信道的特点将信号矩阵构建成一个3维张量，并且利用平行因子分解算法对张量进行分解。然后利用压缩感知理论将分解后的矩阵转化为稀疏信号的恢复问题。最后，利用改进的双线性交替最小二乘算法对信道进行求解。仿真结果表明，与现有的BALS算法、wBALS算法和LSKRF算法相比，本文算法估计精度较高。

Abstract

A channel estimation algorithm based on parallel factor（PARAFAC） decomposition is proposed. Firstly， the channel is modeled according to the inherent sparse characteristics of the millimeter-wave channel. Then， the signal matrix is constructed into a three-dimensional tensor by using the characteristics of the block fading channel， and the tensor is decomposed by the parallel factorization algorithm. Then， the compressed sensing（CS） theory is used to transform the decomposed matrix into a sparse signal recovery problem. Finally， the bilinear alternating least squares（NBALS） algorithm is improved to solve the channel. The simulation shows that compared with the existing BALS algorithm， wBALS algorithm， and LSKRF algorithm， the proposed algorithm improves the estimation accuracy.

关键词

可重构智能表面毫米波通信信道估计张量平行因子分解

Keywords

IRSmillimeter wave communicationchannel estimationtensorparallel factorization

references

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