Multi-user joint RIS channel estimation based on ADMM

ZHU Luhu; WANG Anding

doi:10.11959/j.issn.1000-0801.2024252

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Multi-user joint RIS channel estimation based on ADMM

Research and Development | 更新时间：2024-12-30

- Multi-user joint RIS channel estimation based on ADMM
- Telecommunications Science Vol. 40, Issue 12, Pages: 74-85(2024)
- 作者机构：
  
  浙江工商大学信息与电子工程学院，浙江杭州 310018
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2024252
  CLC： TP301
- Received：11 July 2024，
  
  Revised：29 October 2024，
  
  Published：20 December 2024
- 稿件说明：
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朱路虎,王安定.一种基于ADMM的多用户联合的RIS信道估计方案[J].电信科学,2024,40(12):74-85.

ZHU Luhu,WANG Anding.Multi-user joint RIS channel estimation based on ADMM[J].Telecommunications Science,2024,40(12):74-85.
朱路虎,王安定.一种基于ADMM的多用户联合的RIS信道估计方案[J].电信科学,2024,40(12):74-85. DOI： 10.11959/j.issn.1000-0801.2024252.

ZHU Luhu,WANG Anding.Multi-user joint RIS channel estimation based on ADMM[J].Telecommunications Science,2024,40(12):74-85. DOI： 10.11959/j.issn.1000-0801.2024252.

摘要

针对智能反射面（reconfigurable intelligent surface，RIS）辅助的毫米波通信系统中传统信道估计方案导频开销过高、计算复杂度较大的问题，提出了一种基于多用户联合场景的交替方向乘子法（alternating direction method of multipliers，ADMM）信道估计方案。首先，利用不同用户级联信道存在公共BS-RIS部分，估计出用户信号的公共子空间并进行投影，有效减弱了噪声的影响。其次，考虑多用户级联信道的相关性和稀疏性，构建了稀疏级联信道矩阵和公共缩放因子矩阵的优化问题。对于该非凸联合优化问题，采用ADMM算法，交替优化估计稀疏矩阵和公共缩放因子矩阵。仿真结果表明，与现有方法相比，提出的基于多用户联合的ADMM信道估计方案导频开销将减少约50%。

Abstract

Addressing the challenges of high pilot overhead and computational complexity in traditional channel estimation methods for millimeter-wave communication systems aided by reconfigurable intelligent surfaces (RIS)

a novel channel estimation algorithm based on the alternating direction method of multipliers (ADMM) for multi-user joint scenarios was proposed. Firstly

leveraging the shared base station (BS)-RIS component within the cascaded channels of different users

the common subspace of user signals was estimated and projected to effectively mitigate noise interference. Secondly

considering the correlation and sparsity of multi-user cascaded channels

an optimization problem for the sparse cascaded channel matrix and common scaling factor matrix was formulated. To solve this non-convex joint optimization problem

the ADMM algorithm was employed to alternately optimize the sparse matrix and the common scaling factor matrix. Simulation results demonstrate that

compared to existing methods

the proposed ADMM-based channel estimation algorithm for multi-user joint scenarios reduces pilot overhead by approximately 50%.

关键词

Keywords

references

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