Bayesian Compressed Sensing Channel Estimation Method in Massive MIMO

WU Can; HUANG Jun-wei; ZHANG Shu-chang

doi:10.13756/j.gtxyj.2018.01.018

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Bayesian Compressed Sensing Channel Estimation Method in Massive MIMO

- Bayesian Compressed Sensing Channel Estimation Method in Massive MIMO
- Study on Optical communication Issue 1, Pages: 70-73(2018)
- 作者机构：
  
  重庆邮电大学通信与信息工程学院
- 作者简介：
- 基金信息：
- DOI：10.13756/j.gtxyj.2018.01.018
  CLC： TN919.3
- Published：2018，
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[1]吴灿,黄俊伟,张书畅.大规模MIMO下贝叶斯压缩感知信道估计方法[J].光通信研究,2018(01):70-73.

WU Can, HUANG Jun-wei, ZHANG Shu-chang. Bayesian Compressed Sensing Channel Estimation Method in Massive MIMO. [J]. (1):70-73(2018)
[1]吴灿,黄俊伟,张书畅.大规模MIMO下贝叶斯压缩感知信道估计方法[J].光通信研究,2018(01):70-73. DOI： 10.13756/j.gtxyj.2018.01.018.

WU Can, HUANG Jun-wei, ZHANG Shu-chang. Bayesian Compressed Sensing Channel Estimation Method in Massive MIMO. [J]. (1):70-73(2018) DOI： 10.13756/j.gtxyj.2018.01.018.

摘要

由于存在导频污染问题

基站侧高效、高精度地获取信道状态信息对实现大规模多输入多输出（MIMO）正交频分复用系统的潜在优点至关重要。通过使用压缩感知技术

可以有效解决导频污染问题。然而

在压缩感知信道估计算法中

很难直接获取信道稀疏度的先验知识。为了解决这个问题

文章提出一种基于贝叶斯压缩感知的信道估计方法

该方法将稀疏信号的统计信息作为先验知识

并运用于多用户大规模MIMO系统的上行链路。仿真结果表明

与传统的信道估计方法相比

所提方法能有效重构原始信道系数。

Abstract

Due to the limitations of pilot pollution problems

efficient and highly accurate channel state information at the base station is critical to the potential benefits of implementing massive Multiple Input Multiple Output（MIMO）Orthogonal Frequency Division Multiplexing（OFDM）systems.It has recently been shown that Compressed Sensing（CS）techniques can solve pilot contamination problems.However

in the CS channel estimation algorithm

it is difficult to obtain the prior knowledge of channel sparseness directly.In order to solve this problem

an effective channel estimation method based on Bayesian Compressied Sensing（BCS）is proposed.The method uses sparse signal statistics as a priori knowledge to the multiuser multi-scale MIMO system uplinks.The simulation results show that the proposed method can reconstruct the original channel coefficients more effectively than the traditional channel estimation method.

关键词

大规模多输入多输出贝叶斯压缩感知信道估计导频污染

Keywords

massive MIMOBayesian compressied sensingchannel estimationpilot contamination

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