计算机工程

• 移动互联与通信技术 • 上一篇    下一篇

基于空时域压缩的大规模MIMO导频污染抑制算法

龙恳,闫冰冰,刘月贞,杜飞   

  1. (重庆邮电大学 通信与信息工程学院,重庆 400065)
  • 收稿日期:2016-05-03 出版日期:2017-07-15 发布日期:2017-07-15
  • 作者简介:龙恳(1978—),男,讲师、博士,主研方向为新一代移动通信系统;闫冰冰、刘月贞、杜飞,硕士研究生。
  • 基金项目:
    国家科技重大专项(2014ZX03003004-003)。

Pilot Contamination Mitigation Algorithm in Massive MIMO Based on Spatial-Temporal Domain Compression

LONG Ken,YAN Bingbing,LIU Yuezhen,DU Fei   

  1. (College of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
  • Received:2016-05-03 Online:2017-07-15 Published:2017-07-15

摘要: 导频污染问题是限制大规模多输入多输出(MIMO)系统性能的主要因素。为此,提出一种新的大规模MIMO导频污染抑制算法,建立空时域二维压缩感知模型,并利用传统的匹配追踪算法进行导频信号重构。仿真结果表明,与基于最小均方误差的预编码算法相比,该算法可在相同系统需求的前提下进一步减少导频使用数量,从而有效抑制导频污染,提升大规模MIMO系统整体性能。

关键词: 导频污染, 大规模多输入多输出系统, 空时域, 压缩感知, 重构

Abstract: The problem of pilot contamination is the main factor which influences the performance of Massive Multiple Input Multiple Output(MIMO) system.In order to solve this problem,this paper proposes a new pilot contamination mitigation algorithm in massive MIMO.Firstly,a two-dimensional compression sensing model in spatial and temporal domains is built.Then,pilot signal reconstruction is carried out by using Orthogonal Matching Pursuit(OMP) algorithm.The simulation results show that compared with precoding algorithm based on Minimum Mean Square Error(MMSE),under the condition of the same system demand,this algorithm can further reduce the number of pilots to mitigate pilot contamination effectively and improve the whole performance of massive MIMO system.

Key words: pilot contamination, massive Multiple Input Multiple Output(MIMO) system, spatial-temporal domain, compressive sensing, reconstruction

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