Performance Analysis of Compressive Sensing based LS and MMSE Channel Estimation Algorithm

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of Communications Software and Systems Pub Date : 2021-02-08 DOI:10.24138/JCOMSS.V17I1.1084
A. Munshi, S. Unnikrishnan
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引用次数: 9

Abstract

In this paper, the optimality of Compressive Sensing based Least Square (LS-CS) and Compressive Sensing based Minimum Mean Square (MMSE-CS) channel estimation algorithms in Multi Input Multi Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) system is investigated for a sparse communication channel. The performance of LS, MMSE, LS-CS and MMSE-CS channel estimation algorithms in terms of sparsity of the channel, compressive sensing and mathematical complexity is investigated and analyzed so that optimum ranges can be recommended.
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基于压缩感知的LS和MMSE信道估计算法性能分析
针对稀疏通信信道,研究了多输入多输出(MIMO)正交频分复用(OFDM)系统中基于压缩感知的最小二乘(LS-CS)和基于压缩感知的最小均方(MMSE-CS)信道估计算法的最优性。对LS、MMSE、LS- cs和MMSE- cs信道估计算法在信道稀疏度、压缩感知和数学复杂度方面的性能进行了研究和分析,从而提出了最佳范围。
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来源期刊
Journal of Communications Software and Systems
Journal of Communications Software and Systems Engineering-Electrical and Electronic Engineering
CiteScore
2.00
自引率
14.30%
发文量
28
审稿时长
8 weeks
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