Journal of Communications Software and Systems (Feb 2021)

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

  • Ami Munshi,
  • Srija Unnikrishnan

DOI
https://doi.org/10.24138/jcomss.v17i1.1084
Journal volume & issue
Vol. 17, no. 1
pp. 13 – 19

Abstract

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In this paper, we have developed and implemented Minimum Mean Square Channel Estimation with Compressive Sensing (MMSE-CS) algorithm in MIMO-OFDM systems. The performance of this algorithm is analyzed by comparing it with Least Square channel estimation with compressive sensing (LS-CS), Least Square (LS) and Minimum Mean Square Estimation (MMSE) algorithms. It is observed that the performance of MMSE-CS in terms of Bit Error Rate (BER) metric is definitely better than LS-CS and LS algorithms and it is at par with MMSE algorithm. Moreover the role of compressive sensing theory in channel estimation is accentuated by the fact that in MMSE-CS algorithm only a very small number of channel coefficients are sensed to recreate the transmitted data faithfully as compared to MMSE algorithm.

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