Efficient coordinated recovery of sparse channels in massive MIMO

Mudassir Masood, Laila H. Afify, Tareq Y. Al-Naffouri

Research output: Contribution to journalArticlepeer-review

122 Scopus citations

Abstract

This paper addresses the problem of estimating sparse channels in massive MIMO-OFDM systems. Most wireless channels are sparse in nature with large delay spread. In addition, these channels as observed by multiple antennas in a neighborhood have approximately common support. The sparsity and common support properties are attractive when it comes to the efficient estimation of large number of channels in massive MIMO systems. Moreover, to avoid pilot contamination and to achieve better spectral efficiency, it is important to use a small number of pilots. We present a novel channel estimation approach which utilizes the sparsity and common support properties to estimate sparse channels and requires a small number of pilots. Two algorithms based on this approach have been developed that perform Bayesian estimates of sparse channels even when the prior is non-Gaussian or unknown. Neighboring antennas share among each other their beliefs about the locations of active channel taps to perform estimation. The coordinated approach improves channel estimates and also reduces the required number of pilots. Further improvement is achieved by the data-aided version of the algorithm. Extensive simulation results are provided to demonstrate the performance of the proposed algorithms.
Original languageEnglish (US)
Pages (from-to)104-118
Number of pages15
JournalIEEE Transactions on Signal Processing
Volume63
Issue number1
DOIs
StatePublished - Jan 2015

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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