Adaptive sparse channel estimation for time-variant MIMO-OFDM systems

Guan Gui, Fumiyuki Adachi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)

Abstract

Accurate channel state information (CSI) is required for coherent detection in time-variant multiple-input multiple-output (MIMO) communication systems using orthogonal frequency division multiplexing (OFDM) modulation. One of low-complexity and stable adaptive channel estimation (ACE) approaches is the normalized least mean square (NLMS)-based ACE. However, it cannot exploit the inherent sparsity of MIMO channel which is characterized by a few dominant channel taps. In this paper, we propose two adaptive sparse channel estimation (ASCE) methods to take advantage of such sparse structure information for time-variant MIMO-OFDM systems. Unlike traditional NLMS-based method, two proposed methods are implemented by introducing sparse penalties to the cost function of NLMS algorithm. Computer simulations confirm obvious performance advantages of the proposed ASCEs over the traditional ACE.

Original languageEnglish
Title of host publication2013 9th International Wireless Communications and Mobile Computing Conference, IWCMC 2013
Pages878-883
Number of pages6
DOIs
Publication statusPublished - 2013
Event2013 9th International Wireless Communications and Mobile Computing Conference, IWCMC 2013 - Cagliari, Sardinia, Italy
Duration: 2013 Jul 12013 Jul 5

Publication series

Name2013 9th International Wireless Communications and Mobile Computing Conference, IWCMC 2013

Conference

Conference2013 9th International Wireless Communications and Mobile Computing Conference, IWCMC 2013
Country/TerritoryItaly
CityCagliari, Sardinia
Period13/7/113/7/5

Keywords

  • Adaptive sparse channel estimation (ASCE)
  • L -norm NLMS
  • L-norm NLMS
  • Normalized least mean square (NLMS)

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