Group sparse estimation of time-varying delay OFDM channels based on compressed sensing

Xiaoping Zhou, Jing Zhang, Li Li, Pei Wang

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)

Abstract

Time-varying delay fading of propagating channels degrades the performance of orthogonal frequency-division multiplexing (OFDM) systems. The theory of compressed sensing (CS) shows that sparse channels in high-dimensional spaces can be recovered from a relatively small number of samples. However, existing CS-based channel estimations require the sparsity as a prior for exact recovery. The sparsity of time-varying delay channels could not be well-defined. In this paper, a group sparse estimation of time-varying delay OFDM channels without prior information of the sparsity based on CS is given. The simulation results show that the new channel estimator can provide a considerable performance improvement in estimating time-varying delay channels, especially for the rapidly time-varying channels of a large Doppler frequency.

Original languageEnglish
Pages (from-to)3215-3220
Number of pages6
JournalJournal of Computational Information Systems
Volume8
Issue number8
Publication statusPublished - 15 Apr 2012
Externally publishedYes

Keywords

  • Channel estimation
  • Compressed sensing
  • Sparse channel
  • Time-varying delay

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