Channel estimation for OFDM systems over doubly selective channels

A distributed compressive sensing based approach

Peng Cheng, Zhuo Chen, Yun Rui, Y. Jay Guo, Lin Gui, Meixia Tao, Q. T. Zhang

Research output: Contribution to journalArticle

76 Citations (Scopus)

Abstract

Channel estimation for an orthogonal frequency-division multiplexing (OFDM) broadband system over a doubly selective channel is very challenging. This is mainly due to the significant Doppler shift, which results in a time-frequency doubly-selective (DS) channel. The DS channel features a large number of channel coefficients, which introduces inter-carrier interference (ICI) and forces the need for allocating a large number of pilot subcarriers. To tackle this problem, in this paper we propose a novel channel estimation scheme based on distributed compressive sensing (DCS) theory. Taking advantage of the basis expansion model (BEM) and the channel sparsity in the delay domain, we transform the original DS channel into a novel two-dimensional channel model, where several jointly sparse BEM coefficient vectors become the estimation goal. Then a special decoupling form originating from a novel sparse pilot pattern is designed for such estimation, which results in an ICI-free structure and enables the DCS application to make joint estimation of these vectors accurately. Combined with a smoothing treatment process, the proposed scheme can achieve significantly higher estimation accuracy than the existing ones, although with a much smaller number of pilot subcarriers. Theoretical analysis and simulation results both confirm its performance merits.

Original languageEnglish
Article number6573238
Pages (from-to)4173-4185
Number of pages13
JournalIEEE Transactions on Communications
Volume61
Issue number10
DOIs
Publication statusPublished - Oct 2013
Externally publishedYes

Keywords

  • channel estimation
  • distributed compressive sensing
  • doubly selective
  • OFDM
  • sparse

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