Super-resolution sparse MIMO-OFDM channel estimation based on spatial and temporal correlations

Zhen Gao, Linglong Dai, Zhaohua Lu, Chau Yuen, Zhaocheng Wang

Research output: Contribution to journalArticlepeer-review

76 Citations (Scopus)

Abstract

This letter proposes a parametric sparse multiple input multiple output (MIMO)-OFDM channel estimation scheme based on the finite rate of innovation (FRI) theory, whereby super-resolution estimates of path delays with arbitrary values can be achieved. Meanwhile, both the spatial and temporal correlations of wireless MIMO channels are exploited to improve the accuracy of the channel estimation. For outdoor communication scenarios, where wireless channels are sparse in nature, path delays of different transmit-receive antenna pairs share a common sparse pattern due to the spatial correlation of MIMO channels. Meanwhile, the channel sparse pattern is nearly unchanged during several adjacent OFDM symbols due to the temporal correlation of MIMO channels. By simultaneously exploiting those MIMO channel characteristics, the proposed scheme performs better than existing state-of-the-art schemes. Furthermore, by joint processing of signals associated with different antennas, the pilot overhead can be reduced under the framework of the FRI theory.

Original languageEnglish
Article number6817517
Pages (from-to)1266-1269
Number of pages4
JournalIEEE Communications Letters
Volume18
Issue number7
DOIs
Publication statusPublished - Jul 2014
Externally publishedYes

Keywords

  • Super-resolution
  • finite rate of innovation (FRI)
  • sparse channel estimation MIMO-OFDM
  • spatial and temporal correlations

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