Iterative estimation of sparse and doubly-selective multi-input multi-output (MIMO) channel

Jun Won Choi, Kyeongyeon Kim, Thomas J. Riedl, Andrew C. Singer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The estimation of doubly-selective channels is challenging since long channel impulse response should be estimated with a fast tracking speed. Provided that a structure of the channel response is sparse, i.e., only a few of channel gains are nonzero, tracking performance of the channel estimator can be improved significantly by avoiding estimation of zero taps. In this paper, we study estimation of fast time-varying channels that have a sparse structure in multi-input multi-output (MIMO) systems. In order to exploit the sparse structure, we parameterize locations of nonzero channel taps using a deterministic binary vector and incorporate it into the state-space form built upon autoregressive (AR) time-varying channel model. Then, we derive a joint estimate of the binary vector and channel gains based on maximum likelihood (ML) criterion. Expectation maximization (EM) algorithm is derived to find a sparse structure and channel gains iteratively. According to the simulation study performed over MIMO Rician fading channels, the proposed sparse channel estimator outperforms the previous channel estimation schemes, especially when Doppler rate is high.

Original languageEnglish (US)
Title of host publicationConference Record - 43rd Asilomar Conference on Signals, Systems and Computers
Pages620-624
Number of pages5
DOIs
StatePublished - 2009
Event43rd Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Nov 1 2009Nov 4 2009

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other43rd Asilomar Conference on Signals, Systems and Computers
CountryUnited States
CityPacific Grove, CA
Period11/1/0911/4/09

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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