Semi-blind identification of wideband MIMO channels via stochastic sampling

Christophe Andrieu*, Robert J. Piechocki, Joe P. McGeehan, Simon M. Armour

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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Abstract

In this paper we address the problem of wide-band multiple-input multiple-output (MIMO) channel (multidimensional time invariant FIR filter) identification using Markov chains Monte Carlo methods. Towards this end we develop a novel stochastic sampling technique that produces a sequence of multidimensional channel samples. The method is semi-blind in the sense that it uses a very short training sequence. In such a framework the problem is no longer analytically tractable; hence we resort to stochastic sampling technique. The developed technique samples the channel, the variance of the noise and the symbols in order to build an ergodic Markov chain whose equilibrium distribution is the distribution of interest. The estimates of the MIMO channel and the noise variance are inferred from marginal posterior distributions, which are by-products of the output of the algorithm
Translated title of the contributionSemi-blind identification of wideband MIMO channels via stochastic sampling
Original languageEnglish
Title of host publicationIEEE Vehicular Technology Conference
Pages994-997
Number of pages4
Volume57
Edition2
DOIs
Publication statusPublished - Apr 2003
Event57th IEEE Semiannual Vehicular Technology Conference (VTC2003) - Jeju, Korea, Republic of
Duration: 22 Apr 200325 Apr 2003

Conference

Conference57th IEEE Semiannual Vehicular Technology Conference (VTC2003)
Country/TerritoryKorea, Republic of
CityJeju
Period22/04/0325/04/03

Bibliographical note

Publisher: Institute of Electrical and Electronics Engineers Inc (IEEE)
Name and Venue of Conference: 57th IEEE Vehicular Technology Conference, Spring 2003
Rose publication type: Conference contribution

Sponsorship: The authors wish to thank Toshiba TREL Ltd. for sponsoring the work presented in this article

Terms of use: Copyright © 2003 IEEE. Reprinted from Proceedings of IEEE 57th Vehicular Technology Conference, 2003. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bristol's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected].
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Contributor (Other): Institute of Electrical and Electronics Engineers (IEEE)

Keywords

  • MCMC
  • MIMO
  • Stochastic Sampling
  • Turbo pinciple

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