Improving soft output quality of MIMO demodulation algorithm via importance sampling

Y Jia, C Andrieu, RJ Piechocki, M Sandell

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

4 Citations (Scopus)

Abstract

This paper proposes a two stage algorithm to improve the soft output of the channel demodulation algorithm for a multiple input multiple output (MIMO) system with block fading channels by the Monte Carlo method. In the first stage, the demodulation algorithm, i.e., probability data association detector (PDA) or minimum mean square error (MMSE) algorithm, computes the marginal probability distribution of symbols for each antenna. Then we draw samples from those marginal distributions and use the importance sampling algorithm to correct those distributions to approximate the joint posterior distribution of symbols for all the antennas. Simulation results are given to demonstrate the effectiveness of the new algorithm
Translated title of the contributionImproving soft output quality of MIMO demodulation algorithm via importance sampling
Original languageEnglish
Title of host publicationFifth International Conference on 3G Mobile Communication Technologies, London
PublisherInstitution of Engineering and Technology (IET)
Pages388 - 391
ISBN (Print)0863413889
Publication statusPublished - Oct 2004
Event5th International Conference on 3G Mobile Communication Technologies - London, United Kingdom
Duration: 1 Oct 2004 → …

Conference

Conference5th International Conference on 3G Mobile Communication Technologies
CountryUnited Kingdom
CityLondon
Period1/10/04 → …

Bibliographical note

Conference Proceedings/Title of Journal: Fifth International Conference on 3G Mobile Communication Technologies, 2004
Rose publication type: Conference contribution

Sponsorship: The authors would like to thank Toshiba TREL Ltd. for sponsoring the work presented in this article and the first author would like to thank Toshiba TREL Ltd. for supporting his PhD study at the University of Bristol

Keywords

  • MIMO
  • Sequential Monte Carlo
  • Importance Sampling

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