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Gaussian Approximation of the LLR Distribution for the ML and Partial Marginalization MIMO detectors
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-7599-4367
Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-1082-8325
2011 (English)In: Proceedings of the IEEE International Conference on Acoustics, Speech and SignalProcessing (ICASSP), IEEE conference proceedings, 2011, 3232-3235 p.Conference paper, Published paper (Refereed)
Abstract [en]

We derive a Gaussian approximation of the LLR distribution  conditioned on the transmitted signal and the channel matrix for the  soft-output via partial marginalization MIMO detector. This detector  performs exact ML as a special case. Our main results consist of  discussing the operational meaning of this approximation and a proof  that, in the limit of high SNR, the LLR distribution of interest  converges in probability towards a Gaussian distribution.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2011. 3232-3235 p.
Series
IEEE International Conference on Acoustics, Speech and SignalProcessing, ISSN 1520-6149
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-64368DOI: 10.1109/ICASSP.2011.5946710ISI: 000296062403161ISBN: 978-1-4577-0537-3 (print)OAI: oai:DiVA.org:liu-64368DiVA: diva2:389872
Available from: 2011-01-20 Created: 2011-01-20 Last updated: 2016-08-31

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Čirkić, MirsadPersson, DanielLarsson, Erik G.Larsson, Jan-Åke

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
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  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • nn-NB
  • sv-SE
  • Other locale
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Output format
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