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Iterative LMMSE Channel Estimation and Decoding Based on Probabilistic Bias
University of Electro-Communications, Department of Communication Engineering and Informatics.
University Erlangen-Nürnberg.
KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
2013 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 61, no 7, 2853-2863 p.Article in journal (Refereed) Published
Abstract [en]

Iterative channel estimation and decoding based on probabilistic bias is investigated. In order to control the occurrence probability of transmitted symbols, biased convolutional codes (CCs) are proposed. A biased CC is obtained by puncturing the parity bit of a conventional (unbiased) CC and by inserting a fixed bit at the punctured position when the state is contained in a certain subset of all possible states. A priori information about the imposed bias is utilized for the initial linear minimum mean-squared error (LMMSE) channel estimation. This paper focuses on biased turbo codes that are constructed as the parallel concatenation of two biased CCs with interleaving, and proposes an iterative LMMSE channel estimation and decoding scheme based on approximate belief propagation. The convergence property of the iterative LMMSE channel estimation and decoding scheme is analyzed via density evolution (DE). The DE analysis allows one to design the magnitude of the bias according to the coherence time, in terms of the decoding threshold. The proposed scheme is numerically shown to outperform conventional pilot-based schemes in the moderate signal-to-noise ratio (SNR) regime, at the expense of a performance degradation in the high SNR regime.

Place, publisher, year, edition, pages
2013. Vol. 61, no 7, 2853-2863 p.
Keyword [en]
Biased convolutional codes; belief propagation; density evolution; iterative decoding; linear minimum mean-squared error (LMMSE) channel estimation
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-125039DOI: 10.1109/TCOMM.2013.053013.120919ISI: 000322451800023Scopus ID: 2-s2.0-84881134098OAI: oai:DiVA.org:kth-125039DiVA: diva2:639046
Note

QC 20130812

Available from: 2013-08-05 Created: 2013-08-05 Last updated: 2017-12-06Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
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  • vancouver
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Language
  • de-DE
  • en-GB
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  • Other locale
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