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Space-time block codes: ML detection for unknown channels and unstructured interference
Dept. of Electrical and Computer Engineering, University of Florida, USA.ORCID iD: 0000-0002-7599-4367
Dept. of Systems and Control, Uppsala University, Sweden.
Dept. of Electrical and Computer Engineering, University of Florida, USA.
2001 (English)In: Proc. of Asilomar Conference on Signals, Systems and Computers. 2001. Vol. 2, IEEE , 2001, 916-920 p.Conference paper, Published paper (Refereed)
Abstract [en]

Space-time coding (STC) schemes for communication systems employing multiple transmit and receive antennas have been attracting increased attention. The so-called linear space-time block codes (STBC) have been of particular interest due to their good performance and low decoding complexity. In this paper we take a systematic maximum-likelihood (ML) approach to the decoding of STBC for unknown propagation channels and unknown noise and interference conditions. We derive a low-complexity ML decoding algorithm based on cyclic maximization of the likelihood function. Furthermore, we discuss the design of optimal training sequences and optimal information transfer to an outer decoder. Numerical examples demonstrate the performance of our algorithm.

Place, publisher, year, edition, pages
IEEE , 2001. 916-920 p.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-77381DOI: 10.1109/ACSSC.2001.987629ISBN: 0-7803-7147-X (print)OAI: oai:DiVA.org:liu-77381DiVA: diva2:526600
Conference
Thirty-Fifth Asilomar Conference on Signals, Systems and Computers, 4-7 Nov. 2001, Pacific Grove, CA, USA
Available from: 2012-05-14 Created: 2012-05-14 Last updated: 2016-08-31Bibliographically approved

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Larsson, Erik G.

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf