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  • Ma, ZhengSW Jiaotong University (author)

Quasi-Maximum-Likelihood Multiple-Symbol Differential Detection for Time-Varying Rayleigh Fading Channel

  • Article/chapterEnglish2009

Publisher, publication year, extent ...

  • Institution of Engineering and Technology (IET),2009
  • electronicrdacarrier

Numbers

  • LIBRIS-ID:oai:DiVA.org:liu-51778
  • https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-51778URI
  • https://doi.org/10.1049/el.2009.2069DOI

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  • Language:English
  • Summary in:English

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  • Subject category:ref swepub-contenttype
  • Subject category:art swepub-publicationtype

Notes

  • This paper is a postprint of a paper submitted to and accepted for publication in Electronics Letters and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library Zheng Ma, Pingzhi Fan, Erik G. Larsson and Bahram Honary, Quasi-Maximum-Likelihood Multiple-Symbol Differential Detection for Time-Varying Rayleigh Fading Channel, 2009, Electronics Letters, (45), 22, 1127-1128. http://dx.doi.org/10.1049/el.2009.2069 Copyright: IEE http://www.theiet.org/
  • The maximum-likelihood multiple-symbol differential detector (ML-MSDD) has better bit-error-rate performance than many other detectors for differential modulation. Unfortunately, the computational complexity of ML-MSDD quickly becomes prohibitive as the observation window size grows. While low-complexity MSDD algorithms for the time-invariant Rayleigh fading channel have been considered before, there is a need for low-complexity MSDD algorithms for general time-varying Rayleigh fading channels. A polynomial-time complexity approach called semi-definite relaxation (SDR) is employed to achieve differential detection with near maximum-likelihood (ML) performance. The proposed SDR quasi-maximum-likelihood (QML) multiple-symbol differential detection (SDR-QML-MSDD) is efficient in that its complexity is polynomial in the observation window size, even in the worst case, while it exhibits almost the same performance as ML-MSDD does.

Subject headings and genre

  • TECHNOLOGY
  • TEKNIKVETENSKAP

Added entries (persons, corporate bodies, meetings, titles ...)

  • Fan, PingzhiSW Jiaotong University (author)
  • Larsson, Erik G.Linköpings universitet,Kommunikationssystem,Tekniska högskolan(Swepub:liu)erila39 (author)
  • Honary, BahramUniversity of Lancaster, UK (author)
  • SW Jiaotong UniversityKommunikationssystem (creator_code:org_t)

Related titles

  • In:Electronics Letters: Institution of Engineering and Technology (IET)45:22, s. 1127-11280013-51941350-911X

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Ma, Zheng
Fan, Pingzhi
Larsson, Erik G.
Honary, Bahram
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Electronics Lett ...
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Linköping University

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