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Quasi-Maximum-Likelihood Multiple-Symbol Differential Detection for Time-Varying Rayleigh Fading Channel
SW Jiaotong University.
SW Jiaotong University.
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
University of Lancaster, UK.
2009 (English)In: Electronics Letters, ISSN 0013-5194, Vol. 45, no 22, 1127-1128 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2009. Vol. 45, no 22, 1127-1128 p.
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-51778DOI: 10.1049/el.2009.2069OAI: diva2:277385
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. Copyright: IEE Available from: 2009-11-18 Created: 2009-11-17 Last updated: 2010-02-04

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