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Quasi-Maximum-Likel...
Quasi-Maximum-Likelihood Multiple-Symbol Differential Detection for Time-Varying Rayleigh Fading Channel
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- Ma, Zheng (author)
- SW Jiaotong University
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- Fan, Pingzhi (author)
- SW Jiaotong University
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- Larsson, Erik G. (author)
- Linköpings universitet,Kommunikationssystem,Tekniska högskolan
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- Honary, Bahram (author)
- University of Lancaster, UK
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(creator_code:org_t)
- Institution of Engineering and Technology (IET), 2009
- 2009
- English.
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In: Electronics Letters. - : Institution of Engineering and Technology (IET). - 0013-5194 .- 1350-911X. ; 45:22, s. 1127-1128
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https://doi.org/10.1...
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Abstract
Subject headings
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- 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.
Keyword
- TECHNOLOGY
- TEKNIKVETENSKAP
Publication and Content Type
- ref (subject category)
- art (subject category)
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