The impact of both a priori information and channel estimation errors on the MAP equalizer performance

To combat the effects of intersymbol interference (ISI), the optimal equalizer to be used is based on maximum a posteriori (MAP) detection. In this paper, we consider the case where the MAP equalizer is fed with a priori information on the transmitted data and propose to study analytically their imp...

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Bibliographic Details
Published inIEEE transactions on signal processing Vol. 54; no. 7; pp. 2716 - 2724
Main Authors Sellami, N., Roumy, A., Fijalkow, I.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.07.2006
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Applied sciences
Approximation
Bit error rate
Channel estimation
Channels
Computer Science
Detection, estimation, filtering, equalization, prediction
Engineering Sciences
Equalizers
Equivalence
Exact sciences and technology
Exact solutions
Image Processing
Information analysis
Information, signal and communications theory
Intersymbol interference
Iterative algorithms
MAP equalization
Mathematical analysis
Maximum likelihood detection
Optimization
Performance analysis
Signal and communications theory
Signal and Image Processing
Signal to noise ratio
Signal, noise
Simulation
Telecommunications and information theory
turbo equalization
Viterbi algorithm
Performance evaluation
Estimation error
Parameter estimation
MAP equalization
Error estimation
Data transmission
Impact study
Equalizer
Equalization
Simulation
Intersymbol interference
Channel estimation
A posteriori estimation
Analytical method
A priori estimation
performance analysis
Signal to noise ratio
turbo equalization
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Summary:To combat the effects of intersymbol interference (ISI), the optimal equalizer to be used is based on maximum a posteriori (MAP) detection. In this paper, we consider the case where the MAP equalizer is fed with a priori information on the transmitted data and propose to study analytically their impact on the MAP equalizer performance. We assume that the channel is not perfectly estimated and show that the use of both the a priori information and the channel estimate is equivalent to a shift in terms of signal-to-noise ratio (SNR) for which we provide an analytical expression. Simulation results show that the analytical expression approximates well the equalizer behavior
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2006.874805