Performance Evaluation and Error Propagation Analysis of Decision-Feedback Equalization with Maximum-Likelihood Detector

Hideki SAWAGUCHI  Wataru SAKURAI  

Publication
IEICE TRANSACTIONS on Electronics   Vol.E78-C   No.11   pp.1575-1581
Publication Date: 1995/11/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Issue on Ultra High Density Information Storage Technologies)
Category: 
Keyword: 
decision-feedback equalization,  fixed-delay-tree-search algorithm,  maximum-likelihood sequence detector,  feedback-filter,  error propagation,  

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Summary: 
The performance of decision-feedback equalization combined with maximum-likelihood detection (DFE/ML) using the fixed-delay-tree-search/decision feedback (FDTS/DF) algorithm was estimated analytically in terms of the length of the feedback-filter and the depth of the ML-detector. Performance degradation due to error propagation in the feedback-loop and in the ML-detector was taken into account by using a Markov process analysis. It was quantitatively shown that signal-to-noise-ratio (SNR) performance in high-density magnetic recording channels can be improved by combining an ML-detector with a feedback-filter and that the error propagation in the DFE channel can be reduced by using an ML-detector. Finally, it was found that near-optimum performance with regard to channel SNR and error propagation can be achieved, over the channel density range from 2 to 3, by increasing the sum of the feedback-filter length and the ML-detector depth to six bits.