Adaptive Bayesian decision-feedback equalizer for dispersive mobile radio channels

Sheng Chen, Steve McLaughlin, Bernard Mulgrew, Peter M Grant

Research output: Contribution to journalArticlepeer-review

72 Citations (Scopus)


The paper investigates adaptive equalization of time-dispersive mobile ratio fading channels and develops a robust high performance Bayesian decision feedback equalizer (DFE). The characteristics and implementation aspects of this Bayesian DFE are analyzed, and its performance is compared with those of the conventional symbol or fractional spaced DFE and the maximum likelihood sequence estimator (MLSE). In terms of computational complexity, the adaptive Bayesian DFE is slightly more complex than the conventional DFE but is much simpler than the adaptive MLSE. In terms of error rate in symbol detection, the adaptive Bayesian DFE outperforms the conventional DFE dramatically. Moreover, for severely fading multipath channels, the adaptive MLSE exhibits significant degradation from the theoretical optimal performance and becomes inferior to the adaptive Bayesian DFE.

Original languageEnglish
Pages (from-to)1937-1946
Number of pages10
JournalIEEE Transactions on Communications
Issue number5
Publication statusPublished - May 1995


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