EQUALIZATION FOR MAXIMUM-LIKELIHOOD DETECTORS

In this paper, the minimum mean-square error (MMSE) technique has been used to equalize the recording channel in order to facilitate the app lication of the Viterbi detector. The resulting performance has been c ompared with that of the optimal equalization system which yields the minimum probability of error at the output of the Viterbi detector. Th e results indicate that depending on the constraint used in the MMSE d esign, the amount of noise correlation varies significantly at the equ alizer output, which in turn makes a large difference in the performan ce of the Viterbi detector. In particular, in the jitter-dominant chan nel where unconditioned channel noise samples are highly correlated, t he monic constraint on the equalizer target response tends to whiten t he noise samples at the equalizer output. This results in a significan t performance improvement of the monic constraint upon the fixed-energ y constraint as well as the popular partial response targets of the fo rm (1 - D)(1 + D)n.