Noise-predictive maximum-likelihood (NPML) detection for the magnetic recording channel

Abstract

Sequence estimation detectors for the digital magnetic recording channel are described that are based on noise-predictive partial-response equalization. Called Noise-Predictive Maximum-Likelihood (NPML) detectors, they arise by imbedding a noise prediction/whitening process into the branch metric computation of a Viterbi detector. NPML detectors can be realized in a form that allows easy RAM table look-up implementation of the imbedded feedback. The noise prediction/whitening mechanism can also be applied to detectors using finite delay tree search algorithms instead of the Viterbi algorithm. Simulation results obtained for Lorentzian channels show that a judicious tradeoff between performance and state complexity and/or length of decision feedback leads to practical schemes offering substantial performance gains over both PRML and EPRML detectors. An important practical advantage of the family of NPML detectors is that they can be conveniently integrated into existing PRML architectures.