Noise-predictive maximum likelihood (NPML) detection

Abstract

Sequence detectors for the digital magnetic recording channel that are based on noise-predictive partial-response equalization are described. 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 RAM table look-up implementation of the imbedded feedback. Alternatively, the noise prediction/whitening mechanism can be implemented as an infinite impulse response (IIR) filter. For a Lorentzian channel with operating points in the range 0.5<PW50/T<3.5, IIR predictors with at most two zeros and two poles offer the best possible performance. Simulation results obtained for Lorentzian channels show that a judicious tradeoff between performance and state complexity leads to practical schemes offering substantial performance gains over both PRML and extended PRML detectors. An important practical advantage of the family of NPML detectors is that they can be conveniently integrated into existing PRML architectures.