Equalization and detection for nonlinear recording channels with correlated noise

Abstract

At high recording densities, signal nonlinearity due to both the medium and the magnetoresistive head and correlated noise due to the medium and the equalization process, substantially degrade the error-rate performance of the Viterbi algorithm (VA). This paper describes a method for dealing with both problems by simultaneously adapting the equalizer, its target and the VA branch metrics. A monic constraint is employed to locate a target that limits noise correlation at the input to the VA. Pattern-dependent offsets, rather than actual VA ideal values, are adaptively determined to account for channel nonlinearity in the VA. The effectiveness of these techniques is demonstrated on very high density data collected from a spin stand.