Viterbi Detector for Non-Markov Recording Channels

Channel noise in modern perpendicular channels is well approximated by a linear jitter model. In this paper, we propose a new type of Viterbi detector matched to such a channel model. The differentiating feature of this detector is recursive evaluation of whitened noise strengths for survivor paths using the on-the-fly Cholesky factorization of path-dependent correlation matrices. We study the performance of the detector using the simplest example of low-density channels with intersymbol interference length equal to three. We find that at BER = 10^-4, the new detector outperforms the data-dependent AR-detector of the comparable complexity by about 0.9 dB.