Title :
Comparison Between Viterbi Detectors for Magnetic Recording Channels Based on Regressive and Autoregressive Noise Models
Author :
Maggi, Lorenzo ; Savazzi, Pietro ; Valle, Stefano
Author_Institution :
EURECOM, Sophia-Antipolis, France
Abstract :
A recent work presents a regressive noise model for the data-dependent correlated noise, at the output of a magnetic recording channel detector. We have generalized this channel model, considering digital equalization and a more efficient correlation matrix, in order to make a comparison with the usual detector in a more realistic environment. Simulation results show that the regressive detector performs better when the number of trellis states is lower than needed, while both approaches are comparable when the number of states matches the channel memory.
Keywords :
Viterbi detection; magnetic recording noise; regression analysis; Viterbi detectors; autoregressive noise model; correlation matrix; digital equalization; magnetic recording channel; Additive white noise; Detectors; Gaussian noise; IIR filters; Magnetic noise; Magnetic recording; Perpendicular magnetic recording; Signal to noise ratio; Viterbi algorithm; Working environment noise; Cholesky factorization; Taylor expansion; Viterbi algorithm; data-dependent channel noise; linear model; nonstationary process; perpendicular magnetic recording; regressive and autoregressive models;
Journal_Title :
Magnetics, IEEE Transactions on
DOI :
10.1109/TMAG.2009.2028137