PERFORMANCE ESTIMATION FOR MAXIMUM-LIKELIHOOD DETECTION FOR CHANNELS WITH TRANSITION NOISE

Transition noise is known to be a major cause of errors for high densi ty magnetic recording. This noise is signal dependent and can be model ed as multiplicative noise in a linear channel model. A maximum-likeli hood algorithm was considered for detection of signals in such noise i n [12]. Pn this work, the performance of the detector, based on this a lgorithm, is compared to the traditional Viterbi algorithm (VA) and a modified Viterbi algorithm (MVA) by computer simulations. Results show an improvement of up to 5 dE in signal-to-noise-ratio (SNR) under typ ical conditions with a reasonable complexity.