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Inter-symbol interference (ISI) channels with data dependent Gauss Markovnoise have been used to model read channels in magnetic recording and otherdata storage systems. The Viterbi algorithm can be adapted for performingmaximum likelihood sequence detection in such channels. However, the problem offinding an analytical upper bound on the bit error rate of the Viterbi detectorin this case has not been fully investigated. Current techniques rely on anexhaustive enumeration of short error events and determine the BER using aunion bound. In this work, we consider a subset of the class of ISI channelswith data dependent Gauss-Markov noise. We derive an upper bound on thepairwise error probability (PEP) between the transmitted bit sequence and thedecoded bit sequence that can be expressed as a product of functions dependingon current and previous states in the (incorrect) decoded sequence and the(correct) transmitted sequence. In general, the PEP is asymmetric. The averageBER over all possible bit sequences is then determined using a pairwise statediagram. Simulations results which corroborate the analysis of upper bound,demonstrate that analytic bound on BER is tight in high SNR regime. In the highSNR regime, our proposed upper bound obviates the need for computationallyexpensive simulation.

Performance evaluation for ML sequence detection in ISI channels with Gauss Markov Noise