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Performance Evaluation for ML Sequence Detection in ISI Channels with Gauss Markov Noise
2010
2010 IEEE Global Telecommunications Conference GLOBECOM 2010
Inter-symbol interference (ISI) channels with data dependent Gauss Markov noise have been used to model read channels in magnetic recording and other data storage systems. The Viterbi algorithm can be adapted for performing maximum likelihood sequence detection in such channels. However, the problem of finding an analytical upper bound on the bit error rate of the Viterbi detector in this case has not been fully investigated. Current techniques rely on an exhaustive enumeration of short error
doi:10.1109/glocom.2010.5683963
dblp:conf/globecom/KumarRS10
fatcat:fvnpmaqjfvdndhxrwjckufm6ji