Adaptive channel equalization using context trees

Abstract

The maximum likelihood sequence estimator is the optimal receiver for the inter-symbol interference (ISI) channel with additive white noise. A receiver is demonstrated that estimates sequence likelihood using a variable order Markov model constructed from a crudely quantized training sequence. Receiver performance is relatively unaffected by heavy-tailed noise that can undermine the performance of Gaussian based algorithms such as decision feedback equalization with gradient based (LMS) adaptation. We consider the problem of decoding binary symbols across a linear ISI channel contaminated with additive white noise. Given discrete-time observations of the channel output r n

DOI: 10.1109/ICASSP.1997.598924

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Showing 1-7 of 7 references

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1 Excerpt

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