Adaptive channel equalization using context trees


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

Intersymbol Interference Equalization by Universal Likelihood

  • Owen Ernest Kelly
  • 1996
1 Excerpt

On some relationship between the context tree weighting and general model weighting techniques for tree sources

  • Joe Suzuki
  • 1995
1 Excerpt

Digital Communications

  • John G Proakis
  • 1989
1 Excerpt