Stochastic maximum likelihood methods for semi-blind channel equalization

@article{Cirpan1997StochasticML,
  title={Stochastic maximum likelihood methods for semi-blind channel equalization},
  author={H. A. Cirpan and M. K. Tsatsanis},
  journal={Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136)},
  year={1997},
  volume={2},
  pages={1629-1632 vol.2}
}
A blind stochastic maximum likelihood channel equalization algorithm is adapted to incorporate a known training sequence as part of the transmitted frame. A hidden Markov model formulation of the problem is introduced and the Baum-Welch (1970) algorithm is modified to provide a computationally efficient solution to the resulting optimization problem. The proposed method provides a unified framework for semi-blind channel estimation, which exploits information from both the training and the… CONTINUE READING

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