In this correspondence, we propose applying the hidden
Markov models (HMM) theory to the problem of blind channel estimation
and data detection. The Baum–Welch (BW) algorithm, which is able to
estimate all the parameters of the model, is enriched by introducing
some linear constraints emerging from a linear FIR hypothesis on the
channel. Additionally, a version of the algorithm that is suitable for timevarying
channels is also presented. Performance is analyzed in a GSM
environment using standard test channels and is found to be close to that
obtained with a nonblind receiver.
CitationAnton Haro, C.; Rodríguez Fonollosa, J. A.; Rodríguez Fonollosa, J. Blind channel estimation and data detection using hidden Markov models theory. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1997, vol. 45, núm. 1, p. 241-247.
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