Blind deconvolution using a maximum likelihood channel estimator

A channel estimator is presented that does not depend on a learning sequence or estimated data sequence for identifying the unknown channel. The authors endeavor to solve the problem of blind equalization in two steps. First, a maximum-likelihood estimate is made of the unknown channel from the received data alone. These estimates are then used in a maximum likelihood sequence (Viterbi) decoder to recover the transmitted digital message. Simulation results show that the probability of error obtained by this approach is comparable to that obtained with a Viterbi decoder operating with known rather than estimated channel symbols.<
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