Maximum-likelihood blind equalization

Monisha Ghosh; Charles L. Weber

doi:10.1117/12.49776

1 December 1991 Maximum-likelihood blind equalization

Monisha Ghosh, Charles L. Weber

Proceedings Volume 1565, Adaptive Signal Processing; (1991) https://doi.org/10.1117/12.49776
Event: San Diego, '91, 1991, San Diego, CA, United States

Abstract

A new approach to blind equalization is investigated in which the receiver performs joint data and channel estimation in an iterative manner. Hence, instead of estimating the channel inverse, the receiver computes the maximum likelihood estimate of the channel itself. The iterative algorithm involves maximum likelihood sequence estimation (Viterbi decoding) for the data estimation part and least squared estimation for the channel estimation part. A suboptimal algorithm is also proposed that uses a reduced-state trellis instead of the Viterbi algorithm. Simulation results show that the performance obtained by these algorithms is comparable to that of a receiver operating with complete knowledge of the channel.

Citation Download Citation

Monisha Ghosh and Charles L. Weber "Maximum-likelihood blind equalization", Proc. SPIE 1565, Adaptive Signal Processing, (1 December 1991); https://doi.org/10.1117/12.49776

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