Sequence estimation over linearly-constrained random channels.

This paper presents a new approach using EM(Expectation-Maximization) algorithms for ML (maximum like-lihood) sequence estimation over unknown ISI (inter-symbol in-terference) channels with linearly-constrained random channelcoefficients which may be fast time-varying. By using the EMformulation to marginalize over the underlying channel coeffi-cient distribution, maximum-likelihood estimates of the transmit-ted sequence are obtained. The EM algorithms are shown to per-form better, in terms of BER, than existing algorithms which per-form jointly-optimal sequence and channel estimation, or whichdo not take into account fast time-varying channel effects.

Main Author: Perry, Richard.
Other Authors: Buckley, Kevin.
Format: Villanova Faculty Authorship
Language: English
Published: 2000
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