ICASSP 1997, 22nd IEEE international conference on acoustics, speech, and signal processing, April 21-24, 1997, Munich, Germany
We present two approaches to stochastic Maximum Likelihood identi cation of multiple FIR channels, where the input symbols are assumed Gaussian and the channel de terministic. These methods allow semi-blind identification, as they accommodate a priori knowledge in the form of a (short) training sequence and appears to be more relevant in practice than purely blind techniques. The two approaches are parameterized both in terms of channel coecients and in terms of prediction lter coefficients. Corresponding methods are presented and some are simulated. Furthermore, Cramer-Rao Bounds for semi-blind ML are presented: a significant improvement of the performance for a moderate number of known symbols can be noticed.
Type:
Conférence
City:
Munich
Date:
1997-04-21
Department:
Systèmes de Communication
Eurecom Ref:
81
Copyright:
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