NDLI: Joint parameter estimation and symbol detection for linear or nonlinear unknown channels

Content Provider	IEEE Xplore Digital Library
Author	Ghassan Kawas Kaleh Vallet, R.
Copyright Year	1972
Abstract	We present an iterative method for joint channel parameter estimation and symbol selection via the Baum-Welch algorithm, or equivalently the Expectation-Maximization (EM) algorithm. Channel parameters, including noise variance, are estimated using a maximum likelihood criterion. The Markovian properties of the channel state sequence enable us to calculate the required likelihood using a forward-backward algorithm. The calculated likelihood functions can easily give optimum decisions on information symbols which minimize the symbol error probability. The proposed receiver can be used for both linear and nonlinear channels. It improves the system throughput by making saving in the transmission of known symbols, usually employed for channel identification. Simulation results which show fast convergence are presented.<>
Starting Page	2406
Ending Page	2413
Page Count	8
File Size	733290
File Format	PDF
ISSN	00906778
Volume Number	42
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-07-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Parameter estimation Iterative algorithms Throughput Modems Hidden Markov models Maximum likelihood detection Maximum likelihood estimation Error probability Convergence Dispersion
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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