Implicit channel estimation for ML sequence detection over finite-state Markov communication channels
Date
2006
Authors
Krusevac, Zarko
Kennedy, Rodney
Rapajic, Predrag
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE Inc)
Abstract
This paper shows the existence of the optimal training, in terms of achievable mutual information rate, for an output feedback implicit estimator for finite-state Markov communication channels. Implicit (blind) estimation is based on a measure of how modified is the input distribution when filtered by the channel transfer function and it is shown that there is no modification of an input distribution with maximum entropy rate. Input signal entropy rate reduction enables implicit (blind) channel process estimation, but decreases information transmission rate. The optimal input entropy rate (optimal implicit training rate) which achieves the maximum mutual information rate, is found.
Description
Keywords
Keywords: Finite element method; Markov processes; Parameter estimation; Signal processing; Transfer functions; Feedback implicit estimators; Markov communication channels; Maximum entropy rate; Communication systems
Citation
Collections
Source
Proceedings of the 7th Australian Communications Theory Workshop
Type
Conference paper