Implicit channel estimation for ML sequence detection over finite-state Markov communication channels
Krusevac, Zarko; Kennedy, Rodney; Rapajic, Predrag
Description
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...[Show more]
dc.contributor.author | Krusevac, Zarko | |
---|---|---|
dc.contributor.author | Kennedy, Rodney | |
dc.contributor.author | Rapajic, Predrag | |
dc.coverage.spatial | Perth Australia | |
dc.date.accessioned | 2015-12-08T22:13:50Z | |
dc.date.available | 2015-12-08T22:13:50Z | |
dc.date.created | February 1-3 2006 | |
dc.identifier.isbn | 1424402131 | |
dc.identifier.uri | http://hdl.handle.net/1885/29979 | |
dc.description.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. | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE Inc) | |
dc.relation.ispartofseries | Australian Communications Theory Workshop (AusCTW 2006) | |
dc.source | Proceedings of the 7th Australian Communications Theory Workshop | |
dc.source.uri | http://ausctw06.watri.org.au | |
dc.subject | Keywords: Finite element method; Markov processes; Parameter estimation; Signal processing; Transfer functions; Feedback implicit estimators; Markov communication channels; Maximum entropy rate; Communication systems | |
dc.title | Implicit channel estimation for ML sequence detection over finite-state Markov communication channels | |
dc.type | Conference paper | |
local.description.notes | Imported from ARIES | |
local.description.refereed | Yes | |
dc.date.issued | 2006 | |
local.identifier.absfor | 100510 - Wireless Communications | |
local.identifier.absfor | 090609 - Signal Processing | |
local.identifier.ariespublication | u3357961xPUB70 | |
local.type.status | Published Version | |
local.contributor.affiliation | Krusevac, Zarko, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Kennedy, Rodney, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Rapajic, Predrag , University of Greenwich | |
local.bibliographicCitation.startpage | 128 | |
local.bibliographicCitation.lastpage | 134 | |
dc.date.updated | 2015-12-08T07:46:17Z | |
local.identifier.scopusID | 2-s2.0-33750943015 | |
Collections | ANU Research Publications |
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