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Implementation of Hidden Markov Model spectrum prediction algorithm

Black, Thomas; Kerans, B; Kerans, A

Description

The demand for spectrum is at an all time high due to the increasing popularity of wireless devices. As such it is imperative that technological and regulatory mechanisms are developed to maximise spectral efficiency. This paper documents a method for increasing spectral efficiency through the prediction of spectrum "holes" for use with cognitive radio technologies. An algorithm is developed based upon a Hidden Markov Model of the spectral environment. The Baum-Welch algorithm is employed to...[Show more]

dc.contributor.authorBlack, Thomas
dc.contributor.authorKerans, B
dc.contributor.authorKerans, A
dc.coverage.spatialGold Coast Australia
dc.date.accessioned2015-12-13T22:19:54Z
dc.date.createdOctober 2-5 2012
dc.identifier.isbn9781467311571
dc.identifier.urihttp://hdl.handle.net/1885/72072
dc.description.abstractThe demand for spectrum is at an all time high due to the increasing popularity of wireless devices. As such it is imperative that technological and regulatory mechanisms are developed to maximise spectral efficiency. This paper documents a method for increasing spectral efficiency through the prediction of spectrum "holes" for use with cognitive radio technologies. An algorithm is developed based upon a Hidden Markov Model of the spectral environment. The Baum-Welch algorithm is employed to dynamically calculate the transition parameters of the model. The algorithm is tested upon data collected from the 450-470 MHz band in Australia with a reward function implemented to analyse the performance of the algorithm.
dc.publisherIEEE Communications Society
dc.relation.ispartofseriesInternational Symposium on Communications and Information Technologies (ISCIT 2012)
dc.source.urihttp://www.iscit2012.org/
dc.subjectKeywords: Australia; Baum-Welch algorithms; Cognitive radio technologies; Markov model; Paper documents; Prediction algorithms; Regulatory mechanism; Reward function; Spectral efficiencies; Transition parameter; Wireless devices; Hidden Markov models; Information t
dc.titleImplementation of Hidden Markov Model spectrum prediction algorithm
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2012
local.identifier.absfor100510 - Wireless Communications
local.identifier.ariespublicationf5625xPUB3037
local.type.statusPublished Version
local.contributor.affiliationBlack, Thomas, College of Engineering and Computer Science, ANU
local.contributor.affiliationKerans, B, Australian Communications and Media Authority
local.contributor.affiliationKerans, A, James Cook University
local.description.embargo2037-12-31
local.bibliographicCitation.startpage280
local.bibliographicCitation.lastpage283
local.identifier.doi10.1109/ISCIT.2012.6380906
dc.date.updated2016-02-24T09:05:00Z
local.identifier.scopusID2-s2.0-84872165168
CollectionsANU Research Publications

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