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Hidden Markov model based spectrum sensing for cognitive radio

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dc.contributor.advisor Mark, Brian L.
dc.contributor.advisor Ephraim, Yariv
dc.contributor.author Nguyen, Thao Tran Nhu
dc.creator Nguyen, Thao Tran Nhu
dc.date.accessioned 2013-08-09T15:40:06Z
dc.date.available 2013-08-09T15:40:06Z
dc.date.issued 2013 en_US
dc.identifier.uri https://hdl.handle.net/1920/8288
dc.description.abstract Cognitive radio is an emerging technology for sensing and opportunistic spectrum access in wireless communication networks. It allows a secondary user to detect under-utilized spectrum of a primary user and to dynamically access the spectrum without causing harmful interference to the primary user. A number of spectrum sensing techniques has been proposed in the literature to identify the state of the primary user in the temporal domain. However, most of these techniques make instantaneous decisions based on current measurement received at the cognitive radio, and they do not consider the transmission pattern of the primary user which can be acquired from past measurements. Thus, sensing performance can be improved by incorporating measurement history into the sensing decision. Moreover, using all available data may enable prediction of the primary user activity, which will allow a cognitive radio to better plan for its spectrum usage.
dc.format.extent 92 pages en_US
dc.language.iso en en_US
dc.rights Copyright 2013 Thao Tran Nhu Nguyen en_US
dc.subject Engineering en_US
dc.subject Baum algorithm en_US
dc.subject Bivariate Markov chain en_US
dc.subject Cognitive radio en_US
dc.subject Hidden Markov model en_US
dc.subject Spectrum Sensing en_US
dc.title Hidden Markov model based spectrum sensing for cognitive radio en_US
dc.type Dissertation en
thesis.degree.level Doctoral en
thesis.degree.discipline Electrical and Computer Engineering en
thesis.degree.grantor George Mason University en


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