Cooperative Sensing Algorithm and Machine Learning Technique in Cognitive Radio Network

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atmire.migration.oldid3976
dc.contributor.advisorFattouche, Michael
dc.contributor.authorLu, Yingqi
dc.contributor.committeememberSesay, Abu
dc.contributor.committeememberBartley, Norman
dc.date.accessioned2016-01-05T18:48:55Z
dc.date.available2016-01-05T18:48:55Z
dc.date.issued2016-01-05
dc.date.submitted2015en
dc.description.abstractThis thesis investigates spectrum sensing for Cognitive Radio. First, we deal with the hidden node problem and the selection of sensing frequency in a P2P CR system. Different from existing models where TSU executes sensing and transmitting periodically, a novel detecting model is proposed to consider simultaneous sensing and transmitting. At RSU, BER estimation is applied to detect whether a PU is active or not. Simulation results show that i) simultaneous sensing improves spectrum utilization compared with periodical sensing; ii) The BER estimation improves the probability of detection and spectrum utilization. The second challenge related to decision fusion in cooperative sensing. We propose novel schemes based on machine learning and introduced probability vector to improve system performance. Simulation results demonstrate that the new schemes are better than the traditional ones. The probability vector can shorten the training duration and the classification delay compared with energy vector.en_US
dc.identifier.citationLu, Y. (2016). Cooperative Sensing Algorithm and Machine Learning Technique in Cognitive Radio Network (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/25463en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/25463
dc.identifier.urihttp://hdl.handle.net/11023/2722
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectEngineering--Electronics and Electrical
dc.subject.classificationCognitive Radio Networken_US
dc.subject.classificationMachine Learningen_US
dc.titleCooperative Sensing Algorithm and Machine Learning Technique in Cognitive Radio Network
dc.typemaster thesis
thesis.degree.disciplineElectrical and Computer Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameMaster of Science (MSc)
ucalgary.item.requestcopytrue
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