Analysis and Design of Cognitive Radio Networks and Distributed Radio Resource Management Algorithms

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dc.contributor.authorNeel, James O'Daniellen
dc.contributor.committeechairReed, Jeffrey H.en
dc.contributor.committeememberGiles, Robert H. Jr.en
dc.contributor.committeememberBuehrer, R. Michaelen
dc.contributor.committeememberDaSilva, Luiz A.en
dc.contributor.committeememberMacKenzie, Allen B.en
dc.contributor.departmentElectrical and Computer Engineeringen
dc.date.accessioned2014-03-14T20:19:59Zen
dc.date.adate2007-03-16en
dc.date.available2014-03-14T20:19:59Zen
dc.date.issued2006-09-06en
dc.date.rdate2007-03-16en
dc.date.sdate2006-12-08en
dc.description.abstractCognitive radio is frequently touted as a platform for implementing dynamic distributed radio resource management algorithms. In the envisioned scenarios, radios react to measurements of the network state and change their operation according to some goal driven algorithm. Ideally this flexibility and reactivity yields tremendous gains in performance. However, when the adaptations of the radios also change the network state, an interactive decision process is spawned and once desirable algorithms can lead to catastrophic failures when deployed in a network. This document presents techniques for modeling and analyzing the interactions of cognitive radio for the purpose of improving the design of cognitive radio and distributed radio resource management algorithms with particular interest towards characterizing the algorithms' steady-state, convergence, and stability properties. This is accomplished by combining traditional engineering and nonlinear programming analysis techniques with techniques from game to create a powerful model based approach that permits rapid characterization of a cognitive radio algorithm's properties. Insights gleaned from these models are used to establish novel design guidelines for cognitive radio design and powerful low-complexity cognitive radio algorithms. This research led to the creation of a new model of cognitive radio network behavior, an extensive number of new results related to the convergence, stability, and identification of potential and supermodular games, numerous design guidelines, and several novel algorithms related to power control, dynamic frequency selection, interference avoidance, and network formation. It is believed that by applying the analysis techniques and the design guidelines presented in this document, any wireless engineer will be able to quickly develop cognitive radio and distributed radio resource management algorithms that will significantly improve spectral efficiency and network and device performance while removing the need for significant post-deployment site management.en
dc.description.degreePh. D.en
dc.identifier.otheretd-12082006-141855en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12082006-141855/en
dc.identifier.urihttp://hdl.handle.net/10919/29998en
dc.publisherVirginia Techen
dc.relation.haspartNeel_diss.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectSensor Networksen
dc.subject802.22en
dc.subject802.11en
dc.subjectInterference Reducing Networken
dc.subjectPotential Gamesen
dc.subjectGame Theoryen
dc.subjectSDRen
dc.subjectSoftware Radioen
dc.subjectCognitive radio networksen
dc.subjectDistributed Radio Resource Managementen
dc.subjectMANETen
dc.subjectAd-hoc Networken
dc.subjectDynamic Frequency Selectionen
dc.subjectPower Controlen
dc.titleAnalysis and Design of Cognitive Radio Networks and Distributed Radio Resource Management Algorithmsen
dc.typeDissertationen
thesis.degree.disciplineElectrical and Computer Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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