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dc.contributor.supervisor Cai, Jun (Electrical and Computer Engineering) en_US
dc.contributor.author Tian, Hongqiao
dc.date.accessioned 2016-06-20T16:28:15Z
dc.date.available 2016-06-20T16:28:15Z
dc.date.issued 2015 en_US
dc.identifier.citation IEEE en_US
dc.identifier.uri http://hdl.handle.net/1993/31504
dc.description.abstract We study a dynamic channel selection framework for cognitive radio networks (CRNs) which support both delay sensitive and best effort services. Unlike existing works in the literature, we consider the effect of heterogeneous radio frequency characteristics and heterogeneous primary user activities on channel selection in multi-channel CRNs. Optimal spectrum decision policies are obtained to achieve minimum delay using dynamic programming techniques, such as Markov decision process (MDP) and reinforcement learning, under different assumptions. To address the computational complexity issue in the MDP solutions, a myopic scheme is proposed based on the estimated packet sojourn time. en_US
dc.publisher IEEE en_US
dc.rights info:eu-repo/semantics/openAccess
dc.subject Spectrum Decision, Cognitive Radio Networks en_US
dc.title Dynamic spectrum decision in multi-channel cognitive radio networks with heterogeneous services en_US
dc.type info:eu-repo/semantics/masterThesis
dc.type master thesis en_US
dc.degree.discipline Electrical and Computer Engineering en_US
dc.contributor.examiningcommittee Alfa, Attahiru S. (Electrical and Computer Engineering) Wang, Yang (Computer Science) en_US
dc.degree.level Master of Science (M.Sc.) en_US
dc.description.note October 2016 en_US


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