Title:
Spectrum management in cognitive radio wireless networks

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dc.contributor.advisor Akyildiz, Ian F.
dc.contributor.author Lee, Won Yeol en_US
dc.contributor.committeeMember Ammar, Mostafa
dc.contributor.committeeMember Laskar, Joy
dc.contributor.committeeMember Li, Ye
dc.contributor.committeeMember Sivakumar, Raghupathy
dc.contributor.department Electrical and Computer Engineering en_US
dc.date.accessioned 2010-01-29T19:43:59Z
dc.date.available 2010-01-29T19:43:59Z
dc.date.issued 2009-08-17 en_US
dc.description.abstract The wireless spectrum is currently regulated by government agencies and is assigned to license holders or services on a long-term basis over vast geographical regions. Recent research has shown that a large portion of the assigned spectrum is used sporadically, leading to underutilization and waste of valuable frequency resources. Consequently, dynamic spectrum access techniques are proposed to solve these current spectrum inefficiency problems. This new area of research foresees the development of cognitive radio (CR) networks to further improve spectrum efficiency. The basic idea of CR networks is that the unlicensed devices (also called CR users) share wireless channels with the licensed devices (also known as primary users) that are already using an assigned spectrum. CR networks, however, impose unique challenges resulting from high fluctuation in the available spectrum, as well as diverse quality-of-service (QoS) requirements. These challenges necessitate novel cross-layer techniques that simultaneously address a wide range of communication problems from radio frequency (RF) design to communication protocols, which can be realized through spectrum management functions as follows: (1) determine the portions of the spectrum currently available (spectrum sensing), (2) select the best available channel (spectrum decision), (3) coordinate access to this channel with other users (spectrum sharing), and (4) effectively vacate the channel when a primary user is detected (spectrum mobility). In this thesis, a spectrum management framework for CR networks is investigated that enables seamless integration of CR technology with existing networks. First, an optimal spectrum sensing framework is developed to achieve maximum spectrum opportunities while satisfying interference constraints, which can be extended to multi-spectrum/multi-user CR networks through the proposed sensing scheduling and adaptive cooperation methods. Second, a QoS-aware spectrum decision framework is proposed where spectrum bands are determined by considering the application requirements as well as the dynamic nature of the spectrum bands. Moreover, a dynamic admission control scheme is developed to decide on the spectrum bands adaptively dependent on the time-varying CR network capacity. Next, for spectrum sharing in infrastructure-based CR networks, a joint spectrum and power allocation scheme is proposed to achieve fair resource allocation as well as maximum capacity by opportunistically negotiating additional spectrum based on the licensed user activity (exclusive allocation) and having a share of reserved spectrum for each cell (common use sharing). Finally, we propose a novel CR cellular network architecture based on the spectrum-pooling concept, which mitigates the heterogeneous spectrum availability. Based on this architecture, a unified mobility management framework is devised to support both user and spectrum mobilities in CR networks. en_US
dc.description.degree Ph.D. en_US
dc.identifier.uri http://hdl.handle.net/1853/31712
dc.publisher Georgia Institute of Technology en_US
dc.subject Cognitive radio en_US
dc.subject Spectrum management en_US
dc.subject Spectrum sensing en_US
dc.subject Spectrum decision en_US
dc.subject Spectrum sharing en_US
dc.subject Spectrum mobility en_US
dc.subject.lcsh Cognitive radio networks
dc.subject.lcsh Radio
dc.title Spectrum management in cognitive radio wireless networks en_US
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.corporatename School of Electrical and Computer Engineering
local.contributor.corporatename College of Engineering
relation.isOrgUnitOfPublication 5b7adef2-447c-4270-b9fc-846bd76f80f2
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
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