Exploiting knowledge management for supporting spectrum selection in cognitive radio networks
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hdl:2117/16741
Document typeConference lecture
Defense date2012
Rights accessRestricted access - publisher's policy
Abstract
Abstract—In order to increase Cognitive Radio operation
efficiency, this paper builds up a new knowledge management
functional architecture for supporting spectrum management. It
integrates the fittingness factor concept proposed by the authors
in a prior work and includes a set of advanced statistics capturing
the influence of the radio environment. Then, a Knowledge
Manager (KM) exploiting these statistics and observed fittingness
factor values has been developed to monitor the time-varying
suitability of spectrum resources to support heterogeneous services.
Based on estimated suitability levels, a new strategy
combining Spectrum Selection (SS) and Spectrum Mobility (SM)
functionalities has been proposed. Results have shown that the
proposed strategy efficiently exploits the KM support at low loads
and the SM functionality at high loads to introduce significant
gains (ranging from 85% to 100%) w.r.t. a pure random selection
while exhibiting substantial robustness to changes in interference
levels.
CitationPérez-Romero, J. [et al.]. Exploiting knowledge management for supporting spectrum selection in cognitive radio networks. A: International Conference on Cognitive Radio Oriented Wireless Networks. "7th International Conference on Cognitive Radio Oriented Wireless Networks conference proceedings". Estocolm: 2012, p. 1-6.
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