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Cognitive Radios: Discriminant Analysis for Automatic Signal Detection in Measured Power Spectra
Vrije Universiteit Brussel.
Vrije Universiteit Brussel.
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences. Vrije Universiteit Brussel. (Elektronik)
University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electronics, Mathematics and Natural Sciences. (Elektronik)ORCID iD: 0000-0001-5429-7223
2013 (English)In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 62, no 12, 3351-3360 p.Article in journal (Refereed) Published
Abstract [en]

Signal detection of primary users for cognitive radios enables spectrum use agility. In normal operation conditions, the sensed spectrum is nonflat, i.e., the power spectrum is not constant. A novel method proposes the segmentation of the measured spectra into regions where the flatness condition is approximately valid. As a result, an automatic detection of the significant spectral components together with an estimate of the magnitude of the spectral component and a measure of the quality of classification becomes available. In this paper, we optimize the methodology for signal detection in cognitive radios such that the probability that a spectral component was incorrectly classified is iteratively reduced. Simulation and measurement results show the advantages of the presented technique in different types of spectra.

Place, publisher, year, edition, pages
2013. Vol. 62, no 12, 3351-3360 p.
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:hig:diva-15966DOI: 10.1109/TIM.2013.2265607ISI: 000326979600024Scopus ID: 2-s2.0-84888038785OAI: oai:DiVA.org:hig-15966DiVA: diva2:685201
Available from: 2014-01-09 Created: 2014-01-09 Last updated: 2017-12-06Bibliographically approved

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