Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/6113
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dc.contributor.authorOhize, Henry-
dc.contributor.authorMqhele, Dlodlo-
dc.contributor.authorOnumanyi, Dlodlo-
dc.contributor.authorBello-Salau, Habeeb-
dc.date.accessioned2021-07-03T11:31:00Z-
dc.date.available2021-07-03T11:31:00Z-
dc.date.issued2017-
dc.identifier.citationOhize, H.O, Adeiza Onumanyi, Mqhele Dlodlo, Habeeb Bello-Salau. “An Adaptive Wavelet-Based Scale Space Filtering Algorithm for Spectrum Sensing in Cognitive Radio” in the Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC). San Francisco, CA, USA 2017.en_US
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/6113-
dc.description.abstractAbstract—This paper introduces a novel application of an enhanced Wavelet-based Scale Space Filtering (WSSF) algorithm called Adaptive WSSF (AWSSF). The AWSSF concept was conceived to improve Spectrum Sensing (SS) in Cognitive Radio (CR). The algorithm is based on a novel adaptation of the WSSF and Otsu’s algorithm (from Image Processing). The AWSSF decomposes the estimated signals into different scale levels by using Wavelet Transformation (WT) theory. Thereafter, it directly multiplies samples from adjacent scales towards reducing the noise samples, while simultaneously increasing the true Licensed User (LU) signals. Furthermore, we adapted Otsu’s multi-threshold algorithm for use in the AWSSF to compute the optimum threshold value for the different decomposition levels towards filtering the wavelet coefficients. During evaluation in the low Signal to Noise Ratio (SNR) region, the AWSSF algorithm was compared to the traditional ED, and shown to perform better. We also compared with other WT based approaches at SNR = -10dB, and the AWSSF achieved better results. The AWSSF met the performance requirement of the IEEE 802.22 standard as compared to other approaches, and thus considered viable for application in CR. Index Terms—Wavelet Transform, spectrum sensing, cognitive radio, Otsu threshold, energy detector, Adaptiveen_US
dc.description.sponsorshipTetFunden_US
dc.language.isoenen_US
dc.publisherIn the Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC).en_US
dc.relation.ispartofseries978-1-5090-4183-1/17;-
dc.subjectWavelet Transformen_US
dc.subjectSpectrum Sensingen_US
dc.subjectEnergy Detectoren_US
dc.subjectCognitive Radioen_US
dc.subjectAdaptiveen_US
dc.subjectOtsuen_US
dc.titleAn Adaptive Wavelet-Based Scale Space Filtering Algorithm for Spectrum Sensing in Cognitive Radioen_US
dc.typeArticleen_US
Appears in Collections:Electrical/Electronic Engineering

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