Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/459159
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dc.coverage.spatialCooperative spectrum sensing Techniques using fuzzy logic and Genetic algorithm
dc.date.accessioned2023-02-16T11:22:35Z-
dc.date.available2023-02-16T11:22:35Z-
dc.identifier.urihttp://hdl.handle.net/10603/459159-
dc.description.abstractSpectrum sensing play a key role in Cognitive Radio (CR) technology to identify the unused spectrum available in a spectrum band. Cooperative Spectrum Sensing (CSS) Technique use Secondary Users (SU) or unlicensed users to sense the Primary User (PU) or licensed user spectrum band. The sensing information received from the PU by all SU is passed to the Fusion Centre (FC) to decides the presence or absence of spectrum hole in a PU. newlineCR technology identifies the unused spectrum band and support to utilize the available spectrum band more efficiently. Spectrum Sensing is a challenging task to identify the available unused spectrum in a wireless channel environment due to fading, noise uncertainty, shadowing effects. Due to noise uncertainty, the detection of PU signal in the noise dominant region, where the Signal to Noise Ratio (SNR) value is at negative region is a challenging task. The SU quantize the sensing information to take local decision and transmitted as a one-bit information to the FC for final decision which leads to misdetection due to quantization error. Sensing time is increased due to local decision and waiting for receiving final decision from FC. There is no previous received sample dataset for reference to fix the threshold value. Only one PU detection is performed when one or more SU is in need of spectrum hole for transmission in a CSS model newline
dc.format.extentxxii,151p.
dc.languageEnglish
dc.relationp.143-150
dc.rightsuniversity
dc.titleCooperative spectrum sensing Techniques using fuzzy logic and Genetic algorithm
dc.title.alternative
dc.creator.researcherVenkateshkumar, U
dc.subject.keywordEngineering and Technology
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordCOGNITIVE RADIO
dc.subject.keywordGENETIC ALGORITHM
dc.description.note
dc.contributor.guideRamakrishnan, S
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2021
dc.date.awarded2021
dc.format.dimensions21cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File52.98 kBAdobe PDFView/Open
02_prelim pages.pdf2.81 MBAdobe PDFView/Open
03_content.pdf183.55 kBAdobe PDFView/Open
04_abstract.pdf102.64 kBAdobe PDFView/Open
05_chapter 1.pdf1.4 MBAdobe PDFView/Open
06_chapter 2.pdf1.09 MBAdobe PDFView/Open
07_chapter 3.pdf1.31 MBAdobe PDFView/Open
08_chapter 4.pdf1.54 MBAdobe PDFView/Open
09_chapter 5.pdf1.55 MBAdobe PDFView/Open
10_chapter 6.pdf1.41 MBAdobe PDFView/Open
11_chapter 7.pdf280.94 kBAdobe PDFView/Open
12_annexures.pdf112.42 kBAdobe PDFView/Open
80_recommendation.pdf2.46 MBAdobe PDFView/Open


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