Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/571711
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dc.coverage.spatialCooperative spectrum management in cognitive radio networks using deep learning techniques
dc.date.accessioned2024-06-18T05:26:49Z-
dc.date.available2024-06-18T05:26:49Z-
dc.identifier.urihttp://hdl.handle.net/10603/571711-
dc.description.abstractSpectrum scarcity remains one of the major issues in the era of newlinewireless communication systems, and much of that must be attributed to newlineinefficient spectrum usage amongst licensed users. Governmental regulatory newlineorganizations like the Federal Communications Commission (FCC) manage newlinetraditional Radio Frequency (RF) spectrum allocation and establish newlinetransmission restrictions to ensure minimal spectral interference between newlinewireless devices. Improvements in Information and Communication newlineTechnology (ICT) may cause difficulty in spectrum management as new radio newlinespectrum-dependent devices emerge, placing a huge demand on the allocated newlinewireless spectrum. newlineCognitive Radio (CR) networks are an innovative technology that newlinefocuses on the radical shift in radio and networking technologies that ensemble newlinewith the potential to provide major performance gains in optimizing the newlineefficiency of any spectrum. Cognitive radios play a critical role in identifying newlineand sharing unused spectrum for dynamic, spectrum-demanding applications. newlineAs cognitive radio domains have started to progress significantly, new research newlineis required to address some prevailing technical challenges in dynamic newlinespectrum management methods such as spectrum sensing, monitoring, and newlinedynamic spectrum allocation. newline
dc.format.extentxix,146p.
dc.languageEnglish
dc.relationp.131-145
dc.rightsuniversity
dc.titleCooperative spectrum management in cognitive radio networks using deep learning techniques
dc.title.alternative
dc.creator.researcherSuriya M
dc.subject.keywordComputer Science
dc.subject.keywordComputer Science Information Systems
dc.subject.keywordEngineering and Technology
dc.description.note
dc.contributor.guideSumithra M G
dc.publisher.placeChennai
dc.publisher.universityAnna University
dc.publisher.institutionFaculty of Information and Communication Engineering
dc.date.registered
dc.date.completed2024
dc.date.awarded2024
dc.format.dimensions21cm.
dc.format.accompanyingmaterialDVD
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File24.96 kBAdobe PDFView/Open
02_prelim pages.pdf1.58 MBAdobe PDFView/Open
03_content.pdf31.35 kBAdobe PDFView/Open
04_abstract.pdf83.62 kBAdobe PDFView/Open
05_chapter1.pdf560.87 kBAdobe PDFView/Open
06_chapter2.pdf261.44 kBAdobe PDFView/Open
07_chapter3.pdf821.03 kBAdobe PDFView/Open
08_chapter4.pdf2.55 MBAdobe PDFView/Open
09_chapter5.pdf325.79 kBAdobe PDFView/Open
10_chapter6.pdf28.73 kBAdobe PDFView/Open
11_annexures.pdf137.61 kBAdobe PDFView/Open
80_recommendation.pdf68.59 kBAdobe PDFView/Open


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