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Spectrum Decision Support Framework for Cognitive Radio Networks

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dc.contributor.author Akhtar, Ahmad Naeem
dc.date.accessioned 2019-10-18T11:25:40Z
dc.date.accessioned 2020-04-11T15:39:54Z
dc.date.available 2020-04-11T15:39:54Z
dc.date.issued 2018
dc.identifier.govdoc 17586
dc.identifier.uri http://142.54.178.187:9060/xmlui/handle/123456789/5255
dc.description.abstract The exponential increase of mobile devices and the wide availability of bandwidth-hungry applications have created an eruption in mobile data traffic. Such extraordinary evolution in wireless data usage cause a severe capacity shortage in wireless mobile networks and presents substantial challenges to cellular operators and telecommunication regulatory au thorities. Operators consider various technologies to improve their infrastructure, such as upgrading their entire network to LTE, taking advantage of existing available spectrum, or leveraging new spectrum opportunities such as the newly vacated TV band. However, such networkdesignsdonotfacilitaterobustnessinspectrumusage. CognitiveRadioNetworkof fersacapablesolutionforassuagingthisproblem. Inmobilenetworks,thewirelessspectrum bands are also used by the secondary users in the absence of the licensed users. Spectrum decision is to be performed by secondary users while catering for the inconsistent behavior of fluctuating nature of spectrum slots and diverse service requirements of various wireless applications, secondary users have to adopt, aiming at optimizing the transmission perfor mance of SUs. A SU has to sense multiple target spectrum slots in the shortest possible time before deciding to select and occupy the most suitable to its QoS requirements idle slot for its transmission. Spectrum decision process selects the most suited slot from these availableslotsforopportunisticusebysecondaryusers. AsupportframeworkforCRNshas been proposed, which is called Spectrum decision Support Framework (SDSF). SDSF of fers an intelligent spectrum decision scheme that first senses the idle slots and then enables SUs to swiftly occupy them effectively. SDSF integrates various spectrum decision tech niquesandtakesintoaccountvariousspectrumslotcharacterizationparameters. Ascientific support framework has been developed for SUs in the CRN which includes spectrum slot viz-a-viz SUs’ QoS requirements, simulation evaluation duly validated by practical imple mentation. In this thesis, the proposed SDSF not only enables SUs to occupy the discretely time and frequency slotted channels in the entire wireless spectrum encompassing the spec trum bands of IEEE802.22, GSM, CDMA, LTE, IEEE802.11, Bluetooth, UWB and 5G, but also guarantees QoS requirements of SUs as per wireless service applications and ensures no interference with PUs. Initially the SDSF comprise of three wireless spectrum slot pa rameters; spectrum slot idle time, measured with the history of PUs’ access, spectrum slot possessionbythePUsandthespectrumslotQoS.Thisschemewasvalidatedbytheachieved throughput of SUs at the end of its transmission. The achieved throughput leads to the log ical architectural design of 5G services providing flexibility required to support efficiently a heterogeneous set of wireless services including Internet of Things traffic. The proposed SDFS guaranteed QoS requirements for these applications in terms of end-to-end latency, SUs’mobilityandnointerferencewithPUsaswellaswithotherSUsofCRN.Anempirical SDSF for CRNs consisting of a signal generator, USRP2 and a network analyzer based on the sensing data achieved by a central SU from other (slave) SUs in the CRN has also been proposed. The results obtained validates that the proposed SDSF satisfies complementary receiver operating characteristics at various signal to noise ratio, end-to-end latency and the networkcongestion. Thesimulationresultsindicatethevalidityoftheproposedschemesfor spectrum decision for cognitive radio networks. en_US
dc.description.sponsorship Higher Education Commission, Pakistan en_US
dc.language.iso en_US en_US
dc.publisher National University of Science & Technology, Islamabad en_US
dc.subject Electrical Engineering en_US
dc.title Spectrum Decision Support Framework for Cognitive Radio Networks en_US
dc.type Thesis en_US


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