Multi-Slot Cooperative Spectrum Sensing for Cognitive Radio Networks

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dc.contributor.advisorFalowo, Olabisi
dc.contributor.authorKombani, Ngonidzashe Gideon
dc.date.accessioned2025-11-26T08:51:08Z
dc.date.available2025-11-26T08:51:08Z
dc.date.issued2025
dc.date.updated2025-11-26T08:48:48Z
dc.description.abstractA key challenge with current radio access technologies and a consideration in the implementation of next generation radio access networks is limited spectrum availability. Current mobile technologies have been standardized to operate within reserved, dedicated frequency bands. Network operators are granted exclusive access to the allocated frequency bands, which are reserved regardless of users' activity. This exclusive reservation of frequency bands results in spectrum under-utilization in instances where the primary users of the spectrum are inactive. Research in spectrum utilization patterns has revealed significant occurrences of inactivity and sparse usage patterns within these reserved spectrum bands. This dissertation investigates spectrum sensing cognitive radio with the aim of identifying an efficient model to effectively utilize the available spectrum. A cooperative spectrum sensing cognitive radio model is presented based on energy detection sensing and multi-slot spectrum allocation. The model is evaluated based on two decision strategies, ‘Square Law Combining' Soft fusion, and ‘Majority Rule' Hard fusion sensing. The choice of applying energy detection for local spectrum sensing is due to its efficiency and simplicity in implementation. Simulations of the modelled cognitive radio system positively illustrate the feasibility of applying energy detection in cooperative sensing. Results also show that the soft fusion decision algorithm outperforms the hard fusion algorithm in energy sensing in terms of detection accuracy.
dc.identifier.apacitationKombani, N. G. (2025). <i>Multi-Slot Cooperative Spectrum Sensing for Cognitive Radio Networks</i>. (). University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/42345en_ZA
dc.identifier.chicagocitationKombani, Ngonidzashe Gideon. <i>"Multi-Slot Cooperative Spectrum Sensing for Cognitive Radio Networks."</i> ., University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering, 2025. http://hdl.handle.net/11427/42345en_ZA
dc.identifier.citationKombani, N.G. 2025. Multi-Slot Cooperative Spectrum Sensing for Cognitive Radio Networks. . University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering. http://hdl.handle.net/11427/42345en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Kombani, Ngonidzashe Gideon AB - A key challenge with current radio access technologies and a consideration in the implementation of next generation radio access networks is limited spectrum availability. Current mobile technologies have been standardized to operate within reserved, dedicated frequency bands. Network operators are granted exclusive access to the allocated frequency bands, which are reserved regardless of users' activity. This exclusive reservation of frequency bands results in spectrum under-utilization in instances where the primary users of the spectrum are inactive. Research in spectrum utilization patterns has revealed significant occurrences of inactivity and sparse usage patterns within these reserved spectrum bands. This dissertation investigates spectrum sensing cognitive radio with the aim of identifying an efficient model to effectively utilize the available spectrum. A cooperative spectrum sensing cognitive radio model is presented based on energy detection sensing and multi-slot spectrum allocation. The model is evaluated based on two decision strategies, ‘Square Law Combining' Soft fusion, and ‘Majority Rule' Hard fusion sensing. The choice of applying energy detection for local spectrum sensing is due to its efficiency and simplicity in implementation. Simulations of the modelled cognitive radio system positively illustrate the feasibility of applying energy detection in cooperative sensing. Results also show that the soft fusion decision algorithm outperforms the hard fusion algorithm in energy sensing in terms of detection accuracy. DA - 2025 DB - OpenUCT DP - University of Cape Town KW - Radio Networks KW - Cooperative Spectrum Sensing LK - https://open.uct.ac.za PB - University of Cape Town PY - 2025 T1 - Multi-Slot Cooperative Spectrum Sensing for Cognitive Radio Networks TI - Multi-Slot Cooperative Spectrum Sensing for Cognitive Radio Networks UR - http://hdl.handle.net/11427/42345 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/42345
dc.identifier.vancouvercitationKombani NG. Multi-Slot Cooperative Spectrum Sensing for Cognitive Radio Networks. []. University of Cape Town ,Faculty of Engineering and the Built Environment ,Department of Electrical Engineering, 2025 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/42345en_ZA
dc.language.isoen
dc.language.rfc3066eng
dc.publisher.departmentDepartment of Electrical Engineering
dc.publisher.facultyFaculty of Engineering and the Built Environment
dc.publisher.institutionUniversity of Cape Town
dc.subjectRadio Networks
dc.subjectCooperative Spectrum Sensing
dc.titleMulti-Slot Cooperative Spectrum Sensing for Cognitive Radio Networks
dc.typeThesis / Dissertation
dc.type.qualificationlevelMasters
dc.type.qualificationlevelMSc (Eng)
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