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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...
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| Format: | Thesis |
| Language: | English English |
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Department of Electrical Engineering
2025
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| Summary: | 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. |
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