Notcker, Joachim and Covenant University, Theses (2023) A SPECTRUM SENSING AND ALLOCATION MODEL FOR PRIMARY USER DETECTION AND INTERFERENCE MITIGATION IN TELEVISION WHITESPACE. Masters thesis, Covenant University Ota.
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Abstract
TV White Space (TVWS) is a potentially useful method for overcoming the problem of limited wireless communication spectrum. It refers to the spectrum between 54 MHz and 790 MHz, and its propagation properties have been the focus of an increasing number of investigations in recent years. However, interference is one of the significant issues that limit the utilization of available spectrum in television (TV) bands, lower the quality of services among cognitive(secondary) users, and cause harmful destruction to licensed (primary) users. Extensive works have been devoted to the issue of interference in TVWS networks, with many studies focusing on either preventing interference between primary and secondary users by detecting the presence of primary users, or mitigating interference among cognitive users but did not combine the two. As a result, this work developed an architectural model that integrates spectrum sensing and allocation components to identify the presence of primary user and reducing interference among cognitive users. For spectrum sensing component, an energy detection model was adopted to recognize a primary user so as to avoid interference with secondary users whereas for spectrum allocation component, the particle swarm optimization algorithm was employed to find the optimal allocation of channels among secondary users which result on reducing interference among them. The architectural model was implemented in simulated Cognitive TVWS network using MATLAB R2020a, and its performance was analyzed by taking into account false alarm probability, detection probability, signal to noise ratio (SNR), misdetection probability, and sum throughput. The simulation results showed that when SNR was set to -10 dB, the detection probability for the energy detection was 98.23%, while the matched filter was 92.55%. At false alarm probability of 0.51, the misdetection probability for the energy detection was 0.13%, while the matched filter had a misdetection probability of 2.61%. When 10 channels and 100 secondary users were considered, particle swarm optimization achieved maximum throughput of 279.9 Mbps while artificial bee colony achieved 278.7 Mbps. For 30 channels and 200 secondary users, 1.575Gbps and 1.571Gpps were achieved by particle swarm optimization and artificial bee colony algorithm respectively. Finally, when the number of channels were set to 50 and users to 300, particle swarm optimization achieved 3.879Gbps while artificial bee colony achieves 3.864Gbps. Therefore, the developed energy detection and particle swarm algorithms outperform matched filter and artificial bee colony algorithms respectively.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Spectrum Sensing, Spectrum Allocation, Television Whitespace, Primary User, Interference Mitigation and Secondary User |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | nwokealisi |
| Date Deposited: | 14 Apr 2023 11:29 |
| Last Modified: | 14 Apr 2023 11:29 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/16803 |
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