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Coverage Enhancement Using Heterogeneous Links for Smart Oceans

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dc.contributor.author Mustafa, Waqas
dc.date.accessioned 2024-05-31T09:47:05Z
dc.date.available 2024-05-31T09:47:05Z
dc.date.issued 2024
dc.identifier.other 359402
dc.identifier.uri http://10.250.8.41:8080/xmlui/handle/123456789/43713
dc.description Supervisor: Dr. Huma Ghafoor en_US
dc.description.abstract This study explores how cognitive radios can be used to leverage heterogeneous networks and enhance communication coverage in the maritime industry. Because of things like poor infrastructure, distance from shore stations, weather, and expensive deployment costs, maritime operations frequently struggle to establish consistent, longrange communication. The objective is to increase the communication coverage area of maritime systems to support a variety of marine users by employing unmanned aerial vehicles (UAVs) as mobile base stations and relays using clustering techniques. Coverage restrictions can be overcome by choosing the best routing paths by combining many communication technologies and taking advantage of their complementing capabilities. This thesis focuses at different heterogeneous connection configurations, evaluates their effectiveness, and talks about how relevant they are in marine environments. Comprehensive simulation results show how flexible cognitive radios are and how important they are for overcoming scarcity issue, especially in the harsh maritime environment where safe communication is essential. Moreover, the integration of UAVs in marine environment provides promising solution in an affordable way to increase network coverage. By choosing the best routes, the network becomes more flexible and resilient. It also uses less energy, low latency, manages spectrum issue efficiently, and has high packet delivery rates. en_US
dc.language.iso en en_US
dc.publisher School of Electrical Engineering and Computer Science,(SEECS) NUST en_US
dc.title Coverage Enhancement Using Heterogeneous Links for Smart Oceans en_US
dc.type Thesis en_US


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