Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/11981
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dc.contributor.authorMahima, Bansal-
dc.date.accessioned2023-08-24T08:41:29Z-
dc.date.available2023-08-24T08:41:29Z-
dc.date.issued2023-06-01-
dc.identifier.urihttp://10.1.7.192:80/jspui/handle/123456789/11981-
dc.description.abstract5G technology allows for the creation of a novel network that connects people, machines, objects, and gadgets. Its goal is to provide more users with faster data speeds, minimal delays in data transmission, improved reliability, larger network coverage, and a user encounter that is commendable. 5G’s enhanced efficiency and performance and innovative user experiences, which can benefit various industries. This study focuses on the planning and deployment of 5G networks, with an emphasis on making the process more automated and streamlined, also known as ”Zero Touch”. Heuristic method like the genetic algorithm if used makes the network planning process optimized and the positions of the base stations in a particular geographic region will be reduced. Zero touch provisioning will help to make quicker and easier updates, reduce time of network operations and will cut costs by reducing the time spent on manual tasks.en_US
dc.publisherInstitute of Technologyen_US
dc.relation.ispartofseries21MCEI15;-
dc.subjectComputer 2021en_US
dc.subjectProject Report 2021en_US
dc.subjectComputer Project Reporten_US
dc.subjectProject Reporten_US
dc.subject21MCEen_US
dc.subject21MCEI15en_US
dc.subjectINSen_US
dc.subjectINS 2021en_US
dc.subjectCE (INS)en_US
dc.titleZero touch Provisioning using Evolutionary Computing approaches for Network planning in 5G ecosystemsen_US
dc.typeDissertationen_US
Appears in Collections:Dissertation, CE (INS)

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