Data-driven handover optimization in LTE mobile network
| dc.contributor.author | Kabache et Kermiche, med lamine et Derradji | |
| dc.date.accessioned | 2020-11-11T13:11:07Z | |
| dc.date.available | 2020-11-11T13:11:07Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | The aim of this work is to study and analyze user mobility in mobile networks. Navigating heterogeneous networks, this means that your mobile device changes its link point. The study that was conducted required the implementation of accurate algorithms to make the decision to change the link more dynamic with the user's mobility, in order to ensure the continuity and quality of the service provided. Apply deep learning algorithm using Python program to improve the delivery algorithm. | en_US |
| dc.identifier.uri | http://dspace.univ-msila.dz:8080//xmlui/handle/123456789/20343 | |
| dc.language.iso | en | en_US |
| dc.publisher | FACULTY: Mathematics and Computer Science DEPARTEMENT: Computer Science - OPTION : RTIC | en_US |
| dc.subject | LTE, Handover, mobility, Q-learning, NS-3 | en_US |
| dc.title | Data-driven handover optimization in LTE mobile network | en_US |
| dc.type | Thesis | en_US |