Machine learning based traffic analysis and forecast for 5G Systems

Bernabè, Matteo (2021) Machine learning based traffic analysis and forecast for 5G Systems. [Laurea magistrale], Università di Bologna, Corso di Studio in Telecommunications engineering [LM-DM270], Documento full-text non disponibile
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Mobile traffic forecasting is a relatively new research area, which is becoming of fundamental importance for next-generation networks. Proactively knowing the user demand allows the system to allocate resources and apply energy-saving decisions properly. Classical models are limited by the stationary assumption of time sequences and fail to take correlations into account. This work presents results on cellular network traffic analysis and prediction, providing a novel, robust, and precise machine learning model to efficiently and dynamically manage network resources in 5G systems.

Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Bernabè, Matteo
Relatore della tesi
Correlatore della tesi
Corso di studio
Ordinamento Cds
Parole chiave
Machine learning,mobile cellular traffic,traffic forecasting,time series,deep learning,graph neural network,5G,traffic prediction,mobile cellular traffic prediction
Data di discussione della Tesi
10 Marzo 2021

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