A Framework for User Traffic Prediction and Resource Allocation in 5G Networks

A Framework for User Traffic Prediction and Resource Allocation in 5G Networks

Fifth-Generation (5G) networks deal with dynamic fluctuations in user traffic and the demands of each connected user and application. This creates a need for optimized resource allocation to reduce network congestion in densely populated urban centers and further ensure Quality of Service (QoS) in (...

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Bibliographic Details
Main Authors: Ioannis Konstantoulas, Iliana Loi, Dimosthenis Tsimas, Kyriakos Sgarbas, Apostolos Gkamas, Christos Bouras
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Applied Sciences
Subjects:
5G networks
user allocation
traffic prediction
deep learning
long-short term neural networks
Transformers
Online Access:https://www.mdpi.com/2076-3417/15/13/7603
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