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In this work, the prediction of mobile communications traffic, based on available monitoring data, is addressed. Were used two strategies to predict the future ...
Request PDF | On Nov 1, 2019, Diogo Clemente and others published Assessment of Traffic Prediction Models for Mobile Communication Networks | Find, ...
Abstract—In mobile communication systems, radio access net- work cells transport data in resource elements. Each cell has a maximum capacity of resources ...
Sep 1, 2022 · In this survey, we review the relevant studies on cellular traffic prediction and classify the prediction problems as the temporal and spatiotemporal ...
May 8, 2024 · This paper investigates the efficacy of live prediction algorithms for forecasting cellular network traffic in real-time scenarios.
This survey encompasses representative data, model architectures, and state-of-the-art performance to provide a comprehensive account of deep learning ...
Apr 1, 2024 · A Cluster-based Lightweight PREdiction Model (CLPREM), a method for real-time traffic prediction of 5G mobile networks.
Network traffic prediction involves analyzing data flow patterns, behaviors, and relevant influencing factors within a network to forecast its traffic situation ...
Feb 13, 2020 · We studied the mobile communication traffic data from four aspects: model determination, model recognition, testing and predicting. Analyzing ...
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In this article, we propose Deep Traffic. Predictor (DeepTP), a deep-learning-based end-to- end model, which forecasts traffic demands from spatial-dependent ...