ilias-chatzistefanidis/HetNets-steering
Repo containing Channel Quality Indicator (CQI) data from real car routes in Greece. It contains a reproducable notebook with the implementation of a Bidirectional LSTM Neural Network for real-time CQI forecasting in heterogeneous ultra-dense beyond-5G networks.
This project helps telecommunications network engineers predict mobile network quality in real-time. By analyzing Channel Quality Indicator (CQI) data from mobile devices, it forecasts future link quality. This allows network operators to intelligently direct traffic to ensure a better user experience in complex 5G networks.
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Use this if you need to build or evaluate intelligent traffic steering mechanisms in heterogeneous 5G networks to optimize user Quality of Experience (QoE).
Not ideal if you are looking for a general-purpose forecasting tool outside of cellular network performance data.
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Last pushed
Apr 10, 2024
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