Quantifying the Operational Benefits of Deep Learning Based Dynamic Traffic Prediction using Real-World Dataset

A convolutional neural network is trained using real-world data, for dynamic prediction of the required transceivers supporting 6 G X -haul, leading to 20% and 16% lower average transceiver utilization over static and semi-static cases, respectively.