An Adaptive Curriculum Event-Aware Federated Averaging Framework for Resource Demand Prediction in 5G Non-Standalone Networks
The dynamic and heterogeneous 5G traffic complicates short-term resource-demand prediction. While federated learning (FL) enables privacy-preserving training by keeping raw data local. However, FedAvg and FedProx do not explicitly account for client traffic heterogeneity or sudden demand variations. To address these li...
Rania Kheddara, Ahmed Belhani, Abdelouadoud Loukriz et al.
· Telecom · 0 citations