4 papers
Mitigating Heterogeneity-Induced Drift in Hierarchical Sign-Based Federated Learning
Amirreza Kazemi, Seyed Mohammad Azimi-Abarghouyi, Gabor Fodor +1
Hierarchical federated learning (HFL) is well suited for large-scale wireless and Internet of Things systems, where devices communicate with nearby edge servers before reaching the…
Advancing Network Digital Twin Framework for Generating Realistic Datasets
Oscar Stenhammar, Sundeep Rangan, Gábor Fodor +1
The integration of accurate and reproducible wireless network simulations is a key enabler for research on open, virtualized, and intelligent communication systems. Network Digital…
Joint Clustering and Prediction of the Quality of Service in Vehicular Cellular Networks
Oscar Stenhammar, Gábor Fodor, Carlo Fischione
Machine learning models are increasingly deployed in wireless networks with stringent performance requirements. However, dynamic propagation environments and fluctuating traffic de…
Machine Learning for Spectrum Sharing: A Survey
Francisco R. V. Guimarães, José Mairton B. da Silva, Charles Casimiro Cavalcante +3
The 5th generation (5G) of wireless systems is being deployed with the aim to provide many sets of wireless communication services, such as low data rates for a massive amount of d…