3 papers
cs.LG2026
Multimodal Spatiotemporal-Frequency Fusion with Peak Enhancement for Cellular Traffic Forecasting
Qingzhong Li, Yue Hu, Hui Ma +4
Accurate forecasting of cellular network traffic is essential for network planning, resource allocation, and quality-of-service assurance in modern mobile communication systems. Re…
cs.AI2026
An Adaptive Differentially Private Federated Learning Framework
Jin Wang, Hui Ma, Yajun Zhang +4
Federated learning enables collaborative model training across distributed clients while preserving data privacy. However, in practical deployments, device heterogeneity and non-in…
cs.NI2026
GraFSTNet: Graph-based Frequency SpatioTemporal Network for Cellular Traffic Prediction
Ziyi Li, Hui Ma, Fei Xing +2
With rapid expansion of cellular networks and the proliferation of mobile devices, cellular traffic data exhibits complex temporal dynamics and spatial correlations, posing challen…