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.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…
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…