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cs.LG2026
AI-Enhanced Spatial Cellular Traffic Demand Prediction with Contextual Clustering and Error Correction for 5G/6G Planning
Mohamad Alkadamani, Colin Brown, Halim Yanikomeroglu
Accurate spatial prediction of cellular traffic demand is essential for 5G NR capacity planning, network densification, and data-driven 6G planning. Although machine learning can f…
cs.LG2026
A Graph-Based Approach to Spectrum Demand Prediction Using Hierarchical Attention Networks
Mohamad Alkadamani, Halim Yanikomeroglu, Amir Ghasemi
The surge in wireless connectivity demand, coupled with the finite nature of spectrum resources, compels the development of efficient spectrum management approaches. Spectrum shari…