Spatio-temporal traffic data analysis is essential for 5G and intelligent network systems. However, existing methods often employ isolated models, neglecting shared spatiotemporal correlations and incurring prohibitive computational overhead. To address these issues, we propose UniST, a unified spatio-temporal multi-ta...
Long-Fei Zhang, Peng-Cheng Xia, Xiang Sun et al.· 2026 IEEE 22nd International...· 0 citations
As Fifth Generation (5G) networks evolve toward Sixth Generation (6G), base station energy consumption poses a critical challenge for sustainable wireless infrastructure, demanding intelligent and adaptive resource management strategies. Reinforcement learning (RL) offers a promising approach for such dynamic optimizat...
HiDD-Net is proposed, a hierarchical dual-domain distillation framework that combines a teacher network that integrates multi-granularity spatial views via a cross-attention mechanism to explicitly align fine-grained anomalies with global context, and a compact student model that achieves a competitive cross-dataset av...
