4 papers
Physics-Informed State Space Models for Day-Ahead Photovoltaic Power Forecasting
Phil Aupke, Muhammad Hassan, Khalid Ali +3
Accurate day-ahead photovoltaic (PV) power forecasting requires both strong temporal modeling and adherence to physical PV system constraints. Purely data-driven models often ignor…
Lightweight PID-Based Drift Mitigation for Cellular Traffic Forecasting
John Sengendo, Zineddine Bettouche, Khalid Ali +2
As mobile networks transition from Beyond 5G (B5G) towards 6G, accurate traffic forecasting is a prerequisite for improving network management. However, with increasing heterogenei…
HiSTM: Hierarchical Spatiotemporal Mamba for Cellular Traffic Forecasting
Zineddine Bettouche, Khalid Ali, Andreas Fischer +1
Cellular traffic forecasting is essential for network planning, resource allocation, or load-balancing traffic across cells. However, accurate forecasting is difficult due to intri…
Enhancing Spatiotemporal Networks with xLSTM: A Scalar LSTM Approach for Cellular Traffic Forecasting
Khalid Ali, Zineddine Bettouche, Andreas Kassler +1
Accurate spatiotemporal traffic forecasting is vital for intelligent resource management in 5G and beyond. However, conventional AI approaches often fail to capture the intricate s…