3 papers
eess.SP2026
Generalizable and Robust Beam Prediction for 6G Networks: An Deep-Learning Framework with Positioning Feature Fusion
Yanliang Jin, Yunfan Li, Jiang Jun +5
Beamforming (BF) is essential for enhancing system capacity in fifth generation (5G) and beyond wireless networks, yet exhaustive beam training in ultra-massive multiple-input mult…
cs.LG2025
Clustered Federated Learning for Generalizable FDIA Detection in Smart Grids with Heterogeneous Data
Yunfeng Li, Junhong Liu, Zhaohui Yang +2
False Data Injection Attacks (FDIAs) pose severe security risks to smart grids by manipulating measurement data collected from spatially distributed devices such as SCADA systems a…
cs.LG2025
Rec-AD: An Efficient Computation Framework for FDIA Detection Based on Tensor Train Decomposition and Deep Learning Recommendation Model
Yunfeng Li, Junhong Liu, Zhaohui Yang +2
Deep learning models have been widely adopted for False Data Injection Attack (FDIA) detection in smart grids due to their ability to capture unstructured and sparse features. Howe…