4 papers
CFM-Bench: A Unified Multi-Domain, Multi-Task Benchmark for Channel Foundation Models
Yuan Gao, Wenjun Yu, Jun Jiang +3
The paper introduces CFM-Bench, a unified benchmark that evaluates channel foundation models across multiple wireless domains, tasks, and data configurations, enabling fair compari…
CSI-CLIP++: A Scalable Channel Foundation Model for Wireless Communication via CIR-CSI Consistency
Jun Jiang, Wenjun Yu, Yunfan Li +2
Self-supervised learning can exploit large-scale unlabeled channel data to improve the transferability of wireless AI models. Existing channel foundation models are often built on…
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…
A MIMO Wireless Channel Foundation Model via CIR-CSI Consistency
Jun Jiang, Wenjun Yu, Yunfan Li +2
In the field of artificial intelligence, self-supervised learning has demonstrated superior generalization capabilities by leveraging large-scale unlabeled datasets for pretraining…