9 papers
Generalizable and Computational Efficient Channel Extrapolation for 6G: A Configurable AI-Driven Framework Built from a Modular Perspective
Yuan Gao, Xinyi Wu, Jiang Jun +5
Acquiring channel state information (CSI) with manageable overhead has been essential to provide high-performance communication services, which is extremely challenging in the emer…
JEPA-CFM: A Joint Embedding Predictive Architecture-based Channel Foundation Model for Robust Fluid Antenna Systems
Yuan Gao, Yiming Liu, Jun Jiang +4
Fluid antenna systems (FAS) have emerged as a promising technology for sixth-generation (6G) wireless networks. By allowing antenna elements to move freely within a compact region,…
AI/ML for mobile networks: Current status in Rel. 19 and challenges ahead
Yuan Gao, Xinyi Wu, Jun Jiang +6
The transformative power of artificial intelligence (AI) and machine learning (ML) is recognized as a key enabler for sixth generation (6G) mobile networks by both academia and ind…
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…
AI-Driven Channel State Information (CSI) Extrapolation for 6G: Current Situations, Challenges and Future Research
Yuan Gao, Zichen Lu, Xinyi Wu +7
CSI extrapolation is an effective method for acquiring channel state information (CSI), essential for optimizing performance of sixth-generation (6G) communication systems. Traditi…
Sidelink Positioning: Standardization Advancements, Challenges and Opportunities
Yuan Gao, Guangjin Pan, Zhiyong Zhong +4
With the integration of cellular networks in vertical industries that demand precise location information, such as vehicle-to-everything (V2X), public safety, and Industrial Intern…