13 citations · 32 across the 10 of their papers we have counts for
9 papers · 1 filter
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…
6G Native AI and Channel Foundation Models
Shugong Xu, Jun Jiang, Yuan Gao
The integration of artificial intelligence (AI) and wireless communications is widely regarded as a core objective of sixth-generation (6G) systems. However, both the meaning of na…
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: Release 19 Status and Future Challenges
Yuan Gao, Xinyi Wu, Jun Jiang +8
Artificial intelligence (AI) and machine learning (ML) have become essential drivers of sixth-generation (6G) mobile networks. Unlike earlier surveys that mainly review high-level…
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…
SSNet: Flexible and robust channel extrapolation for fluid antenna systems enabled by an self-supervised learning framework
Yuan Gao, Yiming Liu, Runze Yu +5
Fluid antenna systems (FAS) signify a pivotal advancement in 6G communication by enhancing spectral efficiency and robustness. However, obtaining accurate channel state information…
Enhanced Fingerprint-based Positioning With Practical Imperfections: Deep learning-based approaches
Shugong Xu, Jun Jiang, Wenjun Yu +7
High-precision positioning is vital for cellular networks to support innovative applications such as extended reality, unmanned aerial vehicles (UAVs), and industrial Internet of T…
Enabling 6G Through Multi-Domain Channel Extrapolation: Opportunities and Challenges of Generative Artificial Intelligence
Yuan Gao, Zichen Lu, Yifan Wu +5
Channel extrapolation has attracted wide attention due to its potential to acquire channel state information (CSI) with high accuracy and minimal overhead. This is becoming increas…