From the 1 of 12 linked papers with an AI index.
8 papers · 1 filter
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,…
Towards channel foundation models (CFMs): Motivations, methodologies and opportunities
Jun Jiang, Yuan Gao, Xinyi Wu +1
Artificial intelligence (AI) has emerged as a pivotal enabler for next-generation wireless communication systems. However, conventional AI-based models encounter several limitation…
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…
CSI-MAE: A Masked Autoencoder-based Channel Foundation Model
Jun Jiang, Xiaolong Ruan, Shugong Xu
Self-Supervised Learning (SSL) has emerged as a key technique in machine learning, tackling challenges such as limited labeled data, high annotation costs, and variable wireless ch…
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…
C2S-AE: CSI to Sensing enabled by an Auto-Encoder-based Framework
Jun Jiang, Shugong Xu, Wenjun Yu +1
Next-generation mobile networks are set to utilize integrated sensing and communication (ISAC) as a critical technology, providing significant support for sectors like the industri…