5 papers
Semantic Communications with World Models
Peiwen Jiang, Jiajia Guo, Chao-Kai Wen +2
Semantic communication is a promising technique for emerging wireless applications, which reduces transmission overhead by transmitting only task-relevant features instead of raw d…
Foundation Model-Based Adaptive Semantic Image Transmission for Dynamic Wireless Environments
Fangyu Liu, Peiwen Jiang, Wenjin Wang +3
Foundation model-based semantic transmission has recently shown great potential in wireless image communication. However, existing methods exhibit two major limitations: (i) they o…
MUSE-FM: Multi-task Environment-aware Foundation Model for Wireless Communications
Tianyue Zheng, Jiajia Guo, Linglong Dai +2
Recent advancements in foundation models (FMs) have attracted increasing attention in the wireless communication domain. Leveraging the powerful multi-task learning capability, FMs…
Large AI Models for Wireless Physical Layer
Jiajia Guo, Yiming Cui, Shi Jin +1
Large artificial intelligence models (LAMs) are transforming wireless physical layer technologies through their robust generalization, multitask processing, and multimodal capabili…
LVM4CSI: Enabling Direct Application of Pre-Trained Large Vision Models for Wireless Channel Tasks
Jiajia Guo, Peiwen Jiang, Chao-Kai Wen +2
Accurate channel state information (CSI) is critical to the performance of wireless communication systems, especially with the increasing scale and complexity introduced by 5G and…