3 citations · 8 across the 17 of their papers we have counts for
17 papers
WiFi based Multi user Activity Recognition via User Conditioned Spatial Attention
Chenhan Yuan, Ruijing Liu, Cunhua Pan
WiFi-based human activity recognition has achieved high accuracy under the single-user scene. Recognizing activities performed by multiple concurrent users remains challenging, bec…
Explainable Task-Oriented Token Communication for AI-Native 6G Networks
Feibo Jiang, Lei Mao, Li Dong +3
The integration of Foundation Models (FMs) and wireless communications is driving the evolution of image communication from bit-accurate transmission toward task-oriented transmiss…
Robust Cross-Domain WiFi Fall Detection via Physics-Driven Attention-Enhanced Transformers
Yingzhe Wang, Cunhua Pan, Ruijing Liu +4
Device-free fall detection utilizing WiFi Channel State Information (CSI) has emerged as a promising, privacy-preserving solution for elderly health monitoring in the Internet of T…
Selective Depthwise Separable Convolution for Lightweight Joint Source-Channel Coding in Wireless Image Transmission
Ming Ye, Kui Cai, Cunhua Pan +3
Depthwise separable convolutional (DSConv) layers have been successfully applied to deep learning (DL)-based joint source-channel coding (JSCC) schemes to reduce computational comp…
Aerial Agentic AI: Synergizing LLM and SLM for Low-Altitude Wireless Networks
Li Dong, Feibo Jiang, Kezhi Wang +3
Low-Altitude Wireless Networks (LAWNs), composed of Unmanned Aerial Vehicles (UAVs) and mobile terminals, are emerging as a critical extension of 6G. However, applying Large Langua…
TokenCom: Vision-Language Model for Multimodal and Multitask Token Communications
Feibo Jiang, Siwei Tu, Li Dong +5
Visual-Language Models (VLMs), with their strong capabilities in image and text understanding, offer a solid foundation for intelligent communications. However, their effectiveness…
U-Net-Based Generative Joint Source-Channel Coding for Wireless Image Transmission
Ming Ye, Kui Cai, Cunhua Pan +4
Deep learning (DL)-based joint source-channel coding (JSCC) methods have achieved remarkable success in wireless image transmission. However, these methods either focus on conventi…
Agentic AI Empowered Multi-UAV Trajectory Optimization in Low-Altitude Economy Networks
Feibo Jiang, Li Dong, Xitao Pan +2
This paper proposes a novel Agentic Retrieval-augmented generation with Mamba-Attention Integrated Transformer (ARMAIT) framework for multi-Unmanned Aerial Vehicle (UAV) trajectory…
From Large AI Models to Agentic AI: A Tutorial on Future Intelligent Communications
Feibo Jiang, Cunhua Pan, Li Dong +3
With the advent of 6G communications, intelligent communication systems face multiple challenges, including constrained perception and response capabilities, limited scalability, a…
A Comprehensive Survey of Large AI Models for Future Communications: Foundations, Applications and Challenges
Feibo Jiang, Cunhua Pan, Li Dong +4
The 6G wireless communications aim to establish an intelligent world of ubiquitous connectivity, providing an unprecedented communication experience. Large artificial intelligence…
CommGPT: A Graph and Retrieval-Augmented Multimodal Communication Foundation Model
Feibo Jiang, Wanyun Zhu, Li Dong +4
Large Language Models (LLMs) possess human-level cognitive and decision-making capabilities, making them a key technology for 6G. However, applying LLMs to the communication domain…
FlashSAM: Lightweight Vision Model for Multi-UAV Token Communication in Low-Latitude Wireless Networks
Feibo Jiang, Siwei Tu, Li Dong +5
Token Communication (TokenCom) is a promising paradigm for low-altitude wireless networks, as it focuses on transmitting task-relevant core information, particularly in environment…
M4SC: An MLLM-based Multi-modal, Multi-task and Multi-user Semantic Communication System
Feibo Jiang, Siwei Tu, Li Dong +3
Multi-modal Large Language Models (MLLMs) are capable of precisely extracting high-level semantic information from multi-modal data, enabling multi-task understanding and generatio…
Large Generative Model-assisted Talking-face Semantic Communication System
Feibo Jiang, Siwei Tu, Li Dong +3
The rapid development of generative Artificial Intelligence (AI) continually unveils the potential of Semantic Communication (SemCom). However, current talking-face SemCom systems…
Visual Language Model based Cross-modal Semantic Communication Systems
Feibo Jiang, Chuanguo Tang, Li Dong +3
Semantic Communication (SC) has emerged as a novel communication paradigm in recent years, successfully transcending the Shannon physical capacity limits through innovative semanti…
Personalized Wireless Federated Learning for Large Language Models
Feibo Jiang, Li Dong, Siwei Tu +5
Large language models (LLMs) have driven profound transformations in wireless networks. However, within wireless environments, the training of LLMs faces significant challenges rel…
Large Generative Model Assisted 3D Semantic Communication
Feibo Jiang, Yubo Peng, Li Dong +4
Semantic Communication (SC) is a novel paradigm for data transmission in 6G. However, there are several challenges posed when performing SC in 3D scenarios: 1) 3D semantic extracti…