collaborators

13 papers

eess.IV2026

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…

eess.IV2026

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…

eess.SP2026

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…

cs.IT2026

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…

cs.CV2026

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…

eess.IV2026

U-Net-Based Generative Joint Source-Channel Coding for Wireless Image Transmission

Ming Ye, Kui Cai, Cunhua Pan +3

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…