10 papers
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…
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…
FAST: Flexible and Adaptive Semantic Transmission for Resource-constrained Multi-user Generative Semantic Communication
Yiru Wang, Wanting Yang, Fangli Mou +4
The rapid advancement of generative artificial intelligence has spurred innovative approaches to semantic communication, giving rise to a new paradigm known as generative semantic…
Enhancing Mega-Satellite Networks with Generative Semantic Communication: A Networking Perspective
Binquan Guo, Wanting Yang, Zehui Xiong +5
The advance of direct satellite-to-device communication has positioned mega-satellite constellations as a cornerstone of 6G wireless communication, enabling seamless global connect…
Edge-Assisted Collaborative Fine-Tuning for Multi-User Personalized Artificial Intelligence Generated Content (AIGC)
Nan Li, Wanting Yang, Marie Siew +4
Diffusion models (DMs) have emerged as powerful tools for high-quality content generation, yet their intensive computational requirements for inference pose challenges for resource…
Multi-User Generative Semantic Communication with Intent-Aware Semantic-Splitting Multiple Access
Jiayi Lu, Wanting Yang, Zehui Xiong +4
With the booming development of generative artificial intelligence (GAI), semantic communication (SemCom) has emerged as a new paradigm for reliable and efficient communication. Th…