9 papers
Generative Communications: Overview, Technologies, and Trends
Wenjun Zhang, Zhiyong Chen, Tong Wu +4
The groundbreaking development of generative artificial intelligence (AI) is rapidly boosting the ability to generate content such as images and videos, reshaping communication par…
JSCGC: Joint Source-Channel-Generation Coding for Wireless Generative Communications
Tong Wu, Zhiyong Chen, Guo Lu +4
Conventional communication systems, including both separation-based coding and learning-based joint source-channel coding (JSCC), are typically designed under Shannon's rate-distor…
Joint Source-Channel-Generation Coding: From Distortion-oriented Reconstruction to Semantic-consistent Generation
Tong Wu, Zhiyong Chen, Guo Lu +4
Conventional communication systems, including both separation-based coding and AI-driven joint source-channel coding (JSCC), are largely guided by Shannon's rate-distortion theory.…
Fed-PELAD: Communication-Efficient Federated Learning for Massive MIMO CSI Feedback with Personalized Encoders and a LoRA-Adapted Shared Decoder
Yixiang Zhou, Tong Wu, Meixia Tao +1
This paper addresses the critical challenges of communication overhead, data heterogeneity, and privacy in deep learning for channel state information (CSI) feedback in massive MIM…
Text-Guided Diffusion Model-based Generative Communication for Wireless Image Transmission
Shengkang Chen, Tong Wu, Zhiyong Chen +3
Reliable image transmission over wireless channels is particularly challenging at extremely low transmission rates, where conventional compression and channel coding schemes fail t…
Mixture of Semantics Transmission for Generative AI-Enabled Semantic Communication Systems
Junjie Ni, Tong Wu, Zhiyong Chen +3
In this paper, we propose a mixture of semantics (MoS) transmission strategy for wireless semantic communication systems based on generative artificial intelligence (AI). At the tr…