移动通信2024，Vol.48Issue(5)：2-7,14,7.DOI:10.3969/j.issn.1006-1010.20240325-0004
基于AI的端到端语义编码传输方案设计
Design of an AI-Based End-to-End Semantic Encoding Transmission Scheme
摘要
Abstract
In response to the diverse scenarios of 6G,which demand high performance and low complexity in transmission,this paper proposes an AI-based end-to-end semantic encoding transmission scheme by integrating AI architectures into the joint optimization of wireless transmission protocols.This approach transcends the limitations of traditional modular physical layer design methodologies and classical information theory.Initially,to address the challenge of training transmitters via backpropagation under unknown fading channels,a two-subnetwork architecture based on conditional generative adversarial networks(CGANs)is designed with a phased training methodology,effectively mitigating the effects of fading channels.Furthermore,a system architecture for joint semantic channel coding is introduced,which shows significant advantages in end-to-end joint optimization.Simulation results demonstrate that the proposed scheme enhances system performance through the joint optimization of semantic encoding and transmission,proving its adaptability,intelligence,and efficiency in practical communication settings where channel conditions are unknown.关键词
端到端传输/信源信道联合编码/智能通信/语义通信Key words
end-to-end transmission/joint source channel coding/intelligent communication/semantic communication分类
电子信息工程引用本文复制引用
李立华,杨琳琳,任欣然..基于AI的端到端语义编码传输方案设计[J].移动通信,2024,48(5):2-7,14,7.基金项目
国家自然科学基金"智慧车间复杂传播环境感知、信道重构与资源配置理论研究"(92167202) （92167202）
