无线电工程2025，Vol.55Issue(5)：905-912,8.DOI:10.3969/j.issn.1003-3106.2025.05.001
一种基于残差连接的Swin Transformer增强型联合编码架构设计
A Residual Connection-based Swin Transformer Enhanced Joint Encoding Architecture Design
摘要
Abstract
As an emerging communication paradigm,semantic communication utilizes deep learning models for Joint Source-Channel Coding(JSCC).JSCC has shown excellent compression and interference resistance in wireless image transmission,especially in low Signal to Noise Ratio(SNR)environments.To enhance the ability to extract semantic features from high-resolution images,residual connections are added to a JSCC architecture based on Swin Transformer,a new JSCC architecture called Swinformer-R is proposed,and simulation experiments are designed.Results of comparison with three benchmark schemes demonstrate that the proposed method achieves the best Peak SNR(PSNR)and Multi-Scale Structural Similarity Index(MS-SSIM)across different transmission channels,SNR,and image resolutions.Therefore,the Swinformer-R architecture has significant potential and advantages in improving image reconstruction quality.关键词
语义通信/联合信源信道编码/Swin Transformer/残差结构/图像传输Key words
semantic communication/JSCC/Swin Transformer/residual structure/image transmission分类
电子信息工程引用本文复制引用
香晏,赵响,黄军韬..一种基于残差连接的Swin Transformer增强型联合编码架构设计[J].无线电工程,2025,55(5):905-912,8.基金项目
国家自然科学基金地区科学基金项目(61961007)Regional Science Foundation Project of National Natu-ral Science Foundation of China(61961007) （61961007）
