现代信息科技2025，Vol.9Issue(7)：1-4,4.DOI:10.19850/j.cnki.2096-4706.2025.07.001
基于Swin Transformer的联合信源信道编码算法
Joint Source-Channel Coding Algorithm Based on Swin Transformer
廖潇 1李智1
作者信息
- 1. 四川大学 电子信息学院,四川 成都 610065
- 折叠
摘要
Abstract
Joint Source-Channel Coding(JSCC),as a key research direction in semantic communication,has achieved preliminary research results.However,with the increasing resolution of images,traditional JSCC algorithms based on Convolutional Neural Network(CNN)exhibit limitations in extracting image semantic features.To address this issue,this paper proposes a JSCC algorithm based on Swin Transformer.The algorithm firstly utilizes a Multi-Scale Large Kernel Attention(MLKA)mechanism to initially capture the local information and long-range dependencies of images.Subsequently,Swin Transformer is employed to further hierarchically extract image semantic features and perform adaptive rate coding.Experimental results demonstrate that,under the channel models of Additive White Gaussian Noise(AWGN)and Rayleigh,the proposed algorithm outperforms traditional algorithms in terms of Peak Signal-to-Noise Ratio(PSNR)and Multi-Scale Structural Similarity Index Measure(MS-SSIM).关键词
联合信源信道编码/Swin Transformer/多尺度大核注意力Key words
Joint Source-Channel Coding/Swin Transformer/Multi-Scale Large-Kernel Attention分类
电子信息工程引用本文复制引用
廖潇,李智..基于Swin Transformer的联合信源信道编码算法[J].现代信息科技,2025,9(7):1-4,4.
