光通信技术2024，Vol.48Issue(3)：13-17,5.DOI:10.13921/j.cnki.issn1002-5561.2024.03.003
基于联合残差网络和Bottleneck Transformer的调制格式识别方法
Modulation format identification method based on joint residual network and Bottleneck Transformers
摘要
Abstract
A modulation format recognition(MFI)method based on joint residual network(ResNet)and Bottleneck Transformer(BT)is proposed to meet the transmission requirements in future optical network links.This method combines ResNet and BT to identify signals with six different modulation formats,and applies OptiSystem and TensorFlow to simulate them.The simulation results show that within a wide range of optical signal-to-noise ratio(OSNR),the proposed method achieves an accuracy of 99.72%and can effectively cope with the impact of transmission damage.Compared with other deep learning methods,this method significantly improves its performance.关键词
调制格式识别/深度学习/残差网络/信号传输/光信噪比Key words
modulation format identification/deep learning/residual network/signal transmission/optical signal-to-noise ratio分类
信息技术与安全科学引用本文复制引用
梁坤,刘战胜..基于联合残差网络和Bottleneck Transformer的调制格式识别方法[J].光通信技术,2024,48(3):13-17,5.基金项目
江苏大学高级人才科研启动基金(16JDG023)资助. （16JDG023）
