深度学习在光纤通信系统损伤补偿中的应用

郭虹; 邓鹏程; 杨慧

doi:10.13756/j.gtxyj.2024.220075

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深度学习在光纤通信系统损伤补偿中的应用

光通信系统与网络技术 | 更新时间：2024-04-02

- 深度学习在光纤通信系统损伤补偿中的应用
- Application of Deep Learning in Impairments Compensation of Optical Fiber Communication
- 光通信研究 2024年第2期页码：22007501-22007512
- 作者机构：
  
  西南交通大学　信息科学与技术学院，成都　610031
- 作者简介：
  
  郭虹（1999－），女，四川眉山人。硕士，主要研究方向为基于低复杂度神经网络的光接入网信道损伤补偿。
  杨慧，副教授。E-mail：yanghuifly@swjtu.edu.cn
- 基金信息：
  
  四川省科技计划资助项目(2020YFSY0021)
- DOI：10.13756/j.gtxyj.2024.220075
  中图分类号： TN929
- 纸质出版日期：2024-04-10，
  
  收稿日期：2023-01-22，
  
  修回日期：2023-02-14，
扫描看全文
郭虹，邓鹏程，杨慧. 深度学习在光纤通信系统损伤补偿中的应用[J].光通信研究，2024(2):220075.

Guo H, Deng P C, Yang H. Application of Deep Learning in Impairments Compensation of Optical Fiber Communication [J]. Study on Optical Communications, 2024(2):220075.
郭虹，邓鹏程，杨慧. 深度学习在光纤通信系统损伤补偿中的应用[J].光通信研究，2024(2):220075. DOI： 10.13756/j.gtxyj.2024.220075.

Guo H, Deng P C, Yang H. Application of Deep Learning in Impairments Compensation of Optical Fiber Communication [J]. Study on Optical Communications, 2024(2):220075. DOI： 10.13756/j.gtxyj.2024.220075.

摘要

随着社会信息化程度的逐步提升，人们对光纤通信系统容量的需求持续增长。信道损伤一直是限制光纤通信容量提升的关键因素，信道损伤补偿作为光纤通信系统的基础性功能和关键技术也在不断改进。近年来，将深度学习应用到光纤通信信道损伤补偿中更是吸引了不少研究人员的关注。文章介绍了近年来应用于光纤通信中的常见深度学习模型，阐述了深度学习技术在光纤通信系统信号损伤补偿方面的发展情况。

Abstract

With the development of the social informatization

the demand for optical fiber communication system capacity continues to grow. Channel impairment has always been the key factor limiting the capacity in optical fiber communication system. As the basic function and key technology in optical fiber communication system

channel impairment compensation is constantly improved. Applying deep learning technology in channel impairment compensation of optical fiber communication has attracted the attention of many researchers. This paper introduces the common deep learning models used and the development of deep learning technology for impairments compensation of optical fiber communication systems in recent years.

关键词

光纤通信系统深度学习神经网络损伤补偿

Keywords

fiber-optic communication systemdeep learningneural networkimpairments compensation

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