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。
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.
作者
郭虹
邓鹏程
杨慧
GUO Hong;DENG Pengcheng;YANG Hui(School of Information Science and Technology,Southwest Jiaotong University,Chengdu 610031,China)
出处
《光通信研究》
北大核心
2024年第2期30-41,共12页
Study on Optical Communications
基金
四川省科技厅重点研发计划资助项目(2020YFSY0021)。
关键词
光纤通信系统
深度学习
神经网络
损伤补偿
fiber-optic communication system
deep learning
neural network
impairments compensation