中国光学（中英文）2025，Vol.18Issue(1)：114-120,7.DOI:10.37188/CO.2024-0114
短距光纤通信系统中基于神经网络的非线性均衡器
Nonlinear equalizer based on neural network in high-speed optical fiber communication systems
摘要
Abstract
In order to achieve low complexity balancing of nonlinear damage at the receiver of short-range fiber optic data communication systems,we propose an equalization structure named Decision Feedback Neural Network which introduce the Decision Feedback Structure into the Fully Connected Neural Network.The nonlinear distortion is introduced by using a photodetector with a linear working area that does not match the experimental system.The experimental system is built based on a 56 Gbit/s PAM4 with a C-band direct-modulated laser,and we compare the equalization performance of decision feedback neural network with other equalization schemes.Experimental results show that compared with the fully connected neural network,the improved scheme achieves a sensitivity improvement of 2 dB at 20 km transmission,and the equalization performance is close to the convolutional neural network with lower complexity.This paper has great significance for the rate and capacity upgrade of short-distance optical fiber communication system,and can be used as a reference for further scientific research and industrial application.关键词
短距光通信/光电器件非线性畸变/信号均衡/神经网络/判决反馈Key words
short-reach optical communication/nonlinear distortion of optoelectronic devices/signal equal-ization/neural network/decision feedback分类
计算机与自动化引用本文复制引用
赵晗祺,李娜,吴斌,吴桂龙,陈一童,冯晓芳,何沛礼,李蔚..短距光纤通信系统中基于神经网络的非线性均衡器[J].中国光学（中英文）,2025,18(1):114-120,7.基金项目
南方电网科技项目面向新型电力系统的骨干通信承载网关键技术研究与示范应用资助(No.CG0000022001594227)Supported by Southern Power Grid Technology Project Funding for Key Technology Research and Demon-stration Application of Backbone Communication Carrier Network for New Power Systems(No.CG0000022001594227) （No.CG0000022001594227）
