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

作　　者：赵晗祺[1] 李娜 吴斌[1] 吴桂龙 陈一童 冯晓芳 何沛礼 李蔚 ZHAO Han-qi;LI Na;WU Bin;WU Gui-long;CHEN Yi-tong;FENG Xiao-fang;HE Pei-li;LI Wei(CSG Power Dispatching and Control Center,China Southern Power Grid Company,Ltd.,Guangzhou 510663,China;Wuhan National Laboratory for Optoelectronics,Huazhong University of Science and Technology,Wuhan 430074,China)

机构地区：[1]中国南方电网电力调度控制中心通信处,广东广州510663 [2]华中科技大学武汉光电国家研究中心,湖北武汉430074

出　　处：《中国光学(中英文)》2025年第1期114-120,共7页Chinese Optics

基　　金：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)。

摘　　要：为了实现对短距光纤数据通信系统接收端非线性损伤的低复杂度均衡,提出了一种基于全连接神经网络的接收端均衡算法。这是一种引入判决反馈结构的判决反馈神经网络。非线性畸变是由线性工作区与实验系统不匹配的光电探测器引入的,在此基础上实现了基于C波段直接调制激光器的56 Gbit/s PAM4信号的20 km传输验证实验,并对判决反馈神经网络和其他均衡方案的均衡性能进行了对比实验。实验结果表明,相比全连接神经网络,改进方案在传输距离为20 km时灵敏度提升2 dB。改进方案可以很好地均衡光电器件的非线性,且计算复杂度更低,具有很好的应用意义。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 

分 类 号：TP394.1[自动化与计算机技术—计算机应用技术] TH691.9[自动化与计算机技术—计算机科学与技术]