基于深度学习的多模光纤通信系统的模式与模群识别  

Deep Learning-Based Recognition of Modes and Mode Groups in Multimode Optical Fiber Communication System

作　　者：胡进坤 郭晓洁 李建平 许鸥[2,3] 向梦 彭迪 付松年 秦玉文 Hu Jinkun;Guo Xiaojie;Li Jianping;Xu Ou;Xiang Meng;Peng Di;Fu Songnian;Qin Yuwen(Institute of Photonics Technology,Jinan University,Guangzhou,Guangdong 510632,China;School of Information Engineering,Guangdong University of Technology,Guangzhou,Guangdong 510006,China;Guangdong Provincial Key Laboratory of Information Photonics Technology,Guangzhou,Guangdong 510006,China)

机构地区：[1]暨南大学光子技术研究院,广东广州510632 [2]广东工业大学信息工程学院,广东广州510006 [3]广东省信息光子技术重点实验室,广东广州510006

出　　处：《光学学报》2022年第4期38-45,共8页Acta Optica Sinica

基　　金：国家重点研发计划(2018YFB1800901);国家自然科学基金(62022029);广东省“珠江人才计划”引进创新创业团队项目(2019ZT08X340);广东省重点领域研发计划项目(2018B010114002);粤桂联合基金项目(2021GXNSFDA076001)。

摘　　要：基于模式/模群复用的多模光纤通信系统是目前光通信领域的研究热点。系统中存在多个模式/模群,如何准确识别它们是提升传输系统性能的关键问题之一。提出了一种基于深度学习的多模光纤模式与模群的智能识别模型,通过引入全卷积神经网络(CNN),对噪声影响情况下线偏振模式及其模群进行仿真和实验研究。首先,基于多平面光转换模式复用器件和普通OM2多模光纤,搭建10个模式(LP01、LP11a/b、LP21a/b、LP02、LP12a/b、LP31a/b)及其对应的3个模群的光场信息获取的仿真和实验平台,利用大量数据进行训练和验证。实验结果显示,模式/模群的总体识别率可达到100%。通过将获取的模群光场图片重构为低分辨率图片,研究低密度光电探测器阵列接收条件下,智能识别模型的识别性能。实验结果显示,采取4×4光探测器阵列接收光场信息时,能获得98.3%的识别效率。本研究表明提出的智能识别模型具有良好的光纤模式/模群智能识别能力,其在多模光纤通信系统性能提升与智能光性能监测方面具有一定的应用潜力。A multimode optical fiber communication system based on mode/mode group division multiplexing(MDM/MGDM)is one of the current research hotspots.Since there are multiple modes/mode groups multiplexed in the system,how to accurately recognize them is one of the key issues for improving the system performance.This article proposed an intelligent recognition model(IRM)of multimode fiber(MMF)supported fiber modes and mode groups based on the deep learning method through the introduction of a convolutional neural network(CNN).The theoretical simulation and experimental studies on the linear polarization(LP)modes and mode groups have been implemented under the influence of noise.Firstly,10 LP modes(LP01,LP11 a/b,LP21 a/b,LP0,LP12 a/b,and LP31 a/b)and corresponding mode groups have been simulated and experimentally generated based on a customized multimode multi-plane light converter(MPLC)and a conventional OM2 MMF.Then a large amount of mode profiles can be obtained to train and test of the IRM.The experimental results show that the recognition rate of modes/mode groups can reach 100%by using the high-resolution mode images.Subsequently,we resized the high-resolution mode images into low-resolution ones,and the recognition performance of the intelligent recognition model under the receiving condition of a low density photodetector array is studied.Experimental results show that a recognition rate of 98.3%can be also realized when the light field information is received by a 4×4 photodetector array.Therefore,this research shows that the proposed intelligent recognition model can recognize the optical fiber modes/mode groups effectively.It also meant that this method has the potential applications in the MDM-based communication systems and intelligent optical performance monitoring.

关 键 词：光通信 模分复用 深度学习 模式/模群识别 

分 类 号：TN913.7[电子电信—通信与信息系统]