摘要
为应对相干光通信系统中光纤非线性损伤,结合由非线性薛定谔方程的一阶摄动解推导出的三元组,提出一种基于深度神经网络(DNN)和改进型主成分分析(IPCA)的光纤非线性补偿(NLC)算法。为了验证提出的NLC方案的可行性,构建了单通道32 GBaud偏振复用16阶正交幅度调制(PDM-16QAM)的光传输系统。综合数值仿真结果表明,相较于DNN-NLC方案,IPCA-DNN-NLC方案以Q值降低0.06 dB为代价,使计算复杂度降低了90.7%,由此证明IPCA-DNN-NLC方案能以很低的复杂度实现相近的NLC性能;相较于数字反向传播(DBP)方案,IPCA-DNN-NLC方案在800 km的传输距离下Q值提升了0.91 dB,并可在不预知链路参数的情况下工作,具有普适性和鲁棒性。
To deal with the fiber nonlinear impairments in coherent optical communication systems,this paper proposes a nonlinear compensation(NLC)algorithm based on deep neural network(DNN)and improved principal component analysis(IPCA)by using the triplets derived from the first-order perturbation solution of the nonlinear Schr9 dinger equation.The simulation systems of a single-channel 32 GBaud polarization-division-multiplexing 16-ary quadrature amplitude modulation(PDM-16 QAM)optical transmission system are built to verify the feasibility of the proposed NLC algorithm.Compared with the DNN-NLC scheme,the IPCA-DNN-NLC scheme reduces the computational complexity by 90.7%with only a 0.06 dB Q-factor penalty,which means that the new algorithm enables similar NLC performance with much lower complexity.Compared with the digital back propagation(DBP)scheme,the IPCA-DNN-NLC scheme realizes a 0.91 dB Q-factor improvement over 800 km transmission.The proposed scheme can work normally without prior knowledge of the link parameters,which is versatile and robust.
作者
蒙建宇
张洪波
张敏
蔡炬
张倩武
朱虹霖
钟政
Meng Jianyu;Zhang Hongbo;Zhang Min;Cai Ju;Zhang Qianwu;Zhu Honglin;Zhong Zheng(College of Communication Engineering,Chengdu University of Information Technology,Chengdu,Sichuan 610225,China;Key Laboratory of Specialty Fiber Optics and Optical Access Networks,Shanghai University,Shanghai 200072,China)
出处
《光学学报》
EI
CAS
CSCD
北大核心
2021年第24期30-36,共7页
Acta Optica Sinica
基金
四川省科技计划(2021YFG0149)
上海市科委重点实验室项目(SKLSFO2019-06)
高等学校学科创新引智计划(111)(D20031)。
关键词
光纤光学
相干光通信
深度神经网络
改进型主成分分析
非线性补偿
fiber optics
coherent optical communication
deep neural network
improved principal component analysis
nonlinear compensation
作者简介
通信作者:张洪波,zhanghb@cuit.edu.cn;通信作者:蔡炬,caiju@cuit.edu.cn。
