Joint OSNR and CD monitoring in digital coherent receiver using long short-term memory neural network

被引:39
作者
Wang, Chunxiao [1 ,2 ]
Fu, Songnian [1 ,2 ]
Wu, Hao [1 ,2 ]
Luo, Ming [3 ]
Li, Xiang [3 ]
Tang, Ming [1 ,2 ]
Liu, Deming [1 ,2 ]
机构
[1] Huazhong Univ Sci & Technol, Wuhan Natl Lab Optoelect, Wuhan 430074, Hubei, Peoples R China
[2] Huazhong Univ Sci & Technol, Sch Opt & Elect Informat, Wuhan 430074, Hubei, Peoples R China
[3] Wuhan Res Inst Posts & Telecommun, State Key Lab Opt Commun Technol & Networks, Wuhan 430074, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
PERFORMANCE;
D O I
10.1364/OE.27.006936
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
To enable the high quality-of-service of reliable and dynamic optical networks, it is essential to implement optical performance monitoring (OPM) for fiber optical transmission link. Being directly related to the quality of optical signal, optical signal-to-noise ratio (OSNR) and chromatic dispersion (CD) have become the most vital parameters to be monitored during OPM implementation. However, most existing simultaneous OSNR and CD monitoring schemes still suffer from high implementation complexity and low accuracy. Here, we demonstrate a joint OSNR and CD monitoring scheme for the digital coherent receiver, enabled by the long short-term memory neural network (LSTM-NN). LSTM-NN is able to identify the mapping from the received data to corresponding OSNR and CD values simultaneously, without manual feature pre-engineering. We carry out an experimental verification for optical signals with variable modulation formats and baud-rates. The mean absolute errors (MAEs) of simultaneous OSNR and CD monitoring are below 0.12 dB and 1.09 ps/nm, respectively, when both OSNR and CD are at the range from 15 to 30 dB and 1360 to 2040 ps/nm for 5/10 Gbaud PDM-16QAM/64QAM optical signals. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
引用
收藏
页码:6936 / 6945
页数:10
相关论文
共 18 条
[1]  
Abadi M., 2015, P 12 USENIX S OPERAT
[2]   Social LSTM: Human Trajectory Prediction in Crowded Spaces [J].
Alahi, Alexandre ;
Goel, Kratarth ;
Ramanathan, Vignesh ;
Robicquet, Alexandre ;
Li Fei-Fei ;
Savarese, Silvio .
2016 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2016, :961-971
[3]   Simultaneous chromatic dispersion, polarization-mode-dispersion and OSNR monitoring at 40Gbit/s [J].
Baker-Meflah, Lamia ;
Thomsen, Benn ;
Mitchell, John ;
Bayvel, Polina .
OPTICS EXPRESS, 2008, 16 (20) :15999-16004
[4]   LEARNING LONG-TERM DEPENDENCIES WITH GRADIENT DESCENT IS DIFFICULT [J].
BENGIO, Y ;
SIMARD, P ;
FRASCONI, P .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1994, 5 (02) :157-166
[5]  
Downie J. D., EUR C EXH OPT COMM
[6]   Ultra-long-haul 112 Gb/s PM-QPSK transmission systems using longer spans and Raman amplification [J].
Downie, John D. ;
Hurley, Jason ;
Pikula, Dragan ;
Zhu, Xianming .
OPTICS EXPRESS, 2012, 20 (09) :10353-10358
[7]   Joint Optical Performance Monitoring and Modulation Format/Bit-Rate Identification by CNN-Based Multi-Task Learning [J].
Fan, Xiaojie ;
Xie, Yulai ;
Ren, Fang ;
Zhang, Yiying ;
Huang, Xiaoshan ;
Chen, Wei ;
Zhangsun, Tianwen ;
Wang, Jianping .
IEEE PHOTONICS JOURNAL, 2018, 10 (05)
[8]  
Graves A, 2012, STUD COMPUT INTELL, V385, P1, DOI [10.1162/neco.1997.9.1.1, 10.1007/978-3-642-24797-2]
[9]  
Kauder E., 2015, History of Marginal Utility Theory
[10]  
Khan FN, 2018, 2018 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXPOSITION (OFC)