一种基于高斯过程回归的光信噪比监测技术

鄢然,胡春杰,李蔚. 一种基于高斯过程回归的光信噪比监测技术[J]. 光电工程,2021,48(1):200077. doi: 10.12086/oee.2021.200077
引用本文: 鄢然,胡春杰,李蔚. 一种基于高斯过程回归的光信噪比监测技术[J]. 光电工程,2021,48(1):200077. doi: 10.12086/oee.2021.200077
Yan R, Hu C J, Li W. A novel optical signal-to-noise ratio monitoring technique based on Gaussian process regression[J]. Opto-Electron Eng, 2021, 48(1): 200077. doi: 10.12086/oee.2021.200077
Citation: Yan R, Hu C J, Li W. A novel optical signal-to-noise ratio monitoring technique based on Gaussian process regression[J]. Opto-Electron Eng, 2021, 48(1): 200077. doi: 10.12086/oee.2021.200077

一种基于高斯过程回归的光信噪比监测技术

  • 基金项目:
    国家重点研发计划项目(2018YFB2200900)
详细信息
    作者简介:
    通讯作者: 李蔚(1968-),女,教授,博士生导师,主要从事光纤通信技术方面的研究。E-mail:weilee@hust.edu.cn
  • 中图分类号: TN929.11

A novel optical signal-to-noise ratio monitoring technique based on Gaussian process regression

  • Fund Project: National Key Research and Development Program of China (2018YFB2200900)
More Information
  • 提出并通过实验验证了一种新颖的带内光信噪比(OSNR)监测技术,该技术利用商用的大带宽可调谐光带通滤波器进行采样,将得到的光功率测量值作为高斯过程回归(GPR)的输入特征值,能够准确地估计出大动态范围OSNR值,并且不受光链路的配置影响,具有分布式低成本的特点。针对32 Gbaud PDM-16QAM信号的实验结果表明,在-1 dB~30 dB的大OSNR范围内,光信噪比监测的均方根误差(RMSE)为0.429 dB,平均绝对误差(MAE)为0.294 dB。此外,本文提出的技术被证明对色散、偏振模色散、非线性效应和级联滤波效应(CFE)均不敏感。实验表明,本文提出的技术有潜力被用于在传输信息未知的情况下对中间节点实施链路监控,且由于不需要校准而更易于操作。

  • Overview: The optical performance monitoring (OPM) refers to monitoring various performance parameters of optical signals at intermediate nodes or receiver terminal nodes of the optical fiber communication system in order to reduce network operating costs, ensure full utilization of resources, and guarantee reliable operation and flexible management of the system. The amplified spontaneous emission (ASE) noise introduced by optical amplifiers is the main noise source in the optical fiber communication system. Thus, the optical signal-to-noise ratio (OSNR) parameter used to measure the ASE noise accumulation can accurately reflect the quality of the optical signal, which is one of the most important parameters in OPM. Therefore, accurate monitoring of OSNR is an essential part of optical fiber communication systems. However, with the improvement of the channel capacity and transmission rate of the optical fiber communication system and the evolution of the optical network to the dynamiclly reconfigurable direction, the traditional out-of-band OSNR monitoring technique based on linear interpolation is facing the problem of failure. Thereupon, the in-band OSNR monitoring technique has received more and more attention. We propose a novel GPR-based in-band OSNR monitoring technique suitable for intermediate nodes. Firstly, the technology changes the center wavelength of the broadband tunable optical bandpass filter (OBPF) in a constant step size, so as to realize the sweep filtering of the whole C-band. Then, the optical power sequence collected from the center wavelength of the broadband tunable OBPF in the midpoint range of the channel to be monitored, and the adjacent channel is taken as the input features of the GPR model. Finally, the in-band OSNR monitoring is realized by utilizing the trained GPR model. By constructing a 9×32 Gbaud PDM-16QAM coherent optical communication system, a comprehensive experiment was conducted to verify the effectiveness and feasibility of our proposed technique. The experimental results show that in a 9×32 Gbaud PDM-16QAM system with 50 GHz channel spacing, the root means squared error and the mean absolute error are below 0.43 dB and 0.3 dB in the OSNR range of -1 dB to 30 dB, respectively. Even better, our proposed technique has the following advantages: higher monitoring accuracy; wider monitoring range; strong robustness to chromatic dispersion, polarization mode dispersion, nonlinear effect, and cascade filtering effect; no prior knowledge of link configuration required; low cost; distributed monitoring. Therefore, our proposed technique can realize OSNR monitoring at any node which is suitable for dynamically reconfigurable high-speed dense wavelength division multiplexing (DWDM) optical fiber communication systems and has huge development prospects and wide practical application potential.

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  • 图 1  提出的OSNR监测器的示意图

    Figure 1.  Schematic diagram of the proposed OSNR monitor

    图 2  扫描可调谐OBPF的中心波长后的信号光谱。黑色实线表示信号光谱;绿色虚线表示可调谐OBPF的滤波形状

    Figure 2.  The signal optical spectrum after scanning the center wavelength of the tunable OBPF.The solid black lines represent the signal optical spectrum; the dashed green lines represent the filter shape of the tunable OBPF

    图 3  信号处理单元的架构框图

    Figure 3.  Block diagram of the signal processing unit architecture

    图 4  实验装置。MUX:复用器;AWG:任意波形发生器;VOA:可调光衰减器;OSA:光谱仪

    Figure 4.  Experimental setup.MUX: multiplexer; AWG: arbitrary waveform generator; VOA: variable optical attenuator; OSA: optical spectrum analyzer

    图 5  在第一类系统条件的测试阶段中,PDM-16QAM信号的OSNR监测误差。(a) 输入特征包括传输距离和入纤功率;(b) 输入特征中没有传输距离或发射功率

    Figure 5.  OSNR monitoring error for PDM-16QAM signals during the testing phase in the first category.(a) With the transmission distance and launch power among the input features; (b) Without the transmission distance or launch power among the input features

    图 6  在第二类系统条件的测试阶段中,PDM-16QAM信号的OSNR监测误差。(a) 输入特征包括传输距离和入纤功率;(b) 输入特征中没有传输距离或发射功率

    Figure 6.  OSNR monitoring error for PDM-16QAM signals during the testing phase in the second category.(a) With the transmission distance and launch power among the input features; (b) Without the transmission distance or launch power among the input features

    图 7  在第三类系统条件的测试阶段中,PDM-16QAM信号的OSNR监测误差。(a) 输入特征包括级联WSS个数;(b) 输入特征中无级联WSS个数

    Figure 7.  OSNR monitoring error for PDM-16QAM signals during the testing phase in the third category.(a) With the number of cascaded WSSs among the input features; (b) Without the number of cascaded WSSs among the input features

    图 8  在上述三类系统条件的测试阶段中,PDM-16QAM信号的OSNR监测误差。(a) 输入特征包括传输距离、入纤功率以及级联WSS个数;(b) 输入特征中不包括传输距离、入纤功率和级联WSS个数

    Figure 8.  OSNR monitoring error for PDM-16QAM signals during the testing phase including the above three categories.(a) With the transmission distance, the launch power and the number of cascaded WSSs among the input features; (b) Without the transmission distance, the launch power or the number of cascaded WSSs among the input features

    图 9  在上述三类系统条件的测试阶段中,PDM-16QAM信号与真实OSNR的偏差。(a) 输入特征包括传输距离、入纤功率以及级联WSS个数;(b) 输入特征中不包括传输距离、入纤功率和级联WSS个数

    Figure 9.  OSNR deviation from true OSNR for PDM-16QAM signals during the testing phase including the above three categories.(a) With the transmission distance, the launch power and the number of cascaded WSSs among the input features; (b) Without the transmission distance, the launch power or the number of cascaded WSSs among the input features

    表 1  32 Gbaud PDM-16QAM系统的系统条件

    Table 1.  System conditions for 32 Gbaud PDM-16QAM system

    Ⅰ/Ⅲ Ⅱ/Ⅲ
    Transmission distance/km 480 1440 1920 960 480 1440 1920 960 960 960 960
    Launch power/dBm 2 6 8 4 2 6 8 4 4 4 4
    Number of cascaded WSSs 0 0 0 0 6 6 6 6 3 9 12
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出版历程
收稿日期:  2020-03-11
修回日期:  2020-06-15
刊出日期:  2021-01-15

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