Key parameter joint monitoring method in elastic optical network

An elastic optical network and key parameter technology, applied in neural learning methods, biological neural network models, image data processing and other directions, can solve the problems of poor robustness, few monitoring parameters, and low recognition accuracy, and achieve good robustness, The effect of many monitoring parameters and high recognition accuracy

Active Publication Date: 2021-09-28
LIAOCHENG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] Aiming at the above-mentioned deficiencies in the prior art, the present invention discloses a joint monitoring method for key parameters in an elastic optical network, in order to solve the problems of few monitoring parameters, low recognition accuracy and poor robustness existing in the existing method

Method used

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  • Key parameter joint monitoring method in elastic optical network
  • Key parameter joint monitoring method in elastic optical network
  • Key parameter joint monitoring method in elastic optical network

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Experimental program
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Embodiment 1

[0051] In this embodiment, aiming at the joint monitoring of baud rate, modulation format identification and optical performance of EON system, a joint monitoring method of baud rate, modulation format identification and optical performance based on Radon transform and multi-task neural network is proposed , the specific technical process is as figure 1 shown. In this method, firstly, the coherent receiver is used to complete the photoelectric conversion and analog-to-digital conversion of the dual-polarization high-order modulation format signal, and then digital signal processing is performed on the signal, such as IQ orthogonalization, CD compensation and CMA equalization, etc., and the preprocessed The signal is converted into the corresponding constellation diagram, followed by digital image preprocessing and Radon transformation, and finally the obtained Radon transformation image is sent to the multi-task neural network for multi-parameter joint identification and monit...

Embodiment 2

[0080] In this embodiment, a simulation system is established based on the VPI Transmission Maker Optical System 9.3 and the KerasLibrary machine learning library to verify the performance of this method for joint monitoring of key parameters in an elastic optical network. Figure 8 Shown is the block diagram of the 14 / 28GBaud PDM-EON transmission emulation system used in the demonstration. First, the optical transmitter generates a pseudo-random binary sequence of length 2 15 -1 various EON modulation format signals, including 14 / 28GBaud PDM-QPSK, 14 / 28GBaud PDM-8QAM, 14 / 28GBaud PDM-16QAM, 14 / 28GBaud PDM-32QAM, 14 / 28GBaud PDM-64QAM, etc., and then use doped Erbium fiber amplifiers and variable optical attenuators adjust the optical signal-to-noise ratio (range 10-28dB, step size 1dB), and then use a CD simulator to add a certain residual dispersion in the link (range 0-300ps / nm , the step size is 50ps / nm), and the system uses the polarization mode dispersion simulator to adj...

Embodiment 3

[0087] In this embodiment, in order to further verify the performance of the method, we also built a 14 / 28GBaud coherent optical transmission experimental system. First, digital signal preprocessing is performed on the transmitted signal in an arbitrary waveform generator (AWG, Keysight M8195A), including bit-symbol mapping, pulse shaping with a roll-off factor of 0.75, transmitter pre-distortion processing, etc., pseudo-random bit sequence setting for 2 15 -1. After digital-to-analog conversion with 65GS / s sampling rate per channel and 25GHz analog bandwidth, the AWG outputs 4-channel 14 / 28GBaud QPSK / 16QAM / 32QAM RF signals, which are sent to a polarization multiplexing-IQ modulator. In addition, this system uses two external cavity lasers with a line width of about 100KHz as the emitting laser and the local oscillator laser, and the center wavelength is set at 1550nm. Thereafter, the optical signal output by the transmitter is sent into the optical fiber link for transmissi...

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Abstract

The invention discloses a key parameter joint monitoring method in an elastic optical network (EON), which comprises the following steps: S1, in an EON system, performing photoelectric conversion and analog-to-digital conversion on a dual-polarization high-order modulation format signal through a coherent receiver, performing digital signal preprocessing on the converted signal, and generating a signal constellation diagram according to the preprocessed signal; S2, performing digital image preprocessing on the generated signal constellation diagram; S3, performing Radon transformation on the preprocessed signal constellation diagram to obtain a corresponding three-primary-color image; and S4, according to the obtained three-primary-color image, realizing joint identification and monitoring of a plurality of key parameters through a multi-task neural network model. According to the method, on the basis of Radon transformation and a multi-task neural network, five optical signal key parameters or performance indexes can be intelligently, rapidly and stably identified or monitored; based on specific simulation and experimental verification, the method has the advantages of multiple monitoring parameters, high identification precision and good robustness.

Description

technical field [0001] The invention belongs to the technical field of optical fiber communication, and in particular relates to a key parameter joint monitoring method in an elastic optical network. Background technique [0002] In order to meet the ever-increasing capacity demands of global Internet protocol traffic and further improve the spectrum utilization efficiency of optical fiber communication systems, since 2008, scholars have proposed an Elastic Optical Network (EON) architecture based on coherent reception, using a finer spectrum grid Transceiver with variable grid and bandwidth, adaptively changing various transmitter parameters (such as modulation format, baud rate, number of subcarriers, etc.), providing "just enough" spectrum scheduling for each connection requirement to meet dynamically changing traffic need. Compared with the existing dense wavelength division multiplex (DWDM) system, the spectral efficiency of this network can be increased by 5%-95%, and...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04B10/079H04Q11/00G06K9/62G06N3/04G06N3/08G06T7/13G06T7/136
CPCH04B10/0793H04B10/07953H04B10/0795H04Q11/0062G06N3/08G06T7/13G06T7/136G06T2207/10024G06T2207/20081G06T2207/20084H04Q2011/0083G06N3/047G06N3/045G06F18/2415
Inventor 许恒迎周唐磊唐雪王志国毕岩峰白成林杨立山孙伟斌赵如清李保堃于新阔
Owner LIAOCHENG UNIV
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