Anti-mode-coupling few-mode signal complex format analysis method and device

A mode coupling and analysis method technology, applied in the field of complex format analysis of few-mode signals against mode coupling, can solve the problem of not considering the modulation format identification of few-mode fiber signals, increase the cost and training time of training, and affect the optical performance monitoring. System monitoring performance and other issues, to achieve good generalization ability and recognition performance, reduce computational complexity, and reduce training costs.

Active Publication Date: 2021-11-09
NANJING UNIV OF INFORMATION SCI & TECH
View PDF9 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the neural network has many parameters, and the training and learning process is relatively long. If the optimization method is improper, it is easy to fall into the local optimum.
Moreover, these algorithms do not take into account the identification of signal modulation formats based on few-mode fibers, because there are multiple transmission modes in few-mode fibers
Once the channel parameters are changed, the neural network based on the

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Anti-mode-coupling few-mode signal complex format analysis method and device
  • Anti-mode-coupling few-mode signal complex format analysis method and device
  • Anti-mode-coupling few-mode signal complex format analysis method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] This embodiment provides a domain-adaptive-anti-mode-coupling few-mode signal complex format analysis method.

[0046] Aiming at the poor recognition effect of the modulation format of the elastic optical network based on the few-mode fiber, and the complicated production of the data set, the present invention uses the constellation diagrams of signals with different modulation formats as the classification feature, and proposes a domain-adaptive anti-mode coupling few-mode signal complex format parsing method. Such as figure 1As shown, the implementation of this method is mainly divided into three parts: data generation, network training, and discrimination prediction.

[0047] In the data generation part, the patent of the present invention collects data samples of the source domain and the target domain respectively and performs data enhancement on the collected data to obtain constellation diagrams of signals with different modulation formats. Among them, the data...

Embodiment 2

[0070] This embodiment provides an anti-mode coupling few-mode signal complex format analysis device, the device comprising:

[0071] Data generation module: used to collect data samples in the source domain and target domain and perform data enhancement on the collected data to obtain constellation diagrams of signals in different modulation formats, and then normalize all the collected constellation diagrams to obtain training data ;

[0072] Network training module: used to obtain the network model of the source domain, and train the network model according to the training data to obtain a trained network model;

[0073] Discrimination and prediction module: used to obtain the data of the target domain of the received signal and perform data enhancement, extract the trained network model, and fine-tune the trained network model for the inherent link damage of few models, and obtain the target network model, through The target network model obtains the modulation format of ...

Embodiment 3

[0075] The embodiment of the present invention also provides an anti-mode coupling few-mode signal complex format analysis device, including a processor and a storage medium;

[0076] The storage medium is used to store instructions;

[0077] The processor is configured to operate according to the instructions to perform the steps of the following method:

[0078] Collect data samples in the source domain and target domain and perform data enhancement on the collected data to obtain constellation diagrams of signals in different modulation formats, and then normalize all the collected constellation diagrams to obtain training data;

[0079] Obtain the network model of the source domain, and train the network model according to the training data to obtain a trained network model;

[0080] Obtaining the data of the target domain of the received signal and performing data enhancement, extracting the trained network model, and fine-tuning the trained network model for the inheren...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses an anti-mode-coupling few-mode signal complex format analysis method and device, and aims to solve the problems of poor modulation format identification effect and high training cost of an elastic optical network based on few-mode optical fibers; a wavelength division multiplexing technology is taken as a source domain and a mode division multiplexing technology is taken as a target domain through a domain self-adaption theory. The stimulated Raman scattering effect is analogous to the mode coupling effect, so that the neural network learns the law of energy migration. Compared with a retrained network model, the method can realize modulation format identification of the few-mode signal only by using a small amount of few-mode data, significantly reduces the training cost of the neural network, accelerates the convergence rate of the network model, and reduces the model training time and calculation complexity. Meanwhile, by means of the theoretical advantages of transfer learning, the network has better generalization ability and recognition performance, can adapt to the influence of mode coupling in the few-mode optical fiber on the modulation format, and achieves the modulation format recognition task of the few-mode optical network.

Description

technical field [0001] The invention belongs to the technical field of optical communication, and in particular relates to an anti-mode coupling few-mode signal complex format analysis method and device. Background technique [0002] In recent years, the rapid development of information technology and data applications has brought many new challenges and limitations to optical transmission networks based on single-mode fibers. In order to meet the growing bandwidth demands of data centers, cloud services, 5G, Internet of Things, virtual reality and other emerging services, the existing optical fiber communication system urgently needs an effective expansion method. At present, most physical dimensions of light waves such as amplitude, phase, time slot, and polarization in single-mode fiber systems have been utilized to a large extent. In order to improve the spectral efficiency of the signal, some high-order modulation formats have also been proposed. However, limited by t...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F30/18G06F30/27G06K9/62G06N3/04G06N3/08H04L27/00H04B10/60G06F111/02
CPCG06F30/18G06F30/27G06N3/08H04L27/0012H04B10/60G06F2111/02G06N3/045G06F18/213G06F18/214G06F18/24
Inventor 朱筱嵘刘博毛雅亚朱旭李明烨雷思亮
Owner NANJING UNIV OF INFORMATION SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap