An Implicit Triplet Neural Network and Optical Fiber Nonlinear Damage Equalization Method

A nonlinear damage and neural network technology, applied in the field of implicit triplet neural network and optical fiber nonlinear damage equalization, can solve the problems of high complexity and more training data, and achieve the effect of low computational cost and less training data

Active Publication Date: 2022-07-29
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0004] The purpose of the present invention is to propose an implicit triplet neural network and an optical fiber nonlinear damage equalization method in view of the technical defects that the existing optical fiber nonlinear damage equalization method requires a lot of training data and high complexity

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  • An Implicit Triplet Neural Network and Optical Fiber Nonlinear Damage Equalization Method

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Embodiment 1

[0075] Two series of pseudo-random bit sequences (PRBS) are generated for each channel respectively for the transmission of two polarization states to attach figure 1 The mapping relationship of the two strings of PRBS is mapped to the constellation diagram to obtain dual-polarization 16QAM symbols, which are used as label symbol streams. According to the attached figure 2 Schematic diagram of the system to build a simulation system, and change the fiber input power and transmission distance (the fiber input power is from -4dBm to 2dBm per channel, the step is 1; the transmission distance is from 2400km to 4000km, the step is 80km), according to step 1 to generate different conditional dataset. The training set size ranges from 3000 symbols to 32768 symbols, and the validation and test sets are both 32768 symbols in size.

[0076] According to the attached image 3 The structure diagram of a constructs an implicit triplet neural network to be optimized. For datasets under...

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Abstract

The invention relates to an implicit triplet neural network and an optical fiber nonlinear damage equalization method, belonging to the technical field of optical fiber communication and equalization. It includes an implicit triplet neural network and an optical fiber nonlinear damage equalization method based on the network. The method: 1) generating a training set, a verification set and a test set, specifically: generating a binary bit stream, generating a label symbol stream, acquiring a to-be-processed symbol stream, generating samples and dividing a data set 2) optimizing the implicit triplet neural network network to obtain the optimal implicit triplet neural network; initialize the hyperparameter search process, initialize the tunable parameter iteration process, calculate the loss function and the gradient of all tunable parameters and update the tunable parameters, iterate and evaluate the optimization results, select the most Excellent implicit triplet neural network; 3) Test the implicit triplet neural network to get the equalized signal. Compared with the prior art, the neural network and the method have lower computational cost and can further improve the equalization effect.

Description

technical field [0001] The invention relates to an implicit triplet neural network and an optical fiber nonlinear damage equalization method, and belongs to the technical field of optical fiber communication and equalization. Background technique [0002] The capacity of an optical fiber communication system is limited by the linear damage and nonlinear damage of the optical fiber. With the development of optical fiber communication technology, the communication capacity of optical fiber communication system has approached the Shannon limit in the linear region. To further improve the communication capacity of the optical fiber communication system, it is necessary to break through the limitation of the nonlinear damage of the optical fiber. In addition to link optical compensation methods, typical optical fiber nonlinear compensation methods also include digital signal processing compensation methods. Compensation methods for digital signal processing include digital back...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04B10/2543H04B10/516H04B10/61G06N3/04G06N3/08
CPCH04B10/2543H04B10/516H04B10/6163G06N3/08G06N3/045
Inventor 杨爱英何品靖郭芃冯立辉忻向军
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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