CN-119519839-B - Raman gain self-adaptive regulation and control method and system for multiband optical network

CN119519839BCN 119519839 BCN119519839 BCN 119519839BCN-119519839-B

Abstract

The invention provides a Raman gain self-adaptive regulation and control method and system for a multiband optical network, the method comprises the steps of supplementing gain values of non-target channels, constructing gain vectors based on the gain values of target channels and the gain values of non-target channels, conducting at least one round of iteration, inputting values in a population into a pre-trained inverse model in each iteration, outputting corresponding pump regulation parameters by the inverse model, determining gain values of all channels based on the pump regulation parameters, screening out the gain values of the target channels from the gain values of all channels, calculating fitness based on the gain values of the target channels and the gain values of the screened target channels, regulating the gain values of the non-target channels based on the target function values, reconstructing the gain vectors, conducting the next round of iteration, and screening final pump regulation parameters from all pump regulation parameters after the last iteration is completed.

Inventors

GU RENTAO
GAO XIAOXUAN
LIU SIHAN
JI YUEFENG

Assignees

北京邮电大学

Dates

Publication Date: 20260508
Application Date: 20241121

Claims (10)

1. A Raman gain self-adaptive regulation and control method for a multiband optical network is characterized by comprising the following steps: Gain values of target channels and gain values of non-target channels are obtained, gain vectors are constructed based on the gain values of the target channels and the gain values of the non-target channels, random value taking is carried out in a preset gain interval or the gain values of the non-target channels are supplemented based on the target gain values of two adjacent target channels of the non-target channels, the gain values of the non-target channels are obtained, and at least one round of iteration is carried out; In each iteration of the round, inputting the values in the gain vector into a pre-trained inverse model, the inverse model outputting corresponding pump adjustment parameters; determining gain values of all channels based on the pump regulation parameters, screening gain values of target channels from the gain values of all channels, and calculating a target function value based on the gain values of the targets of the target channels and the gain values of the target channels screened from the gain values of all channels; And adjusting the gain value supplemented by the non-target channel based on the objective function value, reconstructing the gain vector, performing iteration of the next round, and screening the final pump adjustment parameters from all the pump adjustment parameters after the last iteration is completed.
2. The raman gain adaptive control method for a multiband optical network according to claim 1, wherein in the step of supplementing the gain value of the non-target channel based on the target gain values of two adjacent target channels of the non-target channel, a line graph is constructed based on all channels and the target gain values of the target channels, the horizontal axis of the line graph is a channel number, the vertical axis is a gain value, points corresponding to the target gain values of the two adjacent target channels of the non-target channel are connected, and the vertical axis height corresponding to the horizontal axis position of the connection passing through the non-target channel is used as the gain value for supplementing the non-target channel.
3. The raman gain adaptive modulation method for a multiband optical network according to claim 1, wherein in the step of determining gain values of all channels based on the pump adjustment parameters, the pump adjustment parameters are input into a preset forward model, and the forward model outputs the gain values of all channels.
4. The method for adaptively adjusting and controlling the raman gain of a multiband optical network according to claim 3, wherein the forward model and the reverse model adopt the structures of a feedforward neural network, a random forest or a convolutional neural network.
5. The raman gain adaptive modulation method for a multiband optical network according to claim 1, wherein in the step of calculating an objective function value based on a gain value of an objective channel objective and gain values of objective channels selected from gain values of all channels: calculating a root mean square error based on the gain values of the target channels and the gain values of the target channels screened from the gain values of all the channels; an objective function value is calculated based on the root mean square error.
6. The adaptive regulation and control method for raman gain for a multiband optical network according to claim 5, wherein if a genetic algorithm is adopted, the objective function value is an fitness value, and in the step of calculating an objective function value based on the root mean square error, the objective function value is calculated based on the following formula: wherein S is the calculated objective function value, In order to calculate the root mean square error, Representing the target pathway.
7. The method for adaptively adjusting and controlling raman gain of a multiband optical network according to any one of claims 1 to 6, wherein in the step of screening final pump adjustment parameters from all pump adjustment parameters after the last iteration is completed, a first screening strategy or a second screening strategy is adopted, the first screening strategy sets iteration of a preset round, one set of pump adjustment parameters is screened out as final pump adjustment parameters after the complete round of iteration is completed, and the second screening strategy determines final pump adjustment parameters in the iteration process based on a preset screening threshold.
8. The method according to claim 7, wherein in the step of screening out one set of pump adjustment parameters as final pump adjustment parameters, if a genetic algorithm is adopted, the objective function value is an fitness value, and the pump adjustment parameter corresponding to the highest fitness value is used as the final pump adjustment parameter.
9. The method according to claim 7, wherein if a genetic algorithm is adopted, the objective function value is an fitness value, and in the step of determining the final pump adjustment parameter in the iterative process based on a preset screening threshold, after each iteration of a round is completed, the calculated fitness value is compared with the preset fitness threshold, and if the calculated fitness value is greater than the preset fitness threshold, the iteration of the round is used as the iteration of the last round, and the pump adjustment parameter of the round is output as the final pump adjustment parameter.
10. A raman gain adaptive regulation and control system for a multiband optical network, characterized in that the system comprises a computer device, the computer device comprises a processor and a memory, the memory stores computer instructions, the processor is configured to execute the computer instructions stored in the memory, and when the computer instructions are executed by the processor, the system implements the steps implemented by the method according to any one of claims 1 to 9.

Description

Raman gain self-adaptive regulation and control method and system for multiband optical network Technical Field The invention relates to the technical field of optical amplifiers, in particular to a Raman gain self-adaptive regulation and control method and system for a multiband optical network. Background With the development of new technologies such as 5G/6G mobile communication and the continuous evolution of next-generation applications, high-capacity access traffic such as machine-to-machine communication is continuously increased, data traffic of a transmission network is rapidly increased, and an optical network as an infrastructure transmission facility faces a huge traffic demand, so that further expansion is needed. The introduction of advanced modulation formats and constellation shaping is an economical and efficient solution to extend the single channel capacity, but the single channel capacity is eventually limited by nonlinear shannon limits, which is insufficient to support the capacity expansion requirements of the network. The introduction of new band transmission multi-band optical networks is a promising solution that can utilize the entire communication window of Standard Single Mode Fiber (SSMF) to expand the capacity of deployed optical networks, which has proven to be a short and medium term preferred solution for optical network expansion. In a multi-band optical network, where different signal channels are subject to non-uniformities in interactions between the various effects of kerr nonlinearity, amplified spontaneous emission noise, and stimulated raman scattering, the signal channel power curve will likely take on arbitrary shapes. In order to guarantee the quality of the transmitted signal, to optimize the information rate in the multiband, it is necessary to be able to achieve ultra-fast gain profile reconfiguration. The optical fiber Raman amplifier belongs to an optical amplifier based on nonlinear optical effect, has very low noise figure compared with other types of optical amplifiers, and can ensure high-quality transmission of signals. More importantly, the fiber raman amplifier allows for flexible gain profile design by adjusting pump power and wavelength and provides gain availability in the multiband range when operated in a multi-pump configuration, well suited for achieving arbitrary gain profiles in a multiband optical network in a controlled manner. However, in a commercial raman pump module, the pump wavelength and the number are set in advance, and the parameters that can be adjusted are only pump power, so that the limited pump adjustment parameters cannot support the raman amplifier to realize accurate arbitrary gain on all wavelength channels of the whole amplification band. In actual optical transmission, not all channels have traffic transmission, only the wavelength channels of part of the links are generally used, but the prior art can only perform pump adjustment parameters for gain pairs of all channels, and cannot guarantee the pertinence of the wavelength channels of part of the links. Disclosure of Invention In view of this, embodiments of the present invention provide a method and a system for adaptive regulation and control of raman gain for a multi-band optical network, so as to eliminate or improve one or more drawbacks existing in the prior art. The invention provides a Raman gain self-adaptive regulation and control method for a multiband optical network, which comprises the following steps: Gain values of target channels and non-target channels are obtained, gain values of the non-target channels are supplemented, gain vectors are constructed based on the gain values of the target channels and the gain values of the non-target channels, and at least one round of iteration is performed; In each iteration of the round, inputting the values in the gain vector into a pre-trained inverse model, the inverse model outputting corresponding pump adjustment parameters; determining gain values of all channels based on the pump regulation parameters, screening gain values of target channels from the gain values of all channels, and calculating a target function value based on the gain values of the targets of the target channels and the gain values of the target channels screened from the gain values of all channels; And adjusting the gain value of the non-target channel supplement based on the objective function value, reconstructing the gain vector, performing iteration of the next round, and screening the final pump adjustment parameters from all the pump adjustment parameters after the last iteration is completed. According to the scheme, the gain values of the non-target channels are randomly supplemented, the corresponding pump adjusting parameters are obtained through the inverse model, the gain values of all the channels are determined based on the pump adjusting parameters until the fitness meets the requirement, and the pump adjusting paramete