Multi-parameter joint calibration method and system for optical communication system and medium

Abstract

The invention provides a multi-parameter joint calibration method and system for an optical communication system and a medium, and the method comprises the steps: S1, determining a performance evaluation index of the optical communication system, recognizing uncertain parameters needing to be calibrated, and building a digital twin model of the optical communication system; s2, carrying out global sensitivity analysis on uncertain parameters in the digital twinborn model, calculating the influence degree of each uncertain parameter on the system performance, quantifying the influence degree as importance, sorting the parameters according to the importance, and classifying importance levels; and S3, performing a parameter calibration process level by level according to the importance level, introducing a memory perception mechanism, finally obtaining a calibrated complete parameter set, and applying the calibrated complete parameter set to the digital twinborn model. According to the method, the sensitivity is analyzed first and then the parameters are calibrated, so that the parameter correction efficiency and the accuracy of the corrected parameters are improved; a memory perception mechanism is introduced when an optimization problem calibration parameter is solved, so that the parameter calibration efficiency is improved, and the accuracy of the corrected parameter is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of parameter calibration, and in particular to a method, system and medium for joint calibration of multiple parameters of an optical communication system. Background Art

[0002] Digital twin refers to the synchronization of the digital model of a physical entity with its real-world counterpart, thereby achieving full life cycle management and optimization of the physical entity. Optical communication is a communication method based on optical technology for information transmission. It uses optical fiber as a transmission medium to convert information into optical signals for transmission. Compared with traditional telecommunications technology, optical communication has the advantages of higher transmission rate, larger bandwidth, lower loss and longer transmission distance.

[0003] In the process of building optical communication networks, parameter calibration is a research point for building digital twin models of optical communication systems. The purpose is to make the digital twin models as consistent as possible with the actual system.

[0004] A parameter calibration method was proposed in Yan He, Zhiqun Zhai, Liang Dou, Lingling Wang, Yaxi Yan, Chongjin Xie, Chao Lu, and Alan Pak Tao Lau, "Improved QoT estimations through refined signal power measurements and data-driven parameter optimizations in a disaggregated and partially loaded live production network," J. Opt. Commun. Netw. 15, 638-648 (2023). However, the correction order of each model parameter in their method is based on human experience, which is not efficient enough and requires a large amount of measurement data. Summary of the invention

[0005] In view of the defects in the prior art, an object of the present invention is to provide a method, system and medium for joint calibration of multiple parameters of an optical communication system.

[0006] A multi-parameter joint calibration method for an optical communication system provided by the present invention includes:

[0007] Step S1: Determine the performance evaluation index of the optical communication system and identify the uncertain parameters that need to be calibrated, and establish a digital twin model of the optical communication system;

[0008] Step S2: Perform global sensitivity analysis on the uncertain parameters in the digital twin model, calculate the influence of each uncertain parameter on the system performance and quantify it as importance, sort the parameters from high to low according to importance and divide them into importance levels;

[0009] Step S3: Perform parameter calibration process level by level according to the importance level, introduce memory perception mechanism, finally obtain the complete parameter set after calibration, and apply it to the digital twin model.

[0010] Preferably, the step S2 comprises:

[0011] Step S2.1: Calculate the influence of each parameter on system performance by basic effect method and quantify it as importance. The expression is as follows:

[0012]

[0013] In the formula is the i-th parameter x i The importance of F DT (·) is the digital twin model, N r is the number of paths in the basic effect method, r represents the sequence number of each step in the basic effect method, and Δ is the step length of each step in the path of the basic effect method;

[0014] Step S2.2: Classify the parameters into multiple importance levels according to their importance.

[0015] Preferably, step S3 comprises:

[0016] Step S3.1: calibrate the parameters of each level step by step according to the importance level;

[0017] Step S3.2: Obtain the final optimized complete parameter set and apply the calibrated parameters to the digital twin model.

[0018] Preferably, the step S3.1 comprises:

[0019] Step S3.1.1: Abstract the parameter calibration problem into an optimization problem, construct an optimized loss function, introduce memory-aware terms into the optimization objective, and optimize the loss function The expression is as follows:

[0020]

[0021] Where Q DT To use the digital twin model to estimate the performance evaluation index, Q meaa is the performance evaluation index obtained from the actual optical communication system, N s is the number of collected data, m is the number of parameters to be calibrated, and λ MAis a hyperparameter that controls the penalty strength of the memory-aware term, is the i-th parameter x obtained in step S2 i The importance of is the i-th parameter after the previous level of optimization and calibration. If the i-th parameter has not been optimized and calibrated, then

[0022] Step S3.1.2: Starting from the first level of importance, use the optimization algorithm to optimize the constructed optimization problem to minimize the loss function The value of is the target solution x i , The introduction of this item ensures that the current optimization result does not deviate from the previous parameter calibration results, achieving the advantage of keeping the previous parameter calibration results in mind;

[0023] Step S3.1.3: Stop the optimization when all parameters are optimized and calibrated.

[0024] According to the present invention, a multi-parameter joint calibration system for an optical communication system includes:

[0025] Module M1: Determine the performance evaluation indicators of the optical communication system and identify the uncertain parameters that need to be calibrated, and establish a digital twin model of the optical communication system;

[0026] Module M2: Perform global sensitivity analysis on the uncertain parameters in the digital twin model, calculate the impact of each uncertain parameter on the system performance and quantify it as importance, sort the parameters from high to low in importance and divide them into importance levels;

[0027] Module M3: Perform parameter calibration process level by level according to the importance level, introduce memory perception mechanism, finally obtain the complete parameter set after calibration, and apply it to the digital twin model.

[0028] Preferably, the module M2 comprises:

[0029] Module M2.1: Calculate the influence of each parameter on system performance through the basic effect method and quantify it as importance. The expression is as follows:

[0030]

[0031] In the formula is the i-th parameter x i The importance of F DT (·) is the digital twin model, N r is the number of paths in the basic effect method, r represents the sequence number of each step in the basic effect method, and Δ is the step length of each step in the path of the basic effect method;

[0032] Module M2.2: Classify parameters into multiple importance levels based on their importance.

[0033] Preferably, the module M3 comprises:

[0034] Module M3.1: Calibrate the parameters of each level step by step according to the importance level;

[0035] Module M3.2: Obtain the complete parameter set after final optimization and apply the calibrated parameters to the digital twin model.

[0036] Preferably, the module M3.1 comprises:

[0037] Module M3.1.1: Abstract the parameter calibration problem into an optimization problem, construct an optimized loss function, introduce memory perception terms into the optimization objective, and the optimized loss function L is expressed as follows:

[0038]

[0039] Where Q DT To use the digital twin model to estimate the performance evaluation index, Q meas is the performance evaluation index obtained from the actual optical communication system, N s is the number of collected data, m is the number of parameters to be calibrated, and λ MA is a hyperparameter that controls the penalty strength of the memory-aware term, is the i-th parameter x obtained in module M2 i The importance of is the i-th parameter after the previous level of optimization and calibration. If the i-th parameter has not been optimized and calibrated, then

[0040] Module M3.1.2: Starting from the first level of importance, use optimization algorithms to optimize the constructed optimization problem to minimize the loss function The value of is the target solution x i , The introduction of this item ensures that the current optimization result does not deviate from the previous parameter calibration results, achieving the advantage of keeping the previous parameter calibration results in mind;

[0041] Module M3.1.3: Stop optimization when all parameters are optimized and calibrated.

[0042] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the multi-parameter joint calibration method for an optical communication system are implemented.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. The present invention improves the efficiency of parameter correction and the accuracy of the corrected parameters by adopting a method of first performing sensitivity analysis and then calibrating the parameters.

[0045] 2. The present invention introduces a memory perception mechanism when solving the optimization problem and calibrating the parameters, so as to ensure that the previous parameter calibration results are not forgotten, thereby improving the parameter calibration efficiency and enhancing the accuracy of the corrected parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0047] Figure 1 It is a flow chart of the multi-parameter joint calibration method of the optical communication system in the present invention. DETAILED DESCRIPTION

[0048] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0049] The present invention proposes a multi-parameter joint calibration method for an optical communication system, which innovatively combines sensitivity analysis with a memory perception mechanism, and achieves high-precision joint calibration of multiple parameters by quantifying the importance of uncertain parameters and performing multi-stage optimization.

[0050] Reference Figure 1 As shown, the optical communication system multi-parameter joint calibration method of the present invention comprises the following steps:

[0051] Step S1: Determine the performance evaluation index of the optical communication system and identify the uncertain parameters that need to be calibrated, and establish a digital twin model of the optical communication system;

[0052] Step S2: Perform global sensitivity analysis on the uncertain parameters in the digital twin model, calculate the influence of each uncertain parameter on the system performance and quantify it as importance, sort the parameters from high to low according to importance and divide them into importance levels;

[0053] Step S3: Perform parameter calibration process level by level according to the importance level, introduce memory perception mechanism, finally obtain the complete parameter set after calibration, and apply it to the digital twin model.

[0054] In a specific implementation, step S2 includes the following sub-steps:

[0055] Step S2.1: Calculate the influence of each parameter on system performance by basic effect method and quantify it as importance. The expression is as follows:

[0056]

[0057] In the formula is the i-th parameter x i The importance of F DT (·) is the digital twin model, N r is the number of paths in the basic effect method, r represents the sequence number of each step in the basic effect method, and Δ is the step length of each step in the path of the basic effect method;

[0058] Step S2.2: Classify the parameters into multiple importance levels according to their importance, with the most important parameters being classified into the first level, and the lower ones being classified into the second level, the third level, and so on;

[0059] Specifically, step S3 includes the following steps:

[0060] Step S3.1: Calibrate the parameters of each level step by step starting from the first level according to the importance level;

[0061] Step S3.2: Obtain the final optimized complete parameter set and apply the calibrated parameters to the digital twin model;

[0062] Wherein, the step 3.1 specifically includes the following steps:

[0063] Step S3.1.1: Abstract the parameter calibration problem into an optimization problem, construct an optimized loss function, introduce memory-aware terms into the optimization objective, and optimize the loss function The expression is as follows:

[0064]

[0065] Where Q DT To use the digital twin model to estimate the performance evaluation index, Q meas is the performance evaluation index obtained from the actual optical communication system, N s is the number of collected data, m is the number of parameters to be calibrated, and λ MA is a hyperparameter that controls the penalty strength of the memory-aware term, is the i-th parameter x obtained in step 2 i The importance of is the i-th parameter after the previous level of optimization and calibration. If the i-th parameter has not been optimized and calibrated, then

[0066] Step S3.1.2: Starting from the first level of importance, use the optimization algorithm to optimize the constructed optimization problem to minimize the loss function The value of is the target solution x i , The introduction of this item ensures that the current optimization result does not deviate from the previous parameter calibration results, achieving the advantage of keeping the previous parameter calibration results in mind;

[0067] Step S3.1.3: Stop the optimization when all parameters are optimized and calibrated.

[0068] The present invention also provides a multi-parameter joint calibration system for an optical communication system. The multi-parameter joint calibration system for an optical communication system can be implemented by executing the process steps of the multi-parameter joint calibration method for an optical communication system, that is, those skilled in the art can understand the multi-parameter joint calibration method for an optical communication system as a preferred implementation of the multi-parameter joint calibration system for an optical communication system.

[0069] The present invention provides an optical communication system multi-parameter joint calibration system, comprising:

[0070] Module M1: Determine the performance evaluation indicators of the optical communication system and identify the uncertain parameters that need to be calibrated, and establish a digital twin model of the optical communication system;

[0071] Module M2: Perform global sensitivity analysis on the uncertain parameters in the digital twin model, calculate the impact of each uncertain parameter on the system performance and quantify it as importance, sort the parameters from high to low in importance and divide them into importance levels;

[0072] Module M3: Perform parameter calibration process level by level according to the importance level, introduce memory perception mechanism, finally obtain the complete parameter set after calibration, and apply it to the digital twin model.

[0073] Specifically, module M2 includes:

[0074] Module M2.1: Calculate the influence of each parameter on system performance through the basic effect method and quantify it as importance. The expression is as follows:

[0075]

[0076] In the formula is the i-th parameter x i The importance of F DT (·) is the digital twin model, N r is the number of paths in the basic effect method, r represents the sequence number of each step in the basic effect method, and Δ is the step length of each step in the path of the basic effect method;

[0077] Module M2.2: Classify parameters into multiple importance levels based on their importance.

[0078] Specifically, module M3 includes:

[0079] Module M3.1: Calibrate the parameters of each level step by step according to the importance level;

[0080] Module M3.2: Obtain the complete parameter set after final optimization and apply the calibrated parameters to the digital twin model.

[0081] Among them, module M3.1 includes:

[0082] Module M3.1.1: Abstract the parameter calibration problem into an optimization problem, construct an optimized loss function, introduce memory perception terms in the optimization objective, and optimize the loss function The expression is as follows:

[0083]

[0084] Where Q DT To use the digital twin model to estimate the performance evaluation index, Q meas is the performance evaluation index obtained from the actual optical communication system, N s is the number of collected data, m is the number of parameters to be calibrated, and λ MA is a hyperparameter that controls the penalty strength of the memory-aware term, is the i-th parameter x obtained in module M2 i The importance of is the i-th parameter after the previous level of optimization and calibration. If the i-th parameter has not been optimized and calibrated, then

[0085] Module M3.1.2: Starting from the first level of importance, use optimization algorithms to optimize the constructed optimization problem to minimize the loss function The value of is the target solution x i , The introduction of this item ensures that the current optimization result does not deviate from the previous parameter calibration results, achieving the advantage of keeping the previous parameter calibration results in mind;

[0086] Module M3.1.3: Stop optimization when all parameters are optimized and calibrated.

[0087] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0088] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A multi-parameter joint calibration method for an optical communication system, characterized in that: include: Step S1: Determine the performance evaluation index of the optical communication system and identify the uncertain parameters that need to be calibrated, and establish a digital twin model of the optical communication system; Step S2: Perform global sensitivity analysis on the uncertain parameters in the digital twin model, calculate the influence of each uncertain parameter on the system performance and quantify it as importance, sort the parameters from high to low according to importance and divide them into importance levels; Step S3: Perform parameter calibration process level by level according to the importance level, introduce memory perception mechanism, finally obtain the complete parameter set after calibration, and apply it to the digital twin model.

2. The optical communication system multi-parameter joint calibration method according to claim 1, characterized in that: The step S2 comprises: Step S2.1: Calculate the influence of each parameter on system performance by basic effect method and quantify it as importance. The expression is as follows: In the formula is the i-th parameter x i The importance of F DT (·) is the digital twin model, N r is the number of paths in the basic effect method, r represents the sequence number of each step in the basic effect method, and Δ is the step length of each step in the path of the basic effect method; Step S2.2: Classify the parameters into multiple importance levels according to their importance.

3. The optical communication system multi-parameter joint calibration method according to claim 1, characterized in that: The step S3 comprises: Step S3.1: calibrate the parameters of each level step by step according to the importance level; Step S3.2: Obtain the final optimized complete parameter set and apply the calibrated parameters to the digital twin model.

4. The optical communication system multi-parameter joint calibration method according to claim 3, characterized in that: The step S3.1 comprises: Step S3.1.1: Abstract the parameter calibration problem into an optimization problem, construct an optimized loss function, introduce memory-aware terms into the optimization objective, and optimize the loss function The expression is as follows: Where Q DT To use the digital twin model to estimate the performance evaluation index, Q meaa is the performance evaluation index obtained from the actual optical communication system, N s is the number of collected data, m is the number of parameters to be calibrated, and λ MA is a hyperparameter that controls the penalty strength of the memory-aware term, is the i-th parameter x obtained in step S2 i The importance of is the i-th parameter after the previous level of optimization and calibration. If the i-th parameter has not been optimized and calibrated, then Step S3.1.2: Starting from the first level of importance, use the optimization algorithm to optimize the constructed optimization problem to minimize the loss function The value of is the target solution x i ; Step S3.1.3: Stop the optimization when all parameters are optimized and calibrated.

5. A multi-parameter joint calibration system for an optical communication system, characterized in that: include: Module M1: Determine the performance evaluation indicators of the optical communication system and identify the uncertain parameters that need to be calibrated, and establish a digital twin model of the optical communication system; Module M2: Perform global sensitivity analysis on the uncertain parameters in the digital twin model, calculate the impact of each uncertain parameter on the system performance and quantify it as importance, sort the parameters from high to low in importance and divide them into importance levels; Module M3: Perform parameter calibration process level by level according to the importance level, introduce memory perception mechanism, finally obtain the complete parameter set after calibration, and apply it to the digital twin model.

6. The optical communication system multi-parameter joint calibration system according to claim 5, characterized in that: The module M2 comprises: Module M2.1: Calculate the influence of each parameter on system performance through the basic effect method and quantify it as importance. The expression is as follows: In the formula is the i-th parameter x i The importance of F DT (·) is the digital twin model, N r is the number of paths in the basic effect method, r represents the sequence number of each step in the basic effect method, and Δ is the step length of each step in the path of the basic effect method; Module M2.2: Classify parameters into multiple importance levels based on their importance.

7. The optical communication system multi-parameter joint calibration system according to claim 5, characterized in that: The module M3 comprises: Module M3.1: Calibrate the parameters of each level step by step according to the importance level; Module M3.2: Obtain the complete parameter set after final optimization and apply the calibrated parameters to the digital twin model.

8. The optical communication system multi-parameter joint calibration system according to claim 7, characterized in that: The module M3.1 includes: Module M3.1.1: Abstract the parameter calibration problem into an optimization problem, construct an optimized loss function, introduce memory perception terms in the optimization objective, and optimize the loss function The expression is as follows: Where Q DT To use the digital twin model to estimate the performance evaluation index, Q meas is the performance evaluation index obtained from the actual optical communication system, N s is the number of collected data, m is the number of parameters to be calibrated, and λ MA is a hyperparameter that controls the penalty strength of the memory-aware term, is the i-th parameter x obtained in module M2 i The importance of is the i-th parameter after the previous level of optimization and calibration. If the i-th parameter has not been optimized and calibrated, then Module M3.1.2: Starting from the first level of importance, use optimization algorithms to optimize the constructed optimization problem and solve x i ; Module M3.1.3: Stop optimization when all parameters are optimized and calibrated.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the multi-parameter joint calibration method for an optical communication system according to any one of claims 1 to 4 are implemented.

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