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

Abstract

The present invention provides a method, system, and medium for joint calibration of multiple parameters of an optical communication system, comprising: step S1: determining an optical communication system performance evaluation index and identifying uncertain parameters that need to be calibrated, and establishing a digital twin model of the optical communication system; step S2: performing a global sensitivity analysis on the uncertain parameters in the digital twin model, calculating the degree of influence of each uncertain parameter on system performance and quantifying it as importance, sorting the parameters according to importance, and dividing them into importance levels; step S3: performing a parameter calibration process level by level according to the importance level, introducing a memory perception mechanism, and finally obtaining a complete calibrated parameter set, which is applied to the digital twin model. The present invention adopts a method of first performing sensitivity analysis and then calibrating parameters, thereby improving the efficiency of parameter calibration and the accuracy of the parameters after calibration; and adopts a memory perception mechanism when solving the calibration parameters of the optimization problem, thereby improving the efficiency of parameter calibration and the accuracy of the parameters after calibration.

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 twinning involves synchronously updating a digital model of a physical entity with its real-world counterpart, enabling full lifecycle management and optimization of the physical entity. Optical communication is a communication method based on optical technology. It uses optical fiber as a transmission medium, converting information into optical signals for transmission. Compared to traditional telecommunications technologies, optical communication offers advantages such as higher transmission rates, greater bandwidth, lower loss, and longer transmission distances.

[0003] During the construction of 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 signalpower 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, the present invention aims to provide a method, system and medium for joint calibration of multiple parameters in an optical communication system.

[0006] According to the present invention, a multi-parameter joint calibration method for an optical communication system is provided, comprising:

[0007] Step S1: 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;

[0008] Step S2: Perform a 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 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, and finally obtain the complete parameter set after calibration and apply it to the digital twin model.

[0010] Preferably, step S2 includes:

[0011] Step S2.1: Calculate the influence of each parameter on system performance by the 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 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 includes:

[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 includes:

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

[0020]

[0021] Where Q DT To use the performance evaluation index estimated by the digital twin model, Q meaa is the performance evaluation index obtained from the actual optical communication system, N s is the number of collected data, m represents the number of parameters to be calibrated, 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 let

[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 is provided, comprising:

[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 system performance and quantify its importance, sort the parameters from high to low according to their importance and classify them into importance levels;

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

[0028] Preferably, the module M2 includes:

[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 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 includes:

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

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

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

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

[0038]

[0039] Where Q DT To use the performance evaluation index estimated by the digital twin model, Q meas is the performance evaluation index obtained from the actual optical communication system, N s is the number of collected data, m represents the number of parameters to be calibrated, 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 let

[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 calibration parameters, so as to keep the previous parameter calibration results from being 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 upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

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

[0048] The present invention will be described in detail below with reference to specific embodiments. The following examples 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 skilled in the art, several changes and improvements can be made without departing from the scope of the present invention. These all fall within the scope of protection of the present invention.

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

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

[0051] Step S1: 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;

[0052] Step S2: Perform a 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 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, and finally obtain the complete parameter set after calibration and apply it to the digital twin model.

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

[0055] Step S2.1: Calculate the influence of each parameter on system performance by the 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 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 as the first level, and the lower important parameters being classified as 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 the optimized loss function, introduce the memory perception term in the optimization objective, and optimize the loss function. The expression is as follows:

[0064]

[0065] Where Q DT To use the performance evaluation index estimated by the digital twin model, Q meas is the performance evaluation index obtained from the actual optical communication system, N s is the number of collected data, m represents the number of parameters to be calibrated, 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, let

[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 system performance and quantify its importance, sort the parameters from high to low according to their importance and classify them into importance levels;

[0072] Module M3: Perform parameter calibration step by step according to the importance level, introduce a memory perception mechanism, and finally obtain a complete set of calibrated parameters 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 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 final optimized complete parameter set 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 performance evaluation index estimated by the digital twin model, Q meas is the performance evaluation index obtained from the actual optical communication system, N s is the number of collected data, m represents the number of parameters to be calibrated, 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, let

[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 will appreciate that, in addition to implementing the system and its various devices, modules, and units provided by the present invention in purely computer-readable program code, it is entirely possible to implement the same functions of the system and its various devices, modules, and units provided by the present invention 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 a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; the devices, modules, and units for implementing various functions can also be considered as both software modules implementing the method and structures within the hardware component.

[0088] The above describes specific embodiments of the present invention. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. The embodiments of this application and the features in the embodiments may be combined with each other in any manner unless there is a conflict.

Claims

1. A multi-parameter joint calibration method for an optical communication system, characterized in that: include: Step S1: 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; Step S2: Perform a 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 according to importance and divide them into importance levels; Step S3: Perform parameter calibration step by step according to the importance level, introduce a memory perception mechanism, and finally obtain a complete set of calibrated parameters and apply it to the digital twin model; 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; The step S3.1 includes: Step S3.1.1: Abstract the parameter calibration problem into an optimization problem, construct the optimized loss function, introduce the memory perception term in the optimization objective, and optimize the loss function. The expression is as follows: In the formula To use the performance evaluation indicators estimated by the digital twin model, is a performance evaluation index obtained from actual optical communication systems. is the amount of data collected, represents the number of parameters to be calibrated, is a hyperparameter that controls the penalty strength of the memory-aware term. is the first parameters The importance of After the previous level of optimization calibration Parameters, such as If the parameters are not optimized and calibrated, ; 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 the target is solved ; Step S3.1.3: Stop the optimization when all parameters are optimized and calibrated.

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 the basic effect method and quantify it as importance. The expression is as follows: In the formula For the parameters The importance of It is a digital twin model. is the number of paths in the basic effects method, Indicates the sequence number of each step in the basic effects method, is the 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. 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 system performance and quantify its importance, sort the parameters from high to low according to their importance and classify them into importance levels; Module M3: Performs parameter calibration on a level-by-level basis according to importance, introduces a memory-aware mechanism, and ultimately obtains a complete set of calibrated parameters, which are then applied to the digital twin model. The module M3 includes: Module M3.1: Calibrate the parameters of each level step by step according to the importance level; Module M3.2: Obtain the final optimized complete parameter set and apply the calibrated parameters to the digital twin model; 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: In the formula To use the performance evaluation indicators estimated by the digital twin model, is a performance evaluation index obtained from actual optical communication systems. is the amount of data collected, represents the number of parameters to be calibrated, is a hyperparameter that controls the penalty strength of the memory-aware term. The first parameters The importance of After the previous level of optimization calibration Parameters, such as If the parameters are not optimized and calibrated, ; Module M3.1.2: Starting from the first level of importance, use optimization algorithms to optimize the constructed optimization problem and solve it. ; Module M3.1.3: Stop optimization when all parameters are optimized and calibrated.

4. The optical communication system multi-parameter joint calibration system according to claim 3, characterized in that: The module M2 includes: 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 For the parameters The importance of It is a digital twin model. is the number of paths in the basic effects method, Indicates the sequence number of each step in the basic effects method, is the 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.

5. 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 optical communication system multi-parameter joint calibration method according to claim 1 or 2 are implemented.

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