Compensation method and related equipment for optical fiber frequency transmission

Abstract

The present application provides a method and related equipment for compensating for optical fiber frequency transmission. The method comprises: obtaining historical phase jitter data of the round-trip transmission of a frequency signal in an optical fiber link; inputting the historical phase jitter data into a pre-trained target long-short-term memory (LSTM) network model to obtain a predicted value for the phase jitter of the next transmission delay; and compensating for the next transmission delay based on the predicted value. The solution of the present application takes into account the differences in phase jitter between two adjacent transmission delays, improving compensation accuracy and thus achieving phase-stable transmission of frequency signals based on optical fiber.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a compensation method for optical fiber frequency transmission and related equipment. Background Art

[0002] Optical fiber transmission has been widely used in the communications field due to its advantages of low loss, high capacity, high speed, high stability, and safety and reliability. Fiber-based frequency transmission is an effective way to achieve high-precision frequency transmission. However, mechanical vibration or temperature changes can cause fluctuations in the fiber length, resulting in a phase difference between the frequency signal received at the remote end and the phase of the signal transmitted locally.

[0003] To ensure that the phase of a frequency signal remains stable after it is transmitted through an optical fiber to a remote end, real-time detection and compensation of phase jitter caused by fiber length variations are necessary. Conventional optical fiber link phase compensation techniques simply apply the conjugate of historical phase jitter to compensate for the next transmission delay. This approach fails to consider the variability of phase jitter within adjacent transmission delays, resulting in a certain lag in the compensated results. Summary of the Invention

[0004] In view of this, the purpose of this application is to propose a compensation method for optical fiber frequency transmission and related equipment to solve or partially solve the above problems.

[0005] In a first aspect, the present application provides a method for compensating optical fiber frequency transmission, comprising:

[0006] Obtain historical phase jitter data of frequency signals transmitted back and forth in optical fiber links;

[0007] Inputting the historical phase jitter data into a pre-trained target long short-term memory (LSTM) network model to obtain a predicted value of the phase jitter of the next transmission delay;

[0008] The next transmission delay is compensated according to the predicted value.

[0009] In a second aspect of the present application, a compensation device for optical fiber frequency transmission is provided, comprising:

[0010] An acquisition module is configured to acquire historical phase jitter data of a frequency signal transmitted back and forth in an optical fiber link;

[0011] A prediction module is configured to input the historical phase jitter data into a pre-trained target long short-term memory (LSTM) network model to obtain a predicted value of the phase jitter of the next transmission delay;

[0012] The compensation module is configured to compensate for the next transmission delay according to the predicted value.

[0013] In a third aspect of the present application, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor implements the method described in the first aspect when executing the computer program.

[0014] In a fourth aspect of the present application, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium stores computer instructions, wherein the computer instructions are used to enable a computer to execute the method described in the first aspect.

[0015] As can be seen from the above, the compensation method and related equipment for optical fiber frequency transmission provided by the present application obtain the predicted value of the phase jitter of the next transmission delay by inputting the historical phase jitter into the target LSTM model, and compensates for the actual phase jitter within the next transmission delay based on the predicted value. It takes into account the difference in phase jitter between two adjacent transmission delays, improves the compensation accuracy, and thus realizes stable phase transmission of frequency signals based on optical fiber. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in this application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, the drawings described below are merely embodiments of this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0017] Figure 1 A schematic diagram illustrating a principle of an exemplary method for compensating for optical fiber frequency transfer;

[0018] Figure 2 A schematic diagram showing the principle of a method for compensating optical fiber frequency transmission according to an embodiment of the present application;

[0019] Figure 3 A schematic flow chart of a method for compensating optical fiber frequency transmission according to an embodiment of the present application;

[0020] Figure 4 A flowchart of a method for obtaining a target LSTM network model through training according to an embodiment of the present application is provided;

[0021] Figure 5 This is a schematic diagram of the structure of the LSTM network model constructed in the embodiment of the present application;

[0022] Figure 6 This is a schematic diagram of the structure of a single LSTM neuron in an embodiment of the present application;

[0023] Figure 7 This is a schematic structural diagram of a compensation device for optical fiber frequency transmission according to an embodiment of the present application;

[0024] Figure 8 This is a schematic structural diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] In order to make the objectives, technical solutions and advantages of this application more clear, the embodiments of this application are described in detail below with reference to the accompanying drawings.

[0026] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should have the usual meanings understood by people with ordinary skills in the field to which this application belongs. The "first", "second" and similar words used in the embodiments of the present application do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0027] High-precision frequency transmission and synchronization are widely used in important national economic sectors, including the Beidou navigation and positioning system, gravitational wave detection technology in space observation, and the determination of fundamental physical constants. In recent years, high-precision frequency standards have developed rapidly, with commercial hydrogen clocks achieving frequency stability on the order of 10⁻¹⁴ / s, demonstrating exceptional performance. Fiber optic transmission, with its low loss, high capacity, high speed, high stability, and safety and reliability, has become the preferred solution for achieving high-precision frequency transmission.

[0028] However, in practical applications, optical fiber is often laid along railways or highways, making it susceptible to sudden and severe interference from passing vehicles. Furthermore, many optical fiber links have sections exposed to the ground, subject to rapid temperature fluctuations. Consequently, mechanical vibrations or temperature changes can cause fluctuations in the fiber length, which in turn can lead to random phase variations in the frequency signal transmitted through the fiber. This introduces phase noise, causing the phase of the signal received at the far end to desynchronize with the phase of the signal sent locally. To ensure that the phase of the frequency signal remains stable after being transmitted through the optical fiber to the far end, real-time detection and compensation of phase jitter caused by fiber length variations is necessary.

[0029] Figure 1 A schematic diagram showing the principle of an exemplary method for compensating optical fiber frequency transmission.

[0030] like Figure 1As shown, the phase compensation of the optical fiber link in the related art is mainly based on the round-trip transmission phase pre-compensation technology, which uses the phase detector to compare the local reference signal The phase jitter of the optical fiber link is obtained in real time by comparing the round-trip signal that reaches the receiving end after being transmitted through the optical fiber and then returns to the sending end through the receiving end. Adjust the pre-compensated signal based on the detected phase jitter (make And use the compensation module to compensate the pre-compensation signal The actual phase jitter within the next transmission delay However, the above phase compensation method directly uses the conjugate of the historical phase jitter to compensate for the next transmission delay, without considering the difference in phase jitter within adjacent transmission delays. That is, due to the influence of many factors such as laser wavelength drift, mechanical vibration, temperature change, etc., the phase jitter within two adjacent transmission delays is not equal. This results in a certain hysteresis in the compensated result. In addition, optical fiber frequency transmission is continuously developing towards long distance and high precision, so the hysteresis caused by the above-mentioned phase compensation method will have an increasingly greater impact on the transmission process.

[0031] In view of this, the embodiments of the present application provide a method for compensating optical fiber frequency transmission and related equipment. Figure 2 , which is a schematic diagram of the principle of the compensation method for optical fiber frequency transmission in an embodiment of the present application. By inputting the historical phase jitter into the target LSTM network model, a predicted value of the phase jitter for the next transmission delay is obtained, and the actual phase jitter within the next transmission delay is compensated based on the predicted value. Compared with traditional round-trip transmission phase pre-compensation technology, the solution of the present application takes into account the difference in phase jitter between two adjacent transmission delays, improving compensation accuracy and thus achieving phase-stable transmission of frequency signals based on optical fiber.

[0032] Figure 3 FIG. 3 is a flow chart showing a method 300 for compensating for optical fiber frequency transmission according to an embodiment of the present application. Figure 3 As shown, the method 300 may include the following steps.

[0033] Step S301: Acquire historical phase jitter data of a frequency signal transmitted back and forth in an optical fiber link.

[0034] In this embodiment, Figure 2 As shown, for the local reference signal The phase jitter of the optical fiber link is obtained in real time by comparing the round-trip signals that arrive at the receiving end after being transmitted through the optical fiber and then return to the transmitting end through the original path of the receiving end. All the phase jitter data obtained in real time is used as the historical phase jitter data (for example, the data volume is 400,000).

[0035] In specific implementation, in order to accurately obtain the phase difference within adjacent transmission delays, the acquisition interval of the historical phase jitter data can be the length of the optical fiber link (m) / the propagation speed of light in the optical fiber 2×10 8 (m / s).

[0036] Step S302: Input the historical phase jitter data into a pre-trained target LSTM (Long Short-Term Memory) network model to obtain a predicted value of the phase jitter of the next transmission delay.

[0037] In this example, an LSTM network model for testing is obtained. The LSTM network model is constructed and trained to obtain the target LSTM network model. The specific training steps will be described later.

[0038] In this embodiment, the historical phase jitter data is used as test data and input into the target LSTM network model obtained above. According to the prediction result output by the target LSTM network model, the predicted value of the phase jitter of the next transmission delay is determined.

[0039] Step S303: Compensate for the next transmission delay according to the predicted value.

[0040] In this embodiment, Figure 2 As shown, the predicted value of phase jitter is obtained Then, the predicted value The conjugate amount is determined as the pre-compensation signal That is, let And use the pre-compensation signal The actual phase jitter within the next transmission delay To offset.

[0041] According to an embodiment of the present application, the method 400 for training a target LSTM network model can be as follows: Figure 4 The method 400 may include the following steps.

[0042] Step S401: Divide the historical phase jitter data into a training set and a test set according to different component proportions.

[0043] In this embodiment, the above-mentioned historical phase jitter data is divided into a training set for training the constructed LSTM network model and determining the model parameters according to different component proportions, and a test set for testing the trained model and further adjusting the model parameters, and the data distribution in the two parts of the data set is consistent to avoid the impact on the final result caused by the introduction of additional deviations in the division process. For example, the historical phase jitter data is divided into a training set and a test set at a ratio of 8:2 (or 7:3, ...). Assuming a division ratio of 8:2, 400,000 copies of historical phase jitter data can be divided into a training set including 320,000 copies of data and a test set including 80,000 copies of data, so that the model with the best effect is finally selected by training the model. In addition, the above-mentioned 400,000 copies of historical phase jitter data can also be randomly divided into training sets and test sets multiple times, and then the results of the multiple divisions are averaged to ensure randomness.

[0044] Step S402: Build an LSTM network model.

[0045] Figure 5 The schematic diagram of the structure of the LSTM network model constructed in the embodiment of the present application is shown. Figure 5 As shown, the LSTM network model includes: input layer, hidden layer and output layer, wherein the hidden layer includes the hidden layer sequence h t , and the cell state sequence C t , to retain past memory information.

[0046] Specifically, the LSTM network model consists of multiple LSTM neurons. Figure 6 , is a schematic diagram of the structure of a single LSTM neuron in the embodiment of the present application. Figure 6 As shown in the figure, a single LSTM neuron consists of a cell state and three gate structures to protect and control the cell state. The three gates are the forget gate, input gate, and output gate.

[0047] At each time step, the input data x at time t can be calculated based on the forget gate, input gate and output gate. t For ease of explanation, the output data of the forget gate, input gate, and output gate as well as the state data of the hidden layer can be represented by f, i, o, and C respectively. For the input data x at time t t , based on the output data h of the hidden layer at time t-1 t-1 and status data C t-1 , through the forget gate, input gate and output gate to x t Processing is performed to obtain the state data C of the hidden layer at time tt and output data h t .

[0048] Specifically, the forget gate is mainly used to decide which information of the previous cell state to retain and forget through the sigmoid function (non-linear activation function, a commonly used activation function in neurons), f t The output data of the forget gate at time t; the input gate consists of two parts. The first part is used to determine how much information in the input data at time t will be added to the new memory information, thereby generating the output data i of the input gate at time t. t The second part is used to combine the previous memory information with the current input data through the tan h function to generate the candidate state data of the current hidden layer The output gate is used to decide which information to propagate backward. t is the output data of the output gate at time t. Based on the forget gate and input gate, the data of the previous cell state can be combined with the forget gate to discard unnecessary information, and the input data of the current cell state can be combined with the input gate to add new input data information. That is, the memory state of the hidden layer can be updated through the forget gate and the input gate to obtain the state data C of the hidden layer. t Then, according to the state data C of the hidden layer t and input data x t The output data h of the hidden layer can be obtained t , that is, h t is the final output value.

[0049] Step S403: input the training set into the LSTM network model for training, then input the test set into the LSTM network model for testing, and adjust the parameters of the LSTM network model until a preset termination condition is met to obtain the target LSTM network model.

[0050] In this embodiment, a period of data is selected from the historical phase jitter data of the training set obtained by the above division, and the selected data is used to form a time series sequence in chronological order. Input into the LSTM network model constructed above to predict the phase jitter of the next transmission delay For example, the phase jitter within the next transmission delay is predicted based on the phase jitter data within the first four transmission delays.

[0051] In this embodiment, a training loss value is calculated based on the obtained predicted value and the actual value of the corresponding phase jitter in the training set, and the parameters of the LSTM network model are adjusted based on minimizing the training loss. Specifically, the training loss value is calculated based on a loss function, which is a mean square error (MSE) function. The specific form of the MSE function is:

[0052]

[0053] Where n is the number of historical phase jitter data input, is the actual value of the i-th phase jitter, is the predicted value of the i-th phase jitter.

[0054] In some embodiments, in order to prevent the model from overfitting, the performance of the temporary model obtained by the above training can be tested in real time using a test set. Specifically, the historical phase jitter data in the test set obtained by the above division is input into the LSTM network model, and the test loss value is calculated based on the predicted value of the phase jitter of the next transmission delay output by the model and the actual value of the corresponding phase jitter in the test set; the parameters of the LSTM network model are further adjusted based on the minimization of the test loss, and the model with the lowest test loss value is saved in real time. It can be understood that the test loss value is calculated based on the loss function, which is the mean square error MSE function. The specific form of the MSE function is:

[0055]

[0056] Among them, n is the number of test data, is the actual value of the i-th phase jitter, is the predicted value of the i-th phase jitter.

[0057] In practice, the initial batch size can be set to 48. The specific batch size is determined by the loss curve. If the loss curve fluctuates significantly, the batch size is increased; if a single iteration takes too long, the batch size is decreased.

[0058] In this embodiment, the termination condition includes at least one of the following: the number of iterative training reaches a first preset threshold (e.g., 200 times), the prediction accuracy reaches a preset value, and the number of times the test loss value remains unchanged reaches a second preset threshold (e.g., 5 times). It will be understood that the prediction accuracy is obtained by testing the LSTM network model on the test set; the test loss value is obtained based on the test set and the loss function.

[0059] In specific implementation, the generalization capability of the LSTM network model is tested using a test set. Based on the test results, the model parameters are fine-tuned to ultimately determine the optimal model, which is then designated as the target LSTM network model. Specifically, the historical phase jitter data from the test set is input into the model, and the model's prediction accuracy is calculated. This prediction accuracy is then used to assess the model's generalization capability.

[0060] Furthermore, the prediction accuracy evaluation indicators include root mean square error RMSE, mean absolute error MAE and determination coefficient R 2 , the calculation formula of the evaluation index is as follows:

[0061]

[0062]

[0063]

[0064] Among them, n is the number of test data, is the actual value of the i-th phase jitter, is the predicted value of the i-th phase jitter.

[0065] It should be understood that the closer the RMSE value and MAE value obtained in response to the above calculation are to 0, the higher the prediction accuracy of the model; 2 The closer the value is to 1, the higher the model's prediction accuracy. The more accurate the model's prediction, the better the model's generalization ability.

[0066] It should be noted that the above description is limited to some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in an order different from that described in the above embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0067] Based on the same technical concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides a compensation device 700 for optical fiber frequency transmission.

[0068] refer to Figure 7 The optical fiber frequency transmission compensation device 700 comprises:

[0069] An acquisition module 701 is configured to acquire historical phase jitter data of a frequency signal transmitted back and forth in an optical fiber link;

[0070] The prediction module 702 is configured to input the historical phase jitter data into a pre-trained target long short-term memory (LSTM) network model to obtain a predicted value of the phase jitter of the next transmission delay;

[0071] The compensation module 703 is configured to compensate for the next transmission delay according to the predicted value.

[0072] The compensation device, consisting of an acquisition module 701, a prediction module 702, and a compensation module 703, uses the prediction module 702 to obtain a predicted value of the phase jitter of the next transmission delay based on historical phase jitter, and uses the compensation module 703 to compensate for the actual phase jitter within the next transmission delay based on the predicted value. This takes into account the difference in phase jitter between two adjacent transmission delays and realizes phase-stable transmission of frequency signals based on optical fiber.

[0073] For the convenience of description, the above devices are described as being divided into various modules according to their functions. Of course, when implementing this application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0074] The device of the above embodiment is used to implement the corresponding optical fiber frequency transmission compensation method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0075] Based on the same technical concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable by the processor. When the processor executes the computer program, it implements the compensation method for optical fiber frequency transmission as described in any of the above embodiments.

[0076] Figure 8 10 is a schematic diagram showing a more specific hardware structure of an electronic device provided in this embodiment. The device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are communicatively connected to each other within the device via the bus 1050.

[0077] The processor 1010 can be implemented using a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0078] The memory 1020 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage devices, dynamic storage devices, etc. The memory 1020 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1020 and is called and executed by the processor 1010.

[0079] The input / output interface 1030 is used to connect input / output modules to implement information input and output. The input / output modules can be configured as components within the device (not shown in the figure) or can be externally connected to the device to provide corresponding functions. Input devices may include a keyboard, mouse, touch screen, microphone, various sensors, etc., and output devices may include a display, speaker, vibrator, indicator light, etc.

[0080] The communication interface 1040 is used to connect to a communication module (not shown) to enable communication between the device and other devices. The communication module can communicate via a wired method (such as USB, network cable, etc.) or a wireless method (such as mobile network, WiFi, Bluetooth, etc.).

[0081] The bus 1050 comprises a path for transmitting information between the various components of the device (eg, the processor 1010 , the memory 1020 , the input / output interface 1030 , and the communication interface 1040 ).

[0082] It should be noted that although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040, and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. In addition, it will be understood by those skilled in the art that the above device may only include the components necessary to implement the embodiments of this specification, and does not necessarily include all the components shown in the figure.

[0083] The electronic device of the above embodiment is used to implement the corresponding optical fiber frequency transmission compensation method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be described in detail here.

[0084] Based on the same technical concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the compensation method for optical fiber frequency transmission as described in any of the above embodiments.

[0085] The computer-readable media of this embodiment include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0086] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the optical fiber frequency transmission compensation method as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0087] Those skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application (including the claims) is limited to these examples. Within the scope of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0088] In addition, for simplicity of description and discussion, and in order not to make the embodiment of the application difficult to understand, the known power supply / ground connection with integrated circuit (IC) chip and other components may or may not be shown in the accompanying drawings provided. In addition, the device can be shown in the form of a block diagram to avoid making the embodiment of the application difficult to understand, and this also takes into account the following fact, that is, the details of the embodiment of these block diagram devices are highly dependent on the platform to be implemented in the embodiment of the application (that is, these details should be fully within the scope of understanding of those skilled in the art). When specific details (for example, circuit) are set forth to describe exemplary embodiments of the application, it will be apparent to those skilled in the art that the embodiment of the application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0089] Although the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art based on the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may utilize the embodiments discussed.

[0090] The embodiments of the present application are intended to cover all such substitutions, modifications, and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the scope of protection of this application.

Claims

1. A method for compensating optical fiber frequency transmission, characterized in that: include: Obtain historical phase jitter data of frequency signals transmitted back and forth in optical fiber links; Inputting the historical phase jitter data into a pre-trained target long short-term memory (LSTM) network model to obtain a predicted value of the phase jitter of the next transmission delay; Compensating for the next transmission delay according to the predicted value; The obtaining of historical phase jitter data of a frequency signal transmitted back and forth in the optical fiber link includes: Compare the local reference signal with the round-trip signal that arrives at the receiving end after being transmitted through the optical fiber and then returns to the transmitting end through the receiving end, and obtain the phase jitter data of the optical fiber link in real time; All the phase jitter data acquired in real time are used as the historical phase jitter data.

2. The method according to claim 1, characterized in that The acquisition interval of the historical phase jitter data is the length of the optical fiber link in m / the propagation speed of light in the optical fiber 2×10 8 m / s.

3. The method according to claim 1, characterized in that The compensating for the next transmission delay according to the predicted value includes: compensating for the next transmission delay using the conjugate of the predicted value.

4. The method according to claim 1, wherein The target LSTM network model is pre-trained by the following operations: Dividing the historical phase jitter data into a training set and a test set according to different component proportions; Build an LSTM network model; The training set is input into the LSTM network model for training, and then the test set is input into the LSTM network model for testing, and the parameters of the LSTM network model are adjusted until a preset termination condition is met to obtain the target LSTM network model.

5. The method according to claim 4, characterized in that The termination condition includes at least one of the following: the number of iterative training reaches a first preset number threshold, the prediction accuracy reaches a preset value, and the number of times the test loss value remains continuously unchanged reaches a second preset number threshold; The prediction accuracy is obtained by testing the LSTM network model using the test set; and the test loss value is obtained based on the test set and the loss function.

6. The method according to claim 5, characterized in that The loss function is the mean square error MSE function; The specific form of the MSE function is: Among them, n is the number of test data, is the actual value of the i-th phase jitter, is the predicted value of the i-th phase jitter.

7. The method according to claim 5, characterized in that The evaluation indicators of the prediction accuracy include root mean square error RMSE, mean absolute error MAE and determination coefficient R 2 , the calculation formula of the evaluation index is as follows: Among them, n is the number of test data, is the actual value of the i-th phase jitter, is the predicted value of the i-th phase jitter.

8. A compensation device for optical fiber frequency transmission, characterized in that: include: An acquisition module is configured to acquire historical phase jitter data of a frequency signal transmitted back and forth in an optical fiber link; A prediction module is configured to input the historical phase jitter data into a pre-trained target long short-term memory (LSTM) network model to obtain a predicted value of the phase jitter of the next transmission delay; a compensation module, configured to compensate for the next transmission delay according to the predicted value; The acquisition module is specifically configured to: Compare the local reference signal with the round-trip signal that arrives at the receiving end after being transmitted through the optical fiber and then returns to the transmitting end through the receiving end, and obtain the phase jitter data of the optical fiber link in real time; All the phase jitter data acquired in real time are used as the historical phase jitter data.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

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