C+L400G system zero insertion loss optical line protection device and method

Abstract

The present invention provides a zero-insertion-loss optical line protection device and method for a C+L400G system, which relates to the field of optical fiber transmission. The method includes: monitoring and obtaining the real-time optical power and real-time OSNR signal of the main line; determining whether the line switching threshold is met, and if so, switching to the backup line; if not, determining a reference gain curve based on the real-time optical power and real-time OSNR signal analysis, and optimizing the adjustment parameters of the RFA amplification unit with approximation to the reference gain curve as the optimization goal, outputting the optimal adjustment parameters for adaptive control. The invention aims to solve the technical problem that most traditional zero-insertion-loss optical line protection devices rely on manually set fixed gain, lack dynamic control capabilities, and cannot ensure continuous and stable transmission of the link; the invention can dynamically adjust the gain parameters of the RFA amplification unit without interrupting the service, thereby achieving zero-insertion-loss switching and stable transmission of the service optical signal between the main and backup lines.

Description

Technical Field

[0001] The present invention relates to the field of optical fiber transmission, and in particular to a zero-insertion-loss optical line protection device and method for a C+L400G system. Background Art

[0002] With the continuous development of fiber-optic communication technology, optical transmission systems with C+L band speeds of 400G and above have gradually become the mainstream direction of trunk backbone network construction. In practical applications, to ensure the reliability of transmission links and business continuity, optical line protection devices are usually used to achieve rapid switching between primary and backup lines. When a fault such as a fiber break or severe attenuation occurs on the main line, the system can quickly switch the service to the backup line, thus avoiding service interruption. To further reduce signal power disturbances during optical line switching and improve switching smoothness, the industry has proposed "zero insertion loss" optical line protection technology. The core idea is to introduce an adjustable gain amplification module (such as an adjustable optical amplifier RFA) in the primary or backup route. Through gain compensation, the service optical power before and after switching remains consistent.

[0003] However, most existing zero-insertion-loss optical line protection solutions typically configure the RFA by manually setting a fixed gain. This lacks real-time perception and adaptive adjustment capabilities for line status changes. When the primary line fluctuates without reaching the switching threshold (such as optical power drop or OSNR degradation within the limit), the RFA gain cannot be dynamically adjusted accordingly, which may lead to a decrease in service signal quality, an increase in bit error rate, and even the risk of unavailability. At the same time, after switching to the backup line, if the RFA fails to quickly match the appropriate amplification gain, it may also cause power mutations and a decrease in signal-to-noise ratio, affecting the stable transmission of services. Summary of the Invention

[0004] The present invention aims to provide a zero-insertion-loss optical line protection device and method for a C+L400G system. This device addresses the technical issues that most conventional zero-insertion-loss optical line protection devices rely on manually set fixed gains, lack dynamic control capabilities, and are prone to degrading or even interrupting service signal quality, thus failing to ensure continuous and stable link transmission. The device and method include:

[0005] In a first aspect, the present invention provides a C+L400G system zero-insertion-loss optical line protection device, which includes a routing switching unit, an RFA amplification unit, and a power feedback control unit. The power feedback control unit includes an FPGA unit and an MCU unit, and further includes: a data monitoring module, which is used to obtain the real-time optical power and real-time OSNR signal of the main line through fixed-point monitoring of the FPGA unit during optical fiber communication; a data judgment module, which is used to judge whether the real-time optical power and real-time OSNR signal meet the line switching threshold, and if so, switch to the backup line through the routing switching unit; an adjustment parameter optimization module, which is used to determine a reference gain curve based on the real-time optical power and real-time OSNR signal analysis in the MCU unit if not satisfied, and optimize the adjustment parameters of the RFA amplification unit with approximation to the reference gain curve as the optimization goal, and output the optimal adjustment parameters; an adaptive control module, which is used to control the RFA amplification unit according to the optimal adjustment parameters, and perform adaptive iterative control according to real-time monitoring data.

[0006] Preferably, the C+L400G system zero-insertion-loss optical line protection device further includes: obtaining a line switching threshold, wherein the line switching threshold includes an optical power threshold and an OSNR threshold; if the real-time optical power is less than the optical power threshold and / or the real-time OSNR signal is less than the OSNR threshold, then determining that the main line is abnormal, and switching to the backup line through the routing switching unit within a preset switching time, wherein the preset switching time is less than 50 milliseconds.

[0007] Preferably, the C+L400G system zero-insertion-loss optical line protection device further includes: collecting real-time environmental parameters of the optical fiber location through an environmental monitoring unit, wherein the environmental parameters include at least ambient temperature, ambient humidity and vibration parameters; a pre-trained gain curve analyzer; inputting the real-time environmental parameters, real-time optical power and real-time OSNR signals into the gain curve analyzer, and outputting a reference gain curve.

[0008] Preferably, the C+L400G system zero-insertion-loss optical line protection device further includes: collecting a sample environmental parameter set, a sample optical power set, and a sample OSNR signal set based on the historical operation and maintenance records of the optical fiber, and obtaining the corresponding standard gain curves under different sample environmental parameters, sample optical powers, and sample OSNR signals as sample gain curves to obtain a sample gain curve set; using the sample environmental parameter set, sample optical power set, and sample OSNR signal set as input, and using the sample gain curve set as supervision, training the BP neural network until convergence to obtain a gain curve analyzer.

[0009] Preferably, the C+L400G system zero-insertion-loss optical line protection device further includes: obtaining an adjustment parameter threshold of the RFA amplification unit, wherein the adjustment parameters include gain dynamic range, gain adjustment accuracy, and gain response time; pre-training a gain curve predictor; using the adjustment parameter threshold as the optimization space and approximating the reference gain curve as the optimization target, optimizing the adjustment parameter using the gain curve predictor, and outputting the optimal adjustment parameter.

[0010] Preferably, the C+L400G system zero-insertion-loss optical line protection device further includes: collecting a sample environmental parameter set, a sample optical power set, a sample OSNR signal set, and a sample adjustment parameter set based on the historical operation and maintenance records of the optical fiber, and obtaining a historical gain curve adjusted by the sample adjustment parameters as a sample predicted gain curve to obtain a sample predicted gain curve set; using the sample environmental parameter set, sample optical power set, sample OSNR signal set, and sample adjustment parameter set as input, and using the sample predicted gain curve set as supervision, training the BP neural network until convergence to obtain a gain curve predictor.

[0011] Preferably, the C+L400G system zero-insertion-loss optical line protection device further includes: randomly generating a first adjustment parameter within the adjustment parameter threshold, inputting the gain curve predictor, and outputting a first predicted gain curve; performing similarity calculation on the reference gain curve and the first predicted gain curve, and outputting a first similarity; continuing to use the adjustment parameter threshold as the optimization space, iteratively performing parameter random selection, gain curve prediction, and similarity calculation until a preset number of iterations is reached, and outputting the adjustment parameter corresponding to the predicted gain curve with the largest similarity as the optimal adjustment parameter.

[0012] Preferably, the C+L400G system zero-insertion-loss optical line protection device further includes: the backup line also includes a backup power feedback control unit and an RFA amplification unit, wherein the backup power feedback control unit includes a backup FPGA unit and a backup MCU unit, and the backup MCU unit is communicatively connected to the MCU unit; when not switching to the backup line, the optimal adjustment parameters are synchronously transmitted to the backup MCU unit through the MCU unit, and the RFA amplification unit of the backup line is adaptively iteratively controlled; after switching to the backup line, the RFA amplification unit of the backup line is adaptively iteratively controlled through the backup FPGA unit and the backup MCU unit.

[0013] In the second aspect, the present invention also provides a zero-insertion-loss optical line protection method for a C+L400G system, comprising: during optical fiber communication, obtaining the real-time optical power and real-time OSNR signal of the main line through fixed-point monitoring by an FPGA unit; judging whether the real-time optical power and real-time OSNR signal meet the line switching threshold, and if so, switching to the backup line through a routing switching unit; if not, in an MCU unit, determining a reference gain curve based on the real-time optical power and real-time OSNR signal analysis, and optimizing the adjustment parameters of the RFA amplification unit with the approach to the reference gain curve as the optimization goal, and outputting the optimal adjustment parameters; controlling the RFA amplification unit according to the optimal adjustment parameters, and performing adaptive iterative control according to real-time monitoring data.

[0014] The embodiments of the present invention include the following advantages:

[0015] During the optical fiber communication process, the real-time optical power and real-time OSNR signal of the main line are obtained through fixed-point monitoring by the FPGA unit; then, it is determined whether the real-time optical power and real-time OSNR signal meet the line switching threshold. If so, the routing switching unit switches to the backup line; if not, the MCU unit determines the reference gain curve based on the real-time optical power and real-time OSNR signal analysis, and optimizes the adjustment parameters of the RFA amplification unit with the approach to the reference gain curve as the optimization goal, and outputs the optimal adjustment parameters; finally, the RFA amplification unit is controlled according to the optimal adjustment parameters, and adaptive iterative control is performed according to the real-time monitoring data. In other words, by introducing a power feedback control mechanism composed of FPGA and MCU, combined with real-time monitoring, adaptive adjustment and gain optimization algorithms, the gain parameters of the RFA amplification unit can be dynamically adjusted without interrupting the service, thereby achieving zero-insertion-loss switching and stable transmission of the service optical signal between the main and backup lines, which is particularly suitable for protection scenarios of high-speed optical communication networks above 400G in the C+L band. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a schematic structural diagram of a zero-insertion-loss optical line protection device for a C+L400G system according to the present invention;

[0017] Figure 2 The present invention is a flowchart of the steps of a C+L400G system zero-insertion-loss optical line protection method.

[0018] Description of reference numerals:

[0019] Data monitoring module 11, data judgment module 12, adjustment parameter optimization module 13, adaptive control module 14. DETAILED DESCRIPTION

[0020] The present invention provides a zero-insertion-loss optical line protection device and method for a C+L 400G system, addressing the technical issues that most traditional zero-insertion-loss optical line protection devices rely on manually set fixed gain, lack dynamic control capabilities, and easily lead to degradation or even interruption of service signal quality, thus failing to ensure continuous and stable transmission of the link. By introducing a power feedback control mechanism composed of an FPGA and an MCU, combined with real-time monitoring, adaptive adjustment, and a gain optimization algorithm, the gain parameters of the RFA amplification unit can be dynamically adjusted without interrupting services, thereby achieving zero-insertion-loss switching and stable transmission of service optical signals between the primary and backup lines. This device is particularly suitable for protecting high-speed optical communication networks above 400G in the C+L band.

[0021] Below, the technical solutions of the present invention will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention. It should be understood that the present invention is not limited to the example embodiments described herein. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should also be noted that, for the convenience of description, only the parts related to the present invention, rather than all, are shown in the accompanying drawings.

[0022] For example 1, please refer to the attached Figure 1 The present invention provides a C+L400G system zero-insertion-loss optical line protection device, the C+L400G system zero-insertion-loss optical line protection device comprising a routing switching unit, an RFA amplification unit, and a power feedback control unit, the power feedback control unit comprising an FPGA unit and an MCU unit, and further comprising:

[0023] The data monitoring module 11 is used to obtain the real-time optical power and real-time OSNR signal of the main line through fixed-point monitoring of the FPGA unit during the optical fiber communication process.

[0024] Specifically, the present invention provides a C+L400G system zero-insertion-loss optical line protection device, wherein the C+L400G system zero-insertion-loss optical line protection device includes a routing switching unit, an RFA amplification unit, and a power feedback control unit. The routing switching unit is used to automatically switch the service optical signal from the main line to the backup line when detecting a fiber break in the main line or the optical power / OSNR attenuation exceeds a preset switching threshold to ensure that the link is not interrupted; the RFA amplification unit is used to perform gain compensation on the optical signal in the main or backup line to ensure that the optical power and signal-to-noise ratio of the link before and after switching are consistent, thereby achieving zero-insertion-loss switching; the power feedback control unit includes an FPGA unit and an MCU unit, which are used to construct a closed-loop feedback system based on real-time monitoring and adaptive control; the FPGA unit is used to sample the real-time optical power and OSNR signals of the main or backup line at high speed and transmit the data to the MCU unit; the MCU unit calculates and outputs the optimal gain adjustment parameter in real time based on the received real-time data, combined with the built-in adaptive control algorithm and reference gain model, for dynamically controlling the gain value of the RFA amplification unit to ensure stable optical signal quality.

[0025] First, during the fiber-optic communication process, the real-time optical power and real-time OSNR signals of the main line are obtained through fixed-point monitoring by the FPGA unit. The FPGA is connected to a photoelectric detection module (such as a PIN photodetector) or an OSNR monitoring module to regularly sample the optical signal on the main line at fixed time intervals to obtain real-time optical power and real-time OSNR signals, package them into structured data, and send them to the MCU unit through the internal bus. Among them, optical power and OSNR signals are two core parameters for measuring communication quality.

[0026] The data judgment module 12 is used to judge whether the real-time optical power and the real-time OSNR signal meet the line switching threshold. If so, the route switching unit switches to the backup line.

[0027] Furthermore, the data judgment module 12 is further configured to:

[0028] Obtain a line switching threshold, wherein the line switching threshold includes an optical power threshold and an OSNR threshold; if the real-time optical power is less than the optical power threshold and / or the real-time OSNR signal is less than the OSNR threshold, determine that the primary line is abnormal, and switch to the backup line through the routing switching unit within a preset switching time, wherein the preset switching time is less than 50 milliseconds.

[0029] Specifically, first, obtain the line switching threshold, which includes the optical power threshold and the OSNR threshold. The optical power threshold indicates the minimum received optical power allowed on the primary optical fiber line, generally expressed in dBm, such as –10 dBm. When the actual optical power is lower than this value, it means that there is an abnormality in the line (such as a fiber break or sudden insertion loss). The OSNR threshold (optical signal-to-noise ratio threshold) indicates the minimum allowable OSNR value (in dB) while ensuring communication quality. Generally, the C+L band 400G system has higher OSNR requirements (such as >18-20 dB). If the OSNR decreases, it means that the signal is overwhelmed by noise, which may also be a sign of link damage.

[0030] Next, the real-time optical power and real-time OSNR signal are judged based on the optical power threshold and the OSNR threshold, respectively. If the real-time optical power is less than the optical power threshold and / or the real-time OSNR signal is less than the OSNR threshold, it is determined that the primary line is abnormal or unavailable. In this case, the routing switching unit is immediately started to perform a switching operation, quickly switching the service optical signal from the primary line to the backup line (the backup line is usually in a standby state). The switching process is completed by a dedicated optical switch, an electronic control module, or an optical path control circuit. Among them, the switching time is a key indicator of the system's tolerance for service interruption. In this solution, the line switching must be completed within 50 milliseconds (ms) to ensure uninterrupted service or extremely low bit errors.

[0031] Furthermore, the data judgment module 12 is further configured to:

[0032] The backup line also includes a backup power feedback control unit and an RFA amplification unit, wherein the backup power feedback control unit includes a backup FPGA unit and a backup MCU unit, and the backup MCU unit is communicatively connected to the MCU unit; when not switching to the backup line, the optimal adjustment parameters are synchronously transmitted to the backup MCU unit through the MCU unit, and the RFA amplification unit of the backup line is adaptively iteratively controlled; after switching to the backup line, the RFA amplification unit of the backup line is adaptively iteratively controlled through the backup FPGA unit and the backup MCU unit.

[0033] Specifically, the backup line also includes a backup power feedback control unit and an RFA amplification unit. That is, this protection device not only configures a complete detection and gain control mechanism for the main line, but also configures an equivalent system structure for the backup line. The backup RFA amplification unit is used to perform gain compensation on the optical signal of the backup line; the backup power feedback control unit includes a backup FPGA and a backup MCU, which are responsible for monitoring and adjusting the optical power and OSNR of the backup line. This enables the backup line to have complete independent control capabilities, rather than being passively activated after the main line fails.

[0034] Before switching to the backup line, that is, when the system is running, the MCU unit of the main line will perform gain adjustment optimization based on real-time detection results. At the same time, it will synchronously transmit the optimal adjustment parameters obtained from the current optimization to the backup MCU unit. In other words, when the backup line is not enabled, it has already obtained parameter adjustment information that matches the current status of the main line in advance, so as to pre-adjust the backup RFA unit. This ensures that if a main line failure occurs, the switched backup line is already in the optimal access state, without waiting for adjustment.

[0035] After switching to the backup line, the original backup FPGA and backup MCU immediately take over the control logic and continue to adaptively control the RFA based on the actual optical power / OSNR conditions. This ensures that during the transmission process after the switch, it can adjust in real time to adapt to field changes and maintain service signal quality. Compared with existing technologies, this invention can actively adjust the RFA amplification unit in real time, ensuring that the backup line is always available in the absence of alarms. This effectively avoids the situation where performance degradation or unavailability is discovered after the service light is switched to the backup line, resulting in protection failure.

[0036] The adjustment parameter optimization module 13 is used to determine the reference gain curve in the MCU unit based on the real-time optical power and real-time OSNR signal analysis if it is not satisfied, and optimize the adjustment parameters of the RFA amplification unit with the approach to the reference gain curve as the optimization goal, and output the optimal adjustment parameters.

[0037] Furthermore, the adjustment parameter optimization module 13 is further configured to:

[0038] The real-time environmental parameters of the location of the optical fiber are collected by the environmental monitoring unit, wherein the environmental parameters at least include environmental temperature, environmental humidity and vibration parameters.

[0039] Specifically, environmental monitoring equipment is deployed in the optical fiber laying path (such as data centers, base stations, underground pipelines, field environments, etc.) to perceive the status of the physical environment in which the optical fiber is currently located in real time. This type of monitoring can be completed through a sensor integrated module. The module can obtain data through online coupling of optical cables, distributed sensing or centralized acquisition terminals, and obtain real-time environmental parameters of the optical fiber location. The environmental parameters include at least ambient temperature, ambient humidity and vibration parameters. Temperature fluctuations may cause optical power attenuation, dispersion changes, and even device failure; high humidity may cause optical cables to become damp, connectors to rust, and reflection losses to increase; external mechanical vibrations may affect the stability of optical cables, causing micro-bend losses and loose connections. For example, the passing of trains and construction vibrations may cause link fluctuations or failures.

[0040] Pre-training gain curve analyzer.

[0041] Furthermore, the present invention further comprises the steps of:

[0042] According to the historical operation and maintenance records of optical fibers, a sample environmental parameter set, a sample optical power set, and a sample OSNR signal set are collected, and the standard gain curves corresponding to different sample environmental parameters, sample optical powers, and sample OSNR signals are obtained as sample gain curves to obtain a sample gain curve set; the sample environmental parameter set, sample optical power set, and sample OSNR signal set are used as inputs, and the sample gain curve set is used as supervision to train a BP neural network until convergence to obtain a gain curve analyzer.

[0043] Specifically, first, based on the historical operation and maintenance records of the optical fiber, a sample environmental parameter set, a sample optical power set, and a sample OSNR signal set are collected, and the standard gain curve corresponding to different sample environmental parameters, sample optical powers, and sample OSNR signals is obtained and set as a sample gain curve. That is, under each set of input conditions, there is an ideal optimal gain adjustment curve, which can be obtained through experimental testing, simulation, expert experience, or existing network configuration records, and is set as the sample gain curve to obtain a sample gain curve set.

[0044] Next, a gain curve analyzer is constructed based on a BP neural network, wherein the BP neural network includes an input layer, a hidden layer and an output layer, the input data of the input layer are environmental parameters, optical power and OSNR signals, and the output data of the output layer is the optimal gain curve; then, the sample environmental parameter set, the sample optical power set and the sample OSNR signal set are used as input, and the sample gain curve set is used as supervision to perform supervised training on the gain curve analyzer. During the training process, first, the input data (environmental parameters, optical power, OSNR) is input into the network, and after nonlinear mapping of the hidden layer, the predicted gain curve is output; then, the mean square error (MSE) is used as the loss function to calculate the error between the predicted curve and the true sample curve; further, the gradient descent method (such as SGD, Adam) is used to update the weights and biases; iterative training is repeated to make the loss function gradually converge, and the training is terminated when the loss function converges below the set threshold or the number of training rounds reaches the maximum value, thereby obtaining a trained gain curve analyzer. In actual applications, the trained BP neural network model can receive the environmental parameters, optical power, and OSNR signals of the primary or backup optical line in real time, and predict the optimal gain curve in the current scenario, providing a high-precision adjustment basis for the RFA amplification unit, thereby achieving zero-insertion-loss dynamic protection for the system.

[0045] The real-time environmental parameters, real-time optical power and real-time OSNR signals are input into the gain curve analyzer, and a reference gain curve is output.

[0046] Specifically, the real-time environmental parameters, real-time optical power and real-time OSNR signals are finally input into the gain curve analyzer, the current optical line status is comprehensively judged based on the input characteristics, and a reference gain curve that best matches the current working conditions is output. The reference gain curve is used to guide the gain adjustment target of the RFA amplification unit, and can provide a curve basis for subsequent gain parameter optimization and adaptive control, ensuring that the power stability and OSNR of the service optical signal are maintained under different transmission environments, thereby achieving zero insertion loss transmission effect.

[0047] Furthermore, the adjustment parameter optimization module 13 is further configured to:

[0048] The adjustment parameter thresholds of the RFA amplification unit are obtained, where the adjustment parameters include gain dynamic range, gain adjustment accuracy, and gain response time.

[0049] Specifically, the adjustment parameter thresholds of the RFA amplification unit are obtained. The adjustment parameter thresholds are used to define the acceptable adjustment range and performance indicators of the amplification unit during actual operation. The adjustment parameters include gain dynamic range, gain adjustment accuracy, and gain response time. The gain dynamic range refers to the range between the minimum and maximum gain achievable by the RFA amplification unit, typically measured in decibels (dB). For example, within a dynamic adjustment range of 3dB to 7dB, the RFA can flexibly adjust the output power based on the feedback control signal to compensate for line loss or address changes in signal loss under different operating conditions. Gain adjustment accuracy refers to the minimum controllable step value during gain adjustment of the RFA amplification unit, reflecting the precision of the gain adjustment. For example, an adjustment accuracy of 0.1dB indicates that the control unit can fine-tune the gain in steps of 0.1dB, ensuring a smooth and accurate adjustment process. The gain response time refers to the time required for the RFA amplification unit to complete the set adjustment action after receiving the gain adjustment control signal. The response time is usually required to be within 1 millisecond (ms) to meet the stringent requirements of high-speed optical communication systems for adjustment timeliness and ensure that signal quality can be maintained stably when the link status fluctuates rapidly.

[0050] Pre-trained gain curve predictor.

[0051] Furthermore, the present invention further comprises the steps of:

[0052] According to the historical operation and maintenance records of the optical fiber, a sample environmental parameter set, a sample optical power set, a sample OSNR signal set and a sample adjustment parameter set are collected, and the historical gain curve adjusted by the sample adjustment parameters is obtained as a sample predicted gain curve to obtain a sample predicted gain curve set; the sample environmental parameter set, the sample optical power set, the sample OSNR signal set and the sample adjustment parameter set are used as input, and the sample predicted gain curve set is used as supervision to train the BP neural network until convergence to obtain a gain curve predictor.

[0053] Specifically, first, based on the historical operation and maintenance records of the optical fiber, sample environmental parameter sets, sample optical power sets, sample OSNR signal sets and sample adjustment parameter sets are collected. Under each set of sample environmental parameters, optical power and OSNR conditions, according to the adjustment parameter set used at the time, the actual response curve of the RFA gain changing with time or input state is recorded as the sample predicted gain curve. These curves reflect the adjustment behavior of the system under specific conditions, and a sample predicted gain curve set is obtained. Next, the sample environmental parameter set, sample optical power set, sample OSNR signal set, and sample adjustment parameter set are used as inputs, and the sample predicted gain curve set is used as supervision. Specifically, the environmental parameters (such as temperature, humidity, and vibration), optical power values, OSNR values, and adjustment parameters (such as initial gain values, adjustment accuracy, and response time) contained in each group of samples are normalized and preprocessed, and then combined to form an input vector of the training sample. At the same time, the predicted gain curve of the corresponding sample under actual historical conditions is expressed as a time-gain pair or a continuous function curve of several feature points as the supervision output, and the BP neural network is supervised and trained. During the training process, first, the network weights and bias parameters are initialized, and forward propagation is performed using the sample input vector to calculate the predicted gain curve output by the network. Next, the prediction result is compared with the actual sample predicted gain curve for error, and the deviation is calculated using the mean square error (MSE) or a custom loss function. Then, the weights are updated through a back propagation algorithm (BP algorithm) to minimize the output error. The training iteration is repeated until the network loss function converges or a preset training round is reached, at which point the training is stopped to obtain a gain curve predictor that meets the convergence condition.

[0054] The adjustment parameter threshold is used as the optimization space, and approaching the reference gain curve is used as the optimization goal. The adjustment parameter is optimized using the gain curve predictor, and the optimal adjustment parameter is output.

[0055] Furthermore, the present invention further comprises the steps of:

[0056] A first adjustment parameter is randomly generated within the adjustment parameter threshold, input into the gain curve predictor, and a first predicted gain curve is output; a similarity calculation is performed on the reference gain curve and the first predicted gain curve, and a first similarity is output; the adjustment parameter threshold is continued as the optimization space, and parameter random selection, gain curve prediction and similarity calculation are iteratively performed until a preset number of iterations is reached, and the adjustment parameter corresponding to the predicted gain curve with the largest similarity is output as the optimal adjustment parameter.

[0057] Specifically, a random sampling algorithm is first used to generate a set of candidate adjustment parameters within the threshold range of acquired adjustment parameters (such as gain dynamic range, gain adjustment accuracy, and gain response time). These candidate adjustment parameters are then fed into a previously trained gain curve predictor (BP neural network model) along with real-time environmental parameters, optical power, and OSNR signals as inputs. This generates a corresponding first predicted gain curve, which simulates the expected RFA gain response process caused by the adjustment parameters under the current environmental and optical signal conditions. This first predicted gain curve is then compared with a reference gain curve provided by a gain curve analyzer. The fitting error between the two is calculated using a predefined similarity calculation function (such as cosine similarity or Euclidean distance), and a first similarity is output. This first similarity is used to assess the effectiveness of the current adjustment parameters in approximating the reference gain curve and serves as the basis for evaluation in the subsequent parameter optimization process.

[0058] Then, using the adjustment parameter threshold as the optimization space, the method continues to iterate through random parameter selection, gain curve prediction, and similarity calculation. Specifically, a new set of adjustment parameters is randomly selected within the adjustment parameter threshold range as candidate parameters for the current iteration. These candidate adjustment parameters are then input into a gain curve predictor along with the current real-time environmental parameters, real-time optical power, and OSNR signals to generate a corresponding predicted gain curve. A similarity index between the predicted gain curve and the reference gain curve is further calculated. If the current similarity is better than the recorded optimal similarity, the optimal similarity value and the corresponding optimal adjustment parameters are updated. This method continues until a preset number of iterations (e.g., 500) is reached, and the adjustment parameters corresponding to the predicted gain curve with the greatest similarity are output as the optimal adjustment parameters. This method achieves global approximate optimization of the RFA amplification unit adjustment parameters through random sampling and multiple iterations within the parameter space, combined with a prediction model and similarity evaluation mechanism. This ensures the dynamic adaptability and accuracy of gain adjustment, improving the stability of optical signal transmission and the reliability of the protection device.

[0059] The adaptive control module 14 is configured to control the RFA amplification unit according to the optimal adjustment parameters and perform adaptive iterative control according to real-time monitoring data.

[0060] Specifically, the RFA amplification unit is controlled based on the optimal adjustment parameters. Specifically, the optimal adjustment parameters are sent to the RFA amplification unit, adjusting its gain to the predicted optimal state, ensuring that the power and signal-to-noise ratio of the current optical signal transmission meet the expected targets. A power feedback control unit then continuously collects real-time optical power and OSNR signals, monitors line and equipment status, and continuously compares the real-time monitoring data with a reference gain curve. The current state error is calculated and, combined with an adaptive control algorithm (such as an error-based gain adjustment rule or feedback control mechanism), the gain parameters of the RFA amplification unit are dynamically adjusted, correcting deviations in real time and optimizing system performance. This control process forms a closed-loop feedback system, ensuring that the RFA gain can quickly respond to changes in the network environment, enabling stable transmission of service signals and zero-insertion-loss switching. This mechanism not only improves the flexibility and accuracy of gain adjustment but also significantly enhances the optical line protection device's ability to adapt to complex environmental changes, ensuring the highly reliable operation of high-speed optical communication systems.

[0061] In summary, the C+L400G system zero insertion loss optical line protection device provided by the present invention has the following technical effects:

[0062] During the optical fiber communication process, the real-time optical power and real-time OSNR signal of the main line are obtained through fixed-point monitoring by the FPGA unit; then, it is determined whether the real-time optical power and real-time OSNR signal meet the line switching threshold. If so, the routing switching unit switches to the backup line; if not, the MCU unit determines the reference gain curve based on the real-time optical power and real-time OSNR signal analysis, and optimizes the adjustment parameters of the RFA amplification unit with the approach to the reference gain curve as the optimization goal, and outputs the optimal adjustment parameters; finally, the RFA amplification unit is controlled according to the optimal adjustment parameters, and adaptive iterative control is performed according to the real-time monitoring data. In other words, by introducing a power feedback control mechanism composed of FPGA and MCU, combined with real-time monitoring, adaptive adjustment and gain optimization algorithms, the gain parameters of the RFA amplification unit can be dynamically adjusted without interrupting the service, thereby achieving zero-insertion-loss switching and stable transmission of the service optical signal between the main and backup lines, which is particularly suitable for protection scenarios of high-speed optical communication networks above 400G in the C+L band.

[0063] In the second embodiment, based on the same inventive concept as the zero insertion loss optical line protection device of the C+L400G system in the above embodiment, the present invention also provides a zero insertion loss optical line protection method of the C+L400G system, please refer to the attached Figure 2, including: in the process of optical fiber communication, obtaining the real-time optical power and real-time OSNR signals of the main line through fixed-point monitoring of the FPGA unit; judging whether the real-time optical power and real-time OSNR signals meet the line switching threshold, and if so, switching to the backup line through the routing switching unit; if not, in the MCU unit, determining the reference gain curve based on the real-time optical power and real-time OSNR signal analysis, and optimizing the adjustment parameters of the RFA amplification unit with the approach to the reference gain curve as the optimization goal, and outputting the optimal adjustment parameters; controlling the RFA amplification unit according to the optimal adjustment parameters, and performing adaptive iterative control according to the real-time monitoring data.

[0064] Furthermore, the C+L400G system zero-insertion-loss optical line protection method also includes: obtaining a line switching threshold, wherein the line switching threshold includes an optical power threshold and an OSNR threshold; if the real-time optical power is less than the optical power threshold and / or the real-time OSNR signal is less than the OSNR threshold, determining that the main line is abnormal, and switching to the backup line through the routing switching unit within a preset switching time, wherein the preset switching time is less than 50 milliseconds.

[0065] Furthermore, the C+L400G system zero-insertion-loss optical line protection method also includes: collecting real-time environmental parameters of the optical fiber location through an environmental monitoring unit, wherein the environmental parameters include at least ambient temperature, ambient humidity, and vibration parameters; pre-training a gain curve analyzer; inputting the real-time environmental parameters, real-time optical power, and real-time OSNR signals into the gain curve analyzer, and outputting a reference gain curve.

[0066] Furthermore, the C+L400G system zero-insertion-loss optical line protection method also includes: collecting a sample environmental parameter set, a sample optical power set, and a sample OSNR signal set based on the historical operation and maintenance records of the optical fiber, and obtaining the corresponding standard gain curves under different sample environmental parameters, sample optical powers, and sample OSNR signals as sample gain curves to obtain a sample gain curve set; using the sample environmental parameter set, sample optical power set, and sample OSNR signal set as input, and using the sample gain curve set as supervision, training the BP neural network until convergence to obtain a gain curve analyzer.

[0067] Furthermore, the C+L400G system zero-insertion-loss optical line protection method also includes: obtaining an adjustment parameter threshold of the RFA amplification unit, wherein the adjustment parameters include gain dynamic range, gain adjustment accuracy, and gain response time; pre-training a gain curve predictor; using the adjustment parameter threshold as the optimization space and approximating the reference gain curve as the optimization target, optimizing the adjustment parameter using the gain curve predictor, and outputting the optimal adjustment parameter.

[0068] Furthermore, the C+L400G system zero-insertion-loss optical line protection method also includes: collecting a sample environmental parameter set, a sample optical power set, a sample OSNR signal set, and a sample adjustment parameter set based on the historical operation and maintenance records of the optical fiber, and obtaining a historical gain curve adjusted by the sample adjustment parameters as a sample predicted gain curve to obtain a sample predicted gain curve set; using the sample environmental parameter set, sample optical power set, sample OSNR signal set, and sample adjustment parameter set as input, using the sample predicted gain curve set as supervision, training the BP neural network until convergence, and obtaining a gain curve predictor.

[0069] Furthermore, the C+L400G system zero-insertion-loss optical line protection method also includes: randomly generating a first adjustment parameter within the adjustment parameter threshold, inputting the gain curve predictor, and outputting a first predicted gain curve; performing similarity calculation on the reference gain curve and the first predicted gain curve, and outputting a first similarity; continuing to use the adjustment parameter threshold as the optimization space, iteratively performing parameter random selection, gain curve prediction, and similarity calculation until a preset number of iterations is reached, and outputting the adjustment parameter corresponding to the predicted gain curve with the largest similarity as the optimal adjustment parameter.

[0070] Furthermore, the C+L400G system zero-insertion-loss optical line protection method also includes: the backup line also includes a backup power feedback control unit and an RFA amplification unit, wherein the backup power feedback control unit includes a backup FPGA unit and a backup MCU unit, and the backup MCU unit is communicatively connected to the MCU unit; when not switching to the backup line, the optimal adjustment parameters are synchronously transmitted to the backup MCU unit through the MCU unit, and the RFA amplification unit of the backup line is adaptively iteratively controlled; after switching to the backup line, the RFA amplification unit of the backup line is adaptively iteratively controlled through the backup FPGA unit and the backup MCU unit.

[0071] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from the other embodiments. The zero-insertion-loss optical line protection device for a C+L400G system and the specific examples in the aforementioned embodiment 1 are also applicable to the zero-insertion-loss optical line protection method for a C+L400G system in this embodiment. Through the aforementioned detailed description of the zero-insertion-loss optical line protection device for a C+L400G system, those skilled in the art will clearly understand the zero-insertion-loss optical line protection method for a C+L400G system in this embodiment. Therefore, for the sake of brevity, this description will not be repeated here. As for the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant details can be referred to the method description.

[0072] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

[0073] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalents, the present invention is intended to include these modifications and variations.

Claims

1. C+L400G system zero insertion loss optical line protection device, characterized by: The C+L400G system zero-insertion-loss optical line protection device includes a routing switching unit, an RFA amplification unit, and a power feedback control unit. The power feedback control unit includes an FPGA unit and an MCU unit, and further includes: The data monitoring module is used to obtain the real-time optical power and OSNR signals of the main line through fixed-point monitoring of the FPGA unit during the optical fiber communication process; A data judgment module is used to judge whether the real-time optical power and real-time OSNR signal meet the line switching threshold, and if so, switch to the backup line through the routing switching unit; An adjustment parameter optimization module is used to determine a reference gain curve based on the real-time optical power and real-time OSNR signal analysis in the MCU unit if the conditions are not met, and optimize the adjustment parameters of the RFA amplification unit with the goal of approximating the reference gain curve, and output the optimal adjustment parameters; The adaptive control module is used to control the RFA amplification unit according to the optimal adjustment parameters and perform adaptive iterative control according to real-time monitoring data.

2. The C+L400G system zero insertion loss optical line protection device according to claim 1, characterized in that: Determining whether the real-time optical power and the real-time OSNR signal meet a line switching threshold, and if so, switching to a backup line through a routing switching unit, including: Acquire a line switching threshold, wherein the line switching threshold includes an optical power threshold and an OSNR threshold; If the real-time optical power is less than the optical power threshold and / or the real-time OSNR signal is less than the OSNR threshold, it is determined that the main line is abnormal, and the route switching unit switches to the backup line within a preset switching time, wherein the preset switching time is less than 50 milliseconds.

3. The C+L400G system zero insertion loss optical line protection device according to claim 1, characterized in that: Determining a reference gain curve according to the real-time optical power and real-time OSNR signal analysis includes: Collecting real-time environmental parameters of the optical fiber location through an environmental monitoring unit, wherein the environmental parameters include at least ambient temperature, ambient humidity, and vibration parameters; Pre-training gain curve analyzer; The real-time environmental parameters, real-time optical power and real-time OSNR signals are input into the gain curve analyzer, and a reference gain curve is output.

4. The C+L400G system zero insertion loss optical line protection device according to claim 3, characterized in that: Pre-trained gain curve analyzer, including: According to the historical operation and maintenance records of the optical fiber, a sample environmental parameter set, a sample optical power set, and a sample OSNR signal set are collected, and the corresponding standard gain curves under different sample environmental parameters, sample optical power, and sample OSNR signals are obtained as sample gain curves to obtain a sample gain curve set; The sample environment parameter set, the sample optical power set and the sample OSNR signal set are used as inputs, the sample gain curve set is used as supervision, and a BP neural network is trained until convergence to obtain a gain curve analyzer.

5. The C+L400G system zero insertion loss optical line protection device according to claim 1, characterized in that: With the goal of approximating the reference gain curve, the adjustment parameters of the RFA amplification unit are optimized, and the optimal adjustment parameters are output, including: Obtaining adjustment parameter thresholds of the RFA amplification unit, wherein the adjustment parameters include gain dynamic range, gain adjustment accuracy, and gain response time; Pre-trained gain curve predictor; The adjustment parameter threshold is used as the optimization space, and approaching the reference gain curve is used as the optimization goal. The adjustment parameter is optimized using the gain curve predictor, and the optimal adjustment parameter is output.

6. The C+L400G system zero insertion loss optical line protection device according to claim 5, characterized in that: Pre-trained gain curve predictor, including: According to the historical operation and maintenance records of the optical fiber, a sample environmental parameter set, a sample optical power set, a sample OSNR signal set, and a sample adjustment parameter set are collected, and a historical gain curve adjusted by the sample adjustment parameters is obtained as a sample predicted gain curve to obtain a sample predicted gain curve set; The sample environment parameter set, sample optical power set, sample OSNR signal set and sample adjustment parameter set are used as inputs, the sample predicted gain curve set is used as supervision, and a BP neural network is trained until convergence to obtain a gain curve predictor.

7. The C+L400G system zero insertion loss optical line protection device according to claim 5, characterized in that: Taking the adjustment parameter threshold as the optimization space and approaching the reference gain curve as the optimization goal, optimizing the adjustment parameter using the gain curve predictor and outputting the optimal adjustment parameter, including: Randomly generating a first adjustment parameter within the adjustment parameter threshold, inputting the first adjustment parameter into the gain curve predictor, and outputting a first predicted gain curve; performing similarity calculation on the reference gain curve and the first predicted gain curve, and outputting a first similarity; Continue to use the adjustment parameter threshold as the optimization space, iteratively perform parameter random selection, gain curve prediction and similarity calculation until the preset number of iterations is reached, and the adjustment parameter corresponding to the predicted gain curve with the largest output similarity is set as the optimal adjustment parameter.

8. The C+L400G system zero insertion loss optical line protection device according to claim 1, characterized in that: Switching to the backup line through the routing switching unit also includes: The backup line also includes a backup power feedback control unit and an RFA amplification unit, wherein the backup power feedback control unit includes a backup FPGA unit and a backup MCU unit, and the backup MCU unit is communicatively connected to the MCU unit; When the backup line is not switched, the optimal adjustment parameter is synchronously transmitted to the backup MCU unit through the MCU unit, and the RFA amplification unit of the backup line is adaptively iteratively controlled; After switching to the backup line, the RFA amplification unit of the backup line is adaptively iteratively controlled through the backup FPGA unit and the backup MCU unit. 9.C+L400G system zero insertion loss optical line protection method, characterized in that: The invention is implemented by the C+L400G system zero insertion loss optical line protection device according to any one of claims 1 to 8, comprising: During optical fiber communication, the real-time optical power and OSNR signals of the main line are obtained through fixed-point monitoring by the FPGA unit; Determine whether the real-time optical power and the real-time OSNR signal meet the line switching threshold, and if so, switch to the backup line through the routing switching unit; If not, the MCU unit determines a reference gain curve based on the real-time optical power and real-time OSNR signal analysis, optimizes the adjustment parameters of the RFA amplification unit with the goal of approximating the reference gain curve, and outputs the optimal adjustment parameters; The RFA amplification unit is controlled according to the optimal adjustment parameters, and adaptive iterative control is performed according to real-time monitoring data.

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