Single-mode optical fiber communication control system and method based on multi-carrier communication

Abstract

The present invention discloses a single-mode optical fiber communication control system and method based on multi-carrier communication, and relates to the technical field of optical fiber communication. The system of the present invention comprises: a historical data acquisition and signal quality assessment module, a data feature extraction and deviation analysis module, a multi-carrier transmission model construction and simulation module, a real-time transmission and quality monitoring module, and an optimization result output and adjustment prompt module; the historical data acquisition and signal quality assessment module acquires historical transmission data and calculates the signal quality score; the data feature extraction and deviation analysis module extracts feature vectors and defines optimization targets; the multi-carrier transmission model construction and simulation module constructs a multi-carrier transmission model according to template data, simulates data transmission to be optimized and generates an optimization strategy; the real-time transmission and quality monitoring module transmits the data to be optimized in real time according to the optimization strategy; the optimization result output and adjustment prompt module compares the scores of the real-time data and the data to be optimized, and outputs prompt information.

Description

Technical Field

[0001] The present invention relates to the technical field of optical fiber communication, and in particular to a single-mode optical fiber communication control system and method based on multi-carrier communication. Background Art

[0002] With the rapid development of information technology, modern communication systems have an increasing demand for data transmission rate, bandwidth utilization and signal transmission quality. Optical fiber communication, especially single-mode optical fiber communication, has become one of the indispensable core technologies in modern communication networks due to its advantages such as high bandwidth, long-distance transmission and anti-interference. Single-mode optical fiber communication systems can achieve high-speed and large-capacity data transmission and are widely used in data centers, long-distance communications and high-performance computing.

[0003] However, single-mode optical fiber communication systems often face the problem of inter-carrier interference when transmitting at high bandwidth and high speed. Inter-carrier interference refers to the mutual interference between different carriers in multi-carrier transmission, which causes the signal quality to deteriorate and affects the reliability and transmission efficiency of the system. With the increase of communication rate, the impact of inter-carrier interference becomes more and more significant, resulting in reduced signal quality and increased bit error rate, thus limiting the performance of the communication system. In addition, there is also the problem of signal energy loss during single-mode optical fiber transmission. Although optical fiber transmission has low attenuation characteristics, due to the loss of the optical fiber itself and the loss of other devices in the transmission link, the signal will still gradually attenuate during transmission, thereby affecting the stability of communication and the utilization of effective bandwidth. In the existing single-mode optical fiber communication link of carrier communication, although the carrier allocation and transmission strategy are usually adjusted dynamically, these dynamic adjustment strategies still face many challenges due to the time-varying characteristics of the channel and the influence of external interference. Especially in high-bandwidth and high-speed transmission, the problems of inter-carrier interference and signal attenuation are more prominent, resulting in a significant reduction in system performance. Summary of the invention

[0004] The object of the present invention is to provide a single-mode optical fiber communication control system and method based on multi-carrier communication to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A single-mode optical fiber communication control method based on multi-carrier communication comprises the following steps:

[0007] Step S100. Obtain historical transmission data of the single-mode optical fiber communication link through the network monitoring system, extract signal quality parameters of the historical transmission data and form a feature vector; perform signal quality evaluation on each piece of historical transmission data according to the feature vector, and classify the historical transmission data based on the signal quality evaluation result into template transmission data and transmission data to be optimized;

[0008] Step S200. Extract the feature vectors of the template transmission data and the transmission data to be optimized respectively, mark the feature vectors of the template transmission data and the feature vectors of the transmission data to be optimized respectively; analyze the deviation relationship between the feature vectors of the template transmission data and the feature vectors of the transmission data to be optimized, so as to obtain the optimization target of the transmission data to be optimized;

[0009] Step S300. Based on the template transmission data, a multi-carrier transmission model of a single-mode optical fiber communication link is established; according to the multi-carrier transmission model, the transmission process of the transmission data to be optimized is simulated, and real-time adjustments are made according to the optimization target of the transmission data to be optimized, thereby obtaining an optimization strategy for the transmission data to be optimized;

[0010] Step S400. According to the optimization strategy of the transmission data to be optimized, the transmission data to be optimized is transmitted in real time, the real-time transmission data of the single-mode optical fiber communication link is obtained through the network monitoring system, and the signal quality of the real-time transmission data is evaluated; the signal quality evaluation result of the real-time transmission data is compared and analyzed with the signal quality evaluation result of the corresponding transmission data to be optimized, and corresponding prompt information is output according to the comparison and analysis results.

[0011] Furthermore, step S100 includes:

[0012] S101. Obtain historical transmission data of a single-mode optical fiber communication link from a network monitoring system. For each piece of historical transmission data, extract signal quality parameters and form a feature vector X, where the signal quality parameters specifically include: received optical power, optical fiber loss, signal-to-noise ratio, bit error rate, etc.; and X=[x1,x2,...,xm], where x1 represents the feature corresponding to the first signal quality parameter of the historical transmission data, x2 represents the feature corresponding to the second signal quality parameter of the historical transmission data, and so on, xm represents the feature corresponding to the mth signal quality parameter of the historical transmission data, and m represents the number of signal quality parameters; use a deep learning model to map the feature data, thereby obtaining a signal quality score Q, and the corresponding calculation formula is:

[0013] Q=σ{∑i∈[1,n],wi·Φ(Wi·X+bi)},

[0014] Among them, σ represents the activation function of the output layer, wi represents the weight coefficient of the i-th layer, and Φ represents the activation function, such as ReLU or Sigmoid; Wi represents the weight matrix of the i-th layer, and bi represents the bias of the i-th layer; by introducing multiple nonlinear mappings, various indicators of signal quality are taken into consideration comprehensively instead of simply weighted averaging; the design of the activation function (for example, using the Swish activation function) can better capture complex nonlinear relationships.

[0015] S102. Summarize the signal quality scores of all historical transmission data, and calculate the corresponding average value μQ and standard deviation σQ, so as to obtain the signal quality score threshold θ, and θ=μQ+λσQ, where λ represents the adjustment factor; for each piece of historical transmission data, compare the size relationship between the corresponding signal quality score Q and the signal quality score threshold θ, if the signal quality score Q is greater than or equal to the signal quality score threshold θ, then mark this piece of historical transmission data as template transmission data; if the signal quality score Q is less than the signal quality score threshold θ, then mark this piece of historical transmission data as transmission data to be optimized.

[0016] Further, step S200 includes:

[0017] S201. According to the classification results of the historical transmission data, for the template transmission data and the transmission data to be optimized, respectively obtain and mark the template transmission data feature vector X_template and the transmission data feature vector X_optimize to be optimized, and respectively express them as: X_template=[x template 1,x template 2,...,x template m ],X_optimize=[x optimize 1,x optimize 2,...,x optimize m ]; where x template 1 represents the first eigenvalue of the template transmission data eigenvector, x template 2 represents the second eigenvalue of the template transmission data eigenvector, and so on. template m represents the mth eigenvalue of the template transmission data eigenvector; similarly, x optimize 1 represents the first eigenvalue of the eigenvector of the transmission data to be optimized, x optimize 2 represents the second eigenvalue of the eigenvector of the transmission data to be optimized, x optimize m represents the mth eigenvalue of the transmission data eigenvector to be optimized;

[0018] S202. Calculate the difference between the template transmission data feature vector X_template and the transmission data feature vector X_optimize to be optimized, thereby obtaining a deviation metric D, and the specific calculation formula is:

[0019] D = (1 / m) × {∑v∈[1,m],Lv×(x template v -x optimize v )^2}^(1 / 2),

[0020] Among them, Lv represents the weight of the vth feature, x template v represents the vth eigenvalue of the template transmission data eigenvector, x optimize v It represents the vth eigenvalue of the transmission data feature vector to be optimized, where v is a positive integer between 1 and m. According to the deviation metric D, the optimization target O is defined, and the expression is: O=min(D). By adjusting the feature vector X_template of the data to be optimized, the deviation metric D is minimized, thereby obtaining the corresponding optimized feature vector X_template_new.

[0021] Furthermore, step S300 includes:

[0022] S301. Based on the template transmission data, the multipath model of the channel is defined as:

[0023] H(f,t)=∑c∈[1,N],α c (t)e^[-j2πfτ i (t)],

[0024] Among them, α c (t) represents the time-varying attenuation coefficient of the cth path, τ i (t) represents the propagation delay, f represents the frequency, and N represents the number of paths; the transmission signal is divided into multiple frequency bands for simultaneous transmission, and each frequency band is set to f k The transmission signal is s k (t), and the overall transmission signal is expressed as:

[0025] s(t)=∑k∈[1,K],s k (t)·cos(2πf k t),

[0026] Where K represents the number of carriers, f k Indicates the frequency of the kth carrier; combined with the above content, a multi-carrier transmission model is constructed, and the transmission signal of each frequency band in the multi-carrier transmission model is affected by the attenuation of each path, and the transmission process of each signal is expressed as:

[0027] y k (t)=H(f k ,t)·s k (t)+n k (t),

[0028] Among them, y k (t) represents the received signal, n k (t) represents the multipath fading effect of the signals in each frequency band;

[0029] S302. Based on the multi-carrier transmission model, simulate the transmission process of the transmission data to be optimized to obtain the corresponding simulated transmission data; extract the corresponding signal quality parameters from the simulated transmission data, and form a simulated transmission data feature vector X_sim; and based on the optimization target O of the simulated transmission data and the corresponding optimized feature vector X_template_new, adjust the relevant signal parameters, calculate the deviation metric once each time the adjustment is made until the optimization target O is met, and save the last adjustment process to generate an optimization strategy for the transmission data to be optimized.

[0030] Furthermore, step S400 includes:

[0031] S401. According to the optimization strategy of the transmission data to be optimized, the transmission data to be optimized is transmitted in real time, the real-time transmission data of the single-mode optical fiber communication link is obtained through the network monitoring system, and the signal quality score calculation process of the historical transmission data is referred to, and the real-time transmission data is analyzed in the same way, thereby obtaining the signal quality score Q1 of the real-time transmission data;

[0032] S402. Compare the signal quality score Q1 of the real-time transmission data with the signal quality score Q of the corresponding transmission data to be optimized, and calculate the difference ΔQ between the two, and ΔQ=Q1-Q; if ΔQ>0, and Q1>θ, then output "The transmission quality meets expectations and no adjustment is required"; otherwise, output "The signal quality does not meet expectations and it is recommended to adjust the transmission strategy"; relevant personnel shall further process according to the output prompt information.

[0033] The single-mode optical fiber communication control system based on multi-carrier communication includes: historical data collection and signal quality evaluation module, data feature extraction and deviation analysis module, multi-carrier transmission model construction and simulation module, real-time transmission and quality monitoring module, and optimization result output and adjustment prompt module;

[0034] The historical data collection and signal quality assessment module is responsible for obtaining the historical transmission data of the single-mode optical fiber communication link from the network monitoring system, extracting the signal quality parameters and generating feature vectors; mapping the feature data through the deep learning model, calculating the signal quality score of each historical transmission data, and dividing the historical transmission data into template transmission data and transmission data to be optimized;

[0035] The data feature extraction and deviation analysis module extracts the feature vectors of the template transmission data and the transmission data to be optimized according to the classification results; calculates and analyzes the deviation measurement between the feature vectors of the template data and the data to be optimized, thereby defining the optimization target;

[0036] The multi-carrier transmission model building and simulation module builds a multi-carrier transmission model based on the template transmission data, simulates the transmission process of the data to be optimized, adjusts the signal parameters to achieve the optimization goal, and generates an optimization strategy;

[0037] The real-time transmission and quality monitoring module transmits the data to be optimized in real time according to the optimization strategy, obtains the real-time transmission data of the link; evaluates the signal quality of the real-time transmission data, and calculates the corresponding signal quality score;

[0038] The optimization result output and adjustment prompt module compares the quality score of the real-time transmission data with the score of the data to be optimized, and outputs corresponding prompt information according to the comparison result.

[0039] Further, the historical data collection and signal quality assessment module includes a data collection unit, a signal quality assessment unit and a classification unit;

[0040] The data acquisition unit is used to obtain the historical transmission data of the single-mode optical fiber communication link from the network monitoring system; the signal quality evaluation unit extracts the signal quality parameters for each historical transmission data and converts them into feature vectors; the feature vectors are mapped using a deep learning model to calculate the signal quality score; the classification unit summarizes the signal quality scores of all historical transmission data, and compares the signal quality scores of the historical transmission data with the signal quality score threshold, and classifies the historical transmission data into template transmission data and transmission data to be optimized according to the comparison results.

[0041] Further, the data feature extraction and deviation analysis module includes a deviation metric calculation unit and an optimization target definition unit;

[0042] The deviation metric calculation unit extracts the feature vectors of the template transmission data and the transmission data to be optimized respectively, and calculates the deviation metric between the feature vector of the template transmission data and the feature vector of the transmission data to be optimized; the optimization target definition unit defines the optimization target of the transmission data to be optimized based on the deviation metric.

[0043] Furthermore, the multi-carrier transmission model building and simulation module includes a multi-path channel modeling unit, a multi-carrier signal allocation unit, a transmission process simulation unit, and an optimization target adjustment unit;

[0044] The multipath channel modeling unit constructs a multipath model of the channel based on the template transmission data; the multi-carrier signal allocation unit divides the transmission signal into multiple frequency bands, sets the transmission signal of each frequency band, and synthesizes the multi-carrier signal; the simulation transmission process unit simulates the transmission process of the transmission data to be optimized based on the multi-carrier transmission model, extracts the signal quality parameters of the simulated transmission data, and constructs the simulated transmission data feature vector; the optimization target adjustment unit adjusts the signal parameters according to the optimization target and the optimized feature vector, and calculates the deviation metric until the deviation metric meets the optimization target, saves the final adjustment process, and generates the optimization strategy for the transmission data to be optimized.

[0045] Further, the real-time transmission and quality monitoring module includes a real-time transmission control unit and a real-time signal quality assessment unit;

[0046] The real-time transmission control unit transmits the optimized transmission data in real time according to the optimization strategy and adjusts the signal parameters in the transmission process; the real-time signal quality evaluation unit obtains the real-time transmission data of the single-mode optical fiber communication link from the network monitoring system in real time, performs signal quality evaluation on the real-time transmission data, and calculates the signal quality score;

[0047] The optimization result output and adjustment prompt module includes an optimization result output unit and an adjustment prompt generation unit;

[0048] The optimization result output unit outputs the optimization strategy of the transmission data to be optimized for use in the actual transmission process; the adjustment prompt generation unit compares the signal quality score of the real-time transmission data with the signal quality score of the corresponding transmission data to be optimized, and outputs corresponding prompt information based on the comparison result.

[0049] Compared with the prior art, the present invention has the following beneficial effects:

[0050] The signal quality parameters of historical transmission data are mapped through a deep learning model to obtain a more accurate signal quality score; the score takes into account all aspects of signal quality, rather than simply weighted average, making the evaluation result more comprehensive and accurate; this classification method based on historical data effectively distinguishes between template transmission data and transmission data to be optimized, providing a more reliable basis for the subsequent optimization strategy formulation. By analyzing the difference between template transmission data and transmission data to be optimized, the optimization target is obtained using deviation measurement, and the transmission process of transmission data to be optimized is simulated based on a multi-carrier transmission model; by gradually adjusting the transmission parameters, the optimization strategy can adapt to channel changes in real time and dynamically, thereby effectively reducing the impact of inter-carrier interference and signal attenuation on transmission performance; compared with existing fixed or rough adjustment strategies, the present invention can provide a more accurate and intelligent optimization solution. Through the introduction of a multi-carrier transmission model, the invention divides the signal into multiple frequency bands for simultaneous transmission, thereby better adapting to the attenuation characteristics of different paths, and significantly improving the spectrum utilization efficiency during the transmission process; each frequency band in the model is affected by the attenuation of each path, and the optimization process takes these differences into account, effectively reducing inter-carrier interference, thereby reducing the bit error rate, and improving the transmission efficiency and stability of the system. During the actual transmission process, the invention obtains signal quality data in real time through the network monitoring system and compares it with the scores of historical transmission data, thereby realizing real-time monitoring and adjustment of system performance; this real-time feedback mechanism can ensure that the system always remains in the optimal state during operation and effectively cope with the time-varying characteristics of the channel and external interference. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0052] Figure 1 It is a schematic diagram of a single-mode optical fiber communication control system module based on multi-carrier communication of the present invention. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] See also Figure 1 , the present invention provides a technical solution:

[0055] The single-mode optical fiber communication control system based on multi-carrier communication includes: historical data collection and signal quality evaluation module, data feature extraction and deviation analysis module, multi-carrier transmission model construction and simulation module, real-time transmission and quality monitoring module, and optimization result output and adjustment prompt module;

[0056] The historical data collection and signal quality assessment module is responsible for obtaining the historical transmission data of the single-mode optical fiber communication link from the network monitoring system, extracting the signal quality parameters and generating feature vectors; mapping the feature data through the deep learning model, calculating the signal quality score of each historical transmission data, and dividing the historical transmission data into template transmission data and transmission data to be optimized;

[0057] The data feature extraction and deviation analysis module extracts the feature vectors of the template transmission data and the transmission data to be optimized according to the classification results; calculates and analyzes the deviation measurement between the feature vectors of the template data and the data to be optimized, thereby defining the optimization target;

[0058] The multi-carrier transmission model building and simulation module builds a multi-carrier transmission model based on the template transmission data, simulates the transmission process of the data to be optimized, adjusts the signal parameters to achieve the optimization goal, and generates an optimization strategy;

[0059] The real-time transmission and quality monitoring module transmits the data to be optimized in real time according to the optimization strategy, obtains the real-time transmission data of the link; evaluates the signal quality of the real-time transmission data, and calculates the corresponding signal quality score;

[0060] The optimization result output and adjustment prompt module compares the quality score of the real-time transmission data with the score of the data to be optimized, and outputs corresponding prompt information according to the comparison result.

[0061] The historical data collection and signal quality assessment module includes a data collection unit, a signal quality assessment unit and a classification unit;

[0062] The data acquisition unit is used to obtain the historical transmission data of the single-mode optical fiber communication link from the network monitoring system; the signal quality evaluation unit extracts the signal quality parameters for each historical transmission data and converts them into feature vectors; the feature vectors are mapped using a deep learning model to calculate the signal quality score; the classification unit summarizes the signal quality scores of all historical transmission data, and compares the signal quality scores of the historical transmission data with the signal quality score threshold, and classifies the historical transmission data into template transmission data and transmission data to be optimized according to the comparison results.

[0063] The data feature extraction and deviation analysis module includes a deviation metric calculation unit and an optimization target definition unit;

[0064] The deviation metric calculation unit extracts the feature vectors of the template transmission data and the transmission data to be optimized respectively, and calculates the deviation metric between the feature vector of the template transmission data and the feature vector of the transmission data to be optimized; the optimization target definition unit defines the optimization target of the transmission data to be optimized based on the deviation metric.

[0065] The multi-carrier transmission model building and simulation module includes a multi-path channel modeling unit, a multi-carrier signal allocation unit, a transmission process simulation unit, and an optimization target adjustment unit;

[0066] The multipath channel modeling unit constructs a multipath model of the channel based on the template transmission data; the multi-carrier signal allocation unit divides the transmission signal into multiple frequency bands, sets the transmission signal of each frequency band, and synthesizes the multi-carrier signal; the simulation transmission process unit simulates the transmission process of the transmission data to be optimized based on the multi-carrier transmission model, extracts the signal quality parameters of the simulated transmission data, and constructs the simulated transmission data feature vector; the optimization target adjustment unit adjusts the signal parameters according to the optimization target and the optimized feature vector, and calculates the deviation metric until the deviation metric meets the optimization target, saves the final adjustment process, and generates the optimization strategy for the transmission data to be optimized.

[0067] The real-time transmission and quality monitoring module includes a real-time transmission control unit and a real-time signal quality evaluation unit;

[0068] The real-time transmission control unit transmits the optimized transmission data in real time according to the optimization strategy and adjusts the signal parameters in the transmission process; the real-time signal quality evaluation unit obtains the real-time transmission data of the single-mode optical fiber communication link from the network monitoring system in real time, performs signal quality evaluation on the real-time transmission data, and calculates the signal quality score;

[0069] The optimization result output and adjustment prompt module includes an optimization result output unit and an adjustment prompt generation unit;

[0070] The optimization result output unit outputs the optimization strategy of the transmission data to be optimized for use in the actual transmission process; the adjustment prompt generation unit compares the signal quality score of the real-time transmission data with the signal quality score of the corresponding transmission data to be optimized, and outputs corresponding prompt information based on the comparison result.

[0071] A single-mode optical fiber communication control method based on multi-carrier communication comprises the following steps:

[0072] Step S100. Obtain historical transmission data of the single-mode optical fiber communication link through the network monitoring system, extract signal quality parameters of the historical transmission data and form a feature vector; perform signal quality evaluation on each piece of historical transmission data according to the feature vector, and classify the historical transmission data based on the signal quality evaluation result into template transmission data and transmission data to be optimized;

[0073] Step S200. Extract the feature vectors of the template transmission data and the transmission data to be optimized respectively, mark the feature vectors of the template transmission data and the feature vectors of the transmission data to be optimized respectively; analyze the deviation relationship between the feature vectors of the template transmission data and the feature vectors of the transmission data to be optimized, so as to obtain the optimization target of the transmission data to be optimized;

[0074] Step S300. Based on the template transmission data, a multi-carrier transmission model of a single-mode optical fiber communication link is established; according to the multi-carrier transmission model, the transmission process of the transmission data to be optimized is simulated, and real-time adjustments are made according to the optimization target of the transmission data to be optimized, thereby obtaining an optimization strategy for the transmission data to be optimized;

[0075] Step S400. According to the optimization strategy of the transmission data to be optimized, the transmission data to be optimized is transmitted in real time, the real-time transmission data of the single-mode optical fiber communication link is obtained through the network monitoring system, and the signal quality of the real-time transmission data is evaluated; the signal quality evaluation result of the real-time transmission data is compared and analyzed with the signal quality evaluation result of the corresponding transmission data to be optimized, and corresponding prompt information is output according to the comparison and analysis results.

[0076] Step S100 includes:

[0077] S101. Obtain historical transmission data of a single-mode optical fiber communication link from a network monitoring system. For each piece of historical transmission data, extract signal quality parameters and form a feature vector X, where the signal quality parameters specifically include: received optical power, optical fiber loss, signal-to-noise ratio, bit error rate, etc.; and X=[x1,x2,...,xm], where x1 represents the feature corresponding to the first signal quality parameter of the historical transmission data, x2 represents the feature corresponding to the second signal quality parameter of the historical transmission data, and so on, xm represents the feature corresponding to the mth signal quality parameter of the historical transmission data, and m represents the number of signal quality parameters; use a deep learning model to map the feature data, thereby obtaining a signal quality score Q, and the corresponding calculation formula is:

[0078] Q=σ{∑i∈[1,n],wi·Φ(Wi·X+bi)},

[0079] Among them, σ represents the activation function of the output layer, wi represents the weight coefficient of the i-th layer, and Φ represents the activation function, such as ReLU or Sigmoid; Wi represents the weight matrix of the i-th layer, and bi represents the bias of the i-th layer; by introducing multiple nonlinear mappings, various indicators of signal quality are taken into consideration comprehensively instead of simply weighted averaging; the design of the activation function (for example, using the Swish activation function) can better capture complex nonlinear relationships.

[0080] S102. Summarize the signal quality scores of all historical transmission data, and calculate the corresponding average value μQ and standard deviation σQ, so as to obtain the signal quality score threshold θ, and θ=μQ+λσQ, where λ represents the adjustment factor; for each piece of historical transmission data, compare the size relationship between the corresponding signal quality score Q and the signal quality score threshold θ, if the signal quality score Q is greater than or equal to the signal quality score threshold θ, then mark this piece of historical transmission data as template transmission data; if the signal quality score Q is less than the signal quality score threshold θ, then mark this piece of historical transmission data as transmission data to be optimized.

[0081] Step S200 includes:

[0082] S201. According to the classification results of the historical transmission data, for the template transmission data and the transmission data to be optimized, respectively obtain and mark the template transmission data feature vector X_template and the transmission data feature vector X_optimize to be optimized, and respectively express them as: X_template=[x template 1,x template 2,...,x template m ],X_optimize=[x optimize 1,x optimize 2,...,x optimize m ]; where x template 1 represents the first eigenvalue of the template transmission data eigenvector, x template 2 represents the second eigenvalue of the template transmission data eigenvector, and so on. template m represents the mth eigenvalue of the template transmission data eigenvector; similarly, x optimize 1 represents the first eigenvalue of the eigenvector of the transmission data to be optimized, x optimize 2 represents the second eigenvalue of the eigenvector of the transmission data to be optimized, x optimize m represents the mth eigenvalue of the transmission data eigenvector to be optimized;

[0083] S202. Calculate the difference between the template transmission data feature vector X_template and the transmission data feature vector X_optimize to be optimized, thereby obtaining a deviation metric D, and the specific calculation formula is:

[0084] D = (1 / m) × {∑v∈[1,m],Lv×(x template v -x optimize v )^2}^(1 / 2),

[0085] Among them, Lv represents the weight of the vth feature, x template v represents the vth eigenvalue of the template transmission data eigenvector, x optimize v It represents the vth eigenvalue of the transmission data feature vector to be optimized, where v is a positive integer between 1 and m. According to the deviation metric D, the optimization target O is defined, and the expression is: O=min(D). By adjusting the feature vector X_template of the data to be optimized, the deviation metric D is minimized, thereby obtaining the corresponding optimized feature vector X_template_new.

[0086] In this embodiment, the optimization goal is to minimize the deviation between the template transmission data and the transmission data to be optimized. In order to quantify this deviation, the deviation metric D is calculated, and the specific calculation formula is:

[0087] D = (1 / m) × {∑v∈[1,m],Lv×(x template v -x optimize v )^2}^(1 / 2),

[0088] Lv is a weighting factor, which is usually set according to the importance of the feature or the sensitivity to the optimization goal; by squaring the difference, the influence of positive and negative signs can be eliminated, so that large deviations have higher penalties than small deviations. This helps to ensure that during the optimization process, not only the improvement of small deviations is focused on, but also large errors can be effectively corrected, thereby improving the overall model accuracy. By defining the optimization target O, the optimization target is particularly suitable for complex tasks with multiple features, and can be flexibly adjusted to adapt to different business needs and application scenarios. Ultimately, the setting of the optimization target is not only a mathematical simplification, but also an optimization strategy tailored to actual needs, which helps to improve the quality and efficiency of transmitted data.

[0089] Step S300 includes:

[0090] S301. Based on the template transmission data, the multipath model of the channel is defined as:

[0091] H(f,t)=∑c∈[1,N],α c (t)e^[-j2πfτ i (t)],

[0092] Among them, α c (t) represents the time-varying attenuation coefficient of the cth path, τ i (t) represents the propagation delay, f represents the frequency, and N represents the number of paths; the transmission signal is divided into multiple frequency bands for simultaneous transmission, and each frequency band is set to f k The transmission signal is sk (t), and the overall transmission signal is expressed as:

[0093] s(t)=∑k∈[1,K],s k (t)·cos(2πf k t),

[0094] Where K represents the number of carriers, f k Indicates the frequency of the kth carrier; combined with the above content, a multi-carrier transmission model is constructed, and the transmission signal of each frequency band in the multi-carrier transmission model is affected by the attenuation of each path, and the transmission process of each signal is expressed as:

[0095] y k (t)=H(f k ,t)·s k (t)+n k (t),

[0096] Among them, y k (t) represents the received signal, n k (t) represents the multipath fading effect of the signals in each frequency band;

[0097] S302. Based on the multi-carrier transmission model, simulate the transmission process of the transmission data to be optimized to obtain the corresponding simulated transmission data; extract the corresponding signal quality parameters from the simulated transmission data, and form a simulated transmission data feature vector X_sim; and based on the optimization target O of the simulated transmission data and the corresponding optimized feature vector X_template_new, adjust the relevant signal parameters, calculate the deviation metric once each time the adjustment is made until the optimization target O is met, and save the last adjustment process to generate an optimization strategy for the transmission data to be optimized.

[0098] In this embodiment, the optimization goal used is to minimize the bit error rate BER. After each adjustment, correction is performed through the following steps:

[0099] Step 1: Calculate the bit error rate (BER) of each subcarrier based on the current parameters (power allocation, modulation method, etc.).

[0100] Step 2: Adjust parameters (such as subcarrier power, modulation method, channel coding, etc.) according to the gradient descent algorithm.

[0101] Step 3: Update the optimization parameters and return to step 1 to continue iteration.

[0102] For example, at each iteration, it is assumed that the system's bit error rate decreases as the power increases, so the power of some subcarriers, especially those with poor channels, is increased. If some subcarriers have reached the ideal bit error rate, their power can be reduced to save energy.

[0103] The optimization process terminates under the following conditions:

[0104] Error convergence: If the system's bit error rate changes very little over several iterations, it means that the system is close to the optimal solution.

[0105] Maximum number of iterations: To avoid excessive calculations, you can set a maximum number of iterations.

[0106] Performance meets requirements: If the system's bit error rate is lower than a certain predetermined threshold, the optimization can be stopped.

[0107] Ultimately, the optimization process will provide a set of optimal transmission parameters, which can significantly improve the transmission efficiency of the system and reduce the bit error rate. Therefore, the above transmission parameters are used as the corresponding optimization strategy.

[0108] Step S400 includes:

[0109] S401. According to the optimization strategy of the transmission data to be optimized, the transmission data to be optimized is transmitted in real time, the real-time transmission data of the single-mode optical fiber communication link is obtained through the network monitoring system, and the signal quality score calculation process of the historical transmission data is referred to, and the real-time transmission data is analyzed in the same way, thereby obtaining the signal quality score Q1 of the real-time transmission data;

[0110] S402. Compare the signal quality score Q1 of the real-time transmission data with the signal quality score Q of the corresponding transmission data to be optimized, and calculate the difference ΔQ between the two, and ΔQ=Q1-Q; if ΔQ>0, and Q1>θ, then output "The transmission quality meets expectations and no adjustment is required"; otherwise, output "The signal quality does not meet expectations and it is recommended to adjust the transmission strategy"; relevant personnel shall further process according to the output prompt information.

[0111] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0112] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A single-mode optical fiber communication control method based on multi-carrier communication, characterized in that: The method comprises the following steps: Step S100. Obtain historical transmission data of the single-mode optical fiber communication link through the network monitoring system, extract signal quality parameters of the historical transmission data and form a feature vector; perform signal quality evaluation on each piece of historical transmission data according to the feature vector, and classify the historical transmission data based on the signal quality evaluation result into template transmission data and transmission data to be optimized; Step S200. Extract the feature vectors of the template transmission data and the transmission data to be optimized respectively, mark the feature vectors of the template transmission data and the feature vectors of the transmission data to be optimized respectively; analyze the deviation relationship between the feature vectors of the template transmission data and the feature vectors of the transmission data to be optimized, so as to obtain the optimization target of the transmission data to be optimized; Step S300. Based on the template transmission data, a multi-carrier transmission model of a single-mode optical fiber communication link is established; according to the multi-carrier transmission model, the transmission process of the transmission data to be optimized is simulated, and real-time adjustments are made according to the optimization target of the transmission data to be optimized, thereby obtaining an optimization strategy for the transmission data to be optimized; Step S400. According to the optimization strategy of the transmission data to be optimized, the transmission data to be optimized is transmitted in real time, the real-time transmission data of the single-mode optical fiber communication link is obtained through the network monitoring system, and the signal quality of the real-time transmission data is evaluated; the signal quality evaluation result of the real-time transmission data is compared and analyzed with the signal quality evaluation result of the corresponding transmission data to be optimized, and corresponding prompt information is output according to the comparison and analysis results.

2. The single-mode optical fiber communication control method based on multi-carrier communication according to claim 1, characterized in that: The step S100 includes: S101. Obtain historical transmission data of a single-mode optical fiber communication link from a network monitoring system. For each piece of historical transmission data, extract signal quality parameters and form a feature vector X, where X=[x1, x2, ..., xm], where x1 represents the feature corresponding to the first signal quality parameter of the historical transmission data, x2 represents the feature corresponding to the second signal quality parameter of the historical transmission data, and so on, xm represents the feature corresponding to the mth signal quality parameter of the historical transmission data, and m represents the number of signal quality parameters; use a deep learning model to map the feature data, thereby obtaining a signal quality score Q, and the corresponding calculation formula is: Q=σ{∑i∈[1,n],wi·Φ(Wi·X+bi)}, Among them, σ represents the activation function of the output layer, wi represents the weight coefficient of the i-th layer, Φ represents the activation function, Wi represents the weight matrix of the i-th layer, and bi represents the bias of the i-th layer; S102. Summarize the signal quality scores of all historical transmission data, and calculate the corresponding average value μQ and standard deviation σQ, so as to obtain the signal quality score threshold θ, and θ=μQ+λσQ, where λ represents the adjustment factor; for each piece of historical transmission data, compare the size relationship between the corresponding signal quality score Q and the signal quality score threshold θ, if the signal quality score Q is greater than or equal to the signal quality score threshold θ, then mark this piece of historical transmission data as template transmission data; if the signal quality score Q is less than the signal quality score threshold θ, then mark this piece of historical transmission data as transmission data to be optimized.

3. The single-mode optical fiber communication control method based on multi-carrier communication according to claim 2, characterized in that: The step S200 includes: S201. According to the classification results of the historical transmission data, for the template transmission data and the transmission data to be optimized, respectively obtain and mark the template transmission data feature vector X_template and the transmission data feature vector X_optimize to be optimized, and respectively express them as: X_template=[x template 1,x template 2,...,x template m ],X_optimize=[x optimize 1,x optimize 2,...,x optimize m ]; where x template 1 represents the first eigenvalue of the template transmission data eigenvector, x template 2 represents the second eigenvalue of the template transmission data eigenvector, and so on. template m represents the mth eigenvalue of the template transmission data eigenvector; similarly, x optimize 1 represents the first eigenvalue of the eigenvector of the transmission data to be optimized, x optimize 2 represents the second eigenvalue of the eigenvector of the transmission data to be optimized, x optimize m represents the mth eigenvalue of the transmission data eigenvector to be optimized; S202. Calculate the difference between the template transmission data feature vector X_template and the transmission data feature vector X_optimize to be optimized, thereby obtaining a deviation metric D, and the specific calculation formula is: D=(1 / m)×{∑v∈[1,m],Lv×(x template v -x optimize v )^2}^(1 / 2), Among them, Lv represents the weight of the vth feature, x template v represents the vth eigenvalue of the template transmission data eigenvector, x optimize v It represents the vth eigenvalue of the transmission data feature vector to be optimized, where v is a positive integer between 1 and m. According to the deviation metric D, the optimization target O is defined, and the expression is: O=min(D). By adjusting the feature vector X_template of the data to be optimized, the deviation metric D is minimized, thereby obtaining the corresponding optimized feature vector X_template_new.

4. The single-mode optical fiber communication control method based on multi-carrier communication according to claim 3, characterized in that: The step S300 includes: S301. Based on the template transmission data, the multipath model of the channel is defined as: H(f,t)=∑c∈[1,N],α c (t)e^[-j2πfτ i (t)], Among them, α c (t) represents the time-varying attenuation coefficient of the cth path, τ i (t) represents the propagation delay, f represents the frequency, and N represents the number of paths; the transmission signal is divided into multiple frequency bands for simultaneous transmission, and each frequency band is set to f k The transmission signal is s k (t), and the overall transmission signal is expressed as: s(t)=∑k∈[1,K],s k (t)·cos(2πf k t), Where K represents the number of carriers, f k Indicates the frequency of the kth carrier; combined with the above content, a multi-carrier transmission model is constructed, and the transmission signal of each frequency band in the multi-carrier transmission model is affected by the attenuation of each path, and the transmission process of each signal is expressed as: y k (t)=H(f k ,t)·s k (t)+n k (t), Among them, y k (t) represents the received signal, n k (t) represents the multipath fading effect of the signals in each frequency band; S302. Based on the multi-carrier transmission model, simulate the transmission process of the transmission data to be optimized to obtain the corresponding simulated transmission data; extract the corresponding signal quality parameters from the simulated transmission data, and form a simulated transmission data feature vector X_sim; and based on the optimization target O of the simulated transmission data and the corresponding optimized feature vector X_template_new, adjust the relevant signal parameters, calculate the deviation metric once each time the adjustment is made until the optimization target O is met, and save the last adjustment process to generate an optimization strategy for the transmission data to be optimized.

5. The single-mode optical fiber communication control method based on multi-carrier communication according to claim 4, characterized in that: The step S400 includes: S401. According to the optimization strategy of the transmission data to be optimized, the transmission data to be optimized is transmitted in real time, the real-time transmission data of the single-mode optical fiber communication link is obtained through the network monitoring system, and the signal quality score calculation process of the historical transmission data is referred to, and the real-time transmission data is analyzed in the same way, thereby obtaining the signal quality score Q1 of the real-time transmission data; S402. Compare the signal quality score Q1 of the real-time transmission data with the signal quality score Q of the corresponding transmission data to be optimized, and calculate the difference ΔQ between the two, and ΔQ=Q1-Q; if ΔQ>0, and Q1>θ, then output "the transmission quality meets expectations and no adjustment is required"; otherwise, output "the signal quality does not meet expectations and it is recommended to adjust the transmission strategy"; relevant personnel shall further process according to the output prompt information.

6. A single-mode optical fiber communication control system based on multi-carrier communication, applied to a single-mode optical fiber communication control method based on multi-carrier communication as claimed in any one of claims 1 to 5, characterized in that: The system includes: a historical data collection and signal quality assessment module, a data feature extraction and deviation analysis module, a multi-carrier transmission model construction and simulation module, a real-time transmission and quality monitoring module, and an optimization result output and adjustment prompt module; The historical data collection and signal quality assessment module is responsible for acquiring the historical transmission data of the single-mode optical fiber communication link from the network monitoring system, extracting the signal quality parameters and generating feature vectors; mapping the feature data through the deep learning model, calculating the signal quality score of each historical transmission data, and dividing the historical transmission data into template transmission data and transmission data to be optimized; The data feature extraction and deviation analysis module extracts feature vectors of the template transmission data and the transmission data to be optimized according to the classification results; calculates and analyzes the deviation metric between the feature vectors of the template data and the data to be optimized, thereby defining the optimization target; The multi-carrier transmission model construction and simulation module constructs a multi-carrier transmission model according to the template transmission data, simulates the transmission process of the data to be optimized; adjusts the signal parameters to achieve the optimization goal, and generates an optimization strategy; The real-time transmission and quality monitoring module transmits the data to be optimized in real time according to the optimization strategy, obtains the real-time transmission data of the link; evaluates the signal quality of the real-time transmission data, and calculates the corresponding signal quality score; The optimization result output and adjustment prompt module compares the quality score of the real-time transmission data with the score of the data to be optimized, and outputs corresponding prompt information according to the comparison result.

7. The single-mode optical fiber communication control system based on multi-carrier communication according to claim 6, characterized in that: The historical data collection and signal quality assessment module includes a data collection unit, a signal quality assessment unit and a classification unit; The data acquisition unit is used to obtain historical transmission data of a single-mode optical fiber communication link from a network monitoring system; the signal quality evaluation unit extracts signal quality parameters for each piece of historical transmission data and converts them into feature vectors; the feature vectors are mapped using a deep learning model to calculate a signal quality score; the classification unit summarizes the signal quality scores of all historical transmission data, compares the signal quality scores of the historical transmission data with a signal quality score threshold, and classifies the historical transmission data into template transmission data and transmission data to be optimized according to the comparison result.

8. The single-mode optical fiber communication control system based on multi-carrier communication according to claim 6, characterized in that: The data feature extraction and deviation analysis module includes a deviation metric calculation unit and an optimization target definition unit; The deviation metric calculation unit extracts the feature vectors of the template transmission data and the transmission data to be optimized respectively, and calculates the deviation metric between the feature vector of the template transmission data and the feature vector of the transmission data to be optimized; the optimization target definition unit defines the optimization target of the transmission data to be optimized based on the deviation metric.

9. The single-mode optical fiber communication control system based on multi-carrier communication according to claim 6, characterized in that: The multi-carrier transmission model building and simulation module includes a multi-path channel modeling unit, a multi-carrier signal allocation unit, a transmission process simulation unit and an optimization target adjustment unit; The multipath channel modeling unit constructs a multipath model of the channel based on template transmission data; the multi-carrier signal allocation unit divides the transmission signal into multiple frequency bands, sets the transmission signal of each frequency band, and synthesizes the multi-carrier signal; the simulation transmission process unit simulates the transmission process of the transmission data to be optimized based on the multi-carrier transmission model, extracts the signal quality parameters of the simulated transmission data, and constructs a simulated transmission data feature vector; the optimization target adjustment unit adjusts the signal parameters according to the optimization target and the optimized feature vector, and calculates the deviation metric until the deviation metric meets the optimization target, saves the final adjustment process, and generates an optimization strategy for the transmission data to be optimized.

10. The single-mode optical fiber communication control system based on multi-carrier communication according to claim 6, characterized in that: The real-time transmission and quality monitoring module includes a real-time transmission control unit and a real-time signal quality evaluation unit; The real-time transmission control unit transmits the transmission data to be optimized in real time according to the optimization strategy, and adjusts the signal parameters in the transmission process; the real-time signal quality evaluation unit obtains the real-time transmission data of the single-mode optical fiber communication link from the network monitoring system in real time, performs signal quality evaluation on the real-time transmission data, and calculates the signal quality score; The optimization result output and adjustment prompt module includes an optimization result output unit and an adjustment prompt generation unit; The optimization result output unit outputs the optimization strategy of the transmission data to be optimized for use in the actual transmission process; the adjustment prompt generation unit compares the signal quality score of the real-time transmission data with the signal quality score of the corresponding transmission data to be optimized, and outputs corresponding prompt information based on the comparison result.

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