Multi-band compatible 5G isolator array and control method thereof

Abstract

The invention relates to the technical field of communication equipment data processing, provides a multi-band compatible 5G isolator array and a control method thereof, and effectively solves the problem that dynamic allocation of spectrum resources cannot be adaptively adjusted in the prior art. By integrating a data acquisition module, a signal processing module, a data processing module, a data analysis module, a control parameter generation module and the like, real-time monitoring, detection, shunt processing and stability evaluation of signal data of each frequency band are realized. And for unqualified or unstable signal data, standard operating environment configuration information is obtained by utilizing clustering analysis and an isolator operating environment knowledge base, and repairing is carried out through a frequency band signal data repairing model, so that control parameters are finally generated, and the signal transmission quality is optimized. According to the invention, the utilization efficiency of spectrum resources and the stability of signal transmission are obviously improved.

Description

Technical Field

[0001] The present invention relates to the technical field of communication device data processing, and particularly to a multi-band compatible 5G isolator array and its control method. Background Art

[0002] The 5G isolator array is a component in the 5G communication system, mainly used to realize the duplex or unidirectional transmission function of the base station microwave signal. The control method of the multi-band compatible 5G isolator array depends on digital signal processing technology and intelligent algorithms. By integrating high-precision sensors and controllers, the system can monitor the status and interference of signals in each frequency band in real time, and automatically adjust the working parameters of the isolator array to optimize the signal transmission quality. For example, by using machine learning algorithms to learn and analyze a large amount of historical data, the system can predict and adapt to the dynamic changes between different frequency bands, and intelligently adjust the filtering characteristics, power distribution and phase adjustment of the isolator array.

[0003] In the actual application process, the control method of the multi-band compatible 5G isolator array has the following technical pain points. The 5G network adopts multiple frequency bands and multiple modes, and the signals between different frequency bands will generate complex cross-interference. The existing control methods of the multi-band compatible 5G isolator array cannot adaptively adjust the dynamic allocation of spectrum resources. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a multi-band compatible 5G isolator array and its control method, which solves the problem that the existing control method of the multi-band compatible 5G isolator array cannot adaptively adjust the dynamic allocation of spectrum resources, resulting in the inability to obtain the real-time control parameters of the isolator and the low accuracy of the dynamic allocation of spectrum resources.

[0005] To solve the above technical problems, the specific technical solutions of the present invention are as follows: In a first aspect, the present invention provides a multi-band compatible 5G isolator array, including: A data acquisition module, configured to receive the frequency information of the receivable frequency bands, receive microwave signals according to the frequency information of the receivable frequency bands to obtain the microwave signals to be converted, convert the microwave signals from analog signals into electrical signals to obtain the signal data of each frequency band after conversion, and establish frequency band frequency tags for the signal data of each frequency band after conversion according to the frequency information of each frequency band corresponding to the signal data of each frequency band after conversion; A signal processing module, configured to substitute the signal data of each frequency band after conversion into a preset signal detection model one by one to obtain the signal data detection results of each frequency band. The signal data detection results of each frequency band include the signal data of the qualified frequency bands and the unqualified signal data, and substitute the signal data of the qualified frequency bands into a preset signal splitting model to obtain the detection qualified data splitting result; A data processing module, configured to transmit the signal data of the qualified frequency band to the corresponding signal splitter for data processing according to the result of the detection qualified data splitting, receive the data processing information fed back by each signal splitter, substitute the data processing information fed back by each signal splitter into a preset frequency band signal detection model, obtain the signal stability detection result of each signal splitter, where the signal stability detection result of each signal splitter includes that the splitter signal is stable and the splitter signal is unstable, mark the signal data corresponding to the stable splitter signal as successful signal frequency band allocation, and mark the signal data with unstable splitter signal as unsuccessful signal frequency band allocation; A data analysis module, configured to retrieve the signal data with unstable splitter signal and the unqualified signal data, process the signal data with unstable splitter signal and the unqualified signal data respectively, and obtain the standard operating environment configuration information corresponding to the unqualified signal data; A control parameter generation module, configured to substitute the standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data into a preset frequency band signal data repair model, and perform data processing on the data output by the preset frequency band signal data repair model to generate control parameters for the operation of the 5G isolator array.

[0006] Further, the multi-band compatible 5G isolator array of the present invention is characterized in that the data processing module is further configured to: In the data processing module, the specific steps for constructing the frequency band signal stability detection model are as follows: obtain historical frequency band signal data, where the historical frequency band signal data includes signal transmission data in different frequency bands, different times, and different environments, preprocess the historical frequency band signal data to obtain the preprocessed historical frequency band signal data, and use the random forest algorithm to train the historical frequency band signal data to obtain a trained frequency band signal stability detection model, and the frequency band signal stability detection model is used to monitor and evaluate the frequency band signal stability of each signal splitter in real time.

[0007] Further, the multi-band compatible 5G isolator array of the present invention is characterized in that the data analysis module is further configured to: Retrieve the signal data with unstable splitter signal and the unqualified signal data, perform clustering analysis on the signal data with unstable splitter signal and the unqualified signal data respectively to obtain the clustering analysis result of the signal data with unstable splitter signal and the clustering analysis result of the unqualified signal data, substitute the clustering analysis result of the signal data with unstable splitter signal into a pre-constructed isolator operating environment knowledge base to obtain the standard operating environment configuration information corresponding to the signal data with unstable splitter signal, and substitute the clustering analysis result of the unqualified signal data into a pre-constructed isolator operating environment knowledge base to obtain the standard operating environment configuration information corresponding to the unqualified signal data; In the data analysis module, the specific steps for constructing the isolator operating environment knowledge base are as follows: Obtain various signal data and their corresponding operating environment configuration information. The operating environment configuration information includes frequency band, power, interference situation information, device model, and geographical location. Use data mining to perform data mining on various signal data and their corresponding operating environment configuration information, extract the association information between the signal data and the operating environment, and construct an isolator operating environment knowledge base including various signal data and their optimal operating environment configuration information. The isolator operating environment knowledge base can also be used to adapt to the changing signal environment and device status through continuous learning and optimization.

[0008] Further, the multi-band compatible 5G isolator array of the present invention is characterized in that the control parameter generation module is further configured to: For substituting the standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data into a preset frequency band signal data repair model to output the first repaired frequency band data, loading the standard operating environment configuration information corresponding to the unqualified signal data into the isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the unqualified signal data to obtain the first to-be-executed configuration. When performing the frequency band allocation for the first repaired frequency band data, the isolator then starts to load the first to-be-executed configuration. After the repaired frequency band data completes the frequency band allocation and data transmission, the isolator then returns to the default configuration information. Substitute the standard operating environment configuration information corresponding to the signal data with unstable branch signals and the signal data with unstable branch signals into a preset frequency band signal data repair model to output the second repaired frequency band data, load the standard operating environment configuration information corresponding to the signal data with unstable branch signals into the isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the signal data with unstable branch signals to obtain the second to-be-executed configuration. When performing the frequency band allocation for the second repaired frequency band data, the isolator then starts to load the second to-be-executed configuration. After the repaired frequency band data completes the frequency band allocation and data transmission, the isolator then returns to the default configuration information.

[0009] In a second aspect, the present invention provides a multi-band compatible 5G isolator array control method, which is applied to the multi-band compatible 5G isolator array and includes: Step S101, receive the receivable frequency band frequency information, receive the microwave signal according to the receivable frequency band frequency information to obtain the to-be-converted microwave signal, convert the microwave signal from an analog signal into an electrical signal to obtain the signal data of each frequency band after conversion, and establish a frequency band frequency label for the signal data of each frequency band after conversion according to the frequency band frequency information corresponding to the signal data of each frequency band after conversion. Step S102: Substitute the signal data of each converted frequency band into a preset signal detection model to obtain the detection results of the signal data of each frequency band. The detection results of the signal data of each frequency band include the signal data of qualified frequency bands and unqualified signal data. Substitute the signal data of the qualified frequency bands into the preset signal splitting model to obtain the detection qualified data splitting result; Step S103: Transmit the signal data of the qualified frequency bands to the corresponding signal split for data processing according to the detection qualified data splitting result, and receive the data processing information fed back by each signal split. Substitute the data processing information fed back by each signal split into the preset frequency band signal detection model to obtain the signal stability detection results of each signal split. The signal stability detection results of each signal split include split signal stability and split signal instability. Mark the signal data corresponding to split signal stability as successful signal frequency band allocation, and mark the signal data with split signal instability as unsuccessful signal frequency band allocation; Step S104: Used to retrieve the signal data with split signal instability and unqualified signal data, and process the signal data with split signal instability and unqualified signal data respectively to obtain the standard operating environment configuration information corresponding to the unqualified signal data; Step S105: Used to substitute the standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data into the preset frequency band signal data repair model, and perform data processing on the data output by the preset frequency band signal data repair model to generate the control parameters for the operation of the 5G isolator array.

[0010] Further, in the multi-band compatible 5G isolator array control method of the present invention, the step S103 includes: The specific steps for constructing the frequency band signal stability detection model are as follows: Obtain historical frequency band signal data, which includes signal transmission data in different frequency bands, different times, and different environments. Preprocess the historical frequency band signal data to obtain the preprocessed historical frequency band signal data. Use the random forest algorithm to train the historical frequency band signal data to obtain a trained frequency band signal stability detection model. The frequency band signal stability detection model is used to monitor and evaluate the frequency band signal stability of each signal split in real time.

[0011] Further, in the multi-band compatible 5G isolator array control method of the present invention, the step S104 includes: Retrieve the signal data with unstable branch signals and the unqualified signal data, perform clustering analysis on the signal data with unstable branch signals and the unqualified signal data respectively to obtain the clustering analysis results of the signal data with unstable branch signals and the clustering analysis results of the unqualified signal data. Substitute the clustering analysis results of the signal data with unstable branch signals into the pre-constructed isolator operating environment knowledge base to obtain the standard operating environment configuration information corresponding to the signal data with unstable branch signals. Substitute the clustering analysis results of the unqualified signal data into the pre-constructed isolator operating environment knowledge base to obtain the standard operating environment configuration information corresponding to the unqualified signal data; The specific steps for constructing the isolator operating environment knowledge base are as follows. Obtain various signal data and their corresponding operating environment configuration information. The operating environment configuration information includes frequency band, power, interference situation information, device model, and geographical location. Use data mining to perform data mining on various signal data and their corresponding operating environment configuration information, extract the association information between the signal data and the operating environment, and construct an isolator operating environment knowledge base including various signal data and their optimal operating environment configuration information. The isolator operating environment knowledge base can also be used to adapt to the changing signal environment and device status through continuous learning and optimization.

[0012] Furthermore, for the multi-band compatible 5G isolator array control method of the present invention, the step S105 includes: Substitute the standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data into a preset frequency band signal data repair model to output the first repaired frequency band data. Load the standard operating environment configuration information corresponding to the unqualified signal data into the isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the unqualified signal data to obtain the first configuration to be executed. When performing frequency band allocation for the first repaired frequency band data, the isolator starts to load the first configuration to be executed. After the repaired frequency band data completes frequency band allocation and data transmission, the isolator resumes to the default configuration information. Substitute the standard operating environment configuration information corresponding to the signal data with unstable branch signals and the signal data with unstable branch signals into a preset frequency band signal data repair model to output the second repaired frequency band data. Load the standard operating environment configuration information corresponding to the signal data with unstable branch signals into the isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the signal data with unstable branch signals to obtain the second configuration to be executed. When performing frequency band allocation for the second repaired frequency band data, the isolator starts to load the second configuration to be executed. After the repaired frequency band data completes frequency band allocation and data transmission, the isolator resumes to the default configuration information.

[0013] The beneficial effects of the present invention: Through the integrated high-precision sensors and controllers, combined with advanced digital signal processing technologies and intelligent algorithms, the present invention can monitor the status and interference of signals in each frequency band in real time. According to the monitoring results, it automatically adjusts the operating parameters of the isolator array, solving the problem in the prior art that the dynamic allocation of spectrum resources cannot be adaptively adjusted, thereby significantly improving the accuracy and efficiency of spectrum resource allocation. By using machine learning algorithms to deeply learn and analyze a large amount of historical signal data, the system can predict and adapt to the dynamic changes between different frequency bands. By intelligently adjusting the filtering characteristics, power distribution, and phase adjustment of the isolator array, the present invention effectively reduces signal interference, improves the stability and quality of signal transmission, and provides users with a smoother communication experience.

[0014] Through the collaborative work of the data acquisition module, signal processing module, data processing module, data analysis module, and control parameter generation module, the present invention realizes the real-time monitoring, evaluation, and dynamic adjustment of the multi-band compatible 5G isolator array. By constructing a frequency band signal stability detection model and an isolator operating environment knowledge base, the present invention can monitor and evaluate the frequency band signal stability of each signal branch in real time. When unqualified signals or unstable signal stability are detected, the system can timely provide the corresponding standard operating environment configuration information to help the isolator array adjust to the optimal working state, thereby reducing the system failure rate and improving the reliability and stability of the system. The isolator operating environment knowledge base can continuously adapt to the changing signal environment and device status through continuous learning and optimization.

[0015] In summary, by providing a multi-band compatible 5G isolator array and its control method, the present invention significantly improves the utilization efficiency of spectrum resources, the quality of signal transmission, and the overall performance of the system. At the same time, it enhances the real-time performance, intelligence, reliability, and adaptability of the system, providing strong support for the development and application of 5G communication systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, for those of ordinary skill in the art, other drawings can also be obtained according to the drawings without creative efforts.

[0017] Figure 1 It is a schematic flowchart of the control method for the multi-band compatible 5G isolator array provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below with reference to the drawings.

[0019] To better understand the objectives of the present invention, the present invention will be further described in detail below.

[0020] In a first aspect, the present invention provides a multi-band compatible 5G isolator array, including: A data acquisition module, configured to receive the frequency information of the receivable frequency bands, receive microwave signals according to the frequency information of the receivable frequency bands, obtain the microwave signals to be converted, convert the microwave signals from analog signals into electrical signals, obtain the signal data of each converted frequency band, and establish frequency band frequency tags for the signal data of each converted frequency band according to the frequency information of each frequency band corresponding to the signal data of each converted frequency band; The core responsibility of the data acquisition module is to receive and process input signals. The data acquisition module first receives the frequency information of the receivable frequency bands from an external device, and the frequency information of the frequency bands clearly defines the frequency bands of the microwave signals to be processed by the system. Subsequently, based on the frequency information of the frequency bands, the data acquisition module receives the microwave signals of the corresponding frequency bands, and the microwave signals of the corresponding frequency bands are initially in analog form. For the convenience of subsequent processing, the data acquisition module efficiently converts these analog microwave signals into electrical signals, and then obtains the digital signal data of each frequency band. Finally, based on the frequency information of the signal data of each frequency band, the data acquisition module establishes frequency band frequency tags for the frequency information of the signal data of each frequency band, so that the subsequent data acquisition module can accurately identify and distinguish the signals of different frequency bands.

[0021] A signal processing module, configured to substitute the signal data of each converted frequency band into a preset signal detection model one by one to obtain the signal data detection results of each frequency band. The signal data detection results of each frequency band include the signal data of qualified frequency bands and unqualified signal data, and substitute the signal data of the qualified frequency bands into a preset signal splitting model to obtain the detection qualified data splitting results; The signal processing module is responsible for the preliminary analysis and processing of the signal data in each frequency band transmitted from the data acquisition module. The signal processing module sequentially inputs the converted signal data into a preset signal detection model. The preset signal detection model is obtained through training and can accurately identify signals and distinguish qualified and unqualified signal data. Qualified signal data needs to meet preset quality standards, such as signal-to-noise ratio, bit error rate, etc.; while unqualified signal data fails to meet these standards. For qualified signals, the signal processing module further sends them into a preset signal splitting model. The preset signal splitting model intelligently determines the signal transmission path based on the frequency band and other key attributes of the signal, so as to achieve accurate splitting of the detected qualified data. The data processing module is used to transmit the signal data in the qualified frequency band to the corresponding signal splitting path for data processing according to the signal splitting result of the detected qualified data, receive the data processing information fed back by each signal splitting path, substitute the data processing information fed back by each signal splitting path into a preset frequency band signal detection model, and obtain the signal stability detection result of each signal splitting path. The signal stability detection result of each signal splitting path includes that the splitting signal is stable and the splitting signal is unstable. Mark the signal data corresponding to the stable splitting signal as successful signal frequency band allocation, and mark the signal data with unstable splitting signal as unsuccessful signal frequency band allocation; The data processing module is responsible for transmitting the qualified signal data to the corresponding signal splitting path for in-depth processing and monitoring the processing situation throughout the process. The data processing module receives the feedback information of each signal splitting path. The feedback information of the signal splitting path comprehensively reflects the processing status and quality of the signal in the splitting path. Subsequently, the data processing module inputs the feedback information of each signal splitting path into a preset frequency band signal stability detection model to evaluate the stability of each signal splitting path in real time. The preset frequency band signal stability detection model is based on historical data and advanced machine learning algorithms and can monitor and evaluate the stability of the signal splitting path. According to the evaluation result, the data processing module clearly classifies the signals into two categories: "stable splitting signal" and "unstable splitting signal", and marks the success or failure of the signal frequency band allocation accordingly.

[0022] The data analysis module is used to retrieve the signal data with unstable splitting signals and the unqualified signal data, process the signal data with unstable splitting signals and the unqualified signal data respectively, and obtain the standard operating environment configuration information corresponding to the unqualified signal data; The data analysis module focuses on processing signal data that is marked as having unsuccessful signal band allocation or unstable split signals. The data analysis module first retrieves this critical data and then uses data mining and clustering analysis techniques for in-depth analysis. Through clustering analysis, the data analysis module can reveal hidden patterns and associations in the data, providing strong support for understanding signal problems. Next, the data analysis module compares the analysis results with a pre-constructed knowledge base of isolator operating environments. The knowledge base aggregates various signal data and their corresponding optimal operating environment configuration information, such as frequency bands, power, interference conditions, device models, and geographical locations. By querying the knowledge base, the data analysis module can find the matching standard operating environment configuration information for the unqualified signal data.

[0023] The control parameter generation module is used to substitute the standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data into a preset frequency band signal data repair model, and perform data processing on the data output by the preset frequency band signal data repair model to generate control parameters for the operation of the 5G isolator array.

[0024] The control parameter generation module is the core hub of the system and is responsible for generating the operation control parameters of the 5G isolator array based on the information provided by the data analysis module. The control parameter generation module first inputs the unqualified signal data and its corresponding standard operating environment configuration information into a preset frequency band signal data repair model. The preset frequency band signal data repair model is constructed by algorithms and can predict and optimize the signal quality according to the signal data and operating environment information, and output the repaired frequency band data and control parameter suggestions. Next, the preset frequency band signal data repair model loads the control parameters (including default configuration information, the first to-be-executed configuration for unqualified signals, and the second to-be-executed configuration for unstable signal stability) into the isolator. During the frequency band allocation and data transmission process, the isolator flexibly adjusts its working state according to these control parameters to ensure the stable transmission of signals and the efficient utilization of spectrum resources. After the transmission is completed, the isolator will intelligently restore to the default configuration state, ready to receive the next adjustment at any time.

[0025] Specifically, for the multi-band compatible 5G isolator array described in the present invention, the data processing module is further used for: In the data processing module, the specific steps for constructing a frequency band signal stability detection model are as follows: Obtain historical frequency band signal data, which includes signal transmission data in different frequency bands, at different times, and in different environments. Preprocess the historical frequency band signal data to obtain the preprocessed historical frequency band signal data. Use the random forest algorithm to train the historical frequency band signal data to obtain a trained frequency band signal stability detection model. The frequency band signal stability detection model is used to monitor and evaluate the frequency band signal stability of each signal branch in real time.

[0026] Obtain historical frequency band signal data. The historical frequency band signal data covers signal transmission records in different frequency bands, different time periods, and different environmental conditions. The diverse historical frequency band signal data helps improve the generalization ability of the model, enabling it to accurately predict the stability of frequency band signals in various complex environments.

[0027] For the collected raw data, perform necessary preprocessing tasks including data cleaning, such as removing outliers and filling missing values, to improve data integrity; data formatting, such as unifying timestamp formats and standardizing numerical ranges, to eliminate data inconsistencies; and feature extraction, to extract features from the raw data that have a key impact on the stability of frequency band signals, providing an accurate and valuable dataset for model training.

[0028] When constructing a frequency band signal stability detection model, the present invention selects the random forest algorithm. This selection is based on the many advantages of the random forest algorithm, such as its ability to handle high-dimensional data, being less prone to overfitting, and having a good tolerance for outliers and noise. These characteristics make the random forest algorithm an ideal choice for predicting the stability of frequency band signals.

[0029] Use the preprocessed historical frequency band signal data to deeply train the random forest model. During the training process, the model will gradually learn how to accurately predict the output (i.e., the stability of the frequency band signal) based on the input features (such as frequency band, time, environmental parameters, etc.). By continuously adjusting model parameters, such as the number of decision trees and the maximum depth, to minimize the prediction error, an optimal model is obtained.

[0030] After the model training is completed, strict verification is required to make its performance meet the expectations. This involves using a part of the dataset that has not participated in the training to test the prediction ability of the model and calculating corresponding performance metrics, such as accuracy, recall rate, F1 score, etc. If it is found that the model performance is insufficient, further tuning work is required, such as adjusting model parameters, adding more training data, or trying other algorithms, to make the model reach the best state.

[0031] When the model passes the verification and is tuned to the best state, it can be deployed to the actual system for real-time monitoring and evaluation of the frequency band signal stability of each signal branch. By continuously collecting new data and updating the model, the model can keep up with the changes in the signal environment and device status, and always maintain a high prediction accuracy and practicality.

[0032] Specifically, the multi-band compatible 5G isolator array described in the present invention is characterized in that the data analysis module is further configured to: Retrieve the signal data with unstable branch signals and the unqualified signal data, perform clustering analysis on the signal data with unstable branch signals and the unqualified signal data respectively, obtain the clustering analysis results of the signal data with unstable branch signals and the clustering analysis results of the unqualified signal data, substitute the clustering analysis results of the signal data with unstable branch signals into the pre-constructed isolator operating environment knowledge base, obtain the standard operating environment configuration information corresponding to the signal data with unstable branch signals, and substitute the clustering analysis results of the unqualified signal data into the pre-constructed isolator operating environment knowledge base, obtain the standard operating environment configuration information corresponding to the unqualified signal data; In the data analysis module, the specific steps for constructing the isolator operating environment knowledge base are as follows. Obtain various signal data and their corresponding operating environment configuration information. The operating environment configuration information includes frequency band, power, interference situation information, device model, and geographical location. Use data mining to perform data mining on various signal data and their corresponding operating environment configuration information, extract the association information between the signal data and the operating environment, and construct an isolator operating environment knowledge base including various signal data and their optimal operating environment configuration information. The isolator operating environment knowledge base can also be used to adapt to the changing signal environment and device status through continuous learning and optimization.

[0033] The data analysis module first accurately retrieves the signal data with unstable branch signals and the unqualified signal data from the system. These data cover a variety of key parameters, such as frequency band, power, interference level, signal strength, etc., providing rich basic materials for subsequent in-depth analysis. To improve the accuracy of the analysis results, the module will perform strict preprocessing on these original data, including data cleaning (removing invalid or incorrect data), denoising (reducing random fluctuations in the data), normalization (converting the data to a unified standard range), etc., so as to ensure the integrity and consistency of the data and lay a solid foundation for subsequent analysis.

[0034] After the preprocessing is completed, the data analysis module will perform clustering analysis on these data respectively. As an unsupervised learning method, clustering analysis can intelligently group similar data points together, revealing the internal structure and potential patterns of the data.

[0035] In the present invention, clustering analysis is used to finely divide the signal data with unstable branch signals and the unqualified signal data, and classify them into different categories respectively. Each category represents a type of data with similar characteristics, which helps to more deeply understand the specific reasons and types of signal instability or unqualified, and provides targeted guidance for subsequent repair and optimization.

[0036] After the clustering analysis is completed, the data analysis module will match the clustering analysis results with the pre-constructed isolator operating environment knowledge base. The knowledge base is a database that stores a large amount of signal data and its corresponding optimal operating environment configuration information, and is carefully constructed based on data mining and machine learning technologies.

[0037] By matching the clustering analysis results with the information in the knowledge base, the data analysis module can quickly and accurately find the standard operating environment configuration information corresponding to the signal data with unstable shunt signals and the unqualified signal data. The standard operating environment configuration information covers multiple aspects such as frequency band setting, power adjustment, interference suppression measures, equipment model optimization suggestions, and geographical location optimization suggestions, providing comprehensive and specific guidance for subsequent repair and optimization work.

[0038] In the data analysis module, constructing the isolator operating environment knowledge base is a systematic and complex process, and the specific steps are as follows: widely collect various signal data and their corresponding operating environment configuration information, which comes from multiple channels such as experimental tests, actual operation data, and user feedback, to improve the comprehensiveness and diversity of the data.

[0039] Use advanced data mining technologies to deeply analyze these data and extract the association rules and patterns between the signal data and the operating environment. This includes using various algorithms such as association rule mining, decision trees, and neural networks to discover hidden knowledge and rules, providing strong support for the construction of the knowledge base.

[0040] Knowledge base construction, based on the results of data mining, carefully construct an isolator operating environment knowledge base including various signal data and their optimal operating environment configuration information. This knowledge base not only stores static configuration information but also contains strategies and rules for dynamically adjusting the configuration according to the signal state, enabling the flexibility and adaptability of the system.

[0041] As the signal environment and device status are constantly changing, the isolator operating environment knowledge base also needs to keep pace with the times. Therefore, the module will maintain the effectiveness of the knowledge base through continuous learning and optimization, including means such as regularly updating data, adjusting algorithm parameters, and introducing new analysis methods, so that the knowledge base can keep up with the pace of technological development and provide a solid guarantee for the long-term stable operation of the system.

[0042] Specifically, the multi-band compatible 5G isolator array described in the present invention is characterized in that the control parameter generation module is further used for: The standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data are substituted into a preset frequency band signal data repair model to output the first repaired frequency band data. The standard operating environment configuration information corresponding to the unqualified signal data is loaded into an isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the unqualified signal data to obtain a first to-be-executed configuration. When performing frequency band allocation for the first repaired frequency band data, the isolator starts to load the first to-be-executed configuration. After the repaired frequency band data completes frequency band allocation and data transmission, the isolator resumes to the default configuration information. The standard operating environment configuration information corresponding to the signal data with unstable split signals and the signal data with unstable split signals are substituted into a preset frequency band signal data repair model to output the second repaired frequency band data. The standard operating environment configuration information corresponding to the signal data with unstable split signals is loaded into an isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the signal data with unstable split signals to obtain a second to-be-executed configuration. When performing frequency band allocation for the second repaired frequency band data, the isolator starts to load the second to-be-executed configuration. After the repaired frequency band data completes frequency band allocation and data transmission, the isolator resumes to the default configuration information.

[0043] The control parameter generation module substitutes the unqualified signal data and its corresponding standard operating environment configuration information into a preset frequency band signal data repair model. The preset frequency band signal data repair model is constructed based on deep learning or machine learning algorithms and can accurately identify and correct errors or abnormal parts in the signal through learning a large amount of historical signal data.

[0044] After being processed by the repair model, the first repaired frequency band data is output, enabling the originally unqualified signal data to be improved and meet the transmission requirements.

[0045] Configuration information loading and storage: The control parameter generation module loads the standard operating environment configuration information corresponding to the unqualified signal data into an isolator. As a key component in signal transmission, the isolator needs to adjust its working state according to the configuration information.

[0046] After receiving the configuration information, the isolator stores it to form a first to-be-executed configuration. This step provides the optimal operating environment configuration for subsequent frequency band allocation and data transmission.

[0047] During the process of performing frequency band allocation for the first repaired frequency band data, the isolator starts to load the first to-be-executed configuration. This means that the isolator will adjust its parameters and settings according to the previously stored standard operating environment configuration information to adapt to the repaired signal data.

[0048] When the frequency band allocation and data transmission are completed, the isolator will automatically restore to the default configuration information. This step enables the isolator to be prepared for the next signal processing tasks and avoids the residue and interference of the configuration information.

[0049] For the signal data with unstable split signals, the above processing flow is also carried out: The control parameter generation module substitutes the corresponding standard operating environment configuration information and the signal data itself into the preset frequency band signal data repair model to output the second repaired frequency band data.

[0050] Subsequently, the standard operating environment configuration information corresponding to the signal data with unstable split signals is loaded into the isolator and stored as the second to-be-executed configuration.

[0051] When frequency band allocation needs to be performed on the second repaired frequency band data, the isolator will start to load the second to-be-executed configuration to ensure the stability and quality of signal transmission.

[0052] Similarly, when the frequency band allocation and data transmission are completed, the isolator will restore to the default configuration information.

[0053] Steps in the process of constructing the signal detection model: Collect historical microwave signal data covering different frequency bands, times, and environments to provide rich materials for model training. Perform preprocessing such as denoising and normalization on the collected signal data to improve data quality and lay a solid foundation for subsequent feature extraction. Extract key features from the preprocessed signal data, which can accurately reflect the quality or state of the signal. Use machine learning algorithms such as support vector machines and neural networks to train the extracted features to construct a signal detection model to accurately distinguish qualified and unqualified signals. Verify the model performance through methods such as cross-validation and optimize according to the verification results to improve the accuracy and generalization ability of the model.

[0054] Steps in the process of constructing the signal splitting model: Clearly define the functional requirements of the signal splitting model, that is, accurately allocate the signal to the corresponding signal split according to features such as the frequency band of the signal. Select a suitable algorithm according to the requirements analysis, such as a rule-based classification algorithm or a clustering algorithm, to improve the classification effect. Use historical qualified signal data to construct the signal splitting model, and generate signal splitting rules or clustering centers through algorithm processing. Conduct a comprehensive test on the model, evaluate the splitting effect, and make adjustments according to the test results to improve the splitting accuracy and efficiency.

[0055] Steps for constructing the frequency band signal stability detection model: Collect signal transmission data in different frequency bands, at different times, and in different environments as historical frequency band signal data to support model training. Perform preprocessing tasks such as cleaning and feature extraction on the historical frequency band signal data to improve data quality. Use the random forest algorithm to train the historical frequency band signal data to construct a frequency band signal stability detection model for real-time monitoring and evaluation of signal stability. Verify the model performance through methods such as cross-validation and optimize according to the verification results to improve the stability and accuracy of the model.

[0056] Steps for constructing the isolator operating environment knowledge base: Widely collect various signal data and their corresponding operating environment configuration information, including frequency band, power, interference situation, device model, geographical location, etc. Use data mining techniques to deeply mine this information and extract the correlation information between signal data and the operating environment. Construct an isolator operating environment knowledge base based on the data mining results, including various signal data and their optimal operating environment configuration information. Through continuous data update and model optimization, enable the knowledge base to adapt to the constantly changing signal environment and device status.

[0057] Steps for constructing the frequency band signal data repair model: Define the goal of the frequency band signal data repair model, that is, to repair signal data based on unqualified signal data and their corresponding standard operating environment configuration information. Select an appropriate algorithm according to the problem analysis, such as regression algorithm, generative adversarial network, etc., to achieve the repair effect. Use historical unqualified signal data and their repaired data to construct a frequency band signal data repair model to learn the mapping relationship between signal data and operating environment configuration information. Conduct comprehensive testing on the model, evaluate the repair effect, and make adjustments according to the test results to improve the repair accuracy and generalization ability of the model.

[0058] Second, the present invention provides a multi-band compatible 5G isolator array control method applied to the multi-band compatible 5G isolator array, including: Step S101, receive the receivable frequency band frequency information, receive microwave signals according to the receivable frequency band frequency information to obtain the microwave signals to be converted, convert the microwave signals from analog signals into electrical signals to obtain the signal data of each frequency band after conversion, and establish a frequency band frequency label for the signal data of each frequency band after conversion according to the frequency information of each frequency band corresponding to the signal data of each frequency band after conversion; Step S102, substitute the signal data of each frequency band after conversion into a preset signal detection model in turn to obtain the signal data detection results of each frequency band. The signal data detection results of each frequency band include the signal data of qualified frequency bands and unqualified signal data. Substitute the signal data of qualified frequency bands into a preset signal splitting model to obtain the detection qualified data splitting result; Step S103: According to the shunt result of the qualified detection data, transmit the signal data of the qualified frequency band to the corresponding signal shunt for data processing, receive the data processing information fed back by each signal shunt, substitute the data processing information fed back by each signal shunt into the preset frequency band signal detection model, obtain the signal stability detection result of each signal shunt. The signal stability detection result of each signal shunt includes that the shunt signal is stable and the shunt signal is unstable. Mark the signal data corresponding to the stable shunt signal as successful signal frequency band allocation, and mark the signal data with unstable shunt signal as unsuccessful signal frequency band allocation; Step S104: Used to retrieve the signal data with unstable shunt signal and the unqualified signal data, and process the signal data with unstable shunt signal and the unqualified signal data respectively to obtain the standard operating environment configuration information corresponding to the unqualified signal data; Step S105: Used to substitute the standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data into the preset frequency band signal data repair model, and process the data output by the preset frequency band signal data repair model to generate the control parameters for the operation of the 5G isolator array.

[0059] Specifically, for the multi-band compatible 5G isolator array control method of the present invention, the step S103 includes: The specific steps for constructing the frequency band signal stability detection model are as follows: Obtain historical frequency band signal data, which includes signal transmission data in different frequency bands, at different times, and in different environments. Preprocess the historical frequency band signal data to obtain the preprocessed historical frequency band signal data. Use the random forest algorithm to train the historical frequency band signal data to obtain a trained frequency band signal stability detection model. The frequency band signal stability detection model is used to monitor and evaluate the frequency band signal stability of each signal shunt in real time.

[0060] Specifically, for the multi-band compatible 5G isolator array control method of the present invention, the step S104 includes: Retrieve the signal data with unstable shunt signal and the unqualified signal data, perform clustering analysis on the signal data with unstable shunt signal and the unqualified signal data respectively to obtain the clustering analysis results of the signal data with unstable shunt signal and the clustering analysis results of the unqualified signal data. Substitute the clustering analysis results of the signal data with unstable shunt signal into the pre-constructed isolator operating environment knowledge base to obtain the standard operating environment configuration information corresponding to the signal data with unstable shunt signal. Substitute the clustering analysis results of the unqualified signal data into the pre-constructed isolator operating environment knowledge base to obtain the standard operating environment configuration information corresponding to the unqualified signal data; The specific steps to build the knowledge base of the isolator operating environment are as follows: Obtain various signal data and their corresponding operating environment configuration information. The operating environment configuration information includes frequency band, power, interference situation information, device model, and geographical location. Use data mining to perform data mining on various signal data and their corresponding operating environment configuration information, extract the association information between the signal data and the operating environment, and build a knowledge base of the isolator operating environment including various signal data and their optimal operating environment configuration information. The knowledge base of the isolator operating environment can also be used to adapt to the changing signal environment and device status through continuous learning and optimization.

[0061] Specifically, for the multi-band compatible 5G isolator array control method described in the present invention, the step S105 includes: Substitute the standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data into a preset frequency band signal data repair model to output the first repaired frequency band data. Load the standard operating environment configuration information corresponding to the unqualified signal data into the isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the unqualified signal data to obtain the first configuration to be executed. When performing the frequency band allocation for the first repaired frequency band data, the isolator starts to load the first configuration to be executed. After the repaired frequency band data completes the frequency band allocation and data transmission, the isolator returns to the default configuration information. Substitute the standard operating environment configuration information corresponding to the signal data with unstable branch signals and the signal data with unstable branch signals into a preset frequency band signal data repair model to output the second repaired frequency band data. Load the standard operating environment configuration information corresponding to the signal data with unstable branch signals into the isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the signal data with unstable branch signals to obtain the second configuration to be executed. When performing the frequency band allocation for the second repaired frequency band data, the isolator starts to load the second configuration to be executed. After the repaired frequency band data completes the frequency band allocation and data transmission, the isolator returns to the default configuration information.

[0062] The technical solution of the present invention effectively solves the problems that the existing control method of the multi-band compatible 5G isolator array cannot adaptively adjust the dynamic allocation of spectrum resources, resulting in the inability to obtain the real-time control parameters of the isolator and the low accuracy of the dynamic allocation of spectrum resources through a series of carefully designed modules and steps. The following is a detailed elaboration of the specific solutions: The data acquisition module receives the receivable frequency band frequency information and accurately receives microwave signals based on this information. Subsequently, the microwave signals are converted from analog signals to electrical signals to obtain the signal data of each frequency band. With the assistance of the frequency band frequency label, the system can accurately distinguish and preliminarily process signals of different frequency bands, providing a reliable data basis for subsequent processing.

[0063] The converted signal data of each frequency band are substituted into a preset signal detection model to strictly detect the qualification of the signals. Only the signals that are confirmed to be qualified after detection will be further substituted into the signal splitting model for data splitting processing. This step effectively eliminates unqualified signals and improves the utilization rate of spectrum resources.

[0064] The signal data of the qualified frequency bands are transmitted to the corresponding signal splits in this module for further data processing. At the same time, the module receives the data processing information fed back by each signal split and evaluates the stability of each signal split in real time through a preset frequency band signal stability detection model. For the signal data of unqualified signals and signals with unstable signal stability, this module conducts cluster analysis and obtains the corresponding standard operating environment configuration information from the pre-constructed isolator operating environment knowledge base. By deeply analyzing this data, the module can identify the root cause of the problem and provide targeted suggestions for subsequent repair and optimization.

[0065] The unqualified signal data and their corresponding standard operating environment configuration information are substituted into a preset frequency band signal data repair model. After being processed by the model, the repaired frequency band data are output, and corresponding control parameters are generated. These control parameters include default configuration information, the first configuration to be executed for unqualified signal data, and the second configuration to be executed for signal data with unstable signal stability. When performing frequency band allocation, the isolator will be adjusted according to these configuration information to enable the stable transmission of signals and the effective utilization of spectrum resources.

[0066] Through the collaborative work of the above modules, the technical solution of the present invention realizes the real-time monitoring, evaluation, and dynamic adjustment of the multi-band compatible 5G isolator array. This solution not only significantly improves the utilization efficiency of spectrum resources and the stability of signal transmission but also provides a strong guarantee for the reliability and performance of the 5G communication system.

Claims

1. A multi-band compatible 5G isolator array, characterized in that Including: A data acquisition module, configured to receive frequency information of a receivable frequency band, receive a microwave signal according to the frequency information of the receivable frequency band to obtain a microwave signal to be converted, convert the microwave signal from an analog signal into an electrical signal to obtain signal data of each converted frequency band, and establish a frequency band frequency label for the signal data of each converted frequency band according to the frequency information of each frequency band corresponding to the signal data of each converted frequency band; A signal processing module, configured to substitute the signal data of each converted frequency band into a preset signal detection model in turn to obtain a signal data detection result of each frequency band. The signal data detection result of each frequency band includes signal data of a qualified frequency band and unqualified signal data, and substitute the signal data of the qualified frequency band into a preset signal splitting model to obtain a detection qualified data splitting result; A data processing module, configured to transmit the signal data of the qualified frequency band to the corresponding signal splitting for data processing according to the detection qualified data splitting result, receive the data processing information fed back by each signal splitting, and substitute the data processing information fed back by each signal splitting into a preset frequency band signal detection model to obtain a signal stability detection result of each signal splitting. The signal stability detection result of each signal splitting includes that the splitting signal is stable and the splitting signal is unstable. Mark the signal data corresponding to the stable splitting signal as successful signal frequency band allocation, and mark the signal data with unstable splitting signal as unsuccessful signal frequency band allocation; A data analysis module, configured to retrieve the signal data with unstable splitting signal and unqualified signal data, and process the signal data with unstable splitting signal and unqualified signal data respectively to obtain the standard operating environment configuration information corresponding to the unqualified signal data; A control parameter generation module, configured to substitute the standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data into a preset frequency band signal data repair model, and perform data processing on the data output by the preset frequency band signal data repair model to generate control parameters for the operation of the 5G isolator array.

2. The multi-band compatible 5G isolator array according to claim 1, wherein The data processing module is further configured to: In the data processing module, the specific steps for constructing a frequency band signal stability detection model are as follows: obtain historical frequency band signal data, where the historical frequency band signal data includes signal transmission data in different frequency bands, different times, and different environments, preprocess the historical frequency band signal data to obtain preprocessed historical frequency band signal data, and use the random forest algorithm to train the historical frequency band signal data to obtain a trained frequency band signal stability detection model. The frequency band signal stability detection model is used to monitor and evaluate the frequency band signal stability of each signal splitting in real time.

3. The multi-band compatible 5G isolator array according to claim 1, characterized in that, The data analysis module is further configured to: Retrieve the signal data with unstable branch signals and the unqualified signal data, perform clustering analysis on the signal data with unstable branch signals and the unqualified signal data respectively to obtain the clustering analysis results of the signal data with unstable branch signals and the clustering analysis results of the unqualified signal data. Substitute the clustering analysis results of the signal data with unstable branch signals into the pre-constructed isolator operating environment knowledge base to obtain the standard operating environment configuration information corresponding to the signal data with unstable branch signals. Substitute the clustering analysis results of the unqualified signal data into the pre-constructed isolator operating environment knowledge base to obtain the standard operating environment configuration information corresponding to the unqualified signal data; In the data analysis module, the specific steps for constructing the isolator operating environment knowledge base are as follows: Obtain various signal data and their corresponding operating environment configuration information. The operating environment configuration information includes frequency band, power, interference situation information, device model, and geographical location. Use data mining to perform data mining on various signal data and their corresponding operating environment configuration information, extract the association information between the signal data and the operating environment, and construct an isolator operating environment knowledge base including various signal data and their optimal operating environment configuration information. The isolator operating environment knowledge base can also be used to adapt to the changing signal environment and device status through continuous learning and optimization.

4. The multi-band compatible 5G isolator array according to claim 1, characterized in that, The control parameter generation module is further used for: Substitute the standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data into a preset frequency band signal data repair model, and output the first repaired frequency band data. Load the standard operating environment configuration information corresponding to the unqualified signal data into the isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the unqualified signal data to obtain the first configuration to be executed; When performing frequency band allocation for the first repaired frequency band data, the isolator starts to load the first configuration to be executed. After the repaired frequency band data completes frequency band allocation and data transmission, the isolator resumes to the default configuration information. Substitute the standard operating environment configuration information corresponding to the signal data with unstable branch signals and the signal data with unstable branch signals into a preset frequency band signal data repair model, and output the second repaired frequency band data; Load the standard operating environment configuration information corresponding to the signal data with unstable branch signals into the isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the signal data with unstable branch signals to obtain the second configuration to be executed. When performing frequency band allocation for the second repaired frequency band data, the isolator starts to load the second configuration to be executed. After the repaired frequency band data completes frequency band allocation and data transmission, the isolator resumes to the default configuration information.

5. A multi-band compatible 5G isolator array control method, applied to the multi-band compatible 5G isolator array described in any one of claims 1 to 4, characterized in that, Including: Step S101: Receive the frequency information of the receivable frequency band, receive the microwave signal according to the receivable frequency band frequency information to obtain the microwave signal to be converted, convert the microwave signal from an analog signal into an electrical signal, obtain the signal data of each frequency band after conversion, and establish frequency band frequency tags for the signal data of each frequency band after conversion according to the frequency information of each frequency band corresponding to the signal data of each frequency band after conversion; Step S102: Substitute the signal data of each frequency band after conversion into the preset signal detection model one by one to obtain the detection results of the signal data of each frequency band. The detection results of the signal data of each frequency band include the signal data of the qualified frequency band and the unqualified signal data. Substitute the signal data of the qualified frequency band into the preset signal splitting model to obtain the detection qualified data splitting result; Step S103: Transmit the signal data of the qualified frequency band to the corresponding signal splitter for data processing according to the detection qualified data splitting result, and receive the data processing information fed back by each signal splitter. Substitute the data processing information fed back by each signal splitter into the preset frequency band signal detection model to obtain the signal stability detection result of each signal splitter. The signal stability detection result of each signal splitter includes that the split signal is stable and the split signal is unstable. Mark the signal data corresponding to the stable split signal as the successful signal frequency band allocation, and mark the signal data with unstable split signal as the unsuccessful signal frequency band allocation; Step S104: It is used to retrieve the signal data with unstable split signal and the unqualified signal data, and process the signal data with unstable split signal and the unqualified signal data respectively to obtain the standard operating environment configuration information corresponding to the unqualified signal data; Step S105: It is used to substitute the standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data into the preset frequency band signal data repair model, and perform data processing on the data output by the preset frequency band signal data repair model to generate the control parameters for the operation of the 5G isolator array.

6. The multi-band compatible 5G isolator array control method according to claim 5, wherein, The said step S103 includes: The specific steps for constructing the frequency band signal stability detection model are as follows: Obtain the historical frequency band signal data, which includes signal transmission data in different frequency bands, different times, and different environments. Preprocess the historical frequency band signal data to obtain the preprocessed historical frequency band signal data. Use the random forest algorithm to train the historical frequency band signal data to obtain the trained frequency band signal stability detection model. The frequency band signal stability detection model is used to monitor and evaluate the frequency band signal stability of each signal splitter in real time.

7. The multi-band compatible 5G isolator array control method according to claim 5, characterized in that, The said step S104 includes: Retrieve the signal data with unstable branch signals and the unqualified signal data, perform clustering analysis on the signal data with unstable branch signals and the unqualified signal data respectively to obtain the clustering analysis results of the signal data with unstable branch signals and the clustering analysis results of the unqualified signal data. Substitute the clustering analysis results of the signal data with unstable branch signals into the pre-constructed isolator operating environment knowledge base to obtain the standard operating environment configuration information corresponding to the signal data with unstable branch signals. Substitute the clustering analysis results of the unqualified signal data into the pre-constructed isolator operating environment knowledge base to obtain the standard operating environment configuration information corresponding to the unqualified signal data; The specific steps for constructing the isolator operating environment knowledge base are as follows: Obtain various signal data and their corresponding operating environment configuration information. The operating environment configuration information includes frequency band, power, interference situation information, device model, and geographical location. Use data mining to perform data mining on various signal data and their corresponding operating environment configuration information, extract the association information between the signal data and the operating environment, and construct an isolator operating environment knowledge base including various signal data and their optimal operating environment configuration information. The isolator operating environment knowledge base can also be used to adapt to the changing signal environment and device status through continuous learning and optimization.

8. The multi-band compatible 5G isolator array control method according to claim 5, characterized in that The step S105 includes: Substitute the standard operating environment configuration information corresponding to the unqualified signal data and the unqualified signal data into a preset frequency band signal data repair model to output the first repaired frequency band data. Load the standard operating environment configuration information corresponding to the unqualified signal data into the isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the unqualified signal data to obtain the first configuration to be executed; When performing frequency band allocation for the first repaired frequency band data, the isolator starts to load the first configuration to be executed. After the repaired frequency band data completes frequency band allocation and data transmission, the isolator returns to the default configuration information. Substitute the standard operating environment configuration information corresponding to the signal data with unstable branch signals and the signal data with unstable branch signals into a preset frequency band signal data repair model to output the second repaired frequency band data; Load the standard operating environment configuration information corresponding to the signal data with unstable branch signals into the isolator, and the isolator stores the loaded standard operating environment configuration information corresponding to the signal data with unstable branch signals to obtain the second configuration to be executed. When performing frequency band allocation for the second repaired frequency band data, the isolator starts to load the second configuration to be executed. After the repaired frequency band data completes frequency band allocation and data transmission, the isolator returns to the default configuration information.

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