Multi-band signal optimization control system of user 5G communication terminal

Abstract

The invention relates to the technical field of resource allocation, in particular to a multiband signal optimization control system for a user 5G communication terminal, and the system comprises a geometric structure modeling module which is based on a multiband radio frequency front end of the user 5G communication terminal, collects multiband signals, and obtains the signal intensity through an MIMO antenna. In the invention, the dynamic environment of 5G communication is optimized through an acquisition and analysis method, the adaptability of signal processing is improved by utilizing real-time analysis of geometric structure data and topological characteristics, and the system is allowed to adjust the signal strength and frequency band use according to real-time data, so that the accuracy and efficiency of signal transmission are improved, and the system is suitable for popularization and application. Potential signal offset can be foreseen and adjusted in advance by evaluating the stability and variation trend of the signal, the communication quality is ensured not to be affected, and the adaptive capacity and predictive adjustment to the dynamic environment optimize the spectrum utilization rate and reduce the signal interference, especially in the environment with dense users and complex signals.

Description

Technical Field

[0001] The present invention relates to the technical field of resource allocation, and in particular to a multi-band signal optimization control system for a user 5G communication terminal. Background Art

[0002] Resource allocation is a technology commonly used in various scientific and technological fields. Its main goal is to efficiently allocate limited resources to maximize the overall performance and efficiency of the system. This technology is often used in fields such as communication networks, computing resource management, and energy management. In communication networks, resource allocation technology focuses on how to fairly and efficiently allocate bandwidth and channels to ensure that network users get the best data transmission experience. In computing resource management, it involves the allocation of CPU, memory, and storage resources with the goal of optimizing processing speed and response time. In energy management, resource allocation attempts to optimize the use of energy such as electricity and fuel to improve energy efficiency and reduce environmental impact. The methods and tools covered by this technology include but are not limited to algorithm design, optimization theory, and artificial intelligence technology.

[0003] Among them, the multi-band signal optimization control system refers to a system that uses resource allocation technology to optimize the signal processing and transmission efficiency of multiple frequency bands. The main purpose of this system is to ensure that the signals of various frequency bands can be effectively managed in wireless communications and broadcasting, thereby improving spectrum utilization and communication quality. By dynamically adjusting and optimizing the use of each frequency band, the multi-band signal optimization control system can reduce signal interference and improve data transmission speed and reliability, especially in complex network environments and high user density scenarios. The implementation of this technology is of great significance for achieving efficient network operation and management.

[0004] Traditional resource allocation technologies often show shortcomings such as slow processing speed and poor adaptability when facing the highly variable and user-intensive 5G network environment. These technologies are usually based on static resource allocation models and lack the ability to quickly respond to real-time changes in network status, resulting in insufficient resource allocation when demand suddenly changes and inability to effectively handle sudden data transmission needs. In addition, traditional technologies lack high flexibility and dynamic adjustment capabilities in resource management, resulting in frequent resource waste or insufficient signal coverage in different communication environments, especially in scenarios with limited resources and complex requirements. These shortcomings affect communication efficiency and user experience. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings existing in the prior art and propose a multi-band signal optimization control system for a user 5G communication terminal.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: A multi-band signal optimization control system for a user 5G communication terminal includes: The geometric structure modeling module is based on the multi-band RF front end of the user's 5G communication terminal, collects multi-band signals, obtains signal strength through the MIMO antenna, records channel allocation and frequency band parameters, calculates geometric structure data, and obtains a geometric structure data table; The topology characteristic analysis module extracts topology characteristics based on the geometric structure data table using a baseband processor, evaluates continuous changes in characteristics, identifies key changes in channel resources, and generates a topology resource characteristic table; The structural difference evaluation module adopts the topological resource feature table, uses the resource allocator to compare the signal structure of the differentiated time, calculates the Gromov-Hausdorff distance, evaluates the stability and change amplitude, determines the signal offset, and generates a channel stability evaluation result; The signal optimization and control module adjusts channel allocation according to the channel stability evaluation result, enhances low-quality frequency bands, configures power control strategies, dynamically adjusts the output power of the multi-band RF front end, and obtains optimized signal quality data.

[0007] As a further solution of the present invention, the step of obtaining the geometric structure data table is specifically as follows: Collect multi-band radio frequency signals from 5G communication terminals, measure the signal strength and frequency band characteristics of the multi-bands, and obtain multi-band signal characteristics; Based on the multi-band signal characteristics, the signal receiving capability is enhanced by the MIMO antenna system, and matching analysis between the signal and the frequency band is performed to obtain matched multi-band signal data; The matched multi-band signal data is used for geometric structure analysis using the formula:

[0008] Calculate the spatial geometric intensity of each frequency band signal to obtain a geometric structure data table; in, Represents the total intensity of the geometric structure data, which is calculated by weighting the spatial geometric intensity of multiple frequency band signals. Representative The signal amplitude of a frequency band measures the signal strength of the frequency band. Representative The frequency of each frequency band is used to adjust the weight of the signal amplitude of the corresponding frequency band, and the weight adopts the inverse square of the frequency.

[0009] As a further solution of the present invention, the step of obtaining the topology resource feature table is specifically as follows: Analyze the geometric structure data table, extract the spatial position and intensity characteristics of the multi-band signal using a baseband processor, and generate signal spatial characteristic data; Based on the signal spatial characteristic data, continuous changes of multi-band signals are evaluated, and changes between adjacent frequency bands are compared using a differential analysis method to obtain channel change characteristic results; The channel change feature result is applied to topology feature extraction using the formula:

[0010] Calculate the topological feature scores and generate a topological resource feature table; in, Represents the topology resource feature table, Representative The signal strength of a frequency band is expressed as the amplitude of the signal received by the frequency band. Representative The signal strength of a frequency band is also expressed as the amplitude of the signal received by the frequency band. is a regularization parameter used to add a small constant value to the signal strength calculation to avoid the situation where the denominator is zero.

[0011] As a further solution of the present invention, the step of obtaining the channel stability evaluation result is specifically: Analyzing the signal structure recorded in the topology resource feature table by a resource allocator, comparing the signal structures at different time points, identifying structural differences, and generating a time point signal structure comparison result; Using the signal structure comparison results of the time points, applying the Gromov-Hausdorff distance calculation method, evaluating the difference between the signal structures, calculating the distance value between each pair of time points, and obtaining the distance data between the time points; From the distance data between the time points, the stability and variation of the signal are evaluated using the formula:

[0012] Perform variance analysis to generate channel stability assessment results; in, Indicates the channel stability assessment result. The smaller the value, the more stable the signal. Variance analysis reflects the discrete degree of signal change. represents the Gromov-Hausdorff distance between consecutive time points, which is a metric used to measure the difference between two sets. is the distance value The arithmetic mean of is used to represent the average degree of signal structure difference at all time points. is the total number of measurement time points used to calculate the number of distance samples.

[0013] As a further solution of the present invention, the step of obtaining the optimized signal quality data is specifically: Analyze the channel stability assessment results, determine the low-quality frequency bands that need to be enhanced, analyze the assessment results, identify the frequency bands below the predetermined quality threshold, and generate a list of frequency bands that need to be optimized; Applying a predefined power control strategy to adjust the power of the frequency bands in the list of frequency bands to be optimized, simulating and predicting the performance of multiple frequency bands under differentiated power input, determining the optimal power adjustment value, and obtaining the adjusted power configuration; Based on the adjusted power configuration, dynamic power control is implemented to monitor the real-time power output and adjust the power output of the RF front end according to the actual signal quality feedback to ensure that each frequency band operates according to the current power configuration, using the formula:

[0014] generating optimized signal quality data; in, represents the adjusted output power, is the initial power, which indicates the received power of the band before any adjustment is made. It is the power change amount obtained based on the channel quality adjustment, which is used to indicate the amount of power that needs to be increased or decreased for the target frequency band. It is a dynamic adjustment coefficient, based on real-time signal quality data.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, the dynamic environment of 5G communication is optimized through the collection and analysis method, and the real-time analysis of geometric structure data and topological features is used to improve the adaptability of signal processing, allowing the system to adjust the signal strength and frequency band usage according to real-time data, thereby improving the accuracy and efficiency of signal transmission. By evaluating the stability and change trend of the signal, potential signal deviation can be foreseen and adjusted in advance to ensure that the communication quality is not affected. This adaptability and predictive adjustment to the dynamic environment optimizes spectrum utilization and reduces signal interference, especially in environments with dense users and complex signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is a system flow chart of the present invention; Figure 2 A flowchart of the steps for obtaining the geometric structure data table of the present invention; Figure 3 A flowchart of the steps for obtaining the topology resource feature table of the present invention; Figure 4 A flow chart of the steps for obtaining the channel stability evaluation result of the present invention; Figure 5 This is a flow chart of the steps for obtaining signal quality data after optimization of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0018] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. Example

[0019] See also Figure 1 , a multi-band signal optimization control system for a user 5G communication terminal includes: The geometric structure modeling module is based on the multi-band RF front end of the user's 5G communication terminal, collects multi-band signals, obtains signal strength through the MIMO antenna, records channel allocation and frequency band parameters, calculates geometric structure data, and obtains a geometric structure data table; The topology characteristic analysis module uses the baseband processor to extract topology characteristics based on the geometric structure data table, evaluate the continuous changes of characteristics, identify the key changes of channel resources, and generate a topology resource characteristic table; The structural difference assessment module uses the topological resource feature table and the resource allocator to compare the signal structure of the differentiated time, calculate the Gromov-Hausdorff distance, evaluate the stability and change amplitude, determine the signal offset, and generate the channel stability assessment result; The signal optimization and control module adjusts channel allocation according to the channel stability evaluation results, enhances low-quality frequency bands, configures power control strategies, dynamically adjusts the output power of the multi-band RF front end, and obtains optimized signal quality data.

[0020] The geometry data table specifically includes signal strength, frequency band parameters, and channel allocation; the topology resource feature table specifically includes topology features, continuous feature changes, and key changes in channel resources; the channel stability evaluation results specifically refer to the Gromov-Hausdorff distance, stability evaluation, change amplitude, and signal offset; the optimized signal quality data specifically includes adjusted channel allocation, enhanced low-quality frequency bands, and power control strategies.

[0021] See also Figure 2 , the specific steps for obtaining the geometric structure data table are: Collect multi-band radio frequency signals from 5G communication terminals, measure the signal strength and frequency band characteristics of the multi-bands, and obtain multi-band signal characteristics; Collect multi-band RF signals from user 5G communication terminals to ensure the diversity of signal sources and the ability to cover the entire frequency band. Record multi-band signals, including signal strength and frequency band characteristics. Capture signals through measuring equipment to ensure the reliability and accuracy of the obtained data. This process involves using a spectrum analyzer to analyze and record the characteristics of multiple frequency bands. At the same time, the recorded data provides a basis for subsequent signal processing and analysis. Through this series of operations, a multi-band signal characteristic data set is obtained. This data set provides the necessary input for the next step of signal processing and optimization.

[0022] Based on the characteristics of multi-band signals, the MIMO antenna system is used to enhance the signal receiving capability, and the matching analysis between the signal and the frequency band is performed to obtain the matched multi-band signal data; According to the characteristics of the acquired multi-band signals, the MIMO antenna system is used to enhance the signal reception capability. This technology can effectively improve the signal reception quality and stability, and refine the matching analysis of the signal and the frequency band. This analysis process includes calculating and evaluating the matching degree of the multi-band signals, and using signal processing algorithms to optimize the signal matching process to ensure that the signals of each frequency band can be effectively identified and utilized. Through this step, an optimized multi-band signal data set is generated, which not only improves the utilization efficiency of the signal, but also provides a guarantee for data transmission and communication quality.

[0023] The matched multi-band signal data is used for geometric structure analysis using the formula:

[0024] Calculate the spatial geometric intensity of each frequency band signal to obtain a geometric structure data table; in, Represents the total intensity of the geometric structure data, which is calculated by weighting the spatial geometric intensity of multiple frequency band signals. Representative The signal amplitude of a frequency band measures the signal strength of the frequency band. Representative The frequency of each frequency band is used to adjust the weight of the signal amplitude of the corresponding frequency band, and the weight adopts the inverse square of the frequency.

[0025] formula:

[0026] The benefit of the formula is that, by weighting the reciprocal square of the frequency, the importance of the low-frequency signal in the total signal is emphasized, so that the signal processing obtains better sensitivity and accuracy in the low-frequency region, which helps to improve the overall quality and availability of the signal.

[0027] Detailed explanation of the formula and the process of formula calculation: There are three frequency bands of signals, and the signal amplitudes are , , , the corresponding frequency is MHz, MHz, MHz.

[0028] Substituting the values ​​into the formula, the calculation process is as follows:

[0029] The results show that by weighting the signal amplitude and frequency, an overall signal strength score is obtained, which helps to analyze the contribution of multiple frequency bands in the entire spectrum and optimize the signal processing strategy.

[0030] See also Figure 3 , the specific steps for obtaining the topology resource feature table are: Analyze the geometric structure data table, use the baseband processor to extract the spatial position and intensity characteristics of the multi-band signal, and generate signal spatial characteristic data; The baseband processor performs preliminary processing on the data collected from the 5G communication terminal. By calculating and comparing the signal characteristics of multiple frequency bands, including the signal strength and spatial position, these signal data are analyzed and processed to generate signal spatial characteristic data. This process involves signal analysis and characteristic evaluation of multiple frequency bands to ensure the accuracy and availability of the data. For the processing of each frequency band, the baseband processor will perform independent signal strength and frequency band characteristic measurements. These measurements are based on the real-time signal reception quality and refer to environmental noise and signal interference. The obtained signal spatial characteristic data is the basis for subsequent steps and provides the necessary input data for the next step of signal characteristic analysis and topology analysis.

[0031] Based on the signal spatial characteristic data, the continuous changes of multi-band signals are evaluated, and the changes between adjacent frequency bands are compared using the differential analysis method to obtain the channel change characteristic results; After obtaining preliminary signal spatial characteristic data, the continuous changes of multi-band signals were evaluated through a refined analysis method, and the signal changes between adjacent bands were compared. This process used the differential analysis method, which can effectively identify and analyze the minimum changes between frequency bands, thereby ensuring the accuracy of channel resource change analysis. This analysis is critical for frequency band resource management and signal quality control. It provides a channel change characteristic result, which refers to multiple factors, including frequency band allocation strategy, signal quality changes and the influence of environmental factors, in order to better manage and optimize frequency band resources.

[0032] The channel change feature results are applied to topology feature extraction using the formula:

[0033] Calculate the topological feature scores and generate a topological resource feature table; in, Represents the topology resource feature table, Representative The signal strength of a frequency band is expressed as the amplitude of the signal received by the frequency band. Representative The signal strength of a frequency band is also expressed as the amplitude of the signal received by the frequency band. is a regularization parameter used to add a small constant value to the signal strength calculation to avoid the situation where the denominator is zero.

[0034] formula:

[0035] The formula is useful because it is calculated by adding the regularization parameter to the average of the sum of squares This method can effectively balance the influence of signal strength when calculating the topological feature scores of adjacent frequency bands, thereby enhancing the stability and reliability of the results.

[0036] Detailed explanation of the formula and the process of formula calculation and derivation: Setting adjacent frequency bands and The signal strengths are and , and the regularization parameter ; First calculate the average of the sum of squares: ; Then add : ; Finally, calculate the topological feature score: ; The results show that for a given signal strength, the calculated topological feature score is 3.766, which indicates strong signal continuity between adjacent frequency bands. The score is helpful for optimizing frequency band allocation and signal processing strategies.

[0037] See also Figure 4 , the specific steps for obtaining the channel stability evaluation result are: The resource allocator analyzes the signal structure recorded in the topology resource feature table, compares the signal structures at different time points, identifies the structural differences, and generates a comparison result of the signal structures at different time points; The signal structure recorded in the topology resource feature table is analyzed by the resource allocator. This process relies on the recognition ability of the resource allocator to detect and analyze the signal data at multiple time points in the table. By comparing the data at different time points, the resource allocator can identify structural changes and thus locate changes in the signal structure in the time series. The configuration and settings of the resource allocator are adjusted according to the real-time data fluidity and signal complexity to ensure the accuracy and real-time performance of data processing. This process involves signal capture, comparison, and data preprocessing. The obtained time point signal structure comparison results are a direct response to the signal structure changes under continuous monitoring by the resource allocator.

[0038] Using the comparison results of signal structures at different time points, the Gromov-Hausdorff distance calculation method was applied to evaluate the differences between signal structures, and the distance value between each pair of time points was calculated to obtain the distance data between time points. Based on the comparison results of signal structures at different time points, the Gromov-Hausdorff distance calculation method was used to evaluate the differences between signal structures. The calculation was performed by measuring the maximum value of the shortest mapping distance between differentiated structures. It is suitable for data sets with complex geometric shapes or distributions. The Gromov-Hausdorff distance calculation here not only depends on the algorithm, but also requires accurate adjustment and preprocessing of the data before and after comparison to ensure that each calculation can reflect the real structural changes. The processing and analysis of these data depends on high-performance computing systems and accurate calculation of the differences between data points to obtain the distance value between each pair of time points, ensuring the scientificity and practicality of the analysis results.

[0039] From the distance data between time points, the stability and change amplitude of the signal are evaluated using the formula:

[0040] Perform variance analysis to generate channel stability assessment results; in, Indicates the channel stability assessment result. The smaller the value, the more stable the signal. Variance analysis reflects the discrete degree of signal change. represents the Gromov-Hausdorff distance between consecutive time points, which is a metric used to measure the difference between two sets. is the distance value The arithmetic mean of is used to represent the average degree of signal structure difference at all time points. is the total number of measurement time points used to calculate the number of distance samples.

[0041] formula:

[0042] The benefit of the formula is that it provides an intuitive method to measure signal stability and variation by quantifying the differences in signal structure between time points. It can reflect the changing trend and stability of the signal at differentiated time points and is suitable for signal monitoring and analysis in dynamic environments.

[0043] Detailed explanation of the formula and the process of formula calculation and derivation: Set the signal data at n time points in a certain time period, and the Gromov-Hausdorff distance at each time point It is calculated that the average distance is .in is the sample size, is the distance data between time points obtained from step 2. By substituting numbers: , , , , , , the average distance The calculation in the formula is as follows:

[0044] The results show that the calculated channel stability assessment value is 0.113, which means that the signal variation and stability are relatively low during the captured period, indicating that the signal has good stability at these time points.

[0045] See also Figure 5 , the steps for obtaining the optimized signal quality data are as follows: Analyze the channel stability assessment results, determine the low-quality frequency bands that need to be enhanced, analyze the assessment results, identify the frequency bands below the predetermined quality threshold, and generate a list of frequency bands that need to be optimized; Based on the analysis of the channel stability assessment results, low-quality frequency bands that need to be enhanced are identified. This identification process involves quantitative evaluation of multiple parameters of the existing channels, including measurement and analysis of indicators such as signal loss, interference level, and transmission efficiency. Combining data and prediction models, the reasons for insufficient frequency band performance are identified, thereby determining a list of target frequency bands. This process ensures the pertinence and efficiency of the power adjustment strategy and obtains a list of frequency bands that need to be optimized.

[0046] Apply the predefined power control strategy to adjust the power of the frequency bands in the frequency band list to be optimized, simulate and predict the performance of multiple frequency bands under differentiated power input, determine the optimal power adjustment value, and obtain the adjusted power configuration; After calculating the power requirements of multiple frequency bands in the list of frequency bands to be optimized, a dynamic power adjustment strategy was applied. The strategy dynamically adjusted the power output based on real-time feedback of signal quality data. The optimal power adjustment amount required for each frequency band was determined by comparing simulation prediction with actual measurement data. This process involves data processing technology, including signal quality analysis, power output simulation, and real-time optimization of adjustment parameters. The system power configuration was adjusted in combination with channel characteristics to obtain the adjusted power setting.

[0047] Based on the adjusted power configuration, dynamic power control is implemented to monitor the real-time power output and adjust the power output of the RF front end according to the actual signal quality feedback to ensure that each frequency band operates according to the current power configuration, using the formula:

[0048] generating optimized signal quality data; in, represents the adjusted output power, is the initial power, which indicates the received power of the band before any adjustment is made. It is the power change amount obtained based on the channel quality adjustment, which is used to indicate the amount of power that needs to be increased or decreased for the target frequency band. It is a dynamic adjustment coefficient, based on real-time signal quality data.

[0049] formula:

[0050] The formula is useful because it dynamically adjusts the coefficients , adjusts power output based on real-time channel quality data to match environmental changes and maintain signal quality, which improves the adaptability of signal processing and the overall efficiency of the system.

[0051] Detailed explanation of the formula and the process of formula calculation and derivation: Setting the initial power dBm, planned increase dBm, dynamic adjustment coefficient Based on the current channel quality, it is set to 0.8; the calculation process is: dBm.

[0052] The results show that by adaptively adjusting the power output, the power is increased from the original 50dBm to 54dBm. This adjustment helps improve the signal transmission quality of the target frequency band and enables the system to better cope with environmental changes.

[0053] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A multi-band signal optimization control system for a user 5G communication terminal, characterized in that: The system comprises: The geometric structure modeling module is based on the multi-band RF front end of the user's 5G communication terminal, collects multi-band signals, obtains signal strength through the MIMO antenna, records channel allocation and frequency band parameters, calculates geometric structure data, and obtains a geometric structure data table; The topology characteristic analysis module extracts topology characteristics based on the geometric structure data table using a baseband processor, evaluates continuous changes in characteristics, identifies key changes in channel resources, and generates a topology resource characteristic table; The structural difference evaluation module adopts the topological resource feature table, uses the resource allocator to compare the signal structure of the differentiated time, calculates the Gromov-Hausdorff distance, evaluates the stability and change amplitude, determines the signal offset, and generates a channel stability evaluation result; The signal optimization and control module adjusts channel allocation according to the channel stability evaluation result, enhances low-quality frequency bands, configures power control strategies, dynamically adjusts the output power of the multi-band RF front end, and obtains optimized signal quality data.

2. The multi-band signal optimization control system for a user 5G communication terminal according to claim 1, characterized in that: The steps for obtaining the geometric structure data table are specifically as follows: Collect multi-band radio frequency signals from 5G communication terminals, measure the signal strength and frequency band characteristics of the multi-bands, and obtain multi-band signal characteristics; Based on the multi-band signal characteristics, the signal receiving capability is enhanced by the MIMO antenna system, and matching analysis between the signal and the frequency band is performed to obtain matched multi-band signal data; The matched multi-band signal data is used for geometric structure analysis using the formula: ； Calculate the spatial geometric intensity of each frequency band signal to obtain a geometric structure data table; in, Represents the total intensity of the geometric structure data, which is calculated by weighting the spatial geometric intensity of multiple frequency band signals. Representative The signal amplitude of a frequency band measures the signal strength of the frequency band. Representative The frequency of each frequency band is used to adjust the weight of the signal amplitude of the corresponding frequency band, and the weight adopts the inverse square of the frequency.

3. The multi-band signal optimization control system of the user 5G communication terminal according to claim 2 is characterized in that: The steps of obtaining the topology resource feature table are specifically as follows: Analyze the geometric structure data table, extract the spatial position and intensity characteristics of the multi-band signal using a baseband processor, and generate signal spatial characteristic data; Based on the signal spatial characteristic data, continuous changes of multi-band signals are evaluated, and changes between adjacent frequency bands are compared using a differential analysis method to obtain channel change characteristic results; The channel change feature result is applied to topology feature extraction using the formula: ； Calculate the topological feature scores and generate a topological resource feature table; in, Represents the topology resource feature table, Representative The signal strength of a frequency band is expressed as the amplitude of the signal received by the frequency band. Representative The signal strength of a frequency band is also expressed as the amplitude of the signal received by the frequency band. is a regularization parameter used to add a small constant value to the signal strength calculation to avoid the situation where the denominator is zero.

4. The multi-band signal optimization control system for a user 5G communication terminal according to claim 3, characterized in that: The steps for obtaining the channel stability evaluation result are specifically as follows: Analyzing the signal structure recorded in the topology resource feature table by a resource allocator, comparing the signal structures at different time points, identifying structural differences, and generating a time point signal structure comparison result; Using the signal structure comparison results of the time points, applying the Gromov-Hausdorff distance calculation method, evaluating the difference between the signal structures, calculating the distance value between each pair of time points, and obtaining the distance data between the time points; From the distance data between the time points, the stability and variation of the signal are evaluated using the formula: ； Perform variance analysis to generate channel stability assessment results; in, Indicates the channel stability assessment result. The smaller the value, the more stable the signal. Variance analysis reflects the discrete degree of signal change. represents the Gromov-Hausdorff distance between consecutive time points, which is a metric used to measure the difference between two sets. is the distance value The arithmetic mean of is used to represent the average degree of signal structure difference at all time points. is the total number of measurement time points used to calculate the number of distance samples.

5. The multi-band signal optimization control system for a user 5G communication terminal according to claim 4, characterized in that: The steps for obtaining the optimized signal quality data are specifically as follows: Analyze the channel stability assessment results, determine the low-quality frequency bands that need to be enhanced, analyze the assessment results, identify the frequency bands below the predetermined quality threshold, and generate a list of frequency bands that need to be optimized; Applying a predefined power control strategy to adjust the power of the frequency bands in the list of frequency bands to be optimized, simulating and predicting the performance of multiple frequency bands under differentiated power input, determining the optimal power adjustment value, and obtaining the adjusted power configuration; Based on the adjusted power configuration, dynamic power control is implemented to monitor the real-time power output and adjust the power output of the RF front end according to the actual signal quality feedback to ensure that each frequency band operates according to the current power configuration, using the formula: ； generating optimized signal quality data; in, represents the adjusted output power, is the initial power, which indicates the received power of the band before any adjustment is made. It is the power change amount obtained based on the channel quality adjustment, which is used to indicate the amount of power that needs to be increased or decreased for the target frequency band. It is a dynamic adjustment coefficient, based on real-time signal quality data.

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