Signal monitoring method and system for 6G key scene

Abstract

The invention discloses a signal monitoring method and system for a 6G key scene, and belongs to the technical field of electric digital data processing. The method comprises the following steps: acquiring each signal monitoring period, and collecting working environment data and 6G signal characteristic data of each signal monitoring period; performing comprehensive analysis according to the working environment data of each signal monitoring period to obtain a working environment influence degree evaluation value of each signal monitoring period; performing comprehensive analysis according to the 6G signal characteristic data of each signal monitoring period to obtain a 6G network performance anomaly index of each signal monitoring period; and according to the working environment influence degree evaluation value of each signal monitoring period and the 6G network performance abnormity index, performing comprehensive analysis to obtain a signal quality evaluation index of each signal monitoring period, and according to the signal quality evaluation index of each signal monitoring period, performing feedback adjustment on the operation parameters of the target equipment. The problem of low monitoring signal quality precision is solved.

Description

Technical Field

[0001] The present invention relates to the field of electrical digital data processing technology, and in particular to a signal monitoring method and system for 6G key scenarios. Background Art

[0002] With the rapid development of mobile communication technology, wireless communication technology continues to break through performance bottlenecks to meet the growing demand for data transmission and connection. As the next generation of communication technology, 6G is expected to achieve higher data rates, lower latency, greater connection density and wider coverage to meet the needs of future application scenarios such as the intelligent connection of all things and immersive interaction.

[0003] The research on 6G signal monitoring methods involves many aspects, including terahertz communication technology, intelligent communication environment, communication perception integration technology, artificial intelligence and machine learning, and multiple access and wireless resource management technology. With the continuous development and improvement of these technologies, 6G signal monitoring methods will become more mature and efficient.

[0004] For example, the signal monitoring method, device, chip and electronic device announced in the invention patent with announcement number: CN117789805B include: storing the input signal in a FIFO register according to the waveform change of the first source clock corresponding to the input signal; taking out the signal from the FIFO register according to the waveform change of the second source clock to obtain an output signal, the frequency of the second source clock is less than the frequency of the first source clock, and the frequency of the output signal is less than the frequency of the input signal; transmitting the output signal to an external monitoring module, the external monitoring module is used to monitor the correctness of the output signal, and the convergence frequency of the external monitoring module is less than the frequency of the input signal and greater than the frequency of the output signal.

[0005] For example, a signal monitoring circuit and implementation method disclosed in the invention patent with publication number CN114326932B include: a signal delay module, a signal data analysis module, and a signal quality analysis module, wherein the signal delay module is used to delay the periodic signal according to the rising edge and the falling edge respectively, and send the delayed signal to the signal data analysis module; the signal data analysis module is used to, after receiving signals with different delays, use the original periodic signal to sample the signal after each level of delay, calculate the number of leading zeros in the delay level and send the result to the signal quality analysis module; the signal quality analysis module is used to receive the calculated number of leading zeros and the configured duty cycle and jitter ratio, and output an interrupt alarm when the duty cycle or jitter of the periodic signal exceeds the configured range.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the prior art, existing monitoring equipment may not be able to accurately capture signal changes due to insufficient sensitivity. When the signal is interfered with or in an abnormal situation, the monitoring equipment cannot respond in time, resulting in the problem of low accuracy of the monitored signal quality. Summary of the invention

[0008] The embodiments of the present application provide a signal monitoring method and system for 6G key scenarios, thereby solving the problem that existing monitoring equipment in the prior art may be unable to accurately capture signal changes due to insufficient sensitivity, and when the signal is interfered with or in an abnormal situation, the monitoring equipment cannot respond in time, resulting in low accuracy of the monitored signal quality, thereby improving the real-time and accuracy of signal monitoring.

[0009] An embodiment of the present application provides a signal monitoring method for 6G key scenarios, comprising the following steps: obtaining each signal monitoring cycle, and collecting working environment data and 6G signal feature data of each signal monitoring cycle; obtaining a working environment impact degree assessment value of each signal monitoring cycle based on a comprehensive analysis of the working environment data of each signal monitoring cycle; obtaining a 6G network performance anomaly index of each signal monitoring cycle based on a comprehensive analysis of the 6G signal feature data of each signal monitoring cycle; obtaining a signal quality assessment index of each signal monitoring cycle based on a comprehensive analysis of the working environment impact degree assessment value and the 6G network performance anomaly index of each signal monitoring cycle, and performing feedback adjustment on the target device operating parameters based on the signal quality assessment index of each signal monitoring cycle.

[0010] Furthermore, the step of obtaining an evaluation value of the degree of working environment impact of each signal monitoring period through comprehensive analysis of the working environment data of each signal monitoring period includes: the working environment data of each signal monitoring period includes noise power and electromagnetic intensity; obtaining the critical noise power and critical electromagnetic intensity from the 6G signal database; and obtaining an evaluation value of the degree of working environment impact of each signal monitoring period through comprehensive analysis.

[0011] Furthermore, the step of obtaining the 6G network performance abnormality index of each signal monitoring period by comprehensive analysis based on the 6G signal characteristic data of each signal monitoring period includes: the 6G signal characteristic data of each signal monitoring period includes signal strength, data transmission rate and bit error rate; obtaining the critical signal strength, critical data transmission rate and critical bit error rate from the 6G signal database; and obtaining the 6G network performance abnormality index of each signal monitoring period by comprehensive analysis.

[0012] Furthermore, the method for obtaining the signal quality evaluation index of each signal monitoring period is as follows:

[0013]

[0014] In the formula, ξ i represents the signal quality evaluation index of the i-th signal monitoring cycle, μ represents the signal quality evaluation index weight factor corresponding to the working environment, λ represents the signal quality evaluation index weight factor corresponding to the 6G network performance abnormality index, ξ e(i) represents the evaluation value of the working environment impact degree of the i-th signal monitoring cycle, ξ p(i) It represents the 6G network performance abnormality index of the i-th signal monitoring cycle, when i is the signal monitoring cycle number, i=1,2,3,...,n, and n is the number of signal monitoring cycles.

[0015] Furthermore, the step of feedback-adjusting the target device operating parameters according to the signal quality evaluation index of each signal monitoring cycle includes: obtaining a signal quality evaluation index threshold from a 6G signal database; comparing the signal quality evaluation index of each signal monitoring cycle with the signal quality evaluation index threshold; if the signal quality evaluation index of a signal monitoring cycle is greater than or equal to the signal quality evaluation index threshold, the signal monitoring device of the signal monitoring cycle is not processed; if the signal quality evaluation index of a signal monitoring cycle is less than the signal quality evaluation index threshold, feedback-adjusting the target device operating parameters of the signal monitoring cycle.

[0016] Furthermore, the step of feedback-adjusting the target device operating parameters of the signal monitoring cycle includes: the target device operating parameters include signal monitoring device parameters and network device parameters; obtaining a working environment assessment threshold and a 6G network performance anomaly index threshold from a 6G signal database; subtracting the working environment assessment threshold from the working environment impact assessment value of each signal monitoring cycle, and marking the difference result as the environmental anomaly value of each signal monitoring cycle, and adjusting the signal monitoring device parameters of each signal monitoring cycle according to the environmental anomaly value of each signal monitoring cycle; subtracting the 6G network performance anomaly index threshold from the 6G network performance anomaly index of each signal monitoring cycle, and marking the difference result as the signal anomaly value of each signal monitoring cycle, and adjusting the network device parameters of each signal monitoring cycle according to the signal anomaly value of each signal monitoring cycle; collecting target device operating status data of each signal monitoring cycle after adjustment, evaluating the operating status of the target device operating parameters of each signal monitoring cycle, adjusting according to the operating status of the target device operating parameters, and evaluating and feeding back the adjustment effect.

[0017] Furthermore, the step of adjusting the signal monitoring equipment parameters of each signal monitoring cycle according to the environmental abnormality value of each signal monitoring cycle includes: the signal monitoring equipment parameters include a signal amplification factor and a signal-to-noise ratio threshold; comparing the environmental abnormality value of each signal monitoring cycle with zero, if the environmental abnormality value of a signal monitoring cycle is less than or equal to zero, then the signal monitoring equipment parameters of the signal monitoring cycle are not adjusted, if the environmental abnormality value of a signal monitoring cycle is greater than zero, then the environmental abnormality value of the signal monitoring cycle is matched with the signal amplification factor and the signal-to-noise ratio threshold corresponding to each environmental abnormality value interval stored in the 6G signal database, to obtain the demand-adjusted signal amplification factor and the demand-adjusted signal-to-noise ratio threshold, and adjust the signal monitoring equipment parameters according to the demand-adjusted signal amplification factor and the demand-adjusted signal-to-noise ratio threshold.

[0018] Furthermore, the step of adjusting the network equipment parameters of each signal monitoring period according to the signal anomaly value of each signal monitoring period includes: the network equipment parameters include bandwidth and sampling rate; comparing the signal anomaly value of each signal monitoring period with zero, if the signal anomaly value of a certain signal monitoring period is less than or equal to zero, then the network equipment parameters of the signal monitoring period are not adjusted, if the signal anomaly value of a certain signal monitoring period is greater than zero, then the signal anomaly value of the signal monitoring period is matched with the bandwidth network topology and sampling rate threshold corresponding to each environmental anomaly value interval stored in the 6G signal database, to obtain the demand-adjusted bandwidth network topology and the demand-adjusted sampling rate threshold, and adjust the network equipment parameters according to the demand-adjusted bandwidth network topology and the demand-adjusted sampling rate threshold.

[0019] Furthermore, the step of evaluating the operating status of the operating parameters of the target device in each signal monitoring period and making adjustments according to the operating status of the operating parameters of the target device includes: the operating status data of the target device in each signal monitoring period, including internal temperature and power consumption; obtaining the standard internal temperature value, the allowable deviation internal temperature value and the power consumption threshold from the 6G signal database; comprehensively analyzing to obtain the abnormal evaluation value of the operating status of the target device in each signal monitoring period, and evaluating and feeding back the adjustment effect according to the abnormal evaluation value of the operating status of the target device in each signal monitoring period.

[0020] Furthermore, a signal monitoring system for 6G key scenarios includes a data acquisition module, an environment assessment module, a performance assessment module, an anomaly detection module, a signal monitoring management module and a 6G signal database; wherein the data acquisition module is used to acquire each signal monitoring cycle, and collect the working environment data and 6G signal feature data of each signal monitoring cycle; the environment assessment module is used to obtain the working environment impact degree assessment value of each signal monitoring cycle according to the comprehensive analysis of the working environment data of each signal monitoring cycle; the performance assessment module is used to obtain the 6G network performance anomaly index of each signal monitoring cycle according to the comprehensive analysis of the 6G signal feature data of each signal monitoring cycle; the anomaly detection module is used to obtain the signal quality assessment index of each signal monitoring cycle according to the comprehensive analysis of the working environment impact degree assessment value and the 6G network performance anomaly index of each signal monitoring cycle, and feedback-adjust the target device operating parameters according to the signal quality assessment index of each signal monitoring cycle; the signal monitoring management module is used to collect, analyze and store the data of the signal detection equipment, and provide real-time monitoring data and alarm information to the management personnel.

[0021] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0022] 1. The present invention provides a signal monitoring method and system for 6G key scenarios, thereby realizing dynamic optimization of the equipment operation status, ensuring the stability and efficiency of the signal quality, and further realizing accurate monitoring and optimization of 6G network performance, thereby enhancing the adaptability and stability of the equipment in different environments.

[0023] 2. The present invention obtains the working environment impact assessment value of each signal monitoring period based on a comprehensive analysis of the working environment data of each signal monitoring period, thereby ensuring the comprehensiveness and objectivity of the working environment assessment results, and further realizing comprehensive and continuous monitoring and assessment of the working environment.

[0024] 3. The present invention can accurately reflect the actual status of signal quality by real-time monitoring and calculating the signal quality evaluation index of each signal monitoring cycle, provide a reliable basis for subsequent feedback adjustment, and thus realize timely feedback adjustment, reduce equipment failures and downtime caused by signal quality fluctuations, and improve the overall stability and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A flow chart of a signal monitoring method for 6G key scenarios provided in an embodiment of the present application.

[0026] Figure 2 A graph showing changes in abnormal evaluation values ​​of target device operating status based on signal monitoring of 6G key scenarios provided in an embodiment of the present application.

[0027] Figure 3 A structural schematic diagram of a signal monitoring system for 6G key scenarios provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] The embodiments of the present application provide a signal monitoring method and system for 6G key scenarios, which solves the problem that the existing monitoring equipment in the prior art may not be able to accurately capture signal changes due to insufficient sensitivity, and when the signal is interfered with or in an abnormal situation, the monitoring equipment cannot respond in time, resulting in low accuracy of the monitored signal quality. The signal quality evaluation index of each signal monitoring period is obtained through comprehensive analysis based on the working environment impact evaluation value of each signal monitoring period and the 6G network performance abnormality index, and the target device operating parameters are feedback-adjusted based on the signal quality evaluation index of each signal monitoring period, thereby improving the real-time and accuracy of signal monitoring.

[0029] The technical solution in the embodiment of the present application is to solve the problem that the above-mentioned existing monitoring equipment may not be able to accurately capture signal changes due to insufficient sensitivity. When the signal is interfered or abnormal, the monitoring equipment cannot respond in time, resulting in low accuracy of the monitored signal quality. The overall idea is as follows:

[0030] By setting the signal monitoring cycle and data collection, and then evaluating the signal working environment and network performance, a comprehensive analysis is conducted to obtain the signal quality evaluation index, and then feedback adjustment is performed on the target device operating parameters based on the signal quality evaluation index, thus achieving a continuous monitoring and adjustment system, continuously optimizing the operating status of the equipment, and improving the reliability and efficiency of signal transmission.

[0031] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0032] like Figure 1 As shown, a flow chart of a signal monitoring method for 6G key scenarios provided in an embodiment of the present application is provided, and the method includes the following steps: obtaining each signal monitoring period, and collecting working environment data and 6G signal feature data of each signal monitoring period; obtaining a working environment impact degree assessment value of each signal monitoring period according to a comprehensive analysis of the working environment data of each signal monitoring period; obtaining a 6G network performance anomaly index of each signal monitoring period according to a comprehensive analysis of the 6G signal feature data of each signal monitoring period; obtaining a signal quality assessment index of each signal monitoring period according to a comprehensive analysis based on the working environment impact degree assessment value and the 6G network performance anomaly index of each signal monitoring period, and performing feedback adjustment on the target device operating parameters according to the signal quality assessment index of each signal monitoring period.

[0033] In this embodiment, the signal status is monitored by setting a fixed time interval, which helps to capture the dynamic process of signal changes. In each monitoring cycle, two types of key data are collected: one is the working environment data, which may affect the propagation and reception of the signal; the other is the 6G signal characteristic data, which directly reflects the quality of the signal. Combined with the working environment impact assessment value and the 6G network performance abnormality index, the signal quality assessment index is calculated through a comprehensive assessment algorithm. This index fully reflects the quality status of the signal in the current environment. According to the signal quality assessment index, the operating parameters of the target device are automatically adjusted. Through real-time monitoring and adjustment, the signal quality can be ensured to be in the best state, reduce communication interruptions or quality degradation caused by environmental factors or network problems, and promptly discover and solve potential problems, reduce system failure rates, and improve the stability and reliability of the entire communication system.

[0034] In addition, the 6G signal database is used to store signal monitoring system related data for 6G key scenarios, including: signal quality evaluation index threshold, working environment evaluation threshold, 6G network performance abnormality index threshold, standard internal temperature value, allowable deviation internal temperature value and power consumption threshold, etc. The data in the 6G signal database can be obtained by utilizing existing research institutions and laboratories or in academic journals and conferences such as the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM).

[0035] Furthermore, the step of obtaining an evaluation value of the degree of working environment impact of each signal monitoring period through comprehensive analysis of the working environment data of each signal monitoring period includes: the working environment data of each signal monitoring period includes noise power and electromagnetic intensity; obtaining the critical noise power and critical electromagnetic intensity from the 6G signal database; and obtaining an evaluation value of the degree of working environment impact of each signal monitoring period through comprehensive analysis.

[0036] In this embodiment, the working environment impact degree evaluation value represents a quantitative value of the impact degree of the working environment data on the working environment. The greater the working environment impact degree evaluation value, the greater the degree of interference to the working environment. Noise power refers to the total energy or power of the noise signal within a given frequency band. The greater the noise power, the higher the working environment impact degree evaluation value. The value of noise power is usually obtained through experimental measurement or simulation. In the experiment, a special noise measurement device, such as a spectrum analyzer, can be used to measure the noise power within a specific frequency band. In the simulation, the noise power can be calculated by establishing a mathematical model of the system and considering the influence of various noise sources; electromagnetic intensity refers to the intensity of electromagnetic radiation, which affects the propagation and reception of signals. The greater the electromagnetic intensity, the higher the working environment impact degree evaluation value. The value of electromagnetic intensity can also be obtained through experimental measurement or simulation. Experimental measurement can be carried out using equipment such as an electromagnetic field intensity meter, while simulation requires the establishment of a mathematical model of the electromagnetic field and the consideration of the influence of the surrounding environment (such as buildings, terrain, etc.) on the electromagnetic field. Noise power and electromagnetic intensity both play an important role in communication systems, but they describe different physical quantities. Noise power focuses on the random interference part of the signal, while electromagnetic strength focuses on the strength of the electromagnetic field itself. However, in some cases, electromagnetic strength may affect noise power. For example, in an environment with a complex electromagnetic environment, strong electromagnetic radiation may introduce additional noise sources, thereby increasing noise power. A comprehensive analysis combining noise power and electromagnetic strength can provide a more comprehensive understanding of the working environment of the signal monitoring cycle, and can also reveal the impact of the electromagnetic environment on signal transmission, as well as the distribution of noise sources in a specific environment.

[0037] Furthermore, the step of obtaining the 6G network performance abnormality index of each signal monitoring period by comprehensive analysis based on the 6G signal characteristic data of each signal monitoring period includes: the 6G signal characteristic data of each signal monitoring period includes signal strength, data transmission rate and bit error rate; obtaining the critical signal strength, critical data transmission rate and critical bit error rate from the 6G signal database; and obtaining the 6G network performance abnormality index of each signal monitoring period by comprehensive analysis.

[0038] In this embodiment, the 6G network performance anomaly index represents a quantitative value of the degree of influence of the 6G signal characteristic data on the 6G network performance. The larger the 6G network performance anomaly index, the more serious the anomaly of the 6G network performance. Signal strength reflects the attenuation of the signal during transmission and is an important parameter for measuring signal quality. The higher the signal strength, the smaller the 6G network performance anomaly index. Signal strength can usually be measured using a spectrum analyzer, wireless network test tools or software such as Wi-Fi Analyzer; data transmission rate refers to the amount of data transmitted per unit time, which is a key indicator for measuring communication efficiency. The faster the data transmission rate, the smaller the 6G network performance anomaly index. The data transmission rate can be measured through network test tools such as Speedtest, IPerf, etc. These tools can simulate the actual network environment and measure the data transmission speed; the bit error rate refers to the probability of an error occurring during data transmission, which is an important indicator for measuring communication accuracy. The lower the bit error rate, the smaller the 6G network performance anomaly index, and the higher the reliability of data transmission. The bit error rate is usually measured by comparing the data at the sender and the receiver. The sender sends a set of known data, and the receiver receives and compares this set of data, and calculates the ratio of the number of bits with errors to the total number of bits, which is the bit error rate. The number of bits can be obtained through network packet capture tools such as Wi reshark. In addition, there is a correlation between these three. Generally speaking, the stronger the signal strength, the higher the data transmission rate, because a stronger signal means less attenuation and better transmission quality, thus supporting a higher data transmission rate; the signal strength and the bit error rate are usually inversely proportional. The stronger the signal strength, the lower the bit error rate; conversely, the weaker the signal strength, the higher the bit error rate. Because weaker signals are more susceptible to noise and interference, errors occur during data transmission; and there is a certain trade-off between data transmission rate and bit error rate. In order to increase the data transmission rate, more advanced modulation and coding technologies may be used, but this may increase the risk of bit error rate. By comprehensively analyzing the three indicators of signal strength, data transmission rate and bit error rate, the performance of the 6G network can be accurately evaluated, that is, the network coverage, signal quality, efficiency and accuracy of data transmission can be understood, and potential problems in the network can be discovered, such as signal attenuation, data transmission bottlenecks or excessive bit error rates.

[0039] Furthermore, the method for obtaining the signal quality evaluation index of each signal monitoring period is as follows:

[0040]

[0041] In the formula, ξ irepresents the signal quality evaluation index of the i-th signal monitoring cycle, μ represents the signal quality evaluation index weight factor corresponding to the working environment, λ represents the signal quality evaluation index weight factor corresponding to the 6G network performance abnormality index, ξ e(i) represents the evaluation value of the working environment impact degree of the i-th signal monitoring cycle, ξ p(i) It represents the 6G network performance abnormality index of the i-th signal monitoring cycle, when i is the signal monitoring cycle number, i=1,2,3,...,n, and n is the number of signal monitoring cycles.

[0042] In this embodiment, μ and λ are respectively the signal quality evaluation index weight factors corresponding to the working environment and the 6G network performance anomaly index preset in the 6G signal database, respectively representing the numerical values ​​of the degree of influence of the working environment and the 6G network performance anomaly index on the signal quality evaluation index, and can be directly obtained from the 6G signal database when used. For example, a mapping set is formed by the working environment impact assessment value and the signal quality evaluation index weight factor corresponding to the working environment preset in the 6G signal database, and the signal quality evaluation index weight factor corresponding to the working environment of a certain signal monitoring period is obtained by inputting the working environment impact assessment value of the mapping set according to the signal monitoring period, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the weight factor in this embodiment is between 0 and 1.

[0043] The method for obtaining the working environment impact assessment value of each signal monitoring period is as follows:

[0044]

[0045] In the formula, ξ e(i) represents the evaluation value of the working environment impact degree of the i-th signal monitoring cycle, α 1 Represents the weight factor of the working environment impact assessment value corresponding to the noise power, α 2 Indicates the weight factor of the impact assessment value of the working environment corresponding to the electromagnetic intensity, N 1(i) represents the noise power of the i-th signal monitoring period, N 0 represents the critical noise power, E 1(i) represents the electromagnetic intensity of the ith signal monitoring period, E 0 represents the critical electromagnetic intensity, i is the signal monitoring period number, i=1,2,3,...,n, n is the number of signal monitoring periods.

[0046] α 1 and α 2The weight factors of the working environment impact assessment value corresponding to the noise power and electromagnetic strength preset in the 6G signal database respectively represent the numerical values ​​of the impact of the noise power and electromagnetic strength on the working environment impact assessment value, and can be directly obtained from the 6G signal database when used. For example, a mapping set is formed by forming a noise power and a weight factor of the working environment impact assessment value corresponding to the noise power preset in the 6G signal database, and the weight factor of the working environment impact assessment value corresponding to the noise power of a certain signal monitoring period is obtained according to the noise power input mapping set of the signal monitoring period, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the weight factor in this embodiment is between 0 and 1.

[0047] Among them, the method for obtaining the 6G network performance abnormality index of each signal monitoring period is as follows:

[0048]

[0049] In the formula, ξ p(i) represents the 6G network performance anomaly index of the i-th signal monitoring cycle, β 1 Indicates the weight factor of 6G network performance anomaly index corresponding to signal strength, β 2 Indicates the weight factor of 6G network performance anomaly index corresponding to data transmission rate, β 3 represents the weight factor of the 6G network performance anomaly index corresponding to the bit error rate, S 1(i) represents the signal strength of the i-th signal monitoring period, S 0 Indicates the critical signal strength, V 1(i represents the data transmission rate of the ith signal monitoring cycle, V 0 represents the critical data transmission rate, B 1(i represents the bit error rate of the i-th signal monitoring cycle, B 0 represents the critical bit error rate, i is the signal monitoring period number, i=1,2,3,...,n, n is the number of signal monitoring periods.

[0050] β 1 , β 2 and β 3The 6G network performance abnormality indicator weight factors corresponding to the signal strength, data transmission rate and bit error rate preset in the 6G signal database respectively represent the numerical values ​​of the influence of the signal strength, data transmission rate and bit error rate on the 6G network performance abnormality indicator, and can be directly obtained from the 6G signal database when used. For example, the signal strength and the 6G network performance abnormality indicator weight factors corresponding to the signal strength preset in the 6G signal database form a mapping set, and the 6G network performance abnormality indicator weight factor corresponding to the signal strength of a certain signal monitoring period is obtained according to the signal strength input mapping set of the signal monitoring period, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the weight factor in this embodiment is between 0 and 1.

[0051] Furthermore, the step of feedback-adjusting the target device operating parameters according to the signal quality evaluation index of each signal monitoring cycle includes: obtaining a signal quality evaluation index threshold from a 6G signal database; comparing the signal quality evaluation index of each signal monitoring cycle with the signal quality evaluation index threshold; if the signal quality evaluation index of a signal monitoring cycle is greater than or equal to the signal quality evaluation index threshold, the signal monitoring device of the signal monitoring cycle is not processed; if the signal quality evaluation index of a signal monitoring cycle is less than the signal quality evaluation index threshold, feedback-adjusting the target device operating parameters of the signal monitoring cycle.

[0052] In this embodiment, when the signal quality evaluation index of a signal monitoring cycle is greater than or equal to the signal quality evaluation index threshold, it means that the signal quality of the cycle meets the standard and no additional processing is required; when the signal quality evaluation index of a signal monitoring cycle is less than the signal quality evaluation index threshold, it means that the signal quality of the cycle does not meet the standard and feedback adjustment is required for the target device operating parameters of the signal monitoring cycle. The feedback adjustment mechanism can dynamically adjust the operating parameters of the target device according to changes in signal quality to avoid waste and overuse of resources, which helps to reduce operating costs and improve resource utilization efficiency; through real-time monitoring and feedback adjustment, signal quality problems can be discovered and resolved in a timely manner, thereby improving the stability and reliability of communications.

[0053] Furthermore, the step of feedback-adjusting the target device operating parameters of the signal monitoring cycle includes: the target device operating parameters include signal monitoring device parameters and network device parameters; obtaining a working environment assessment threshold and a 6G network performance anomaly index threshold from a 6G signal database; subtracting the working environment assessment threshold from the working environment impact assessment value of each signal monitoring cycle, and marking the difference result as the environmental anomaly value of each signal monitoring cycle, and adjusting the signal monitoring device parameters of each signal monitoring cycle according to the environmental anomaly value of each signal monitoring cycle; subtracting the 6G network performance anomaly index threshold from the 6G network performance anomaly index of each signal monitoring cycle, and marking the difference result as the signal anomaly value of each signal monitoring cycle, and adjusting the network device parameters of each signal monitoring cycle according to the signal anomaly value of each signal monitoring cycle; collecting target device operating status data of each signal monitoring cycle after adjustment, evaluating the operating status of the target device operating parameters of each signal monitoring cycle, adjusting according to the operating status of the target device operating parameters, and evaluating and feeding back the adjustment effect.

[0054] In this embodiment, the target device operating parameters are clearly divided into signal monitoring device parameters and network device parameters. This classification helps to locate the problem more accurately and take corresponding adjustment measures; the working environment assessment threshold is subtracted from the working environment impact assessment value of each signal monitoring cycle to obtain the environmental anomaly value. The environmental anomaly value reflects the degree of deviation between the working environment of the equipment and the ideal state. The signal monitoring device parameters are adjusted according to the environmental anomaly value to improve the working environment of the equipment and improve the accuracy and stability of signal monitoring; the 6G network performance anomaly index threshold is subtracted from the 6G network performance anomaly index of each signal monitoring cycle to obtain the signal anomaly value. The signal anomaly value reflects the gap between network performance and the expected target. The network device parameters are adjusted according to the signal anomaly value to optimize network performance and ensure smooth and efficient communication.

[0055] Furthermore, the step of adjusting the signal monitoring equipment parameters of each signal monitoring cycle according to the environmental abnormality value of each signal monitoring cycle includes: the signal monitoring equipment parameters include a signal amplification factor and a signal-to-noise ratio threshold; comparing the environmental abnormality value of each signal monitoring cycle with zero, if the environmental abnormality value of a signal monitoring cycle is less than or equal to zero, then the signal monitoring equipment parameters of the signal monitoring cycle are not adjusted, if the environmental abnormality value of a signal monitoring cycle is greater than zero, then the environmental abnormality value of the signal monitoring cycle is matched with the signal amplification factor and the signal-to-noise ratio threshold corresponding to each environmental abnormality value interval stored in the 6G signal database, to obtain the demand-adjusted signal amplification factor and the demand-adjusted signal-to-noise ratio threshold, and adjust the signal monitoring equipment parameters according to the demand-adjusted signal amplification factor and the demand-adjusted signal-to-noise ratio threshold.

[0056] In this embodiment, the signal monitoring device is equipped with a magnification knob, and the magnification can be adjusted by rotating the knob or pressing the corresponding button; the signal-to-noise ratio can be adjusted by optimizing the hardware structure of the device or adopting more advanced signal processing technology, such as using a low-noise amplifier, a filter, or a noise suppression algorithm. By dynamically adjusting the signal amplification factor and the signal-to-noise ratio threshold according to the environmental anomaly value, the system can better adapt to the signal monitoring needs under different environmental conditions. For example, increasing the signal-to-noise ratio threshold in a noisy environment helps to filter out more background noise, thereby more accurately capturing the target signal. The parameter adjustment corresponding to the environmental anomaly value interval stored in the preset 6G signal database ensures the accuracy and scientificity of the parameter adjustment and avoids the problems that may be caused by blind adjustment.

[0057] Furthermore, the step of adjusting the network equipment parameters of each signal monitoring period according to the signal anomaly value of each signal monitoring period includes: the network equipment parameters include bandwidth and sampling rate; comparing the signal anomaly value of each signal monitoring period with zero, if the signal anomaly value of a certain signal monitoring period is less than or equal to zero, then the network equipment parameters of the signal monitoring period are not adjusted, if the signal anomaly value of a certain signal monitoring period is greater than zero, then the signal anomaly value of the signal monitoring period is matched with the bandwidth network topology and sampling rate threshold corresponding to each environmental anomaly value interval stored in the 6G signal database, to obtain the demand-adjusted bandwidth network topology and the demand-adjusted sampling rate threshold, and adjust the network equipment parameters according to the demand-adjusted bandwidth network topology and the demand-adjusted sampling rate threshold.

[0058] In this embodiment, the bandwidth network topology can be adjusted by cleaning up unused network devices, reducing network complexity or adding wireless access points to ensure uniform signal coverage and avoid dead spots; the sampling rate adjustment can be adjusted through the network management interface, command line interface or dedicated software according to the model and configuration of the network device. Each signal monitoring cycle generates a signal anomaly value, which reflects the gap between the current network performance and the expected target. The signal anomaly value is compared with zero to determine whether the network device parameters need to be adjusted. If the signal anomaly value is greater than zero, it means that there is a problem with the network performance and adjustment is required. The signal anomaly value is matched with the corresponding environmental anomaly value interval stored in the 6G signal database to find the bandwidth and sampling rate threshold that best suits the current situation for adjustment.

[0059] Furthermore, the step of evaluating the operating status of the operating parameters of the target device in each signal monitoring period and making adjustments according to the operating status of the operating parameters of the target device includes: the operating status data of the target device in each signal monitoring period, including internal temperature and power consumption; obtaining the standard internal temperature value, the allowable deviation internal temperature value and the power consumption threshold from the 6G signal database; comprehensively analyzing to obtain the abnormal evaluation value of the operating status of the target device in each signal monitoring period, and evaluating and feeding back the adjustment effect according to the abnormal evaluation value of the operating status of the target device in each signal monitoring period.

[0060] In this embodiment, the target device operation state abnormality evaluation value is an indicator used to quantitatively evaluate the abnormal operation state of the target device. This evaluation value is derived based on the operation state data of the target device and is used to judge the health and performance of the device. The larger the target device operation state abnormality evaluation value is, the worse the target device operation state is. The internal temperature refers to the temperature of key components (such as chips, circuit boards, etc.) inside the device. The temperature sensor is usually integrated inside the device to monitor the temperature of key components in real time. The greater the absolute value of the difference between the current internal temperature value and the standard internal temperature value, the greater the target device operation state abnormality evaluation value is; power consumption refers to the electrical energy consumed by the device during operation. The input power of the device can be directly measured using a power meter to obtain power consumption data. The greater the power consumption, the greater the target device operation state abnormality evaluation value is. There is a certain correlation between internal temperature and power consumption. As the power consumption of the device increases, the internal temperature will also increase accordingly. This is because the increase in power consumption means that more energy inside the device is converted into heat energy, which leads to an increase in temperature. Conversely, if the internal temperature of the device is too high, it may also lead to increased power consumption, because high temperature will affect the operating efficiency of the device and increase additional energy consumption. By comprehensively analyzing the two parameters of internal temperature and power consumption, the operating status and potential problems of the equipment can be more comprehensively evaluated. At the same time, targeted performance optimization suggestions can be put forward based on the analysis results to help users improve the operating efficiency and stability of the equipment. When evaluating and feeding back the adjustment effect based on the abnormal evaluation value of the target device operating status of each signal monitoring cycle, the target device operating status abnormal evaluation threshold can be obtained from the 6G signal database, and the target device operating status abnormal evaluation value of each signal monitoring cycle is compared with the target device operating status abnormal evaluation threshold. If the target device operating status abnormal evaluation value of a certain signal monitoring cycle is less than the target device operating status abnormal evaluation threshold, it means that the adjustment effect is normal; if the target device operating status abnormal evaluation value of a certain signal monitoring cycle is greater than or equal to the target device operating status abnormal evaluation threshold, it means that the adjustment state is abnormal, and it can be adjusted by re-evaluating and adjusting the set values ​​of the signal monitoring device parameters and network device parameters, or by replacing or upgrading the hardware of the device.

[0061] Among them, the method for obtaining the abnormal evaluation value of the target device operation status in each signal monitoring period is as follows:

[0062]

[0063] In the formula, ξ s(i) represents the abnormal evaluation value of the target device operation status in the i-th signal monitoring cycle, γ 1 represents the weight factor of the abnormal evaluation value of the target device operation status corresponding to the internal temperature, γ 2 Represents the weight factor of the abnormal evaluation value of the target device operation status corresponding to the power consumption, T 0(i) represents the internal temperature of the ith signal monitoring period, T 1 Indicates the standard internal temperature value, T 2 Indicates the allowable deviation internal temperature value, C 0(i) represents the power consumption of the i-th signal monitoring cycle, C 1 represents the power consumption threshold, i is the signal monitoring cycle number, i=1,2,3,...,n, and n is the number of signal monitoring cycles.

[0064] γ 1 and γ 2 The weight factors of the abnormal operation status evaluation value of the target device corresponding to the internal temperature and power consumption preset in the 6G signal database respectively represent the numerical values ​​of the degree of influence of the internal temperature and power consumption on the abnormal operation status evaluation value of the target device, and can be directly obtained from the 6G signal database when used. For example, the internal temperature and the weight factors of the abnormal operation status evaluation value of the target device corresponding to the internal temperature preset in the 6G signal database form a mapping set, and the weight factors of the abnormal operation status evaluation value of the target device corresponding to the internal temperature of a certain signal monitoring period are obtained according to the internal temperature input mapping set of the signal monitoring period, wherein the mapping relationship is a many-to-one or one-to-one relationship, and the value range of the weight factor in this embodiment is between 0 and 1.

[0065] Furthermore, a signal monitoring system for 6G key scenarios is characterized by: comprising a data acquisition module, an environment assessment module, a performance assessment module, an anomaly detection module, a signal monitoring management module and a 6G signal database; wherein the data acquisition module is used to acquire each signal monitoring cycle, and collect the working environment data and 6G signal feature data of each signal monitoring cycle; the environment assessment module is used to obtain the working environment impact degree assessment value of each signal monitoring cycle according to the comprehensive analysis of the working environment data of each signal monitoring cycle; the performance assessment module is used to obtain the 6G network performance anomaly index of each signal monitoring cycle according to the comprehensive analysis of the 6G signal feature data of each signal monitoring cycle; the anomaly detection module is used to obtain the signal quality assessment index of each signal monitoring cycle according to the comprehensive analysis of the working environment impact degree assessment value and the 6G network performance anomaly index of each signal monitoring cycle, and feedback-adjust the target device operating parameters according to the signal quality assessment index of each signal monitoring cycle; the signal monitoring management module is used to collect, analyze and store the data of the signal detection equipment, and provide real-time monitoring data and alarm information to the management personnel.

[0066] The weight factor of the target device operation status abnormal evaluation value corresponding to the internal temperature is set to 0.4, the weight factor of the target device operation status abnormal evaluation value corresponding to the power consumption is set to 0.6, the standard internal temperature value is set to 20°C, the allowable deviation internal temperature value is set to 5°C, and the power consumption threshold is set to 100W. Under the condition of the same power consumption and different internal temperatures, the target device operation status abnormal evaluation value is calculated. As shown in Table 1, the target device operation status abnormal evaluation value data table based on the 6G signal monitoring method.

[0067] Table 1. Data table of abnormal evaluation values ​​of target equipment operation status based on 6G signal monitoring method

[0068] i <![CDATA[T 0i (℃)]]> <![CDATA[C 0i (In)]]> <![CDATA[ξ si ]]> 1 10 100 0.927 2 15 100 0.901 3 20 100 0.834 4 25 100 0.901 5 30 100 0.927

[0069] like Figure 2 As shown, it is a graph showing the change of abnormal evaluation value of target device operation status based on signal monitoring of 6G key scenarios provided in an embodiment of the present application, which is composed of Figure 2 It can be seen from Table 1 that the target device operation status abnormality assessment value weight factor corresponding to the internal temperature, the target device operation status abnormality assessment value weight factor corresponding to the power consumption, the standard internal temperature value, the allowable deviation internal temperature value, the power consumption threshold and the change in the target device operation status abnormality assessment value when the power consumption is the same and the internal temperature is different.

[0070] like Figure 3As shown, it is a structural diagram of a signal monitoring system for 6G key scenarios provided in an embodiment of the present application. A signal monitoring system for 6G key scenarios provided in an embodiment of the present application includes: a data acquisition module, an environment assessment module, a performance assessment module, an anomaly detection module, a signal monitoring management module and a 6G signal database.

[0071] In summary, the embodiment of the present application sets the signal monitoring cycle and data collection, then evaluates the signal working environment and network performance, comprehensively analyzes to obtain the signal quality evaluation index, and then feedback adjusts the target device operating parameters according to the signal quality evaluation index, thereby achieving a continuous monitoring and adjustment system, continuously optimizing the operating status of the equipment, and thereby improving the reliability and efficiency of signal transmission.

[0072] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0073] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0074] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0075] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0076] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0077] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A signal monitoring method for 6G key scenarios, characterized in that: The following steps are involved: Obtain each signal monitoring period, and collect working environment data and 6G signal characteristic data of each signal monitoring period; The working environment impact assessment value of each signal monitoring period is obtained by comprehensive analysis of the working environment data of each signal monitoring period; The 6G network performance anomaly index of each signal monitoring period is obtained by comprehensive analysis of the 6G signal characteristic data of each signal monitoring period; According to the working environment impact assessment value of each signal monitoring period and the 6G network performance abnormality index, a comprehensive analysis is conducted to obtain the signal quality assessment index of each signal monitoring period, and feedback adjustment is performed on the target device operating parameters based on the signal quality assessment index of each signal monitoring period.

2. A signal monitoring method for 6G key scenarios as claimed in claim 1, characterized in that: The step of obtaining the working environment impact assessment value of each signal monitoring period according to the comprehensive analysis of the working environment data of each signal monitoring period comprises: The working environment data of each signal monitoring period, including noise power and electromagnetic intensity; Obtain critical noise power and critical electromagnetic intensity from the 6G signal database; Comprehensive analysis is performed to obtain the evaluation value of the working environment impact degree of each signal monitoring cycle.

3. A signal monitoring method for 6G key scenarios as claimed in claim 1, characterized in that: The step of obtaining the 6G network performance abnormality index of each signal monitoring period according to the comprehensive analysis of the 6G signal characteristic data of each signal monitoring period includes: The 6G signal characteristic data of each signal monitoring period, including signal strength, data transmission rate and bit error rate; Obtain critical signal strength, critical data transmission rate, and critical bit error rate from the 6G signal database; Comprehensive analysis is performed to obtain the 6G network performance anomaly indicators of each signal monitoring period.

4. A signal monitoring method for 6G key scenarios as claimed in claim 1, characterized in that: The method for obtaining the signal quality evaluation index of each signal monitoring period is as follows: In the formula, ξ i represents the signal quality evaluation index of the i-th signal monitoring cycle, μ represents the signal quality evaluation index weight factor corresponding to the working environment, λ represents the signal quality evaluation index weight factor corresponding to the 6G network performance abnormality index, ξ ei represents the evaluation value of the working environment impact degree of the i-th signal monitoring cycle, ξ pi It represents the 6G network performance abnormality index of the i-th signal monitoring cycle, when i is the signal monitoring cycle number, i=1,2,3,...,n, and n is the number of signal monitoring cycles.

5. A signal monitoring method for 6G key scenarios as claimed in claim 1, characterized in that: The step of feedback-adjusting the target device operating parameters according to the signal quality evaluation index of each signal monitoring period comprises: Obtain a signal quality assessment index threshold from a 6G signal database; The signal quality assessment index of each signal monitoring cycle is compared with the signal quality assessment index threshold. If the signal quality assessment index of a signal monitoring cycle is greater than or equal to the signal quality assessment index threshold, the signal monitoring equipment of this signal monitoring cycle will not be processed. If the signal quality assessment index of a signal monitoring cycle is less than the signal quality assessment index threshold, the operating parameters of the target equipment of this signal monitoring cycle will be feedback adjusted.

6. A signal monitoring method for 6G key scenarios as claimed in claim 5, characterized in that: The step of feedback-adjusting the target device operating parameters of the signal monitoring period comprises: The target device operating parameters include signal monitoring device parameters and network device parameters; Obtain working environment assessment thresholds and 6G network performance abnormality indicator thresholds from the 6G signal database; Subtract the working environment assessment threshold from the working environment impact assessment value of each signal monitoring period, and mark the difference result as the environmental abnormality value of each signal monitoring period, and adjust the signal monitoring equipment parameters of each signal monitoring period according to the environmental abnormality value of each signal monitoring period; Subtract the 6G network performance anomaly index threshold from the 6G network performance anomaly index of each signal monitoring period, and mark the difference result as the signal anomaly value of each signal monitoring period, and adjust the network device parameters of each signal monitoring period according to the signal anomaly value of each signal monitoring period; Collect the target device operating status data of each signal monitoring cycle after adjustment, evaluate the operating status of the target device operating parameters of each signal monitoring cycle, make adjustments based on the operating status of the target device operating parameters, and evaluate and feedback the adjustment effect.

7. A signal monitoring method for 6G key scenarios as claimed in claim 6, characterized in that: The step of adjusting the signal monitoring equipment parameters of each signal monitoring period according to the environmental abnormality value of each signal monitoring period comprises: The signal monitoring equipment parameters include signal amplification factor and signal-to-noise ratio threshold; The environmental abnormality value of each signal monitoring period is compared with zero. If the environmental abnormality value of a signal monitoring period is less than or equal to zero, the signal monitoring equipment parameters of the signal monitoring period are not adjusted. If the environmental abnormality value of a signal monitoring period is greater than zero, the environmental abnormality value of the signal monitoring period is matched with the signal amplification factor and signal-to-noise ratio threshold corresponding to each environmental abnormality value interval stored in the 6G signal database to obtain the demand-adjusted signal amplification factor and the demand-adjusted signal-to-noise ratio threshold, and the signal monitoring equipment parameters are adjusted according to the demand-adjusted signal amplification factor and the demand-adjusted signal-to-noise ratio threshold.

8. A signal monitoring method for 6G key scenarios as claimed in claim 6, characterized in that: The step of adjusting the network device parameters of each signal monitoring period according to the signal abnormality value of each signal monitoring period comprises: The network equipment parameters include bandwidth and sampling rate; The signal anomaly value of each signal monitoring period is compared with zero. If the signal anomaly value of a signal monitoring period is less than or equal to zero, the network equipment parameters of the signal monitoring period are not adjusted. If the signal anomaly value of a signal monitoring period is greater than zero, the signal anomaly value of the signal monitoring period is matched with the bandwidth network topology and sampling rate threshold corresponding to each environmental anomaly value interval stored in the 6G signal database to obtain the demand-adjusted bandwidth network topology and the demand-adjusted sampling rate threshold, and the network equipment parameters are adjusted according to the demand-adjusted bandwidth network topology and the demand-adjusted sampling rate threshold.

9. A signal monitoring method for 6G key scenarios as claimed in claim 6, characterized in that: The step of evaluating the operating state of the target device operating parameters in each signal monitoring period and adjusting according to the operating state of the target device operating parameters comprises: The target device operating status data of each signal monitoring period, including internal temperature and power consumption; Obtain a standard internal temperature value, an allowable deviation internal temperature value, and a power consumption threshold from a 6G signal database; Comprehensive analysis is performed to obtain the abnormal operation status evaluation value of the target equipment in each signal monitoring period, and the adjustment effect is evaluated and fed back based on the abnormal operation status evaluation value of the target equipment in each signal monitoring period.

10. A signal monitoring system for a 6G key scenario, using a signal monitoring method for a 6G key scenario as described in any one of claims 1 to 9, characterized in that: It includes data acquisition module, environment assessment module, performance assessment module, anomaly detection module, signal monitoring management module and 6G signal database; The data acquisition module is used to acquire each signal monitoring period and collect working environment data and 6G signal characteristic data of each signal monitoring period; The environmental assessment module is used to obtain an assessment value of the degree of impact of the working environment in each signal monitoring period based on a comprehensive analysis of the working environment data in each signal monitoring period; The performance evaluation module is used to obtain the 6G network performance anomaly index of each signal monitoring period according to the comprehensive analysis of the 6G signal characteristic data of each signal monitoring period; The anomaly detection module is used to comprehensively analyze the signal quality evaluation index of each signal monitoring period according to the working environment impact evaluation value of each signal monitoring period and the 6G network performance anomaly index, and feedback-adjust the target device operating parameters according to the signal quality evaluation index of each signal monitoring period; The signal monitoring management module is used to collect, analyze and store data from signal detection equipment and provide real-time monitoring data and alarm information to management personnel.

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