Communication equipment performance evaluation method and device

Abstract

The invention discloses a communication equipment performance evaluation method and device, relates to the technical field of communication performance evaluation, and solves the problem that the performance of communication equipment is difficult to dynamically evaluate according to the change of environmental data because a fixed threshold value is mostly adopted for performance evaluation in the prior art. And thus, the performance evaluation result of the communication equipment is not accurate enough. The method comprises the following steps: acquiring network state data and equipment environment data of to-be-tested communication equipment; calculating a network quality score of the to-be-tested communication equipment based on the network state data and the equipment environment data; performing performance analysis based on the network state change curve to obtain a plurality of performance evaluation indexes; and determining the performance state of the to-be-tested communication equipment based on the plurality of performance evaluation indexes. According to the method, the operation trend of the communication equipment in different time periods can be dynamically reflected, deviation possibly brought by a traditional static evaluation mode is avoided, and therefore the accuracy of performance evaluation on the communication equipment can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of communication performance evaluation, and in particular relates to a communication equipment performance evaluation method and device. Background Art

[0002] With the rapid development of communications technology, communications equipment has become increasingly central to the modern information society. Whether in mobile communication networks, Internet of Things (IoT) systems, satellite communications, or industrial automation, the performance of communications equipment directly determines system stability, efficiency, and user experience. Therefore, scientific and comprehensive performance evaluation of communications equipment has become a critical step in ensuring the quality of communications services.

[0003] Existing solutions monitor the operating data of communication equipment in real time, compare this data with preset performance evaluation thresholds, and evaluate the performance of the communication equipment based on the comparison results. However, in reality, some communication equipment is installed in areas with frequent environmental changes, such as outdoor areas. Existing technologies mostly use fixed thresholds for performance evaluation, making it difficult to dynamically evaluate the performance of communication equipment based on changes in environmental data, resulting in inaccurate performance evaluation results. Summary of the Invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes a communication equipment performance evaluation method and device, which are used to solve the technical problem that most of the prior art uses fixed thresholds for performance evaluation, making it difficult to dynamically evaluate the performance of the communication equipment according to changes in environmental data, thereby resulting in inaccurate results of the performance evaluation of the communication equipment.

[0005] To achieve the above-mentioned object, a first aspect of the present invention provides a communication device performance evaluation method, comprising:

[0006] Obtain network status data and device environment data of the communication device under test;

[0007] Calculate the network quality score of the communication device under test based on the network status data and the device environment data;

[0008] Perform linear fitting on the network quality scores of several consecutive periods to obtain the network status change curve;

[0009] Perform performance analysis based on the network status change curve to obtain several performance evaluation indicators;

[0010] The performance status of the communication device under test is determined based on several performance evaluation indicators.

[0011] Preferably, the calculating of the network quality score of the communication device under test based on the network status data and the device environment data includes:

[0012] Extracting network status data and device environment data of the communication device under test; wherein the network status data includes network bandwidth, transmission rate, packet loss rate, and network delay;

[0013] By formula Calculate the network quality score WZP of the communication device under test; where WDK is the network bandwidth, CSL is the transmission rate, DBL is the packet loss rate, and WYC is the network delay; a1, a2, a3, and a4 are all proportional coefficients greater than 0; K is the environmental correction coefficient, which is calculated based on the device environment data.

[0014] Preferably, the environmental correction coefficient is calculated based on the equipment environment data, including:

[0015] Extracting device environment data of the communication device under test; wherein the device environment data includes device temperature, rainfall, and wind speed;

[0016] By formula Calculate the environmental correction factor K; where SWD is the device temperature, JYL is the rainfall, and FS is the wind speed; b1, b2, and b3 are all proportional coefficients greater than 0.

[0017] Preferably, the environmental correction coefficient can also be obtained through a correction coefficient generation model, and the training process of the correction coefficient generation model includes:

[0018] Extract several groups of equipment environment data and environmental correction coefficients, and integrate them into several groups of training data and test data; use the training data to train the artificial intelligence model; use the test data to test the trained artificial intelligence model, and adjust the artificial intelligence model according to the test results; finally obtain a correction coefficient generation model with the equipment environment data as input and the environmental correction coefficient as output; wherein the artificial intelligence model includes a BP neural network model or an RBF neural network model.

[0019] Preferably, performing linear fitting on the network quality scores of several consecutive periods includes:

[0020] The network quality scores of several consecutive periods are extracted; time is used as the independent variable and the network quality score is used as the dependent variable, and the network status change curve is obtained through linear fitting.

[0021] Preferably, the performance analysis based on the network status change curve includes:

[0022] Extracting the network status change curve to obtain the network status standard curve of the communication equipment under test when it leaves the factory; wherein the network status standard curve is obtained by linear fitting the network quality score of the communication equipment under test when it leaves the factory;

[0023] Calculate the difference between the network state change curve and the network state standard curve to obtain a network state difference curve; perform an integration operation on the network state difference curve to obtain a state difference cumulative value;

[0024] Determine the proportion of network status abnormality duration based on the network status change curve and the network status standard curve;

[0025] Calculate the first-order derivative function of the network state change curve and take the absolute value to obtain the network state fluctuation function; calculate the average value between the maximum function value and the minimum function value of the network state fluctuation function to obtain the state fluctuation value;

[0026] The cumulative value of status difference, the proportion of network status abnormality duration and the status fluctuation value are integrated into performance evaluation indicators.

[0027] Preferably, determining the proportion of abnormal network status duration based on the network status change curve and the network status standard curve includes:

[0028] Extract the network status change curve and the network status standard curve to obtain the monitoring cycle duration;

[0029] The time point where the network status change curve intersects the network status standard curve is marked as a network abnormal point;

[0030] According to the time sequence of several network anomaly points, the interval between two adjacent network anomaly points is marked as an anomaly interval;

[0031] Calculate the sum of the durations corresponding to several abnormal intervals to obtain the cumulative value of abnormal duration;

[0032] Calculate the ratio of the accumulated abnormal duration to the monitoring period to obtain the proportion of network status abnormal duration.

[0033] Preferably, the determining the performance status of the communication device to be tested based on a number of performance evaluation indicators includes:

[0034] Extracting several performance evaluation indicators of the communication equipment under test;

[0035] Calculating a performance evaluation coefficient of the communication device under test based on a number of performance evaluation indicators;

[0036] If the performance evaluation coefficient is less than a preset evaluation threshold, the performance status of the communication device to be tested is marked as abnormal performance; wherein the performance status includes normal performance and abnormal performance.

[0037] Preferably, the calculating of the performance evaluation coefficient of the communication device to be tested based on a plurality of performance evaluation indicators includes:

[0038] Extract several performance evaluation indicators; through the formula Calculate the performance evaluation coefficient XNP of the communication equipment under test; where ZLJ is the cumulative value of the state difference, YCZ is the proportion of the network state abnormality duration, and ZBD is the state fluctuation value; c1, c2, and c3 are all proportional coefficients greater than 0.

[0039] A second aspect of the present invention provides a communication equipment performance evaluation device, comprising: a data processing module, and a data acquisition module and a performance evaluation module connected thereto;

[0040] The data acquisition module is used to obtain network status data and device environment data of the communication device under test;

[0041] The data processing module is used to calculate the network quality score of the communication device under test based on the network status data and the device environment data; perform linear fitting on the network quality scores of several consecutive periods to obtain a network status change curve; perform performance analysis based on the network status change curve to obtain several performance evaluation indicators;

[0042] The performance evaluation module is used to determine the performance status of the communication device to be tested based on a number of performance evaluation indicators.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] 1. The present invention obtains the network status data and equipment environment data of the communication equipment to be tested, comprehensively considers the internal and external factors that affect the performance of the equipment, and improves the comprehensiveness and accuracy of the evaluation results. On this basis, the network quality score is calculated, and the scores of multiple consecutive cycles are linearly fitted to obtain the network status change curve, which can dynamically reflect the operating trend of the communication equipment in different time periods and avoid the deviation that may be caused by the traditional static evaluation method. Furthermore, by performing performance analysis on the network status change curve and extracting several key performance evaluation indicators, the evaluation system is made more structured and quantitative, which is convenient for subsequent judgment and decision-making. Finally, the overall performance status of the equipment is determined based on these performance evaluation indicators, which is conducive to improving the accuracy of performance evaluation of communication equipment, and thus helps to timely discover potential problems, predict equipment life and optimize network resource configuration.

[0045] 2. The present invention extracts the network status change curve during the operation of the equipment, and combines it with the standard curve obtained by linear fitting based on the quality score at the time of leaving the factory to construct a difference curve and calculate its integral to obtain the cumulative value of the state difference, thereby quantitatively reflecting the overall deviation degree of the network status; further, by identifying the intersection of the change curve and the standard curve, accurately dividing the abnormal interval, calculating the abnormal duration ratio, and realizing a quantitative assessment of the persistence of network abnormalities; then, combining the maximum and minimum average values ​​of the absolute value of the first-order derivative of the change curve, the state fluctuation value is obtained to measure the stability of the network status. Finally, the cumulative value of the state difference, the abnormal duration ratio, and the state fluctuation value are integrated into a comprehensive performance evaluation index, which can comprehensively and objectively reflect the actual operating performance of the communication equipment in the network environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0047] Figure 1 is an overall flow chart of the communication device performance evaluation method of the present invention;

[0048] Figure 2 Schematic diagram of the principle of the communication equipment performance evaluation system of the present invention;

[0049] Figure 3 This is a flow chart of the performance analysis based on the network status change curve in the present invention. DETAILED DESCRIPTION

[0050] The technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0051] See also Figure 1-Figure 3 The first embodiment of the present invention provides a communication device performance evaluation method, comprising:

[0052] S1: Obtain network status data and device environment data of the communication device under test;

[0053] S2: Calculate the network quality score of the communication device under test based on the network status data and device environment data;

[0054] S3: Perform linear fitting on the network quality scores of several consecutive periods to obtain a network status change curve;

[0055] S4: Perform performance analysis based on the network status change curve to obtain several performance evaluation indicators;

[0056] S5: Determine the performance status of the communication device to be tested based on several performance evaluation indicators.

[0057] In this embodiment, calculating the network quality score of the communication device under test based on the network status data and the device environment data includes:

[0058] Extracting network status data and device environment data of the communication device under test; wherein the network status data includes network bandwidth, transmission rate, packet loss rate, and network delay;

[0059] By formula Calculate the network quality score WZP of the communication device under test; where WDK is the network bandwidth, CSL is the transmission rate, DBL is the packet loss rate, and WYC is the network delay; a1, a2, a3, and a4 are all proportional coefficients greater than 0, and the values ​​of a1, a2, a3, and a4 are set by relevant experts based on experience; K is the environmental correction coefficient, which is calculated based on the device environment data.

[0060] For example, the proportional coefficients a1=0.2, a2=5, a3=1.5, and a4=2 are set; the network bandwidth WDK=100Mbps, the transmission rate CSL=8MB / s, the packet loss rate DBL=3%, and the network delay WYC=0.025s; and the network quality score WZP≈3.01 of the communication device under test is obtained by calculation through the formula.

[0061] It should be noted that the values ​​of the proportional coefficients a1, a2, a3, and a4 are related to the service life of the communication equipment under test; when the service life of the communication equipment under test is older, the actual values ​​of the proportional coefficients a1, a2, a3, and a4 are set to be smaller.

[0062] In this embodiment, the environmental correction coefficient is calculated based on the device environment data, including:

[0063] Extracting device environment data of the communication device under test; wherein the device environment data includes device temperature, rainfall, and wind speed;

[0064] By formula Calculate the environmental correction coefficient K; where SWD is the equipment temperature, JYL is the rainfall, and FS is the wind speed; b1, b2, and b3 are all proportional coefficients greater than 0. The specific values ​​of b1, b2, and b3 are set by relevant experts based on experience.

[0065] For example, the proportional coefficients b1=0.1, b2=0.1, and b3=1 are set; the equipment temperature SWD=42° C., the rainfall JYL=24 mm / day, and the wind speed FS=3 m / s; and the environmental correction coefficient K≈2.70 is calculated by the formula.

[0066] In this embodiment, the environmental correction coefficient can also be obtained through a correction coefficient generation model. The training process of the correction coefficient generation model includes:

[0067] Extract several groups of equipment environment data and environmental correction coefficients and integrate them into several groups of original data, use 80% of the original data as training data and 20% as test data; use the training data to train the artificial intelligence model; use the test data to test the trained artificial intelligence model, and adjust the artificial intelligence model according to the test results; finally obtain a correction coefficient generation model with equipment environment data as input and environmental correction coefficient as output; wherein the artificial intelligence model includes a BP neural network model or an RBF neural network model.

[0068] In this embodiment, linear fitting is performed on the network quality scores of several consecutive periods, including:

[0069] The network quality scores of several consecutive periods are extracted; time is used as the independent variable and the network quality score is used as the dependent variable, and the network status change curve is obtained through linear fitting.

[0070] In this embodiment, the performance analysis based on the network status change curve includes:

[0071] Extracting the network status change curve to obtain the network status standard curve of the communication equipment under test when it leaves the factory; wherein the network status standard curve is obtained by linear fitting the network quality score of the communication equipment under test when it leaves the factory;

[0072] Calculate the difference between the network state change curve and the network state standard curve to obtain a network state difference curve; perform an integration operation on the network state difference curve to obtain a state difference cumulative value;

[0073] Determine the proportion of network status abnormality duration based on the network status change curve and the network status standard curve;

[0074] Calculate the first-order derivative function of the network state change curve and take the absolute value to obtain the network state fluctuation function; calculate the average value between the maximum function value and the minimum function value of the network state fluctuation function to obtain the state fluctuation value;

[0075] The cumulative value of status difference, the proportion of network status abnormality duration and the status fluctuation value are integrated into performance evaluation indicators.

[0076] The present invention extracts the network status change curve during device operation and combines it with the standard curve obtained by linear fitting based on the quality score at the time of shipment to construct a difference curve and calculate its integral to obtain the cumulative value of the state difference, thereby quantitatively reflecting the overall deviation degree of the network status. Furthermore, by identifying the intersection of the change curve and the standard curve, the abnormal interval is accurately divided and the abnormal duration ratio is calculated to achieve a quantitative assessment of the persistence of network abnormalities. The maximum and minimum values ​​of the absolute value of the first-order derivative of the change curve are then averaged to obtain the state fluctuation value to measure the stability of the network status. Finally, the cumulative value of the state difference, the abnormal duration ratio, and the state fluctuation value are integrated into a comprehensive performance evaluation index, which can comprehensively and objectively reflect the actual operating performance of the communication equipment in the network environment.

[0077] In this embodiment, determining the network status abnormality duration ratio based on the network status change curve and the network status standard curve includes:

[0078] Extract the network status change curve and the network status standard curve to obtain the monitoring cycle duration;

[0079] The time point where the network status change curve intersects the network status standard curve is marked as a network abnormal point;

[0080] According to the time sequence of several network anomaly points, the interval between two adjacent network anomaly points is marked as an anomaly interval;

[0081] Calculate the sum of the durations corresponding to several abnormal intervals to obtain the cumulative value of abnormal duration;

[0082] Calculate the ratio of the accumulated abnormal duration to the monitoring period to obtain the proportion of network status abnormal duration.

[0083] For example, a total of 3 abnormal intervals are set, the duration corresponding to abnormal interval 1 is 2s, the duration corresponding to abnormal interval 2 is 1s, and the duration corresponding to abnormal interval 3 is 3s; the monitoring cycle duration is 60s; the sum of the durations corresponding to several abnormal intervals is calculated, and the cumulative value of the abnormal duration is 6s; the ratio of the cumulative value of the abnormal duration to the monitoring cycle duration is calculated, and the proportion of the abnormal duration of the network status is 0.1.

[0084] By extracting the intersection of the actual operating curve and the standard reference curve as the start and end points of the anomaly, the present invention can accurately divide the network anomaly interval and then calculate the cumulative value of the anomaly duration and its proportion in the monitoring period. This method fully utilizes the dynamic characteristics of the curve, improves the accuracy and objectivity of network anomaly identification, and avoids the risk of misjudgment in traditional fixed threshold methods. The proportion of anomaly duration obtained by performing a time integration operation on the anomaly interval can quantitatively reflect the stability of network operation, providing a reliable basis for network performance evaluation and service quality optimization.

[0085] In this embodiment, the performance status of the communication device to be tested is determined based on several performance evaluation indicators, including:

[0086] Extracting several performance evaluation indicators of the communication equipment under test;

[0087] Calculating a performance evaluation coefficient of the communication device under test based on a number of performance evaluation indicators;

[0088] If the performance evaluation coefficient is greater than a preset evaluation threshold, the performance status of the communication device to be tested is marked as abnormal performance; wherein the performance status includes normal performance and abnormal performance.

[0089] Exemplarily, the performance evaluation coefficient of the communication device under test is set to 2.76, and the preset evaluation threshold is 4; since the performance evaluation coefficient of the communication device under test is less than the preset evaluation threshold, the performance status of the communication device under test is marked as abnormal performance.

[0090] It should be noted that, when the performance evaluation coefficient of the communication device to be tested is smaller, it means that the overall performance of the communication device to be tested is worse.

[0091] In this embodiment, the performance evaluation coefficient of the communication device under test is calculated based on several performance evaluation indicators, including:

[0092] Extract several performance evaluation indicators; through the formula Calculate the performance evaluation coefficient XNP of the communication equipment under test; where ZLJ is the cumulative value of the state difference, YCZ is the proportion of the network state abnormality duration, and ZBD is the state fluctuation value; c1, c2, and c3 are all proportional coefficients greater than 0, and the values ​​of c1, c2, and c3 are set by relevant experts based on experience.

[0093] Exemplarily, the proportional coefficients c1=1, c2=0.5, and c3=2 are set; the cumulative value of state difference ZLJ=5, the proportion of network state abnormality duration YCZ=10%, and the state fluctuation value ZBD=0.05; the performance evaluation coefficient XNP≈2.76 of the communication equipment to be tested is obtained by calculation through the formula.

[0094] A second aspect of the present invention provides a communication equipment performance evaluation device, comprising: a data processing module, and a data acquisition module and a performance evaluation module connected thereto;

[0095] Data acquisition module: used to obtain network status data and device environment data of the communication device under test;

[0096] Data processing module: used to calculate the network quality score of the communication device under test based on the network status data and device environment data; perform linear fitting on the network quality scores of several consecutive periods to obtain a network status change curve; perform performance analysis based on the network status change curve to obtain several performance evaluation indicators;

[0097] Performance evaluation module: used to determine the performance status of the communication device under test based on several performance evaluation indicators.

[0098] A second embodiment of the present invention provides a communication device performance evaluation device, including:

[0099] Some of the data in the above formula are calculated by removing the dimensions and taking their numerical values. The formula is a formula that is closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0100] Working principle of the present invention:

[0101] The present invention obtains network status data and device environment data of a communication device to be tested; calculates a network quality score of the communication device to be tested based on the network status data and the device environment data; performs linear fitting on the network quality scores of several consecutive periods to obtain a network status change curve; performs performance analysis based on the network status change curve to obtain several performance evaluation indicators; and determines the performance status of the communication device to be tested based on the several performance evaluation indicators.

[0102] The above embodiments are only used to illustrate the technical method of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A communication equipment performance evaluation method, characterized in that: include: Obtain network status data and device environment data of the communication device under test; Calculate the network quality score of the communication device under test based on the network status data and the device environment data; Perform linear fitting on the network quality scores of several consecutive periods to obtain the network status change curve; Perform performance analysis based on the network status change curve to obtain several performance evaluation indicators; The performance status of the communication device under test is determined based on several performance evaluation indicators.

2. A communication equipment performance evaluation method according to claim 1, characterized in that: The calculating of the network quality score of the communication device to be tested based on the network status data and the device environment data includes: Extracting network status data and device environment data of the communication device under test; wherein the network status data includes network bandwidth, transmission rate, packet loss rate, and network delay; By formula Calculate the network quality score WZP of the communication device under test; where WDK is the network bandwidth, CSL is the transmission rate, DBL is the packet loss rate, and WYC is the network delay; a1, a2, a3, and a4 are all proportional coefficients greater than 0; K is the environmental correction coefficient, which is calculated based on the device environment data.

3. A communication equipment performance evaluation method according to claim 2, characterized in that: The environmental correction factor is calculated based on the equipment environment data, including: Extracting device environment data of the communication device under test; wherein the device environment data includes device temperature, rainfall, and wind speed; By formula Calculate the environmental correction factor K; where SWD is the device temperature, JYL is the rainfall, and FS is the wind speed; b1, b2, and b3 are all proportional coefficients greater than 0.

4. A communication equipment performance evaluation method according to claim 2, characterized in that: The environmental correction coefficient can also be obtained through a correction coefficient generation model. The training process of the correction coefficient generation model includes: Extract several groups of equipment environment data and environmental correction coefficients, and integrate them into several groups of training data and test data; use the training data to train the artificial intelligence model; use the test data to test the trained artificial intelligence model, and adjust the artificial intelligence model according to the test results; finally obtain a correction coefficient generation model with the equipment environment data as input and the environmental correction coefficient as output; wherein the artificial intelligence model includes a BP neural network model or an RBF neural network model.

5. A communication equipment performance evaluation method according to claim 1, characterized in that: The linear fitting of the network quality scores of a plurality of consecutive periods includes: The network quality scores of several consecutive periods are extracted; time is used as the independent variable and the network quality score is used as the dependent variable, and the network status change curve is obtained through linear fitting.

6. A communication equipment performance evaluation method according to claim 1, characterized in that: The performance analysis based on the network status change curve includes: Extracting the network status change curve to obtain the network status standard curve of the communication equipment under test when it leaves the factory; wherein the network status standard curve is obtained by linear fitting the network quality score of the communication equipment under test when it leaves the factory; Calculate the difference between the network state change curve and the network state standard curve to obtain a network state difference curve; perform an integration operation on the network state difference curve to obtain a state difference cumulative value; Determine the proportion of network status abnormality duration based on the network status change curve and the network status standard curve; Calculate the first-order derivative function of the network state change curve and take the absolute value to obtain the network state fluctuation function; calculate the average value between the maximum function value and the minimum function value of the network state fluctuation function to obtain the state fluctuation value; The cumulative value of status difference, the proportion of network status abnormality duration and the status fluctuation value are integrated into performance evaluation indicators.

7. A communication equipment performance evaluation method according to claim 6, characterized in that: Determining the network status abnormality duration ratio based on the network status change curve and the network status standard curve includes: Extract the network status change curve and the network status standard curve to obtain the monitoring cycle duration; The time point where the network status change curve intersects the network status standard curve is marked as a network abnormal point; According to the time sequence of several network anomaly points, the interval between two adjacent network anomaly points is marked as an anomaly interval; Calculate the sum of the durations corresponding to several abnormal intervals to obtain the cumulative value of abnormal duration; Calculate the ratio of the accumulated abnormal duration to the monitoring period to obtain the proportion of network status abnormal duration.

8. A communication equipment performance evaluation method according to claim 1, characterized in that: Determining the performance status of the communication device to be tested based on a number of performance evaluation indicators includes: Extracting several performance evaluation indicators of the communication equipment under test; Calculating a performance evaluation coefficient of the communication device under test based on a number of performance evaluation indicators; If the performance evaluation coefficient is less than a preset evaluation threshold, the performance status of the communication device to be tested is marked as abnormal performance; wherein the performance status includes normal performance and abnormal performance.

9. A communication equipment performance evaluation method according to claim 8, characterized in that: The calculation of the performance evaluation coefficient of the communication device to be tested based on a plurality of performance evaluation indicators includes: Extract several performance evaluation indicators; through the formula Calculate the performance evaluation coefficient XNP of the communication equipment under test; where ZLJ is the cumulative value of the state difference, YCZ is the proportion of the network state abnormality duration, and ZBD is the state fluctuation value; c1, c2, and c3 are all proportional coefficients greater than 0.

10. A communication equipment performance evaluation device, used to implement a communication equipment performance evaluation method according to any one of claims 1 to 9, characterized in that: include: Data processing module, and the data acquisition module and performance evaluation module connected thereto; The data acquisition module is used to obtain network status data and device environment data of the communication device under test; The data processing module is used to calculate the network quality score of the communication device under test based on the network status data and the device environment data; perform linear fitting on the network quality scores of several consecutive cycles to obtain a network status change curve; Perform performance analysis based on the network status change curve to obtain several performance evaluation indicators; The performance evaluation module is used to determine the performance status of the communication device to be tested based on a number of performance evaluation indicators.

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