Terminal access exception identification method, device, equipment, medium and program product

Abstract

The application relates to the technical field of communication, and provides a terminal access anomaly identification method, device, equipment, medium and program product. The method comprises the following steps: obtaining running data of a target terminal under a target base station, and generating a data identity of the target terminal according to the running data; matching the data identity with an identity template of the target base station, and calculating the dispersion degree of the data identity and the identity template; identifying whether the wireless access of the target terminal is abnormal according to the dispersion degree; the identity template is generated based on historical data identities of each terminal historically accessed to the target base station and corresponding abnormal labels of the historical data identities; and the historical data identities are generated based on historical running data of each terminal under the target base station. Through matching of the terminal data identity and the identity template, the dispersion degree of the two is calculated, the anomaly of the wireless access of the terminal can be quickly identified, timely processing of the access anomaly is facilitated, and the service operation quality of the terminal point is ensured.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, apparatus, device, medium and program product for identifying abnormal terminal access. Background Technology

[0002] With the continuous expansion of 5G private network applications, wireless access issues for terminals in mobile application scenarios are becoming increasingly prominent. For example, without adjusting the antenna tilt angle and power of the 5G terminal and base station, the terminal can normally use the 5G network for data transmission. However, in mobile private network application scenarios, changes in terminal location can lead to changes in the received wireless signal strength, channel, and access station. Currently, the network quality of the terminal is not correlated with its location, and terminal quality issues are not correlated with base station access problems. In this situation, due to the mobility of the terminal, when a wireless access anomaly occurs, maintenance personnel cannot quickly locate the problem and can only wait for the fault to reproduce before analyzing and judging the anomaly. This analysis and handling of the anomaly has a certain lag, affecting the service operation quality of the terminal location. Summary of the Invention

[0003] This application provides a terminal access anomaly identification method, device, equipment, medium, and program product to solve the defects in existing terminal wireless access anomaly handling, such as the inability of maintenance personnel to quickly locate anomalies, the lag in anomaly analysis and processing, and the potential impact on the service operation quality of terminal locations.

[0004] This application provides a method for identifying abnormal terminal access, including:

[0005] Obtain the operating data of the target terminal under the target base station, and generate the data identity of the target terminal based on the operating data;

[0006] The data identity is matched with the identity template of the target base station, and the dispersion of the data identity and the identity template is calculated.

[0007] The discrepancy is used to identify whether there is an anomaly in the wireless access of the target terminal;

[0008] The identity template is generated based on the historical data identities of each terminal that has historically accessed the target base station, as well as the abnormal tags corresponding to the historical data identities. The historical data identities are generated based on the historical operating data of each terminal under the target base station.

[0009] In one embodiment, the data identity includes the terminal location of the target terminal and the service quality index of the target terminal at the terminal location; the step of matching the data identity with the identity template of the target base station and calculating the dispersion of the data identity and the identity template includes:

[0010] The data identity is matched with the identity template of the target base station to obtain a target identity template that matches the terminal location in the data identity;

[0011] Based on a preset relative entropy algorithm, the dispersion of the service quality indicators in the data identity and the service quality indicators in the target identity template is calculated; the service quality indicators include at least one of latency, jitter, uplink physical resource block utilization, and access success rate.

[0012] In one embodiment, the operational data includes the terminal location of the target terminal and operational quality data of the target terminal at the terminal location; generating the data identity of the target terminal based on the operational data includes:

[0013] The terminal location in the operational data is correlated with the operational quality data to determine the operational quality of the target base station at the terminal location;

[0014] Based on the operational quality, determine the health of each service quality indicator of the target base station at the terminal location;

[0015] Based on the health status and the terminal location, the data identity of the target terminal is generated.

[0016] In one embodiment, before matching the data identity with the identity template of the target base station and calculating the dispersion of the data identity and the identity template, the method further includes:

[0017] Acquire historical operational data of each terminal of the target base station within a historical time period of a first preset duration; the historical operational data includes historical terminal location and historical identity data, and the historical identity data includes operational quality data, base station access information, and base station operational indicators.

[0018] The historical terminal location and historical identity data in the historical operation data are correlated to determine the historical operation quality of the target base station at each of the historical terminal locations;

[0019] Based on the historical operational quality, the historical health of the service quality indicators of the target base station at each of the historical terminal locations is determined;

[0020] Based on the historical terminal location and the historical health status, a historical data identity is generated for each terminal;

[0021] The historical data identities of each terminal are superimposed to obtain the identity template of the target base station.

[0022] In one embodiment, the historical identity data further includes base station alarm information of the target base station; the step of overlaying the historical identity data of each terminal to obtain the identity template of the target base station includes:

[0023] Based on the base station alarm information in the historical identity data, identify abnormal and normal locations in the locations of each historical terminal.

[0024] A baseline quality operation database is generated based on the historical data identity of the normal locations, and an abnormal quality operation database is generated based on the historical data identity of the abnormal locations. The abnormal quality operation database is then associated with the base station alarm information.

[0025] The abnormal quality operation database is superimposed on the baseline quality operation database to obtain the identity template of the target base station.

[0026] In one embodiment, after identifying whether the wireless access of the target terminal is abnormal based on the discreteness, the method further includes:

[0027] If the wireless access of the target terminal is abnormal, the target operation data of the target terminal during a historical time period of a second preset duration is obtained, and a target quality operation database of the target terminal is generated based on the target operation data.

[0028] Based on a preset relative entropy algorithm, the target dispersion of the target quality operation database and the abnormal quality operation database corresponding to the identity template is calculated.

[0029] Based on the target dispersion, obtain the abnormal data identity with the smallest data identity dispersion relative to the target terminal;

[0030] Based on the base station alarm information associated with the abnormal data identity, the abnormal information of the target terminal's wireless access is identified.

[0031] This application embodiment also provides a terminal access anomaly identification device, including:

[0032] The data acquisition module is used to acquire the operational data of the target terminal under the target base station;

[0033] The data identity generation module is used to generate the data identity of the target terminal based on the running data;

[0034] An identity template matching module is used to match the data identity with the identity template of the target base station and calculate the dispersion of the data identity and the identity template.

[0035] An anomaly detection module is used to identify whether there is an anomaly in the wireless access of the target terminal based on the dispersion.

[0036] The identity template is generated based on the historical data identities of each terminal that has historically accessed the target base station, as well as the abnormal tags corresponding to the historical data identities. The historical data identities are generated based on the historical operating data of each terminal under the target base station.

[0037] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of the terminal access anomaly identification method described above.

[0038] This application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the terminal access anomaly identification method as described above.

[0039] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the terminal access anomaly identification method described above.

[0040] The terminal access anomaly identification method, apparatus, device, medium, and program product provided in this application generate the terminal's data identity under the base station by acquiring the terminal's operating data, thereby associating the terminal's operating data and matching it with the base station's identity template, calculating the dispersion between the terminal's data identity and the base station's identity template, realizing rapid identification of terminal wireless access anomalies, which is conducive to timely handling of anomaly issues and ensuring the service operation quality of terminal locations. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a flowchart illustrating the terminal access anomaly identification method provided in this application embodiment;

[0043] Figure 2This is a schematic diagram of the terminal access anomaly identification process provided in the embodiments of this application;

[0044] Figure 3 This is a schematic diagram illustrating the generation of the benchmark quality operation database provided in the embodiments of this application;

[0045] Figure 4 This is a schematic diagram illustrating the generation of the abnormal quality operation database provided in an embodiment of this application;

[0046] Figure 5 This is a schematic diagram of the terminal access anomaly identification device provided in the embodiments of this application;

[0047] Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0049] Figure 1 This is a flowchart illustrating the terminal access anomaly identification method provided in this application embodiment, as shown below. Figure 1 As shown, the method includes the following steps:

[0050] Step 100: Obtain the operating data of the target terminal under the target base station, and generate the data identity of the target terminal based on the operating data;

[0051] Step 200: Match the data identity with the identity template of the target base station, and calculate the dispersion of the data identity and the identity template;

[0052] Step 300: Identify whether there is an anomaly in the wireless access of the target terminal based on the dispersion.

[0053] The identity template is generated based on the historical data identities of each terminal that has historically accessed the target base station, as well as the abnormal tags corresponding to the historical data identities. The historical data identities are generated based on the historical operating data of each terminal under the target base station.

[0054] The system acquires operational data of the target terminal under the target base station and generates a data identity for the target terminal based on the acquired operational data. There can be one or more base stations, and the target base station can be any one of these base stations. Similarly, the target base station can include one or more terminals, and the target terminal can be any one of the multiple terminals under the target base station.

[0055] Optionally, the data identity of the target terminal under the target base station is used to characterize the operation status of the target terminal under the target base station, and may include, but is not limited to, the access status and service quality of the target terminal.

[0056] The generated target terminal's data identity is matched with the target base station's identity template, and the dispersion between the data identity and the identity template is calculated. Based on this dispersion, it is used to identify whether there is any abnormality in the target terminal's wireless access.

[0057] The target base station's identity template is generated based on the historical data identities of each terminal that has historically accessed the target base station, as well as the abnormal tags corresponding to those historical data identities. The historical data identities are generated based on the historical operational data of each terminal under the target base station.

[0058] Optionally, the base station's identity template includes anomaly tags for each terminal location. These anomaly tags characterize whether the data identity at the corresponding terminal location is abnormal, and if so, the type of anomaly. By matching the target terminal's data identity with the target base station's identity template, the identity template with the highest similarity to the target terminal's data identity is selected, and the dispersion between the two is calculated. If the calculated dispersion is less than a preset threshold, it is considered that the target terminal and the identity template share the same anomaly. The anomaly tags of the identity template are used to identify whether the target terminal is abnormal, and if so, the type of anomaly.

[0059] Optionally, the identity template of the target base station includes the data identities of multiple terminals. By matching the data identities of the target terminals with the identity template of the base station, the dispersion of the data identities of the target terminals with those of other terminals can be calculated, which is the dispersion of the operational data of the target terminals with that of other terminals.

[0060] Optionally, if the dispersion is greater than a preset threshold, the wireless access of the target terminal is abnormal; otherwise, if the dispersion is less than or equal to the preset threshold, the wireless access of the target terminal is not abnormal.

[0061] In one embodiment, when matching the data identity of the target terminal under the target base station with the identity template of the target base station, the operating data of the target terminal in the most recent period is obtained to form an operating database. The first dispersion of the data identity of the target terminal under the target base station and the identity template of the target base station, and the second dispersion of the operating database and the identity template of the target base station are calculated respectively. If the first dispersion is greater than the second dispersion, the wireless access of the target terminal under the target base station is abnormal.

[0062] In some embodiments, the acquired operational data of the target terminal under the target base station is operational data at any given moment, and the generated data identity of the target terminal is the data identity of the target terminal at that moment, which is used as the first data identity of the target terminal. When matching the data identity of the target terminal with the identity template of the target base station, the operational data of the target terminal within a preset time period is acquired, and the data identity of the target terminal within that time period is generated, which is used as the second data identity of the target terminal. Then, a first dispersion between the first data identity of the target terminal and the identity template of the target base station, and a second dispersion between the second data identity of the target terminal and the identity template of the target base station are calculated respectively. If the first dispersion is greater than the second dispersion, the wireless access of the target terminal under the target base station is abnormal.

[0063] In this embodiment, the terminal's data identity under the base station is generated by acquiring the terminal's operating data. The terminal's operating data is then associated with the base station's identity template and matched with the identity template. The dispersion between the terminal's data identity and the base station's identity template is calculated, enabling rapid identification of abnormal wireless access of the terminal. This facilitates timely handling of abnormal issues and ensures the service operation quality of the terminal location.

[0064] In one embodiment, the generated data identity of the target terminal includes the terminal location of the target terminal and the service quality indicators of the target terminal at that location. That is, by generating the data identity of the target terminal, the location and operational quality of the target terminal are correlated. Based on this, in step 200, the data identity of the target terminal is matched with the identity template of the target base station, and the dispersion between the data identity and the identity template is calculated. Specifically, this includes:

[0065] Step 210: Match the data identity with the identity template of the target base station to obtain a target identity template that matches the terminal location in the data identity;

[0066] Step 220: Based on a preset relative entropy algorithm, calculate the dispersion of the service quality indicators in the data identity and the service quality indicators in the target identity template; the service quality indicators include at least one of latency, jitter, uplink physical resource block utilization, and access success rate.

[0067] The base station has multiple identity templates, each corresponding to a data identity. The target terminal's data identity is matched against the target base station's identity templates to obtain a target identity template that matches the terminal location of the data identity. If the terminal location in the target identity template is the same as or close to the terminal location in the target terminal's data identity, a preset relative entropy algorithm is used to calculate the dispersion between the service quality indicators in the data identity and the service quality indicators in the target identity template. This dispersion is the difference between the target terminal's data identity and the target base station's identity template.

[0068] Optionally, service quality metrics include at least one of latency, jitter, uplink physical resource block utilization, and access success rate.

[0069] In one embodiment, the operational data of the target terminal under the target base station includes the terminal location of the target terminal and the operational quality data of the target terminal at the terminal location. When generating the data identity of the target terminal, it is necessary to associate the terminal location with the operational quality data. Therefore, step 100, generating the data identity of the target terminal based on the operational data of the target terminal, includes:

[0070] Step 110: Associate the terminal location in the operation data with the operation quality data to determine the operation quality of the target base station at the terminal location;

[0071] Step 120: Determine the health of each service quality indicator of the target base station at the terminal location based on the operational quality;

[0072] Step 130: Generate the data identity of the target terminal based on the health status and the terminal location.

[0073] The terminal location in the operational data is correlated with the operational quality data to determine the operational quality of the target base station at that terminal location. This operational quality is determined by service quality indicators. Furthermore, based on the operational quality of the target base station at that terminal location, the health of various service quality indicators of the target base station at that terminal location is determined. These service quality indicator health indicators include latency health, jitter health, uplink physical resource block utilization health, and access success rate health.

[0074] Based on the health status of the target base station at the terminal location, the data identity of the target terminal is generated. In one embodiment, based on the health status of the service quality indicators of the target base station at the terminal location, the unhealthiness of the service quality indicators is determined, and the data identity of the target terminal is generated based on the unhealthiness.

[0075] For example, the location of the target terminal is represented by latitude and longitude, and service quality indicators such as latency, jitter, uplink physical resource block utilization, and access success rate are used as the identity data basis for the target terminal. The data identity of the target terminal is generated according to the following formula 1:

[0076] (1)

[0077] in, This indicates the data identity of terminal numbered m at time n, where n is also the time when the target terminal's running data was collected; Let D represent the unhealthiness of the delay D of terminal number m at time n. The unhealthiness of the jitter S at time n is represented by terminal number m. U represents the unhealthiness of the uplink physical resource block utilization rate U of terminal number m at time n. The unhealthiness of the access success rate I of terminal number m at time n is represented by this value. This represents the unhealthiness level of alarm data A at time n.

[0078] Furthermore, , , , In other words, the unhealthiness of a business quality indicator is the ratio of its value at any given time to its maximum value. Optionally, the sum of the healthiness and unhealthiness of the same business quality indicator is 1.

[0079] Reference Figure 2 The illustrated abnormal identification process for terminal wireless access mainly includes stages such as data collection, data association, data identity generation, and identity template matching. Specifically, in the data collection stage, the terminal's operational data under the base station is collected, including the terminal's location and operational quality data. In the data association stage, the terminal's location and operational quality data are associated. In the data identity generation stage, the terminal's data identity is generated according to the method shown in Formula 1 above. In the identity template matching stage, the terminal's data identity is matched with the base station's identity template to identify whether there is an abnormality in the terminal's wireless access.

[0080] Optionally, when the acquired terminal's running data packet contains the terminal's location, by matching the terminal's data identity with the base station's identity template, it is possible to quickly identify whether there is an anomaly in the terminal's wireless access at that location. While quickly identifying the terminal's access anomaly, it is also possible to locate the abnormal terminal location.

[0081] In some embodiments, before matching the data identity of the target terminal with the identity template of the target base station and calculating the dispersion of the data identity of the target terminal with the identity template of the target base station, the method may further include:

[0082] Step 201: Obtain historical operating data of each terminal of the target base station within a historical time period of a first preset duration; the historical operating data includes historical terminal location and historical identity data, and the historical identity data includes operating quality data, base station access information and base station operating indicators;

[0083] Step 202: Associate the historical terminal location and historical identity data in the historical operation data to determine the historical operation quality of the target base station at each of the historical terminal locations;

[0084] Step 203: Determine the historical health of the service quality indicators of the target base station at each of the historical terminal locations based on the historical operational quality.

[0085] Step 204: Generate the historical data identity of each terminal based on the historical terminal location and the historical health status;

[0086] Step 205: Overlay the historical data identities of each terminal to obtain the identity template of the target base station.

[0087] When generating the identity template of the target base station, firstly, the historical operation data of each terminal of the target base station within a historical time period of a first preset duration is obtained. The historical operation data includes the historical terminal location of each terminal and the historical identity data at each historical terminal location. The historical identity data is used to generate the identity template of the target base station with the historical terminal location.

[0088] Optionally, historical identity data includes terminal operational quality data, base station access information, and base station operational metrics. The historical time period corresponding to the first preset duration can be a relatively long period. In some embodiments, all historical operational data of the target base station can be obtained to generate a map-level identity template.

[0089] Specifically, when generating the identity template, the historical terminal locations and historical identity data in historical operation are associated to determine the historical operation quality of the target base station at each historical terminal location. Based on the historical operation quality, the historical health of the service quality indicators of the target base station at each historical terminal location is determined. Based on the historical terminal location and historical health of each terminal, the historical data identity of each terminal is generated. The historical data identities of different terminals are superimposed to obtain the identity template of the target base station.

[0090] Optionally, the historical terminal location and historical identity data in the historical operation data can be correlated, including the correlation between historical terminal location and operation quality data, the correlation between historical terminal location and base station access information, and the correlation between historical terminal location and base station operation indicators.

[0091] Optionally, the data identity of any terminal can be stored in a multidimensional information database. The formal representation of is shown in Formula 2 below:

[0092] (2)

[0093] In Formula 2, These are the latitude and longitude coordinates of the terminal's location. This indicates the base station ID that the terminal is connected to.

[0094] Based on the multidimensional information database corresponding to the terminal's data identity The base station ID is determined by overlaying the data identities of m terminals under the same base station into a multi-dimensional information database. This generates identity templates for selected base stations, thereby obtaining a quality operation database for massive terminal access under large-scale base station coverage conditions. .like Figure 3 As shown, by overlaying the location data identities from B1 to Bn, the data identities of n terminals are overlaid, generating a quality operation database Q, which serves as the identity template for each base station for efficient matching of the operation data of the access terminals.

[0095] In some embodiments, the historical identity data of the base station also includes base station alarm information, such as alarm data A in Formula 1 above. The association between historical terminal location and historical identity data also includes the association between historical terminal location and base station alarm information. Optionally, the identity template of the base station includes a normal identity template and an abnormal identity template. In step 205, the historical identity data of each terminal is superimposed to obtain the identity template of the target base station, including:

[0096] Step 215: Based on the base station alarm information in the historical identity data, identify abnormal and normal locations in each of the historical terminal locations;

[0097] Step 225: Generate a baseline quality operation database based on the historical data identity of the normal locations, and generate an abnormal quality operation database based on the historical data identity of the abnormal locations, and associate the abnormal quality operation database with the base station alarm information;

[0098] Step 235: Overlay the abnormal quality operation database onto the benchmark quality operation database to obtain the identity template of the target base station.

[0099] Based on base station alarm information in historical identity data, abnormal and normal locations in each historical terminal location are identified. A baseline quality operation database is generated based on the historical data identities at normal locations, and an abnormal quality operation database is generated based on the historical data identities at abnormal locations. The abnormal quality operation database is associated with base station alarm information, thereby using the base station alarm information as anomaly tags for each abnormal data identity in the abnormal quality operation database.

[0100] Furthermore, the abnormal quality operation database is overlaid onto the baseline quality operation database to obtain the base station's identity template.

[0101] In some embodiments, a baseline quality operation database Q can be obtained by overlaying a long-term database of quality operation data without anomalies, and an abnormal quality operation database can be generated based on the data identity and location analysis results of abnormal data points. Abnormal quality operation database The generation principle is as follows Figure 4 As shown. In the historical terminal locations of n terminals, abnormal locations are identified based on base station alarm information. The data identities at these abnormal locations (B1 to Bn) are overlaid to obtain an abnormal quality operation database. An anomaly database is obtained by overlaying outlier points onto the quality operation database Q. It identifies and records abnormal locations based on base station alarm information and associates them with abnormal alarms from the base station.

[0102] Optionally, when a base station experiences a fault that affects services, the fault will impact access at surrounding locations, generating abnormal locations and associated with fault alarms, thus forming an abnormal quality operation database. Optionally, different faults or quality issues may generate different abnormal quality operation databases, or, within the same abnormal quality operation database, different faults or quality issues may be identified using different abnormal tags to distinguish different fault types.

[0103] In some embodiments, after identifying whether there is an anomaly in the wireless access of the target terminal based on the calculated dispersion, the method may further include:

[0104] Step 301: If the wireless access of the target terminal is abnormal, the target terminal's target operation data for a historical time period of a second preset duration is obtained, and a target quality operation database of the target terminal is generated based on the target operation data.

[0105] Step 302: Based on the preset relative entropy algorithm, calculate the target dispersion of the target quality operation database and the abnormal quality operation database corresponding to the identity template;

[0106] Step 303: Obtain the abnormal data identity with the smallest data identity dispersion relative to the target terminal based on the target dispersion;

[0107] Step 304: Identify the abnormal information of the target terminal's wireless access based on the base station alarm information associated with the abnormal data identity.

[0108] If the target terminal's wireless access is abnormal, the system acquires the target terminal's historical operational data for a second preset time period and generates a target quality operational database based on this data. Using a preset relative entropy algorithm, it calculates the target dispersion between the target quality operational database and the abnormal quality operational database corresponding to the identity template. Based on the calculated target dispersion, it acquires the abnormal data identity with the smallest dispersion relative to the target terminal's data identity. Then, based on the base station alarm information associated with this abnormal data identity, it identifies the abnormal information of the target terminal's wireless access, including but not limited to the abnormality type.

[0109] The second preset duration is different from the first preset duration. Optionally, the second preset duration is much shorter than the first preset duration.

[0110] In some embodiments, the target quality operation database can also be acquired before identifying whether there is an anomaly in the wireless access of the target terminal based on the dispersion, and the anomaly in the wireless access of the target terminal can be identified based on the data identity of the target terminal and the target quality operation database.

[0111] To obtain the daily operating data of the target terminal and generate a target quality operating database. For example, the data identity B of the terminal at any given time is compared with the target quality operating database. Each sample is matched against the baseline quality operating database Q, and the dispersion is calculated based on the relative entropy algorithm, as shown in the following formulas 3-4:

[0112] (3)

[0113] (4)

[0114] like If the target terminal's wireless access is abnormal, the relative entropy algorithm can be used again to calculate the dispersion, and the identity template corresponding to the abnormal quality running database with the smallest data identity dispersion with the target terminal can be obtained:

[0115] (5)

[0116] By matching the target terminal's data identity B with the database of abnormal quality with the smallest dispersion, i.e. the most suitable database, the access anomalies of the target terminal can be quickly located and identified, which helps to speed up fault handling.

[0117] In this embodiment, by constructing a baseline quality operation database and an abnormal quality operation database for the base station, and superimposing the abnormal quality operation database onto the baseline quality operation database as an identity template for the base station, the abnormal terminal and its location can be quickly identified through discreteness matching, and the cause of the abnormality can be quickly identified, thereby accelerating the analysis and repair of base station fault locations and improving operation and maintenance efficiency.

[0118] The terminal access anomaly identification device provided in the embodiments of this application is described below. The terminal access anomaly identification device described below can be referred to in correspondence with the terminal access anomaly identification method described above.

[0119] Reference Figure 5 The terminal access anomaly identification device provided in this application embodiment includes:

[0120] Data acquisition module 10 is used to acquire the operating data of the target terminal under the target base station;

[0121] Data identity generation module 20 is used to generate the data identity of the target terminal based on the running data;

[0122] The identity template matching module 30 is used to match the data identity with the identity template of the target base station and calculate the dispersion of the data identity and the identity template.

[0123] Anomaly identification module 40 is used to identify whether there is an anomaly in the wireless access of the target terminal based on the dispersion.

[0124] The identity template is generated based on the historical data identities of each terminal that has historically accessed the target base station, as well as the abnormal tags corresponding to the historical data identities. The historical data identities are generated based on the historical operating data of each terminal under the target base station.

[0125] In one embodiment, the data identity includes the terminal location of the target terminal and the service quality index of the target terminal at the terminal location; the identity template matching module 30 is further configured to:

[0126] The data identity is matched with the identity template of the target base station to obtain a target identity template that matches the terminal location in the data identity;

[0127] Based on a preset relative entropy algorithm, the dispersion of the service quality indicators in the data identity and the service quality indicators in the target identity template is calculated; the service quality indicators include at least one of latency, jitter, uplink physical resource block utilization, and access success rate.

[0128] In one embodiment, the operational data includes the terminal location of the target terminal and operational quality data of the target terminal at the terminal location; the data identity generation module 20 is further configured to:

[0129] The terminal location in the operational data is correlated with the operational quality data to determine the operational quality of the target base station at the terminal location;

[0130] Based on the operational quality, determine the health of each service quality indicator of the target base station at the terminal location;

[0131] Based on the health status and the terminal location, the data identity of the target terminal is generated.

[0132] In one embodiment, the terminal access anomaly identification device further includes an identity template generation module, used for:

[0133] Acquire historical operational data of each terminal of the target base station within a historical time period of a first preset duration; the historical operational data includes historical terminal location and historical identity data, and the historical identity data includes operational quality data, base station access information, and base station operational indicators.

[0134] The historical terminal location and historical identity data in the historical operation data are correlated to determine the historical operation quality of the target base station at each of the historical terminal locations;

[0135] Based on the historical operational quality, the historical health of the service quality indicators of the target base station at each of the historical terminal locations is determined;

[0136] Based on the historical terminal location and the historical health status, a historical data identity is generated for each terminal;

[0137] The historical data identities of each terminal are superimposed to obtain the identity template of the target base station.

[0138] In one embodiment, the historical identity data further includes base station alarm information of the target base station; the identity template generation module is further configured to:

[0139] Based on the base station alarm information in the historical identity data, identify abnormal and normal locations in the locations of each historical terminal.

[0140] A baseline quality operation database is generated based on the historical data identity of the normal locations, and an abnormal quality operation database is generated based on the historical data identity of the abnormal locations. The abnormal quality operation database is then associated with the base station alarm information.

[0141] The abnormal quality operation database is superimposed on the baseline quality operation database to obtain the identity template of the target base station.

[0142] In one embodiment, the terminal access anomaly identification device further includes an anomaly analysis module, used for:

[0143] If the wireless access of the target terminal is abnormal, the target operation data of the target terminal during a historical time period of a second preset duration is obtained, and a target quality operation database of the target terminal is generated based on the target operation data.

[0144] Based on a preset relative entropy algorithm, the target dispersion of the target quality operation database and the abnormal quality operation database corresponding to the identity template is calculated.

[0145] Based on the target dispersion, obtain the abnormal data identity with the smallest data identity dispersion relative to the target terminal;

[0146] Based on the base station alarm information associated with the abnormal data identity, the abnormal information of the target terminal's wireless access is identified.

[0147] Figure 6 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 6 As shown, the electronic device may include: a processor 610, a communications interface 620, a memory 630, and a communication bus 640, wherein the processor 610, the communications interface 620, and the memory 630 communicate with each other via the communication bus 640. The processor 610 can call logical instructions in the memory 630 to execute the steps of the terminal access anomaly identification method, such as including:

[0148] Obtain the operating data of the target terminal under the target base station, and generate the data identity of the target terminal based on the operating data;

[0149] The data identity is matched with the identity template of the target base station, and the dispersion of the data identity and the identity template is calculated.

[0150] The discrepancy is used to identify whether there is an anomaly in the wireless access of the target terminal;

[0151] The identity template is generated based on the historical data identities of each terminal that has historically accessed the target base station, as well as the abnormal tags corresponding to the historical data identities. The historical data identities are generated based on the historical operating data of each terminal under the target base station.

[0152] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0153] On the other hand, this application also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can perform the steps of the terminal access anomaly identification method provided in the above embodiments, such as including:

[0154] Obtain the operating data of the target terminal under the target base station, and generate the data identity of the target terminal based on the operating data;

[0155] The data identity is matched with the identity template of the target base station, and the dispersion of the data identity and the identity template is calculated.

[0156] The discrepancy is used to identify whether there is an anomaly in the wireless access of the target terminal;

[0157] The identity template is generated based on the historical data identities of each terminal that has historically accessed the target base station, as well as the abnormal tags corresponding to the historical data identities. The historical data identities are generated based on the historical operating data of each terminal under the target base station.

[0158] In another aspect, this application also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the terminal access anomaly identification method provided in the above embodiments, including, for example:

[0159] Obtain the operating data of the target terminal under the target base station, and generate the data identity of the target terminal based on the operating data;

[0160] The data identity is matched with the identity template of the target base station, and the dispersion of the data identity and the identity template is calculated.

[0161] The discrepancy is used to identify whether there is an anomaly in the wireless access of the target terminal;

[0162] The identity template is generated based on the historical data identities of each terminal that has historically accessed the target base station, as well as the abnormal tags corresponding to the historical data identities. The historical data identities are generated based on the historical operating data of each terminal under the target base station.

[0163] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0164] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0165] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for identifying abnormal terminal access, characterized in that, include: Obtain the operating data of the target terminal under the target base station, and generate the data identity of the target terminal based on the operating data; The data identity is matched with the identity template of the target base station, and the dispersion of the data identity and the identity template is calculated. The discrepancy is used to identify whether there is an anomaly in the wireless access of the target terminal; The identity template is generated based on the historical data identities of each terminal that has historically accessed the target base station, and the abnormal tags corresponding to the historical data identities. The historical data identities are generated based on the historical operating data of each terminal under the target base station. The data identity includes the terminal location of the target terminal and the service quality index of the target terminal at the terminal location; the matching of the data identity with the identity template of the target base station and the calculation of the dispersion of the data identity and the identity template include: The data identity is matched with the identity template of the target base station to obtain a target identity template that matches the terminal location in the data identity; Based on a preset relative entropy algorithm, the dispersion of the service quality indicators in the data identity and the service quality indicators in the target identity template is calculated; the service quality indicators include at least one of latency, jitter, uplink physical resource block utilization, and access success rate.

2. The terminal access anomaly identification method according to claim 1, characterized in that, The operational data includes the terminal location of the target terminal, and the operational quality data of the target terminal at the terminal location; The step of generating the data identity of the target terminal based on the operational data includes: The terminal location in the operational data is correlated with the operational quality data to determine the operational quality of the target base station at the terminal location; Based on the operational quality, determine the health of each service quality indicator of the target base station at the terminal location; Based on the health status and the terminal location, the data identity of the target terminal is generated.

3. The terminal access anomaly identification method according to claim 1, characterized in that, Before matching the data identity with the identity template of the target base station and calculating the dispersion of the data identity and the identity template, the method further includes: Acquire historical operational data of each terminal of the target base station within a historical time period of a first preset duration; the historical operational data includes historical terminal location and historical identity data, and the historical identity data includes operational quality data, base station access information, and base station operational indicators. The historical terminal location and historical identity data in the historical operation data are correlated to determine the historical operation quality of the target base station at each of the historical terminal locations; Based on the historical operational quality, the historical health of the service quality indicators of the target base station at each of the historical terminal locations is determined; Based on the historical terminal location and the historical health status, a historical data identity is generated for each terminal; The historical data identities of each terminal are superimposed to obtain the identity template of the target base station.

4. The terminal access anomaly identification method according to claim 3, characterized in that, The historical identity data also includes base station alarm information of the target base station; the process of overlaying the historical identity data of each terminal to obtain the identity template of the target base station includes: Based on the base station alarm information in the historical identity data, identify abnormal and normal locations in the locations of each historical terminal. A baseline quality operation database is generated based on the historical data identity of the normal locations, and an abnormal quality operation database is generated based on the historical data identity of the abnormal locations. The abnormal quality operation database is then associated with the base station alarm information. The abnormal quality operation database is superimposed on the baseline quality operation database to obtain the identity template of the target base station.

5. The terminal access anomaly identification method according to claim 4, characterized in that, After identifying whether the target terminal's wireless access is abnormal based on the discreteness, the method further includes: If the wireless access of the target terminal is abnormal, the target operation data of the target terminal during a historical time period of a second preset duration is obtained, and a target quality operation database of the target terminal is generated based on the target operation data. Based on a preset relative entropy algorithm, the target dispersion of the target quality operation database and the abnormal quality operation database corresponding to the identity template is calculated. Based on the target dispersion, obtain the abnormal data identity with the smallest data identity dispersion relative to the target terminal; Based on the base station alarm information associated with the abnormal data identity, the abnormal information of the target terminal's wireless access is identified.

6. A terminal access anomaly identification device, characterized in that, include: The data acquisition module is used to acquire the operational data of the target terminal under the target base station; The data identity generation module is used to generate the data identity of the target terminal based on the running data; An identity template matching module is used to match the data identity with the identity template of the target base station and calculate the dispersion of the data identity and the identity template. An anomaly detection module is used to identify whether there is an anomaly in the wireless access of the target terminal based on the dispersion. The identity template is generated based on the historical data identities of each terminal that has historically accessed the target base station, and the abnormal tags corresponding to the historical data identities. The historical data identities are generated based on the historical operating data of each terminal under the target base station. The data identity includes the terminal location of the target terminal and the service quality indicators of the target terminal at the terminal location; the identity template matching module is further used for: The data identity is matched with the identity template of the target base station to obtain a target identity template that matches the terminal location in the data identity; Based on a preset relative entropy algorithm, the dispersion of the service quality indicators in the data identity and the service quality indicators in the target identity template is calculated; the service quality indicators include at least one of latency, jitter, uplink physical resource block utilization, and access success rate.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the terminal access anomaly identification method as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the terminal access anomaly identification method as described in any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the terminal access anomaly identification method as described in any one of claims 1 to 5.

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