Method and device for detecting root cause of antenna feeder anomaly, electronic equipment and storage medium

Abstract

The application provides a method and device for detecting the root cause of antenna feeder abnormalities, electronic equipment and a computer readable storage medium, and relates to the field of wireless communication. The detection method comprises: obtaining an abnormal event in a wireless call record, and extracting target index data of an abnormal event occurrence area, wherein the target index data comprises coverage and interference type index data; determining whether the occurrence of the abnormal event is attributed to coverage interference according to the target index data; if yes, detecting whether there is an abnormality in the lobe angle and / or the antenna azimuth angle according to a root cause detection algorithm. At least the problems of diagnosis and analysis of antenna feeder problems in the related art relying on manual operation of experts, time and manpower consumption, and insufficient experience solidification of first-line personnel in positioning problems, which leads to low problem positioning accuracy, are solved.

Description

Technical Field

[0001] This invention relates to the field of wireless communication, and in particular to a method, apparatus, electronic device, and computer-readable storage medium for detecting the root cause of antenna feeder anomalies. Background Technology

[0002] Network operations by telecom operators often focus on cell-level statistical data collected by operations, management, and maintenance systems. This data can only reflect the surface causes of problems and cannot provide details at the user level. More importantly, it cannot directly pinpoint the root cause of network issues. In existing networks, antenna and feeder problems directly impact air interface wireless coverage and service quality, making it difficult for operators to directly understand the actual performance at the user level and the reasons for service anomalies.

[0003] Given this situation, the 3rd Generation Partnership Project (3GPP) standardized Mobility Tracking and Minimization of Drive Tests (MDTs). MDTs aim to automatically collect user-level information to diagnose antenna and feeder problems and analyze Radio Access Network (RAN) performance. However, post-hoc analysis of tracking information for troubleshooting remains manual. Experts must invest significant time analyzing motion traces to identify problems encountered by each user during connection, which is extremely time-consuming. Furthermore, root cause analysis relies entirely on expert experience, leading to a shortage of expert personnel, insufficient experience consolidation, inadequate problem-solving skills among frontline staff, and low accuracy in problem location. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to address the above-mentioned shortcomings of the prior art by providing a method, device, electronic device and computer-readable storage medium for detecting the root cause of antenna feeder anomalies. This method can realize the automatic detection of the root cause of antenna feeder problems, improve the efficiency and accuracy of antenna feeder problem diagnosis and analysis, save time and manpower costs, and change the probability of antenna feeder problems or the impact of antenna feeder problems, thereby improving the user's perception level.

[0005] In a first aspect, the present invention provides a method for detecting the root cause of antenna feeder anomalies, comprising: acquiring anomaly events in wireless call records and extracting target indicator data of the area where the anomaly events occur, wherein the target indicator data includes coverage-related and interference-related indicator data; determining whether the occurrence of the anomaly event is attributable to coverage interference based on the target indicator data; if so, detecting whether there are anomalies in the beam lobe angle and / or antenna azimuth angle according to a root cause detection algorithm.

[0006] Preferably, determining whether the occurrence of an abnormal event is attributable to coverage interference based on the target indicator data specifically includes: comparing the target indicator data with the target indicator threshold value; if the target indicator data exceeds the target indicator threshold value, then it is determined that the occurrence of the abnormal event is attributable to coverage interference.

[0007] Preferably, the step of detecting whether there is an anomaly in the beam lobe angle and / or antenna azimuth angle according to the root cause detection algorithm specifically includes: detecting whether there is an anomaly in the beam lobe angle according to the beam lobe angle anomaly detection algorithm; if there is an anomaly in the beam lobe angle, then processing the beam lobe angle anomaly; and / or, if there is no anomaly in the beam lobe angle or the beam lobe angle anomaly has been processed, then detecting whether there is an anomaly in the antenna azimuth angle according to the antenna azimuth angle anomaly detection algorithm.

[0008] Preferably, the step of detecting whether there is an anomaly in the beam lobe angle according to the beam lobe angle anomaly detection algorithm specifically includes: determining whether the number of effective coverage grids in the cell where the anomaly event occurred is greater than a first preset threshold; if it is greater than the first preset threshold, determining whether the number of effective coverage azimuth angles is greater than or equal to a second preset threshold; if it is greater than or equal to the second preset threshold, determining whether the number of effective coverage grids within 1 beam lobe angle is less than 0.6 times the number of effective coverage grids; if it is less than 0.6 times the number of effective coverage grids, determining that there is an anomaly in the beam lobe angle.

[0009] Preferably, the step of detecting whether there is an anomaly in the antenna azimuth angle according to the antenna azimuth angle anomaly detection algorithm specifically includes: determining whether the number of effective coverage grids in the cell where the anomaly event occurred is greater than a first preset threshold; if it is greater than the first preset threshold, determining whether the number of effective coverage azimuth angles is less than a second preset threshold; if it is less than the second preset threshold, determining whether the number of effective coverage grids within the beam angle meets a preset condition; if it meets the preset condition, determining whether the number of effective coverage grids in the reverse direction of the cell is less than half of the number of effective coverage grids; if it is less than half of the number of effective coverage grids, determining that there is an anomaly in the antenna azimuth angle.

[0010] Preferably, determining whether the number of effective coverage grids within a beam angle meets a preset condition specifically includes: determining whether the number of effective coverage grids within 1 beam angle is less than half of the total number of effective coverage grids, to obtain a first determination result; determining whether the number of effective coverage grids within 3 beam angles is greater than 0, to obtain a second determination result; determining whether the number of effective coverage grids within 1 beam angle is less than the number of effective coverage grids within 3 beam angles or whether the number of effective coverage grids within 1 beam angle is less than 3 times the number of effective coverage grids, to obtain a third determination result; determining whether the sum of the number of effective coverage grids within 3 beam angles and the number of effective coverage grids within 2 beam angles is greater than the number of effective coverage grids within 1 beam angle, to obtain a fourth determination result; if all of the first to fourth determination results are yes, then it is determined that the number of effective coverage grids within the beam angle meets the preset condition.

[0011] Secondly, the present invention also provides a device for detecting the root cause of antenna feeder anomalies, comprising: an acquisition module, a judgment module, and a detection module. The acquisition module is used to acquire abnormal events in wireless call records and extract target indicator data of the area where the abnormal events occur, wherein the target indicator data includes coverage-related and interference-related indicator data. The judgment module is connected to the acquisition module and is used to determine whether the occurrence of the abnormal event is attributed to coverage interference based on the target indicator data. The detection module is connected to the judgment module and is used to detect whether there are abnormalities in the beam lobe angle and / or antenna azimuth angle according to the root cause detection algorithm.

[0012] Preferably, the judgment module includes: a comparison unit and a determination unit. The comparison unit is used to compare the target indicator data with the target indicator threshold value. The determination unit is connected to the comparison unit and is used to determine that if the target indicator data exceeds the target indicator threshold value, the occurrence of the abnormal event is attributed to coverage interference. The detection module includes: a first detection unit and a second detection unit. The first detection unit is used to detect whether there is an abnormality in the beam lobe angle according to the beam lobe angle anomaly detection algorithm. The second detection unit is connected to the second detection unit and is used to detect whether there is an abnormality in the antenna azimuth angle according to the antenna azimuth angle anomaly detection algorithm.

[0013] Thirdly, the present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the method for detecting the root cause of antenna anomalies provided in the first aspect above.

[0014] Fourthly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the method for detecting the root cause of antenna feeder anomalies provided in the first aspect.

[0015] This invention provides a method, apparatus, electronic device, and computer-readable storage medium for detecting the root cause of antenna feeder anomalies. It detects whether there are anomalies in the beam lobe angle and / or antenna azimuth angle by analyzing coverage and interference index data of abnormal events in wireless call logs and using a root cause detection algorithm. This accurately pinpoints the root cause of wireless environment degradation as an anomaly in the beam lobe angle and / or antenna azimuth angle. Therefore, this invention enables automatic detection of the root cause of antenna feeder problems, improving the efficiency and accuracy of antenna feeder problem diagnosis and analysis, saving time and manpower costs, and altering the likelihood or impact of antenna feeder problems, thereby enhancing user experience. Attached Figure Description

[0016] Figure 1 This is a flowchart of a method for detecting the root cause of antenna feeder anomalies according to Embodiment 1 of the present invention; Figure 2This is a schematic diagram of the structure of a detection device for the root cause of antenna feed anomalies in Embodiment 2 of the present invention. Detailed Implementation

[0017] To enable those skilled in the art to better understand the technical solution of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0018] It is understood that the specific embodiments and accompanying drawings described herein are merely for explaining the invention and are not intended to limit the invention.

[0019] It is understood that, without conflict, the various embodiments and features in the embodiments of the present invention can be combined with each other.

[0020] It is understood that, for ease of description, only the parts related to the present invention are shown in the accompanying drawings, while the parts unrelated to the present invention are not shown in the drawings.

[0021] It is understood that each unit or module involved in the embodiments of the present invention may correspond to only one entity structure, or may be composed of multiple entity structures, or multiple units or modules may be integrated into one entity structure.

[0022] It is understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of this invention may occur in a different order than that marked in the accompanying drawings.

[0023] It is understood that the flowcharts and block diagrams of this invention illustrate the possible architecture, functions, and operations of systems, apparatuses, devices, and methods according to various embodiments of this invention. Each block in the flowchart or block diagram may represent a unit, module, program segment, or code, containing executable instructions for implementing the specified function. Furthermore, each block or combination of blocks in the block diagram and flowchart can be implemented using a hardware-based system to achieve the specified function, or using a combination of hardware and computer instructions.

[0024] It is understood that the units and modules involved in the embodiments of the present invention can be implemented by software or by hardware. For example, the units and modules can be located in a processor.

[0025] Example 1: In this embodiment, antenna feeder anomalies typically have several possible root causes. Some common causes include: Antenna failure: The antenna may be physically damaged, loose, or have poor connections, leading to signal attenuation or interruption. Poor connection: Cables or connectors connected to the antenna may be loose, corroded, or worn, resulting in poor signal transmission or complete interruption. Antenna orientation error: If the antenna is not correctly aligned with the base station, signal reception and transmission will be affected, leading to a decrease in communication quality. Antenna obstruction: If buildings, obstacles, or vegetation block the line of sight between the antenna and the base station, it will cause signal weakening or loss. Power supply issues: Unstable power supply, a damaged power adapter, or insufficient battery power may affect the normal operation of the antenna feeder. System setting errors: Incorrect settings such as device configuration parameters, frequency selection, and power adjustment may also cause antenna feeder anomalies. Other interference sources: Other wireless devices, electromagnetic interference sources, or environmental factors such as lightning strikes may also be causes of antenna feeder anomalies. To locate the antenna feeder anomaly, the above possible root causes can be checked step by step, and corresponding repairs or adjustments can be made. This embodiment primarily investigates the root causes of antenna feeder anomalies, focusing on those caused by incorrect antenna orientation leading to abnormal antenna azimuth angles, and those caused by antenna design issues, incorrect parameter settings, or equipment malfunctions resulting in excessively small or large signal coverage areas radiated by the antenna, leading to abnormal beamwidth angles. Here, antenna azimuth angle refers to the angle at which the antenna is aligned with the base station on a horizontal plane, and beamwidth angle refers to the signal coverage area radiated by the antenna.

[0026] like Figure 1 As shown, this embodiment provides a method for detecting the root cause of antenna feeder anomalies, including: Step S101: Obtain abnormal events from the wireless call log and extract target indicator data of the area where the abnormal events occurred, wherein the target indicator data includes coverage and interference indicator data.

[0027] In this embodiment, abnormal events occurring during the entire process of RRC (Radio Resource Control) connection establishment → cell handover → connection release, such as re-establishment, dropped calls, and missed calls, are identified from the radio call log data. The 12 types of abnormal events extracted from the call log data are shown in Table 1. Table 1. 12 types of abnormal events extracted from call log data

[0028] In this embodiment, diagnosing the cause of a user's abnormal event requires extracting representative indicators from the signaling to reflect the occurrence of the abnormal event. These indicators are derived from necessary events that occurred before the end of the abnormal event flow. The extracted indicators mainly come from two sources: first, relevant information extracted from the Measurement Report (MR); and second, extended field information (uu-extend) of the UU interface. This embodiment extracts coverage and interference indicator data (i.e., data on wireless environment, resource load, and service quality) of the abnormal event occurrence area (grid level / cell level) from the relevant information extracted from the MR in the measurement report or the extended field information (uu-extend) of the UU interface. The extracted coverage and interference indicator data are used to assist in subsequent network problem localization.

[0029] Step S102: Determine whether the occurrence of the abnormal event is attributable to coverage interference based on the target indicator data.

[0030] Specifically, step S102: Determine whether the occurrence of the abnormal event is attributable to coverage interference based on the target indicator data, including steps a1-a2: Step a1: Compare the target indicator data with the target indicator threshold value.

[0031] Step a2: If the target indicator data exceeds the target indicator threshold, the occurrence of the abnormal event is determined to be due to coverage interference.

[0032] In this embodiment, the captured coverage and interference index data are compared with the corresponding index threshold values ​​to output the primary cause of the abnormal event (e.g., weak coverage, overlapping coverage, cross-area coverage, etc.). For example, if the RSRP (Reference Signal Receiving Power) of the macro base station coverage area is less than -110 and the sampling points are greater than 20%, and the RSRP of the indoor distributed antenna system coverage area is less than -110 and the sampling points are greater than 10%, then the primary cause of the corresponding abnormal event is weak coverage. Since azimuth and beam angle anomalies usually cause coverage and interference problems, this embodiment narrows the scope of root cause detection by judging whether the apparent cause of the abnormal event is a coverage interference problem, promoting the subsequent detection of azimuth and beam angle anomalies, and improving the efficiency and accuracy of antenna feeder anomaly root cause detection. The threshold values ​​corresponding to the coverage and interference indices are shown in Table 2. Table 2 Threshold values ​​for coverage and interference indicators

[0033] Step S103: If yes, then detect whether there is an anomaly in the beam lobe angle and / or antenna azimuth angle according to the root cause detection algorithm.

[0034] In this embodiment, anomalies in the beam lobe angle or antenna azimuth angle can be detected. To improve the accuracy of root cause detection, this embodiment uses a root cause detection algorithm to detect anomalies in the antenna azimuth angle and beam lobe angle.

[0035] Specifically, step S103: Detect whether there are abnormalities in the beam lobe angle and / or antenna azimuth angle according to the root cause detection algorithm, including steps b1-b2: In this embodiment, the root cause detection algorithm includes: a beam lobe angle anomaly detection algorithm and an antenna azimuth angle anomaly detection algorithm.

[0036] Step b1: Detect whether there is an anomaly in the beam lobe angle using the beam lobe angle anomaly detection algorithm. If an anomaly is found, process the anomaly. And / or, In this embodiment, the coverage and interference indicators that actually occur at the location of the antenna lobe are sampled to verify whether the cell lobe angle is too large.

[0037] Specifically, step b1: Detect whether there is an anomaly in the beam lobe angle according to the beam lobe angle anomaly detection algorithm, including: Determine whether the number of effective coverage grids in the cell where the abnormal event occurred is greater than a first preset threshold.

[0038] In this embodiment, the latitude and longitude coordinates of the primary service sampling points in the cell where the abnormal event occurred are extracted from the wireless trace measurement report. The sample points and total sample points of each grid in the cell where the abnormal event occurred are counted. The effective coverage grid of the cell where the abnormal event occurred is calculated. The effective coverage grid is a grid in which the ratio of the sample points of the serving cell to the total sample points is greater than 20%. The grid is a 30m×30m geospatial square. The first preset threshold must be greater than or equal to 10. In this embodiment, the first preset threshold is 10. If the number of effective coverage grids is too small (i.e., less than 10), it will affect the accuracy of the beam lobe angle anomaly detection algorithm. When the number of effective coverage grids is greater than 10, the next step of verification is performed.

[0039] If the number of effective azimuth angles covered is greater than or equal to the first preset threshold, then determine whether the number of effective azimuth angles covered is greater than or equal to the second preset threshold.

[0040] In this embodiment, the azimuth angle is divided into 12 parts, with each 30-degree area considered as an azimuth angle. If there is an effective coverage grid within the divided 30-degree sector area, the azimuth angle (i.e., the divided 30-degree sector area) is considered a valid coverage azimuth angle. The second preset threshold in this embodiment is 7. The number of valid coverage azimuth angles is counted. If the number of valid coverage azimuth angles is greater than or equal to 7, the next step of verification is performed.

[0041] If the value is greater than or equal to the second preset threshold, then it is determined whether the number of effective coverage grids within 1 lobe angle is less than 0.6 times the number of effective coverage grids. If it is less than 0.6 times the number of effective coverage grids, then it is determined that there is an anomaly in the lobe angle.

[0042] In this embodiment, 1 horizontal beam angle (i.e., 1 beam angle, hbwd1) is usually defined as 65°. The number of effective coverage grids within 1 horizontal beam angle is counted. If it is less than 0.6 times the number of effective coverage grids, it is determined that there is an anomaly in the beam angle.

[0043] Step b2: If there is no abnormality in the beam lobe angle or the abnormality in the beam lobe angle has been processed, then the antenna azimuth angle is checked for abnormality according to the antenna azimuth angle abnormality detection algorithm.

[0044] Specifically, step b2: Detect whether there is an abnormality in the antenna azimuth angle according to the antenna azimuth angle anomaly detection algorithm, including: determining whether the effective coverage grid number of the cell where the abnormal event occurred is greater than the first preset threshold.

[0045] In this embodiment, the latitude and longitude coordinates of the primary service sampling points in the cell where the abnormal event occurred are extracted from the wireless trace measurement report. The sample points and total sample points of each grid in the cell where the abnormal event occurred are counted. The effective coverage grid of the cell where the abnormal event occurred is calculated. The effective coverage grid is a grid in which the ratio of the sample points of the serving cell to the total sample points is greater than 20%. The grid is a 30m×30m geospatial square. The first preset threshold must be greater than or equal to 10. In this embodiment, the first preset threshold is 10. If the number of effective coverage grids is too small (i.e., less than 10), it will affect the accuracy of the beam lobe angle anomaly detection algorithm. When the number of effective coverage grids is greater than 10, the next step of verification is performed.

[0046] If the number of effective azimuth angles covered is greater than the first preset threshold, then it is determined whether the number of effective azimuth angles covered is less than the second preset threshold.

[0047] In this embodiment, the azimuth angle is divided into 12 parts, with each 30-degree area considered as an azimuth angle. If there is an effective coverage grid within the divided 30-degree sector area, the azimuth angle (i.e., the divided 30-degree sector area) is considered a valid coverage azimuth angle. The second preset threshold in this embodiment is 7. The number of valid coverage azimuth angles is counted. If the number of valid coverage azimuth angles is less than 7, the next step of verification is performed.

[0048] If it is less than the second preset threshold, then determine whether the number of effective coverage grids within the beam angle meets the preset conditions.

[0049] Specifically, determining whether the number of effective coverage grids within the beam angle meets preset conditions includes: The first judgment result is obtained by determining whether the number of effective coverage grids within 1 lobe angle is less than half of the number of effective coverage grids.

[0050] In this embodiment, 1 horizontal beam angle (i.e., 1 beam angle, hbwd1) is usually defined as 65°. The number of effective coverage grids within 1 horizontal beam angle is counted. If it is less than half of the number of effective coverage grids, the next step of verification is performed.

[0051] The second judgment result is obtained by determining whether the number of effective coverage grids within 3 times the beam angle is greater than 0.

[0052] In this embodiment, 3 times the horizontal beam angle (i.e., 1 beam angle, hbwd3) is usually defined as a range of 65°×3=195°. The number of effective coverage grids within 3 times the horizontal beam angle is counted. If it is greater than 0, the next step of verification is performed.

[0053] The third judgment result is obtained by determining whether the number of effective coverage grids within 1 lobe angle is less than the number of effective coverage grids within 3 lobe angles or whether the number of effective coverage grids within 1 lobe angle is less than 3 times the number of effective coverage grids.

[0054] In this embodiment, if the number of effective coverage grids within 1 lobe angle is less than the number of effective coverage grids within 3 lobe angles or 3 times the number of effective coverage grids, then proceed to the next step of verification.

[0055] The fourth judgment result is obtained by determining whether the sum of the number of effective coverage grids within 3 times the beam angle and the number of effective coverage grids within 2 times the beam angle is greater than the number of effective coverage grids within 1 times the beam angle.

[0056] If all four judgment results are yes, then the number of effective coverage grids within the beam angle is determined to meet the preset condition.

[0057] In this embodiment, the sum of the number of effective coverage grids within 3 times the beam angle and the number of effective coverage grids within 2 times the beam angle is calculated. If it is determined that the sum of the number of effective coverage grids within 3 times the beam angle and the number of effective coverage grids within 2 times the beam angle is greater than the number of effective coverage grids within 1 times the beam angle, then it is determined that the number of effective coverage grids within the beam angle meets the preset condition, and the next step of verification is performed.

[0058] If the preset conditions are met, it is determined whether the number of effective grid cells for reverse coverage of the cell is less than half of the number of effective coverage grid cells. If it is less than half of the number of effective coverage grid cells, it is determined that there is an abnormality in the antenna azimuth angle.

[0059] In this embodiment, the effective coverage grid number of the antenna back lobe is counted, which is the effective coverage grid for reverse coverage. If it is greater than half of the effective coverage grid number, the problem of reverse antenna feed connection is ruled out; if it is less than half of the effective coverage grid number, an antenna azimuth angle anomaly is determined. The beam lobe anomaly detection algorithm in this embodiment has fewer screening conditions than the antenna azimuth angle anomaly detection algorithm. It first screens and resolves beam lobe anomalies, and then screens and resolves antenna azimuth angle anomalies, which can improve the anomaly detection rate and thus improve the root cause detection efficiency of antenna feed anomalies.

[0060] The antenna feeder anomaly root cause detection method provided in this embodiment detects whether there are anomalies in the beam angle and / or antenna azimuth angle by using coverage and interference index data of abnormal events in wireless call records and a root cause detection algorithm. It accurately locates the root cause of wireless environment degradation as an anomaly in the antenna azimuth angle and / or beam angle, achieving automatic detection of the root cause of antenna feeder problems. This improves the efficiency and accuracy of antenna feeder problem diagnosis and analysis, saves time and manpower costs, and changes the probability or impact of antenna feeder problems, thereby improving user perception. Furthermore, since azimuth and beam angle anomalies often cause coverage and interference problems, this embodiment narrows the scope of root cause detection by determining whether the apparent cause of the abnormal event is a coverage or interference problem, promoting subsequent detection of azimuth and beam angle anomalies and improving the efficiency and accuracy of antenna feeder anomaly root cause detection. Because the beam angle anomaly detection algorithm has fewer screening conditions than the antenna azimuth angle anomaly detection algorithm, screening and resolving beam angle anomalies first, followed by screening and resolving antenna azimuth angle anomalies, can improve the anomaly detection rate, thereby improving the efficiency of antenna feeder anomaly root cause detection.

[0061] Example 2: like Figure 2 As shown, this embodiment provides a device for detecting the root cause of antenna feeder anomalies, including: an acquisition module 21, a judgment module 22, and a detection module 23. The acquisition module 21 is used to acquire abnormal events in wireless call records and extract target indicator data of the area where the abnormal event occurs, wherein the target indicator data includes coverage-related and interference-related indicator data. The judgment module 22 is connected to the acquisition module 21 and is used to determine whether the occurrence of the abnormal event is attributed to coverage interference based on the target indicator data. The detection module 23 is connected to the judgment module 22 and is used to detect whether there are abnormalities in the beam lobe angle and / or antenna azimuth angle according to the root cause detection algorithm.

[0062] Specifically, the judgment module 22 includes: a comparison unit 221 and a determination unit 222. The comparison unit 221 is used to compare the target index data with the target index threshold value. The determination unit 222 is connected to the comparison unit 221 and is used to determine that if the target index data exceeds the target index threshold value, the occurrence of the abnormal event is attributed to coverage interference. The detection module 23 includes: a first detection unit 231 and a second detection unit 232. The first detection unit 231 is used to detect whether there is an abnormality in the beam lobe angle according to the beam lobe angle abnormality detection algorithm. The second detection unit 232 is connected to the second detection unit 231 and is used to detect whether there is an abnormality in the antenna azimuth angle according to the antenna azimuth angle abnormality detection algorithm.

[0063] Specifically, the first detection unit 231 includes: a first judgment subunit, a second judgment subunit, and a third judgment subunit. The first judgment subunit is used to determine whether the number of effective coverage grids in the cell where the abnormal event occurred is greater than a first preset threshold. The second judgment subunit is used to determine whether the number of effective azimuth angles is greater than or equal to a second preset threshold. The third judgment subunit is used to determine whether the number of effective coverage grids within 1 beam angle is less than 0.6 times the number of effective coverage grids. If it is less than 0.6 times the number of effective coverage grids, then it is determined that there is an abnormality in the beam angle.

[0064] Specifically, the second detection unit 232 includes: a fourth judgment subunit, a fifth judgment subunit, a sixth judgment subunit, and a seventh judgment subunit. The fourth judgment subunit is used to determine whether the number of effective coverage grids in the cell where the abnormal event occurred is greater than a first preset threshold. The fifth judgment subunit is used to determine whether the number of effective coverage azimuth angles is less than a second preset threshold. The sixth judgment subunit is used to determine whether the number of effective coverage grids within the beam angle meets a preset condition. The seventh judgment subunit is used to determine whether the number of effective coverage grids in the reverse direction of the cell is less than half of the number of effective coverage grids. If it is less than half of the number of effective coverage grids, it is determined that there is an abnormality in the antenna azimuth angle.

[0065] Specifically, the sixth judgment subunit includes: a first case judgment subunit, a second case judgment subunit, a third case judgment subunit, a fourth case judgment subunit, and a determination subunit. The first case judgment subunit determines whether the number of effective coverage grids within 1 lobe angle is less than half of the number of effective coverage grids, and obtains a first judgment result. The second case judgment subunit is used to determine whether the number of effective coverage grids within 3 lobe angles is greater than 0, and obtains a second judgment result. The third case judgment subunit is used to determine whether the number of effective coverage grids within 1 lobe angle is less than the number of effective coverage grids within 3 lobe angles or whether the number of effective coverage grids within 1 lobe angle is less than 3 times the number of effective coverage grids, and obtains a third judgment result. The fourth case judgment subunit is used to determine whether the sum of the number of effective coverage grids within 3 lobe angles and the number of effective coverage grids within 2 lobe angles is greater than the number of effective coverage grids within 1 lobe angle, and obtains a fourth judgment result. The determination subunit is used to determine that the number of effective coverage grids within the lobe angle meets the preset condition if all of the first to fourth judgment results are yes.

[0066] Understandably, the antenna feeder anomaly detection device provided above is used to execute the method corresponding to Embodiment 1 provided above. Therefore, the beneficial effects it can achieve can be referred to the beneficial effects of the method in Embodiment 1 above and the corresponding scheme in the specific implementation below, which will not be repeated here.

[0067] Example 3: This embodiment also provides an electronic device, including a memory and a processor. The memory stores a computer program, and the processor is configured to run the computer program to implement the antenna feed anomaly root cause detection method described in the above embodiment.

[0068] Example 4: This embodiment also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the method for detecting the root cause of antenna feeder anomalies in the above embodiment.

[0069] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of the present invention, and the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A method for detecting the root cause of antenna feeder anomalies, characterized in that, include: Obtain abnormal events from wireless call records and extract target indicator data for the areas where the abnormal events occurred, including coverage and interference indicator data. Determine whether the occurrence of abnormal events is attributable to coverage interference based on the target indicator data; If so, then the root cause detection algorithm is used to check whether there are any anomalies in the beam lobe angle and / or antenna azimuth angle. The root cause detection algorithm is used to detect whether there are anomalies in the beam lobe angle and / or antenna azimuth angle. Specifically, this includes: detecting whether there are anomalies in the beam lobe angle using a beam lobe angle anomaly detection algorithm; if anomalies are found, processing them; and / or, if there are no anomalies in the beam lobe angle or the anomalies have been processed, detecting whether there are anomalies in the antenna azimuth angle using an antenna azimuth angle anomaly detection algorithm. The beam lobe anomaly detection algorithm detects whether there is an anomaly in the beam lobe angle. Specifically, it includes: extracting the primary serving sampling point information of the cell where the anomaly occurred from the wireless trace measurement report; counting the sample points and total sample points of each grid in the cell where the anomaly occurred as serving cells; and calculating the effective coverage grid of the cell where the anomaly occurred, where the ratio of the sample points of the serving cells to the total sample points in the grid is greater than 20%; counting the number of effective coverage azimuth angles and the number of effective coverage grids within 1 horizontal beam lobe angle, where the effective coverage azimuth angle is the azimuth angle where there is an effective coverage grid; determining whether the number of effective coverage grids in the cell where the anomaly occurred is greater than a first preset threshold; if it is greater than the first preset threshold, determining whether the number of effective coverage azimuth angles is greater than or equal to a second preset threshold; if it is greater than or equal to the second preset threshold, determining whether the number of effective coverage grids within 1 beam lobe angle is less than 0.6 times the number of effective coverage grids; if it is less than 0.6 times the number of effective coverage grids, then it is determined that there is an anomaly in the beam lobe angle.

2. The method for detecting the root cause of antenna feeder anomalies according to claim 1, characterized in that, The step of determining whether an abnormal event is attributable to coverage interference based on target indicator data specifically includes: Compare the target indicator data with the target indicator threshold value; If the target indicator data exceeds the target indicator threshold, the occurrence of the abnormal event is determined to be due to coverage interference.

3. The method for detecting the root cause of antenna feeder anomalies according to claim 1, characterized in that, The step of detecting whether there is an anomaly in the antenna azimuth angle according to the antenna azimuth angle anomaly detection algorithm specifically includes: Determine whether the number of effective coverage grids in the cell where the abnormal event occurred is greater than a first preset threshold. If it is greater than the first preset threshold, then determine whether the number of effective azimuth angles covered is less than the second preset threshold; If it is less than the second preset threshold, then determine whether the number of effective coverage grids within the beam angle meets the preset conditions; If the preset conditions are met, it is determined whether the number of effective grid cells for reverse coverage of the cell is less than half of the number of effective coverage grid cells. If it is less than half of the number of effective coverage grid cells, it is determined that there is an abnormality in the antenna azimuth angle.

4. The method for detecting the root cause of antenna feeder anomalies according to claim 3, characterized in that, The determination of whether the number of effective coverage grids within the beam angle meets the preset conditions specifically includes: Determine whether the number of effective coverage grids within 1 lobe angle is less than half of the number of effective coverage grids to obtain the first determination result; Determine whether the number of effective coverage grids within 3 times the beam angle is greater than 0 to obtain the second judgment result; The third judgment result is obtained by determining whether the number of effective coverage grids within 1 lobe angle is less than the number of effective coverage grids within 3 lobe angles or whether the number of effective coverage grids within 1 lobe angle is less than 3 times the number of effective coverage grids. The fourth judgment result is obtained by determining whether the sum of the number of effective coverage grids within 3 times the beam angle and the number of effective coverage grids within 2 times the beam angle is greater than the number of effective coverage grids within 1 times the beam angle. If all four judgment results are yes, then the number of effective coverage grids within the beam angle is determined to meet the preset condition.

5. A device for detecting the root cause of antenna feeder anomalies, characterized in that, include: The module includes an acquisition module, a judgment module, and a detection module. The acquisition module is used to acquire abnormal events in wireless call records and extract target indicator data of the area where the abnormal events occurred. The target indicator data includes coverage-related and interference-related indicator data. The judgment module, connected to the acquisition module, is used to determine whether the occurrence of an abnormal event is attributable to coverage interference based on the target indicator data. The detection module, connected to the judgment module, is used to detect whether there are abnormalities in the beam lobe angle and / or antenna azimuth angle according to the root cause detection algorithm. The root cause detection algorithm is used to detect whether there are anomalies in the beam lobe angle and / or antenna azimuth angle. Specifically, this includes: detecting whether there are anomalies in the beam lobe angle using a beam lobe angle anomaly detection algorithm; if anomalies are found, processing them; and / or, if there are no anomalies in the beam lobe angle or the anomalies have been processed, detecting whether there are anomalies in the antenna azimuth angle using an antenna azimuth angle anomaly detection algorithm. The beam lobe anomaly detection algorithm detects whether there is an anomaly in the beam lobe angle. Specifically, it includes: extracting the primary serving sampling point information of the cell where the anomaly occurred from the wireless trace measurement report; counting the sample points and total sample points of each grid in the cell where the anomaly occurred as serving cells; and calculating the effective coverage grid of the cell where the anomaly occurred, where the ratio of the sample points of the serving cells to the total sample points in the grid is greater than 20%; counting the number of effective coverage azimuth angles and the number of effective coverage grids within 1 horizontal beam lobe angle, where the effective coverage azimuth angle is the azimuth angle where there is an effective coverage grid; determining whether the number of effective coverage grids in the cell where the anomaly occurred is greater than a first preset threshold; if it is greater than the first preset threshold, determining whether the number of effective coverage azimuth angles is greater than or equal to a second preset threshold; if it is greater than or equal to the second preset threshold, determining whether the number of effective coverage grids within 1 beam lobe angle is less than 0.6 times the number of effective coverage grids; if it is less than 0.6 times the number of effective coverage grids, then it is determined that there is an anomaly in the beam lobe angle.

6. The detection device for the root cause of antenna feeder anomalies according to claim 5, characterized in that, The judgment module includes: a comparison unit and a determination unit. The comparison unit is used to compare the target indicator data with the target indicator threshold value. The determination unit, connected to the comparison unit, is used to determine that if the target indicator data exceeds the target indicator threshold, the occurrence of the abnormal event is attributed to coverage interference. The detection module includes: a first detection unit and a second detection unit. The first detection unit is used to detect whether there is an anomaly in the beam lobe angle according to the beam lobe angle anomaly detection algorithm. The second detection unit, connected to the second detection unit, is used to detect whether there is an abnormality in the antenna azimuth angle according to the antenna azimuth angle anomaly detection algorithm.

7. An electronic device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to implement a method for detecting the root cause of antenna feed anomalies as described in any one of claims 1-4.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements a method for detecting the root cause of antenna feeder anomalies as described in any one of claims 1-4.

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