Wireless network external interference troubleshooting method and device, equipment and storage medium

Abstract

This disclosure provides a method, apparatus, device, and storage medium for troubleshooting external interference in wireless networks. The method includes: filtering target cells containing interference sources from the cells to be detected based on the uplink interference level of the cell to be detected; acquiring measurement report data of the target cells, and determining potential interference source users and potential interference source locations in the target cells based on the location of sampling points and signal strength; and determining the location of the interference source to be investigated from the potential interference source locations based on cluster analysis of the potential interference source users and potential interference source locations. This disclosure solves the problem of the inability to actively detect and investigate external interference in the prior art, enabling proactive judgment of interference sources. Automated analysis based on measurement report data can greatly save analysis costs, and cluster analysis can centrally locate the location of interference sources, ensuring the accuracy of location judgment, thereby greatly improving the efficiency and reliability of interference troubleshooting.

Description

Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to a method, apparatus, device, and storage medium for troubleshooting external interference in wireless networks. Background Technology

[0002] In the early stages of wireless network deployment, coverage is often incomplete, resulting in some weak coverage areas. In such cases, some users resort to installing wireless repeaters to improve signal strength. While this method may improve communication quality for the individual installer, these illegally installed repeaters often have poor technical specifications and lack professional testing. Operating in a non-linear range, they can cause external interference such as uplink noise and intermodulation interference. This external interference can severely impact the communication experience of nearby users. Therefore, it is crucial to promptly identify and address external interference sources to ensure a smooth user experience for all users of the wireless network.

[0003] Current methods for locating external interference sources rely on operators carrying frequency scanning equipment to pinpoint the interference source within the cell's coverage area and conduct on-site inspections. This approach is inefficient, fails to proactively detect external interference, and results in poor outcomes for external interference detection. Summary of the Invention

[0004] This disclosure provides a method, apparatus, device, and storage medium for troubleshooting external interference in wireless networks, in order to solve the problem that external interference cannot be actively detected and troubleshooted in the prior art.

[0005] Firstly, this disclosure provides a method for troubleshooting external interference in a wireless network, the method comprising:

[0006] Based on the uplink interference level of the cell to be detected, target cells with interference sources are selected from the cells to be detected;

[0007] Obtain measurement report data for the target cell, which includes the location of the sampling point and signal strength when the terminal user in the target cell connects;

[0008] Based on the location of the sampling points and the signal strength, determine the potential interference source users and the location points of potential interference sources in the target cell;

[0009] Based on cluster analysis of potential interference source users and potential interference source location points, the location of the interference source to be investigated is determined from the potential interference source location points.

[0010] Optionally, based on the uplink interference level of the cell to be detected, a target cell with an interference source is selected from the cells to be detected, including: obtaining the daily uplink interference level of the cell to be detected; determining the average uplink interference level of the cell to be detected over a set period based on the daily uplink interference level; and determining the cell to be detected as a target cell if the average uplink interference level reaches a first set threshold.

[0011] Optionally, based on the location of the sampling point and the signal strength, the potential interference source users and potential interference source locations in the target cell are determined, including: determining the location point to which the sampling point belongs based on a set location granularity and the location of the sampling point in the target cell; removing location points containing fewer than a set number of sampling points; determining the terminal users and access signal strength of the terminal users corresponding to the removed location points; if a location point meets a set condition, then the location point is determined as a potential interference source location point, the set condition including that the proportion of terminal users whose signal strength corresponding to the location point exceeds a first set strength is within a first set range, and the proportion of terminal users whose signal strength is lower than a second set strength is greater than a second set threshold; and determining that the terminal users whose signal strength exceeds the first set strength among the potential interference source location points are potential interference source users.

[0012] Optionally, the measurement report data includes the identification code of the terminal user when accessing the network, and determines the terminal user and the access signal strength of the terminal user corresponding to the location point after the removal process. This includes: determining the average signal strength corresponding to each identification code and the number of times each identification code appears based on the measurement report data; identifying the terminal user corresponding to the identification code that appears more than a set threshold number of times at each location point as the terminal user corresponding to the location point; and determining the average signal strength of the terminal user as the corresponding access signal strength.

[0013] Optionally, the measurement report data includes azimuth parameters and signal propagation time parameters; the set location granularity includes set azimuth granularity and set signal propagation time granularity; based on the set location granularity and the location of the sampling points in the target cell, the location point to which the sampling point belongs is determined, including: taking the integer quotient of the azimuth parameter corresponding to each sampling point in the cell and the set azimuth granularity as the first integer quotient; taking the integer quotient of the signal propagation time parameter corresponding to each sampling point in the cell and the set signal propagation time granularity as the second integer quotient; and determining the sampling points with the same first integer quotient and the same second integer quotient as sampling points belonging to the same location point.

[0014] Optionally, if a location point meets the set conditions, after determining the location point as a potential interference source location point, the method further includes: determining the center longitude and center latitude of the location point based on the azimuth parameters and signal propagation time parameters of all sampling points in each location point.

[0015] Optionally, based on cluster analysis of potential interference source users and potential interference source location points, the location of the interference source to be investigated is determined from the potential interference source location points, including: inputting the location information of the potential interference source location points into the clustering algorithm model, and outputting the cluster corresponding to each potential interference source location point; determining the overlap coefficient between the potential interference source users in each cluster and the terminal users that appear repeatedly in the cluster; and determining the location of the cluster with the highest overlap coefficient as the location of the interference source to be investigated based on the ranking of the overlap coefficients.

[0016] Optionally, determining the overlap coefficient between potential interference source users and recurring terminal users in each cluster includes: determining the number of times the identification code of potential interference source users appears in each cluster as the first count; determining the number of times the identification code of potential interference source users that appears at least twice in each cluster as the second count; and determining the ratio of the second count to the first count as the overlap coefficient corresponding to the cluster.

[0017] Secondly, this disclosure provides a device for troubleshooting external interference in a wireless network, the device comprising:

[0018] The filtering module is used to filter out target cells with interference sources from the cells to be detected based on the uplink interference level of the cell to be detected;

[0019] The acquisition module is used to acquire measurement report data of the target cell. The measurement report data includes the location of the sampling point and the signal strength when the terminal user in the target cell connects.

[0020] The calculation module is used to determine the potential interference source users and potential interference source locations in the target cell based on the location of the sampling points and the signal strength.

[0021] The determination module is used to determine the location of the interference source to be investigated from the potential interference source location points based on cluster analysis of potential interference source users and potential interference source location points.

[0022] Optionally, the data collection module specifically includes: CPU utilization, memory utilization, number of TCP / IP connections, disk I / O read / write utilization, CPU load, network throughput, and number of file handles; the server logs include: user operation logs and application process logs.

[0023] Optionally, the filtering module is specifically used to: obtain the daily uplink interference level of the cell to be detected; determine the average uplink interference level of the cell to be detected over a set period based on the daily uplink interference level; and determine the cell to be detected as the target cell if the average uplink interference level reaches a first set threshold.

[0024] Optionally, the calculation module is specifically used to: determine the location point to which the sampling point belongs based on a set location granularity and the location of the sampling point in the target cell; remove location points containing fewer than a set number of sampling points; determine the terminal users and access signal strength of the terminal users corresponding to the removed location points; if there are location points that meet set conditions, then determine the location points as potential interference source location points, the set conditions including that the proportion of terminal users whose signal strength corresponding to the location point exceeds a first set strength is within a first set range, and the proportion of terminal users whose signal strength is lower than a second set strength is greater than a second set threshold; and determine that terminal users whose signal strength exceeds the first set strength among the potential interference source location points are potential interference source users.

[0025] Optionally, the calculation module is specifically used to: measure the report data including the identification code of the terminal user when accessing the site; determine the average signal strength corresponding to each identification code and the number of times each identification code appears based on the measurement report data; identify the terminal user corresponding to the identification code that appears more than a set threshold number of times at each location point as the terminal user corresponding to the location point; and determine the average signal strength corresponding to the terminal user as the corresponding access signal strength.

[0026] Optionally, the calculation module is specifically used to: if the measurement report data includes azimuth parameters and signal propagation time parameters; set the position granularity including setting the azimuth granularity and setting the signal propagation time granularity; take the integer quotient of the azimuth parameter corresponding to each sampling point in the cell and the set azimuth granularity as the first integer quotient; take the integer quotient of the signal propagation time parameter corresponding to each sampling point in the cell and the set signal propagation time granularity as the second integer quotient; and determine the sampling points with the same first integer quotient and the same second integer quotient as sampling points belonging to the same position point.

[0027] Optionally, the calculation module is also used to determine the center longitude and center latitude of a location point after determining that the location point is a potential interference source location point if there is a location point that meets the set conditions. This is based on the azimuth parameters and signal propagation time parameters of all sampling points in each location point.

[0028] Optionally, the determination module is specifically used to input the location information of potential interference source locations into the clustering algorithm model, output the clusters corresponding to each potential interference source location, determine the overlap coefficient between potential interference source users and terminal users that appear repeatedly in each cluster, and determine the location of the cluster with the highest overlap coefficient as the location of the interference source to be investigated based on the ranking of the overlap coefficients.

[0029] Optionally, the determining module is specifically used to: determine the number of times the identification code of potential interference source users appears in each cluster as the first count; determine the number of times the identification code of potential interference source users that appears at least twice in each cluster as the second count; and determine the ratio of the second count to the first count as the overlap coefficient corresponding to the cluster.

[0030] Thirdly, this disclosure also provides an electronic device comprising:

[0031] At least one processor;

[0032] and memory that is communicatively connected to at least one processor;

[0033] The memory stores instructions that can be executed by at least one processor to cause the electronic device to perform a wireless network external interference detection method corresponding to any embodiment of the first aspect of this disclosure.

[0034] Fourthly, this disclosure also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement a wireless network external interference troubleshooting method as described in any of the first aspects of this disclosure.

[0035] Fifthly, this disclosure also provides a computer program product comprising computer execution instructions, which, when executed by a processor, are used to implement a wireless network external interference troubleshooting method as described in any of the first aspects of this disclosure.

[0036] The wireless network external interference investigation method, apparatus, device, and storage medium disclosed herein screen out target cells with interference sources from the cells to be detected based on the uplink interference level of the cell to be detected; then, it acquires the measurement report data of the target cells and determines the potential interference source users and potential interference source locations in the target cells based on the location of the sampling points and signal strength; finally, based on cluster analysis of the potential interference source users and potential interference source locations, it determines the location of the interference source to be investigated from the potential interference source locations. Therefore, by automatically screening target cells with interference sources based on the uplink interference level of the cells, it achieves proactive judgment of interference sources; by automating the analysis based on measurement report data, it can greatly save analysis costs; and by using cluster analysis, it can centrally locate the location of interference sources, ensuring the accuracy of location judgment, thereby greatly improving the efficiency and reliability of interference investigation. Attached Figure Description

[0037] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0038] Figure 1 This is an application scenario diagram of the wireless network external interference investigation method provided in this disclosure embodiment;

[0039] Figure 2 A flowchart illustrating a method for troubleshooting external interference in a wireless network according to an embodiment of this disclosure;

[0040] Figure 3a A flowchart of a method for troubleshooting external interference in a wireless network provided in yet another embodiment of this disclosure;

[0041] Figure 3b for Figure 3a The flowchart for determining the location of a sampling point provided in the illustrated embodiment;

[0042] Figure 3c for Figure 3a The flowchart for determining the terminal user and access signal strength provided in the illustrated embodiment;

[0043] Figure 3d for Figure 3a The flowchart for determining the overlap coefficient is provided in the illustrated embodiment;

[0044] Figure 4 A schematic diagram of the structure of a wireless network external interference detection device provided in yet another embodiment of this disclosure;

[0045] Figure 5 This is a schematic diagram of the structure of an electronic device provided in yet another embodiment of this disclosure.

[0046] The accompanying drawings have illustrated specific embodiments of this disclosure, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concepts of this disclosure to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0047] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0048] The technical solutions of this disclosure and how they solve the aforementioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of this disclosure will now be described with reference to the accompanying drawings.

[0049] In the early stages of wireless network deployment, coverage is often incomplete, resulting in some weak coverage issues. In such cases, some users resort to installing wireless repeaters to improve signal strength. While this method may improve communication quality for the individual installer, the technical specifications of these privately installed repeaters are often poor, and they haven't undergone professional testing. The equipment operates in a non-linear range, causing external interference such as uplink noise and intermodulation interference. In addition, various devices other than those from telecommunications operators can also cause external interference to wireless base station equipment.

[0050] External interference is often characterized by its high degree of interference, wide range of impact, and fixed timing, severely affecting the communication experience of surrounding users. Therefore, it is necessary to locate and address external interference sources in a timely manner to ensure the overall user experience of the wireless network.

[0051] Current methods for identifying external interference sources cannot proactively determine whether external interference exists within a cell. Instead, they rely on a series of procedures to investigate when severe uplink interference is detected. For external interference, operators carry frequency scanning equipment to locate the interference source within the cell's coverage area and conduct on-site inspections. This approach is inefficient, fails to proactively detect the presence of external interference, and often stops after discovering a privately installed repeater, resulting in poor effectiveness in identifying external interference.

[0052] To address the aforementioned issues, this disclosure provides a method for troubleshooting external interference in wireless networks. Based on uplink interference levels and measurement report data, it proactively identifies the location of external interference sources. This achieves proactive, automated, and accurate location of external interference sources, improving the efficiency and effectiveness of external interference troubleshooting.

[0053] The application scenarios of the embodiments of this disclosure are explained below:

[0054] Figure 1 This diagram illustrates an application scenario of the wireless network external interference troubleshooting method provided in this embodiment of the disclosure. Figure 1 As shown, in the process of troubleshooting external interference in a wireless network, the detection device 100 (which may be a computer, other servers, or dedicated detection equipment) automatically determines the location of the interference source 120 in the cell based on the measurement report data reported by each cell base station 110, thereby realizing the automated troubleshooting of external interference sources.

[0055] It should be noted that, Figure 1 The scenario shown is illustrated using only one example of a detection device, cell base station, and interference source, but this disclosure is not limited to this. In other words, the number of detection devices, cell base stations, and interference sources can be arbitrary.

[0056] The following detailed description of the wireless network external interference troubleshooting method provided in this disclosure uses specific embodiments. It should be noted that the following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0057] Figure 2 This is a flowchart of a method for troubleshooting external interference in a wireless network according to an embodiment of this disclosure.

[0058] like Figure 2 As shown, it includes the following steps:

[0059] Step S201: Based on the uplink interference level of the cell to be detected, select the target cell with interference source from the cells to be detected.

[0060] Specifically, uplink interference refers to interference signals encountered by a base station in the uplink frequency band of a wireless network from external sources. Uplink interference reduces base station coverage because, when uplink interference occurs, the signal strength of the mobile phone or other terminal must be stronger than the signal strength of the interfering signal in order to communicate with the base station. Therefore, the mobile phone must be closer to the base station. Consequently, when uplink interference is present, the terminal's received signal level may be normal, but its transmit power when communicating with the base station is higher than normal. The transmit power under uplink interference can be determined by the uplink interference level.

[0061] Since uplink interference is usually external interference, the uplink interference level can be used to determine whether external interference exists.

[0062] When the uplink interference level of the cell to be tested exceeds the set threshold, it can be considered that there is an interference source in the cell to be tested.

[0063] Uplink interference levels can be obtained from base station-related indicator data provided by the operator. Therefore, it can be used to determine whether there is an interference source in the cell to be detected.

[0064] Step S202: Obtain the measurement report data of the target cell.

[0065] The measurement report data includes the location of the sampling point and the signal strength when the terminal user in the target cell connects.

[0066] Specifically, measurement report data refers to the raw network data that the base station (or network node) receives and reports from the terminal during the end-user access process.

[0067] The measurement report data includes the time point at which the end user generated the measurement report data (i.e., the sampling point, the sampling time, or the sampling period), the encoding / identification code of the network node accessed by the end user, the identity code of the end user when accessing the network node / interface, the signal strength, the accessed base station number, the cell's corresponding frequency number, the cell's corresponding physical identifier, the signal propagation time from the base station to the terminal, and the terminal's reference azimuth angle relative to the base station. Among these, the combination of the accessed base station number, the cell's corresponding frequency number, and the cell's corresponding physical identifier can uniquely identify a cell. The other information can be used to determine the terminal's location, whether it is an interference source, etc.

[0068] Step S203: Based on the location of the sampling point and the signal strength, determine the potential interference source users and the location points of potential interference sources in the target cell.

[0069] Specifically, the location of the sampling point can be calculated using the signal propagation time from the base station to the terminal and the reference azimuth angle of the terminal relative to the base station. This is because the signal propagation time from the base station to the terminal can be converted into the distance between the base station and the terminal. Combined with the reference azimuth angle, the position of the terminal relative to the base station can be obtained, which is the location of the sampling point.

[0070] If the terminal signal strength at the sampling point is too strong, it can be assumed that the terminal user corresponding to the sampling point may have used a privately installed repeater (a privately installed repeater will increase the signal strength when it accesses the base station). Thus, the potential interference source users and the location points of potential interference sources in the target cell (i.e., the location of the corresponding sampling point) can be determined.

[0071] Step S204: Based on the cluster analysis of potential interference source users and potential interference source location points, determine the location of the interference source to be investigated from the potential interference source location points.

[0072] Specifically, since the location and signal strength of the corresponding terminal (such as a mobile phone) of the same end user may change within a certain period of time, such as when moving between different rooms, there may be different sampling points corresponding to the same end user. That is, multiple potential interference source users and potential interference source location points may correspond to the same end user. Therefore, it is necessary to perform cluster analysis on these potential interference source users and potential interference source location points to find potential interference source users and potential interference source location points in the same or similar locations, avoid duplication, and improve the accuracy and reliability of finding external interference sources.

[0073] Since on-site handling is required after locating the interference source (privately installed repeaters cannot be remotely handled through the operator's equipment), the located interference source can be directly identified as the location of the interference source to be investigated. Then, staff can go to the designated location to investigate and handle the interference, thus completing the external interference investigation process.

[0074] The wireless network external interference investigation method provided in this disclosure filters out target cells with interference sources from the cells to be detected based on the uplink interference level of the cell to be detected; then, it acquires the measurement report data of the target cell and determines the potential interference source users and potential interference source locations in the target cell based on the location of the sampling points and the signal strength; finally, based on the cluster analysis of the potential interference source users and potential interference source locations, it determines the location of the interference source to be investigated from the potential interference source locations. Therefore, by automatically filtering target cells with interference sources based on the uplink interference level of the cell, it achieves proactive judgment of interference sources; by performing automated analysis based on measurement report data, it can greatly save analysis costs; and by using cluster analysis, it can centrally locate the location of interference sources, ensuring the accuracy of location judgment, thereby greatly improving the efficiency and reliability of interference investigation.

[0075] Figure 3a This is a flowchart illustrating a method for troubleshooting external interference in a wireless network, as provided in this disclosure. Figure 3a As shown, the wireless network external interference troubleshooting method provided in this embodiment includes the following steps:

[0076] Step S301: Obtain the daily uplink interference level of the cell to be detected.

[0077] Specifically, the detection equipment (which can be a computer, server, or dedicated detection device) can obtain the daily uplink interference level of each cell to be tested on a regular basis (such as at 1 a.m. every day) through the network management data platform provided by the operator.

[0078] The obtained daily uplink interference level can be measured in hours, and the uplink interference level changes of each cell under test can be determined in time-division format.

[0079] Step S302: Based on the uplink interference level of a single day, determine the average uplink interference level of the cell to be detected during a set period.

[0080] Specifically, for end users within the community (rather than end users in office buildings and commercial complexes), the most significant impact on actual experience occurs during the six hours from 8:00 AM to 11:00 AM and from 6:00 PM to 9:00 PM daily. This is because end users are usually at home during these two periods and have a strong need for network access. Therefore, these two periods can be used as the set time periods, and the average uplink interference level during the set time periods can be calculated to determine whether there is significant uplink interference in the community to be tested.

[0081] Step S303: If the average uplink interference level reaches the first set threshold, determine the cell to be detected as the target cell.

[0082] Specifically, the first set threshold is a preset value that is greater than the normal uplink interference level range. If the average uplink interference level during the set time period reaches the first set threshold, it can be considered that there is an interference source in the cell to be detected, causing the average uplink interference level in the cell to be detected to exceed the normal uplink interference level range. Even if the overall uplink interference level of the cell to be detected increases to varying degrees, the cell to be detected can be identified as the target cell so that the cell to be detected can be further analyzed to determine the location of the interference source.

[0083] Step S304: Obtain the measurement report data of the target cell.

[0084] The measurement report data includes the location of the sampling point and the signal strength when the terminal user in the target cell connects.

[0085] Specifically, this step is related to Figure 2 The steps of S202 in the illustrated embodiment are the same and will not be repeated here.

[0086] Step S305: Based on the set location granularity and the location of the sampling point in the target cell, determine the location point to which the sampling point belongs.

[0087] Specifically, since sampling points in a community may be distributed in hundreds of different locations (terminal devices in different rooms of the same household may also generate different sampling points), and the same terminal user may generate multiple sampling points at different times and locations (for example, if the same terminal user is in the living room in the morning and in the bedroom at night, it may correspond to different sampling points), if the analysis is performed directly on the basis of sampling points, it may divide the terminal user corresponding to the same privately installed repeater into a large number of different sampling points (different sampling points may correspond to different specific locations), which will significantly increase the amount of computation and affect the accuracy of the results analysis and judgment.

[0088] Therefore, it is necessary to group the sampling points according to their location to obtain location points containing multiple sampling points, and then perform subsequent analysis on the basis of location points to reduce the amount of calculation and improve the accuracy of the location analysis of interference sources such as privately installed repeaters.

[0089] Because the location parameters expressed in the measurement report data include azimuth parameters and signal propagation time parameters, and the distance corresponding to one unit of signal propagation time parameter is relatively large (a unit of signal propagation time parameter can correspond to a distance of 78.12 meters, and the specific distance from the terminal to the base station can be determined based on the number of units of signal propagation time parameter), while the angle corresponding to one unit of azimuth parameter covers a relatively small range (a unit of azimuth parameter corresponds to an angle change of 0.5 degrees), if only the area corresponding to the unit of azimuth parameter and the unit of signal propagation time parameter is considered as a single location point, there will be a problem of overly fine division, resulting in too many location points.

[0090] Therefore, it is necessary to divide the location points by setting the location granularity to avoid the problem of excessively fine division, which would lead to increased computational load and insufficient accuracy of analysis results.

[0091] Furthermore, such as Figure 3b As shown, this is a flowchart for determining the location of a sampling point, and its specific steps include:

[0092] Step S3051: Take the integer quotient of the azimuth parameter corresponding to each sampling point in the cell and the set azimuth granularity as the first integer quotient.

[0093] Specifically, since the azimuth parameter per unit angle corresponds to a small angle, the azimuth granularity can be set to a value greater than 1, such as 4 unit angles (i.e., the range of every two degrees of azimuth) as a group.

[0094] The integer quotient is the integer result of dividing the azimuth parameter of the sampling point by the set azimuth granularity. This allows for convenient grouping of the azimuth parameters of the sampling points according to the set azimuth granularity.

[0095] Step S3052: Use the integer quotient of the signal propagation time parameter corresponding to each sampling point in the cell and the set signal propagation time granularity as the second integer quotient.

[0096] Specifically, since the distance corresponding to the signal propagation time parameter per unit time is relatively large, the granularity of the signal propagation time can be set to 1 or a value less than 1 (such as 0.5). The algorithm also uses integer quotients to achieve rapid grouping of the signal propagation time parameters.

[0097] Step S3053: The sampling points with the same first integer quotient and the same second integer quotient are determined as sampling points belonging to the same location point.

[0098] Specifically, for two or more sampling points that have the same first integer quotient and the same second integer quotient, they can be assigned to the same location point. This allows for rapid grouping of sampling points, thereby improving the accuracy of subsequent analysis.

[0099] Step S306: Remove locations where the number of sampling points is less than a set value.

[0100] Specifically, the method for dividing location points given in the aforementioned steps will inevitably result in many location points that do not contain sampling points (e.g., the actual location corresponding to the location point is just an open space in the community) or the number of sampling points is insufficient (i.e., less than the set value, e.g., the actual location corresponding to the location point is only temporarily occupied by a terminal, such as a community square). In this case, such location points can be directly removed to improve the accuracy of the analysis.

[0101] In some embodiments, the set value can be set to 100, meaning that only locations with a large number of sampling points need to be analyzed. Locations with fewer sampling points usually do not need to deploy interference sources, and even if interference sources are deployed, they will not have a significant impact on the uplink interference level (because the number of sampling points is small, that is, the terminal corresponding to this location connects to the network less often, and there is no situation of using a privately installed repeater for a long time, so it will not significantly affect the uplink interference level).

[0102] Step S307: Determine the terminal user and the access signal strength of the terminal user corresponding to the location point after the removal process.

[0103] Specifically, to determine whether an interference source exists, it is necessary to consider the location of the terminal users and their signal strength. If the signal strength of some terminal users is significantly stronger than that of other terminal users, then these terminal users are very likely to be users who have used the interference source, i.e., potential interference source users.

[0104] Furthermore, such as Figure 3c This is a flowchart for determining the end user and the access signal strength, and its specific steps include:

[0105] Step S3071: Based on the measurement report data, determine the average signal strength corresponding to each identification code and the number of times each identification code appears.

[0106] Specifically, since each location point contains multiple sampling points, and each sampling point corresponds to an identity code of a terminal user, the number of times the same identity code appears at the same location point can be calculated, and the corresponding average signal strength can be calculated.

[0107] For example, as shown in Table 1, it is a statistical table of the number of times the identification code appears and the average signal strength at the location point.

[0108] Table 1. Frequency of Identification Code Occurrence and Average Signal Strength at Location Points

[0109] Community Name Location point number Identification code Sampling point count Average signal strength cellA No.1 user1 5 -72 cellA No.1 user2 7 -110 cellA No.1 user3 3 -104 cellA No.1 user4 6 -102 cellA No.1 user5 4 -108 … … … … …

[0110] This allows for the rapid identification of end users at each location point and the calculation of their average signal strength, in order to determine whether there are situations where the signal strength is significantly higher than others.

[0111] Step S3072: Identify the terminal users corresponding to the identity codes that appear more than a set threshold number of times at each location point as the terminal users corresponding to the location points.

[0112] Specifically, since there may be some terminal users (identification codes) that have only appeared a few times at the same location, these sampling points are likely to be temporary points where someone passes by (such as sampling points generated when passing by the door of a household). If such data is included in the analysis, it may affect the accuracy of the results (such as when passing by the door, the terminal user passing by usually does not connect to the network node of this household). Therefore, it is necessary to remove the records of terminal users (identification codes) that appear very infrequently.

[0113] In some embodiments, the number of occurrences threshold can be set to 2, meaning that a user appearing more than twice is considered the terminal user corresponding to that location point, in order to improve the accuracy of the analysis.

[0114] Step S3073: Determine the average signal strength corresponding to the terminal user as the corresponding access signal strength.

[0115] Specifically, for ease of analysis, the average signal strength of the end user can be directly used as the signal strength of its access (base station or network node), reducing the amount of subsequent calculations and improving computational efficiency.

[0116] Step S308: If a location point meets the set conditions, then the location point is determined to be a potential interference source location point.

[0117] The set conditions include the proportion of terminal users whose signal strength at a location point exceeds a first set strength and falls within a first set range, and the proportion of terminal users whose signal strength is lower than a second set strength and exceeds a second set threshold.

[0118] Specifically, since the effect of installing a privately installed repeater (i.e., an interference source) is to increase the signal strength of end users while reducing the signal strength of other end users in the vicinity, the presence of an interference source can be determined based on the signal strength distribution of end users at the location point. If the set conditions are met, it is considered that an interference source may exist (because it cannot be completely determined yet, and further verification and judgment are required).

[0119] In some embodiments, the first set intensity can be -80 dB, the second set intensity can be -92 dB, the first set range can be 0 to 15%, and the second set threshold can be 75%. That is, the setting conditions are that the proportion of terminal users (number of identification codes) with signal strength exceeding -80 dB to the total number of terminal users at that location is between 0 and 15%, and the proportion of terminal users with signal strength below -92 dB to the total number of terminal users at that location is greater than 75%. At this time, it is considered that there is an interference source at that location, or that the location is a potential interference source location.

[0120] In some embodiments, after determining the location of potential interference sources, it is also necessary to determine the center longitude and center latitude of the location point based on the azimuth parameters and signal propagation time parameters of all sampling points in each location point.

[0121] Specifically, since each location point actually corresponds to a large area and range, in order to facilitate the specific location of the interference source, the specific coordinates (i.e., longitude and latitude) of each sampling point in the location point can be calculated based on the azimuth parameters and signal propagation time parameters of the sampling points in the location point. Then, the center longitude and center latitude of the location point can be calculated so as to more accurately locate the location point and the location of the interference source.

[0122] The center longitude and center latitude of the location point are calculated by using the longitude and latitude of each sampling point. That is, the coordinates of its center point are calculated based on multiple coordinates. There are many calculation methods, and those skilled in the art can choose any method to calculate it. No limitation is made here.

[0123] Step S309: Identify terminal users whose signal strength exceeds a first set strength at potential interference source locations as potential interference source users.

[0124] Specifically, while determining the location of potential interference sources, it is also possible to identify terminal users whose signal strength exceeds a first set strength as potential interference source users, and these terminal users can be identified using their identification codes.

[0125] For example, the calculation results for each potential interference source location and the corresponding potential interference source user in each cell are shown in the table below.

[0126] Table 2. Locations of potential interference sources within each community, i.e., a list of potential interference source users.

[0127]

[0128] Therefore, it is possible to quickly obtain the location points of potential interference sources in each cell, as well as information on potential interference source users, and to proactively identify interference sources.

[0129] Step S310: Input the location information of potential interference source locations into the clustering algorithm model, and output the clusters corresponding to each potential interference source location.

[0130] Specifically, because the location point division is relatively mechanical, it is easy to assign a household to different location points. Furthermore, each terminal user may appear in different locations (such as different rooms) at different sampling points, and there may be multiple terminal users and multiple location points corresponding to the same interference source (such as a household with four terminal users connected to a privately installed repeater, but this household is assigned to two different location points). Therefore, it is necessary to conduct further cluster analysis on potential interference source location points and potential interference source users to avoid repeatedly identifying the same interference source.

[0131] Since each potential interference source location point usually has more than one potential interference source user, and what actually needs to be investigated is the interference source rather than the user, the potential interference source location point and its location information are used as the object of cluster analysis (rather than the potential interference source user) to ensure the accuracy of the analysis.

[0132] In some embodiments, the clustering algorithm model can employ the DBSCAN algorithm (Density-Based Spatial Clustering of Applications with Noise). This algorithm can divide high-density regions into clusters, that is, it clusters potential interference source locations based on their actual locations (such as the center longitude and center latitude calculated in the aforementioned steps), grouping potential interference source locations that are close in actual location into the same cluster, thereby improving the accuracy of the analysis.

[0133] Furthermore, based on the existing DBSCAN algorithm, the input variable is the actual position of the potential interference source location point, and the calculation content is to calculate the distance between the actual positions of the potential interference source location points.

[0134] The DBSCAN algorithm requires the min_samples parameter (the minimum number of samples required for each cluster) to be set to 3 (this parameter can be increased if the sampling point density of the cell is high, and decreased to 2 if it is low). The eps parameter (the requirement for establishing a cluster is that the distance between min_samples samples and the current sample is less than or equal to the value of the eps parameter) can be set to 100 meters or the distance corresponding to the signal propagation time parameter per unit time (i.e., 78.12 meters).

[0135] This allows us to obtain clustering results for the locations of each potential interference source (each location can be uniquely identified by its cell name and location number), enabling us to more accurately determine the location of the interference source.

[0136] In some embodiments, after calculating the clustering results, it is also necessary to calculate the central longitude and central latitude of the cluster. The calculation method is based on the mean of the central longitude and central latitude of all locations in the cluster.

[0137] Step S311: Determine the overlap coefficient between potential interference source users and recurring terminal users in each cluster.

[0138] Specifically, in step S310, cluster analysis was performed only based on the location of potential interference source points. However, errors may still exist at this point. For example, the potential interference source point corresponding to a certain cluster may only be a frequent path for potential interference source users (e.g., a potential interference source point is on the same floor as the potential interference source point in another cluster). Therefore, it is necessary to recalculate whether the potential interference source users in the cluster have a sufficiently high degree of overlap (i.e., overlap coefficient) with the terminal users that appear repeatedly in the cluster, in order to maximize the accuracy of interference source location judgment.

[0139] Furthermore, such as Figure 3d The flowchart shown is for determining the overlap coefficient, and its specific steps include:

[0140] Step S3111: Determine the number of times the identification code of potential interference source users appears in each cluster as the first count.

[0141] Specifically, determining the overlap coefficient first requires identifying the number of times potential interference source users appear in the cluster, i.e., the first occurrence count. The first occurrence count can be determined by directly counting the number of times the identification codes of potential interference source users appear in the cluster.

[0142] Step S3112: Determine the number of times the identity code of the potential interference source user that appears at least twice in each cluster is the second occurrence number.

[0143] Specifically, the second step is to determine the frequency of occurrence of potential interference source users that will reappear in the cluster, and the second count. The purpose of calculating the overlap coefficient is to see whether the potential interference source users appearing in the cluster are the most frequent potential interference source users in that cluster, rather than potential interference source users along the path. Therefore, the second count only considers potential interference source users that will reappear.

[0144] Step S3113: Determine the ratio of the second number to the first number as the overlap coefficient corresponding to the clustering.

[0145] Specifically, the higher the overlap coefficient, the greater the probability that the potential interference source users appearing in the cluster are the resident users of the corresponding location in the cluster, that is, the users using the interference source (privately installed repeater) at the corresponding location.

[0146] Step S312: Based on the ranking of overlap coefficients, determine the location of the cluster with the highest overlap coefficient as the location of the interference source to be investigated.

[0147] Specifically, after determining the overlap coefficient, the overlap coefficient can be sorted, and the positions of each cluster can be checked in turn to effectively avoid omissions and at the same time realize the active discovery of the location of interference sources.

[0148] In some embodiments, a threshold for the overlap coefficient can also be set. Only when the overlap coefficient is greater than the threshold will the corresponding cluster be identified as the cluster that needs to be investigated, so as to improve the investigation efficiency.

[0149] The wireless network external interference investigation method provided in this disclosure determines the target cell containing interference sources based on the daily uplink interference level of the cell to be detected. It then divides the target cell into location points and identifies potential interference source locations based on the terminal user signal strength at those locations. Finally, it uses cluster analysis to find the possible cluster locations of the interference sources. This approach proactively discovers interference source locations by combining daily data. Furthermore, by dividing the location points and performing cluster analysis, it maximizes the accuracy of interference source location analysis. Finally, by calculating the overlap coefficient, it automatically establishes a list of investigation order, greatly improving the efficiency and effectiveness of the investigation process.

[0150] Figure 4 This is a schematic diagram of a wireless network external interference detection device provided in this disclosure. Figure 4 As shown, the wireless network external interference investigation device 400 includes: a screening module 410, a data acquisition module 420, a calculation module 430, and a determination module 440. Wherein:

[0151] The filtering module 410 is used to filter out target cells with interference sources from the cells to be detected based on the uplink interference level of the cell to be detected.

[0152] The acquisition module 420 is used to acquire measurement report data of the target cell. The measurement report data includes the location of the sampling point and the signal strength when the terminal user in the target cell connects.

[0153] The calculation module 430 is used to determine potential interference source users and potential interference source locations in the target cell based on the location of the sampling point and the signal strength.

[0154] The determination module 440 is used to determine the location of the interference source to be investigated from the potential interference source location points based on cluster analysis of potential interference source users and potential interference source location points.

[0155] Optionally, the data collection module 420 specifically includes: CPU utilization, memory utilization, number of TCP / IP connections, disk input / output read / write utilization, CPU load, network throughput, and number of file handles; the server logs include: user operation logs and application process logs.

[0156] Optionally, the filtering module 410 is specifically used to: obtain the daily uplink interference level of the cell to be detected; determine the average uplink interference level of the cell to be detected over a set period based on the daily uplink interference level; and determine the cell to be detected as the target cell if the average uplink interference level reaches a first set threshold.

[0157] Optionally, the calculation module 430 is specifically used to: determine the location point to which the sampling point belongs based on the set location granularity and the location of the sampling point in the target cell; remove location points containing fewer than a set number of sampling points; determine the terminal users and access signal strength of the terminal users corresponding to the removed location points; if there are location points that meet the set conditions, then determine the location points as potential interference source location points, the set conditions including that the proportion of terminal users whose signal strength corresponding to the location point exceeds a first set strength is within a first set range, and the proportion of terminal users whose signal strength is lower than a second set strength is greater than a second set threshold; and determine that terminal users whose signal strength exceeds the first set strength among the potential interference source location points are potential interference source users.

[0158] Optionally, the calculation module 430 is specifically used to: measure the report data including the identification code of the terminal user when accessing the site; determine the average signal strength corresponding to each identification code and the number of occurrences of each identification code based on the measurement report data; identify the terminal user corresponding to the identification code that appears more than a set threshold number of times at each location point as the terminal user corresponding to the location point; and determine the average signal strength corresponding to the terminal user as the corresponding access signal strength.

[0159] Optionally, the calculation module 430 is specifically used to: if the measurement report data includes azimuth parameters and signal propagation time parameters; set the position granularity including setting the azimuth granularity and setting the signal propagation time granularity; take the integer quotient of the azimuth parameter corresponding to each sampling point in the cell and the set azimuth granularity as the first integer quotient; take the integer quotient of the signal propagation time parameter corresponding to each sampling point in the cell and the set signal propagation time granularity as the second integer quotient; and determine the sampling points with the same first integer quotient and the same second integer quotient as sampling points belonging to the same position point.

[0160] Optionally, the calculation module 430 is further configured to, if a location point satisfies the set conditions, determine the center longitude and center latitude of the location point based on the azimuth parameters and signal propagation time parameters of all sampling points in each location point after determining that the location point is a potential interference source location point.

[0161] Optionally, the determining module 440 is specifically used to input the location information of potential interference source locations into the clustering algorithm model, output the clusters corresponding to each potential interference source location, determine the overlap coefficient between potential interference source users and terminal users that appear repeatedly in each cluster, and determine the location of the cluster with the highest overlap coefficient as the location of the interference source to be investigated based on the ranking of the overlap coefficients.

[0162] Optionally, the determining module 440 is specifically used to: determine the number of times the identification code of a potential interference source user appears in each cluster as the first count; determine the number of times the identification code of a potential interference source user that appears at least twice in each cluster as the second count; and determine the ratio of the second count to the first count as the overlap coefficient corresponding to the cluster.

[0163] In this embodiment, the wireless network external interference investigation device, through the combination of various modules, can solve the problem that external interference cannot be actively detected and investigated in the prior art, realize the active judgment of interference sources, and greatly save analysis costs by performing automated analysis based on measurement report data. Through cluster analysis, the location of interference sources can be centrally located, ensuring the accuracy of location judgment, thereby greatly improving the efficiency and reliability of interference investigation.

[0164] Figure 5 This is a schematic diagram of the structure of an electronic device provided in this disclosure, such as... Figure 5 As shown, the electronic device 500 includes a memory 510 and a processor 520.

[0165] The memory 510 stores a computer program that can be executed by at least one processor 520. This computer program is executed by at least one processor 520 to enable the electronic device to implement the wireless network external interference detection method provided in any of the above embodiments.

[0166] The memory 510 and the processor 520 can be connected via a bus 530.

[0167] The relevant explanations can be understood by referring to the corresponding descriptions and effects in the method embodiments, and will not be repeated here.

[0168] One embodiment of this disclosure provides a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to perform the following: Figures 2 to 3d The corresponding wireless network external interference troubleshooting method in any embodiment.

[0169] The computer-readable storage medium can be ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0170] One embodiment of this disclosure provides a computer program product comprising computer-executable instructions that, when executed by a processor, are used to perform, as follows: Figures 2 to 3d The corresponding wireless network external interference troubleshooting method in any embodiment.

[0171] In the several embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or modules may be electrical, mechanical, or other forms.

[0172] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0173] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for troubleshooting external interference in a wireless network, characterized in that, include: Based on the uplink interference level of the cell to be detected, target cells with interference sources are selected from the cells to be detected; Obtain measurement report data of the target cell, the measurement report data including the location of the sampling point and signal strength when the terminal user in the target cell connects; Based on the location of the sampling points and the signal strength, the potential interference source users and the location points of potential interference sources in the target cell are determined; Based on cluster analysis of the potential interference source users and the potential interference source location points, the location of the interference source to be investigated is determined from the potential interference source location points; The step of determining potential interference source users and potential interference source location points in the target cell based on the location of the sampling points and signal strength includes: Based on the set location granularity and the location of the sampling point in the target cell, the location point to which the sampling point belongs is determined; Remove locations where the number of sampling points is less than a set value; Determine the terminal users and their access signal strengths corresponding to the locations after the removal process; If a location point meets the set conditions, then the location point is determined to be a potential interference source location point. The set conditions include the proportion of terminal users whose signal strength corresponding to the location point exceeds the first set strength being within the first set range, and the proportion of terminal users whose signal strength is lower than the second set strength being greater than the second set threshold. Terminal users whose signal strength exceeds a first set strength at potential interference source locations are identified as potential interference source users.

2. The method for investigating external interference in a wireless network according to claim 1, characterized in that, The process of filtering out target cells containing interference sources from the cells to be detected based on the uplink interference level of the cell to be detected includes: Obtain the daily uplink interference level of the cell to be detected; Based on the single-day uplink interference level, the average uplink interference level of the cell to be detected during a set period is determined; If the average uplink interference level reaches a first preset threshold, the cell to be detected is determined to be the target cell.

3. The method for troubleshooting external interference in a wireless network according to claim 1, characterized in that, The measurement report data includes the identity code of the end user when accessing the system. The process of determining the terminal user and the access signal strength of the terminal user corresponding to the location point after the removal process includes: Based on the measurement report data, the average signal strength corresponding to each identification code and the number of times each identification code appears are determined; The terminal user corresponding to the identity code that appears more than a set threshold number of times at each location point is identified as the terminal user corresponding to the location point. The average signal strength corresponding to the terminal user is determined as the corresponding access signal strength.

4. The method for troubleshooting external interference in a wireless network according to claim 1, characterized in that, The measurement report data includes azimuth parameters and signal propagation time parameters; the set position granularity includes set azimuth granularity and set signal propagation time granularity; The step of determining the location point to which the sampling point belongs based on the set location granularity and the location of the sampling point in the target cell includes: The integer quotient of the azimuth parameter corresponding to each sampling point in the cell and the set azimuth granularity is taken as the first integer quotient; The integer quotient of the signal propagation time parameter corresponding to each sampling point in the cell and the set signal propagation time granularity is used as the second integer quotient; Sampling points with the same first integer quotient and the same second integer quotient are identified as sampling points belonging to the same location point.

5. The method for troubleshooting external interference in a wireless network according to claim 4, characterized in that, After determining that a location point is a potential interference source location point if a location point meets the set conditions, the method further includes: Based on the azimuth parameters and signal propagation time parameters of all sampling points at each location point, the center longitude and center latitude of the location point are determined.

6. The method for investigating external interference in a wireless network according to any one of claims 1 to 5, characterized in that, The step of determining the location of the interference source to be investigated from the potential interference source location points based on cluster analysis of the potential interference source users and the potential interference source location points includes: The location information of the potential interference source points is input into the clustering algorithm model, and the clusters corresponding to each potential interference source point are output. Determine the overlap coefficient between the potential interference source users in each cluster and the recurring terminal users in the cluster; Based on the ranking of the overlap coefficients, the position of the cluster with the highest overlap coefficient is determined as the location of the interference source to be investigated.

7. The method for troubleshooting external interference in a wireless network according to claim 6, characterized in that, Determining the overlap coefficient between the potential interference source users in each cluster and the recurring terminal users in the cluster includes: The number of times the identification code of potential interference source users appears in each cluster is determined as the first count; The number of times the identification code of a potential source of interference that appears at least twice in each cluster is defined as the second occurrence count; The ratio of the second number to the first number is determined as the overlap coefficient corresponding to the clustering.

8. A device for detecting external interference in a wireless network, characterized in that, Applied to servers, including: The filtering module is used to filter out target cells with interference sources from the cells to be detected based on the uplink interference level of the cell to be detected; The acquisition module is used to acquire measurement report data of the target cell, the measurement report data including the location of the sampling point and the signal strength when the terminal user in the target cell connects; The calculation module is used to determine the potential interference source users and potential interference source locations in the target cell based on the location of the sampling points and the signal strength. The determination module is used to determine the location of the interference source to be investigated from the potential interference source location points based on cluster analysis of the potential interference source users and the potential interference source location points; The calculation module is specifically used to determine the location point to which the sampling point belongs based on the set location granularity and the location of the sampling point in the target cell; Remove locations where the number of sampling points is less than a set value; Determine the terminal users and their access signal strengths corresponding to the locations after the removal process; If a location point meets the set conditions, then the location point is determined to be a potential interference source location point. The set conditions include the proportion of terminal users whose signal strength corresponding to the location point exceeds the first set strength being within the first set range, and the proportion of terminal users whose signal strength is lower than the second set strength being greater than the second set threshold. Terminal users whose signal strength exceeds a first set strength at potential interference source locations are identified as potential interference source users.

9. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, cause the electronic device to perform the wireless network external interference investigation method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the wireless network external interference troubleshooting method as described in any one of claims 1 to 7.

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