Method, device and computer storage medium for determining a fault location

Abstract

The application discloses a fault position determination method, device, equipment and computer storage medium. First MR sampling data of a first terminal device in a target room sub-region in a target macro station region and second MR sampling data of the target macro station region are acquired, the target macro station region is a macro station region adjacent to the target room sub-region, and the level of the first terminal device is determined; third MR sampling data matched with the first MR sampling data is screened out from the second MR sampling data; sampling point position information of a sampling point corresponding to the third MR sampling data is acquired; the sampling point corresponding to the third MR sampling data is clustered based on the sampling point position information, and at least one first sampling point set is obtained; and the center position of all sampling points in each first sampling point set is determined, which is the passive device fault position in the target room sub-region. The specific position of the passive device fault can be determined more accurately.

Description

Technical Field

[0001] This application belongs to the field of wireless communication technology, and in particular relates to a method, apparatus, device and computer storage medium for determining fault location. Background Technology

[0002] An indoor distribution system evenly distributes the mobile base station signal throughout a room, ensuring ideal signal coverage for mobile communication among indoor users. An indoor distribution system contains numerous antennas and passive components. Failure of any passive component will affect the communication of terminal devices within the indoor distribution area (the area where the indoor distribution system is installed).

[0003] In existing technologies, fault identification of passive devices in indoor distribution areas is usually achieved through methods such as changes in traffic volume and sampling points. However, this can only determine whether there is a problem with the passive devices in the indoor distribution area, but cannot accurately locate the specific location of the fault. Summary of the Invention

[0004] This application provides a method, apparatus, device, and computer storage medium for determining the location of a fault, which can more accurately determine the specific location of a passive device fault.

[0005] In a first aspect, embodiments of this application provide a method for determining the location of a fault, comprising:

[0006] Acquire the first MR sampling data of the first terminal device in the target macro station area within the target indoor distribution area, and the second MR sampling data in the target macro station area. The target macro station area is the macro station area adjacent to the target indoor distribution area, and is determined based on the level of the first terminal device.

[0007] From the second MR sampling data, select the third MR sampling data that matches the first MR sampling data;

[0008] Obtain the sampling point location information of the sampling point corresponding to the third MR sampling data;

[0009] Based on the sampling point location information, the sampling points corresponding to the third MR sampling data are clustered to obtain at least one set of first sampling points;

[0010] Determine the center position of all sampling points in each first sampling point set as the location of passive device faults within the target indoor distribution area;

[0011] The sampling point represents the location of the terminal device.

[0012] In one possible implementation embodiment, before acquiring the first MR sampling data of the first terminal device in the target macro station area within the target indoor distribution area, the method further includes:

[0013] Within each monitoring cycle, fourth MR sampling data of second terminal devices in multiple indoor distribution areas are collected at preset intervals. The second terminal devices include the first terminal devices.

[0014] For each indoor distribution area, determine the first number of sampling points corresponding to the fourth MR sampling data collected in the nth monitoring cycle, and the second number of sampling points corresponding to the fourth MR sampling data collected in the first m monitoring cycles of the nth monitoring cycle, where n and m are positive integers, and n≥m;

[0015] The target indoor distribution area is defined as the indoor distribution area where the difference between the average of the second quantity and the first quantity is greater than a first threshold.

[0016] In one possible implementation, acquiring the first MR sampling data of the first terminal device in the target macro station area within the target indoor distribution area includes:

[0017] Within each monitoring cycle, the fifth MR sampling data of the third terminal device in the target indoor distribution area is collected at preset intervals. The fifth MR sampling data includes the indoor distribution level and the macro station level of the third terminal device in the target macro station area.

[0018] Based on the indoor distribution level and macro station level, the sampling points corresponding to the fifth MR sampling data collected in the nth monitoring cycle are clustered to obtain the second sampling point set. Then, the sampling points corresponding to the fifth MR sampling data collected in each of the first m monitoring cycles of the nth monitoring cycle are clustered to obtain the third sampling point set. Here, n and m are positive integers, and n≥m.

[0019] Determine a first ratio of the number of sampling points in each second sampling point set to the total number of sampling points corresponding to the fifth MR sampling data, and a second ratio of the number of sampling points in each third sampling point set to the total number of sampling points corresponding to the fifth MR sampling data;

[0020] From the second set of sampling points, select a fourth set of sampling points where the difference between the average of the second ratio and the corresponding first ratio is greater than the second threshold.

[0021] From the fifth MR sampling data, select the first MR sampling data corresponding to each sampling point in the fourth sampling point set.

[0022] In one possible implementation, the target macro station region includes a first target macro station region, a second target macro station region, and a third target macro station region; filtering out third MR sampling data that matches the first MR sampling data from the second MR sampling data includes:

[0023] Compare the first MR sampling data of the first terminal device in the first target macro station area with the second MR sampling data of the first target macro station area, the first MR sampling data of the first terminal device in the second target macro station area with the second MR sampling data of the second target macro station area, and the first MR sampling data of the first terminal device in the third target macro station area with the second MR sampling data of the third target macro station area.

[0024] From the second MR sampling data, select the third MR sampling data that completely matches the first MR sampling data of the first terminal device in the first target macro station area with the second MR sampling data of the first target macro station area, the first MR sampling data of the first terminal device in the second target macro station area with the second MR sampling data of the second target macro station area, and the first MR sampling data of the first terminal device in the third target macro station area with the second MR sampling data of the third target macro station area.

[0025] In one possible implementation, the third MR sampling data includes the horizontal angle, vertical angle, and distance of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area;

[0026] Obtain the sampling point location information corresponding to the sampling points of the third MR sampling data, including:

[0027] Triangulation transformation is performed on the horizontal angle, vertical angle, and distance to obtain the sampling point location information of the sampling point corresponding to the third MR sampling data.

[0028] In one possible implementation, the third MR sampling data further includes a beam ID; before clustering the sampling points corresponding to the third MR sampling data based on the sampling point location information to obtain at least one set of sampling points, the method further includes:

[0029] Obtain the beam direction angle, horizontal beamwidth, beam downtilt angle, and vertical beamwidth corresponding to the beam ID;

[0030] Based on the beam direction angle, horizontal lobe width, beam downtilt angle and vertical lobe width corresponding to the beam ID, and the horizontal and vertical angles of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro station area, determine the sixth MR sampling data in the third MR sampling data whose beam angle meets the preset conditions.

[0031] Based on the sampling point location information, the sampling points corresponding to the third MR sampling data are clustered to obtain at least one set of sampling points, including:

[0032] Based on the sampling point location information, the sampling points corresponding to the sixth MR sampling data are clustered to obtain at least one set of sampling points.

[0033] Secondly, embodiments of this application provide a device for determining the location of a fault, comprising:

[0034] The acquisition module is used to acquire the first MR sampling data of the first terminal device in the target macro station area within the target indoor distribution area, and the second MR sampling data in the target macro station area. The target macro station area is the macro station area adjacent to the target indoor distribution area, and is determined based on the level of the first terminal device.

[0035] The filtering module is used to filter out the third MR sampling data that matches the first MR sampling data from the second MR sampling data;

[0036] The acquisition module is also used to acquire the sampling point location information of the sampling point corresponding to the third MR sampling data;

[0037] The clustering module is used to cluster the sampling points corresponding to the third MR sampling data based on the sampling point location information to obtain at least one set of first sampling points;

[0038] The determination module is used to determine the center position of all sampling points in each first sampling point set, which is the location of passive device faults within the target indoor distribution area;

[0039] The sampling point represents the location of the terminal device.

[0040] Thirdly, embodiments of this application provide an electronic device, the device comprising:

[0041] Processor and memory storing computer program instructions;

[0042] A method for determining the location of a fault that occurs when a processor executes computer program instructions to achieve any of the above-mentioned functions.

[0043] Fourthly, embodiments of this application provide a computer storage medium on which computer program instructions are stored, and when the computer program instructions are executed by a processor, a method for determining the fault location of any of the above-mentioned items is implemented.

[0044] Fifthly, embodiments of this application provide a computer program product, characterized in that, when the instructions in the computer program product are executed by the processor of an electronic device, the electronic device is able to execute any of the above-mentioned methods for determining the fault location.

[0045] This application discloses a method, apparatus, device, and computer storage medium for determining the fault location. The method includes: acquiring first MR sampling data of a first terminal device in a target macro station area within a target indoor distributed antenna system (DAS) region, and second MR sampling data of the target macro station area, wherein the target macro station area is a macro station area adjacent to the target DAS region, and the data is determined based on the voltage level of the first terminal device; filtering out third MR sampling data that matches the first MR sampling data from the second MR sampling data; acquiring sampling point location information of the sampling points corresponding to the third MR sampling data; clustering the sampling points corresponding to the third MR sampling data based on the sampling point location information to obtain at least one first sampling point set; and determining the center position of all sampling points in each first sampling point set as the fault location of the passive device within the target DAS region.

[0046] In this way, for the target indoor distributed antenna system (DAS) area where passive devices have failed, the MR sampling data of the first terminal device in the target indoor DAS area and all MR sampling data of the target macro base station area are obtained. From all the MR sampling data of the target macro base station area, the MR sampling data that matches the MR sampling data of the first terminal device in the target macro base station area are selected. The situation of macro base station replacing indoor DAS coverage is analyzed, that is, the terminal devices that should have used indoor DAS base stations in the target indoor DAS area but actually used macro base stations in the target macro base station area are screened out. The location of the passive device in the target indoor DAS area is determined by the location information of the terminal device when it is sampling, which can more accurately determine the specific location of the passive device failure. Attached Figure Description

[0047] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a flowchart illustrating a method for determining the location of a fault according to an embodiment of this application;

[0049] Figure 2 This is a schematic diagram of a scene containing all sampling points in the first sampling point set provided in another embodiment of this application;

[0050] Figure 3 This is a flowchart illustrating a method for determining the fault location provided in another embodiment of this application;

[0051] Figure 4 This is a schematic diagram illustrating the comparison of the number of sampling points over time according to another embodiment of this application;

[0052] Figure 5This is a flowchart illustrating a method for determining the fault location provided in another embodiment of this application;

[0053] Figure 6 This is a comparison diagram of a macro station replacing an indoor distribution system provided in another embodiment of this application;

[0054] Figure 7 This is a top view of the sampling point relative to the horizontal angle of the base station in the target macro base station area provided in another embodiment of this application;

[0055] Figure 8 This is a side view of the sampling point relative to the vertical angle of the base station in the target macro base station area, provided in another embodiment of this application;

[0056] Figure 9 This is a summary diagram of the horizontal angle, vertical angle, and distance of the sampling points relative to the base station in the target macro base station area, provided in another embodiment of this application;

[0057] Figure 10 This is a schematic diagram of the beam angle corresponding to the beam ID provided in another embodiment of this application;

[0058] Figure 11 This is a schematic diagram of the structure of a fault location determination device provided in another embodiment of this application;

[0059] Figure 12 This is a schematic diagram of the structure of an electronic device provided in another embodiment of this application. Detailed Implementation

[0060] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0061] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0062] An indoor distribution system evenly distributes the mobile base station signal throughout a room, ensuring ideal signal coverage for mobile communication among indoor users. An indoor distribution system contains numerous antennas and passive components. Failure of any passive component will affect the communication of terminal devices within the indoor distribution area (the area where the indoor distribution system is installed).

[0063] In existing technologies, fault identification of passive devices in indoor distribution areas is usually achieved through methods such as changes in traffic volume and sampling points. However, this can only determine whether there is a problem with the passive devices in the indoor distribution area, but cannot accurately locate the specific location of the fault.

[0064] To address the problems of existing technologies, embodiments of this application provide a method, apparatus, device, and computer storage medium for determining fault locations. The method for determining fault locations provided in this application, for a target indoor distributed antenna system (DAS) area where a passive device has failed, acquires measurement report (MR) sampling data of a first terminal device in the target indoor DAS area within the target macro base station area, as well as all MR sampling data of the target macro base station area. From the all MR sampling data of the target macro base station area, MR sampling data matching the MR sampling data of the first terminal device in the target macro base station area is selected. This identifies terminal devices that should have been using the indoor DAS base station in the target indoor DAS area but were actually using the macro base station in the target macro base station area. By using the location information of the terminal device during sampling, the fault location of the passive device in the target indoor DAS area can be determined more accurately, enabling a more precise determination of the specific location of the passive device fault.

[0065] The method for determining the fault location provided in the embodiments of this application will be introduced first below. Figure 1 A flowchart illustrating a method for determining fault location according to an embodiment of this application is shown.

[0066] like Figure 1As shown, the method for determining the fault location provided in this application includes the following steps.

[0067] S110. Acquire the first MR sampling data of the first terminal device in the target macro station area within the target indoor distribution area, and the second MR sampling data of the target macro station area. The target macro station area is a macro station area adjacent to the target indoor distribution area, and is determined based on the level of the first terminal device.

[0068] Here, the target indoor distribution area is the indoor distribution area where the passive device has failed, and the first terminal device is located within the target indoor distribution area.

[0069] It should be noted that, in this embodiment, the MR sampling data is data reported by the terminal device as a sampling point. The data reported by the sampling point may include level, frequency, physical cell representation, sampling point location information, and horizontal angle, vertical angle, and distance relative to the base station, etc.

[0070] In some embodiments, the first MR sampling data of the first terminal device within the target indoor distribution area includes the indoor distribution level and the first MR sampling data of the first terminal device in the target macro base station area, wherein the first MR sampling data in the target macro base station area includes the macro base station level. The second MR sampling data includes the macro base station levels of all terminal devices within the target macro base station area.

[0071] In some embodiments, the target macro base station area is a macro base station area adjacent to the target indoor distributed antenna system (DAS) area. The target macro base station area is determined based on the voltage level of the first terminal device. For the first terminal device, this includes not only the indoor DAS voltage level but also the macro base station voltage level provided by neighboring cells. The target macro base station area is the macro base station area corresponding to the maximum macro base station voltage level. The first MR sampling data of the first terminal device in the target macro base station area also includes the frequency point and physical cell identifier of the target macro base station area, which can uniquely identify the target macro base station area. Second MR sampling data corresponding to the frequency point and physical cell identifier of the target macro base station area is then obtained. Here, the MR sampling data of macro base station areas with the same frequency point and physical cell identifier only needs to be obtained once.

[0072] It should be noted that different target indoor distribution zones can have the same target macro station zone.

[0073] S120. From the second MR sampling data, select the third MR sampling data that matches the first MR sampling data.

[0074] In some embodiments, the third MR sampling data matching the first MR sampling data may be the macro base station level in the second MR sampling data that is consistent with the macro base station level in the first MR sampling data. It is understood that the sampling point corresponding to the third MR sampling data is the location of the terminal equipment that should have used an indoor distributed base station in the target indoor area but actually used a macro base station in the target macro base station area.

[0075] S130. Obtain the sampling point location information of the sampling point corresponding to the third MR sampling data.

[0076] Here, the location information of the sampling point can be represented by (x, y, z), where x is longitude, y is latitude, and z is altitude.

[0077] S140. Based on the sampling point location information, cluster the sampling points corresponding to the third MR sampling data to obtain at least one set of first sampling points.

[0078] In some embodiments, since there may be more than one fault location for a passive device, directly determining the center point of the sampling point corresponding to the third MR sampling data cannot accurately determine multiple fault locations. Therefore, based on the sampling point location information, the sampling points corresponding to the third MR sampling data are first clustered to obtain at least one set of first sampling points. It can be understood that the number of the first sampling point sets is equal to the number of fault locations for the passive device.

[0079] S150. Determine the center position of all sampling points in each first sampling point set, which is the location of the passive device fault within the target indoor distribution area.

[0080] The sampling point represents the location of the terminal device.

[0081] In some embodiments, the center position of all sampling points in each first sampling point set can be represented as (x_0, y_0, z_0). Figure 2 This is a scene diagram showing all sampling points in the first set of sampling points, such as... Figure 2 As shown, x_0 is the mean longitude of all sampling points in a first sampling point set, y_0 is the mean latitude of all sampling points in a first sampling point set, and z_0 is the mean altitude of all sampling points in a first sampling point set.

[0082] In this way, for the target indoor distributed antenna system (DAS) area where passive devices have failed, the MR sampling data of the first terminal device in the target indoor DAS area and all MR sampling data of the target macro base station area are obtained. From all the MR sampling data of the target macro base station area, the MR sampling data that matches the MR sampling data of the first terminal device in the target macro base station area are selected. The situation of macro base station replacing indoor DAS coverage is analyzed, that is, the terminal devices that should have used indoor DAS base stations in the target indoor DAS area but actually used macro base stations in the target macro base station area are screened out. The location of the passive device in the target indoor DAS area is determined by the location information of the terminal device when it is sampling, which can more accurately determine the specific location of the passive device failure.

[0083] Based on this, in some embodiments, such as Figure 3 As shown, prior to S110 above, the method may further include:

[0084] S101. During each monitoring cycle, the fourth MR sampling data of the second terminal devices in multiple indoor distribution areas are collected at preset intervals. The second terminal devices include the first terminal devices.

[0085] S102. For each indoor distribution area, determine the first number of sampling points corresponding to the fourth MR sampling data collected in the nth monitoring cycle, and the second number of sampling points corresponding to the fourth MR sampling data collected in the first m monitoring cycles of the nth monitoring cycle, where n and m are positive integers, and n≥m;

[0086] S103. Determine the indoor distribution area where the difference between the average of the second quantity and the first quantity is greater than the first threshold as the target indoor distribution area.

[0087] Here, the first threshold is preset. In some embodiments, within each monitoring cycle, MR sampling data from second terminal devices in multiple indoor distribution areas are collected at preset intervals. The collected MR sampling data mainly includes the data shown in Table 1, as follows.

[0088] Table 1

[0089]

[0090]

[0091] Wherein, the horizontal angle of arrival, the vertical angle of arrival, and the distance are the horizontal angle, vertical angle, and distance of the sampling point relative to the base station in the macro base station area, respectively.

[0092] It is understood that the actual MR sampling data collected is not limited to the data listed in Table 1. A fourth MR sampling data point is extracted from the collected MR sampling data. This fourth MR sampling data point includes the indoor distribution level, as well as the macro base station level, frequency point, and physical cell identifier of neighboring cells.

[0093] Specifically, for indoor distributed antenna system (DAS) cells that need to be evaluated, the MR data is preprocessed in advance. For each original reported sampling point, key information of the indoor DAS area plus the three strongest neighboring cells is extracted. The preprocessed data format is (NRSc, NRNc_1, NRNc_2, NRNc_3), where NRSc is the key information of the indoor DAS area (such as voltage level), NRNc_1 is the key information of the strongest neighboring cell (such as voltage level, frequency point, and physical cell identifier), NRNc_2 is the key information of the second strongest neighboring cell (such as voltage level, frequency point, and physical cell identifier), and NRNc_3 is the key information of the third strongest neighboring cell (such as voltage level, frequency point, and physical cell identifier).

[0094] In some embodiments, a comparative analysis of the changes in MR sampling points in an indoor distributed antenna system (DAS) region is performed to identify areas with potential passive device faults. Specifically, for each DAS region, a first number of sampling points corresponding to the fourth MR sampling data collected in the nth monitoring cycle is determined, and a second number of sampling points corresponding to the fourth MR sampling data collected in the previous m monitoring cycles of the nth monitoring cycle is determined. The difference between the average of the second number and the first number is calculated, and DAS regions with a difference greater than a first threshold are identified as target DAS regions.

[0095] It should be noted that the difference between the average of the second quantity and the first quantity is the value obtained by subtracting the first quantity from the average of the second quantity.

[0096] As an example, such as Figure 4 As shown, based on the number of fourth MR sampling points collected in the daily granular monitoring indoor distribution area, the total number of sampling points for the day is denoted as MR_num, the total number of sampling points corresponding to the previous Thursday is denoted as MR_num1, and the total number of sampling points corresponding to the previous two Thursdays is denoted as MR_num2. If a holiday occurs, the count is carried forward one week. The daily average is compared with the average of the previous two Thursdays. If the number of sampling points decreases by more than 20%, i.e., MR_num < 0.8 * (MR_num1 + MR_num2) / 2, then the indoor distribution area is designated as a suspected indoor distribution passive device fault area, and this area is designated as the target indoor distribution area.

[0097] In this way, the changes in the number of sampling points within multiple monitoring cycles can be determined in real time. If the number of sampling points in the target indoor distribution area decreases significantly, it indicates that there must be a faulty passive device in the target indoor distribution area. By observing the changes in the number of sampling points, the target indoor distribution area can be identified in real time, thereby determining the location of the fault in the target indoor distribution area, guiding on-site fault handling, and avoiding the impact of passive device faults that cannot be detected by conventional methods on the network user's perception.

[0098] Based on this, in some embodiments, such as Figure 5As shown, in S110 above, acquiring the first MR sampling data of the first terminal device in the target macro station area within the target indoor distribution area can specifically include:

[0099] S210. During each monitoring cycle, the fifth MR sampling data of the third terminal device in the target indoor distribution area is collected at preset intervals. The fifth MR sampling data includes the indoor distribution level and the macro station level of the third terminal device in the target macro station area.

[0100] S220. Based on the indoor distribution level and macro station level, cluster the sampling points corresponding to the fifth MR sampling data collected in the nth monitoring cycle to obtain the second sampling point set, and cluster the sampling points corresponding to the fifth MR sampling data collected in each of the first m monitoring cycles of the nth monitoring cycle to obtain the third sampling point set, where n and m are positive integers, and n≥m;

[0101] S230. Determine a first ratio between the number of sampling points in each second sampling point set and the total number of sampling points corresponding to the fifth MR sampling data, and a second ratio between the number of sampling points in each third sampling point set and the total number of sampling points corresponding to the fifth MR sampling data.

[0102] S240. From the second set of sampling points, select a fourth set of sampling points in which the difference between the average value of the second ratio and the corresponding first ratio is greater than the second threshold.

[0103] S250. From the fifth MR sampling data, select the first MR sampling data corresponding to each sampling point in the fourth sampling point set.

[0104] Here, the second threshold is preset. The sampling points in the fourth sampling point set are the sampling points corresponding to the first terminal device.

[0105] In some embodiments, for a third terminal device in an indoor distributed antenna system (DAS) area suspected of having a faulty passive device, the indoor DAS level and the macro base station level in the target macro base station area are extracted. Based on the indoor DAS level and the macro base station level, the sampling points corresponding to the fifth MR sampling data collected in the nth monitoring cycle are clustered to obtain a second sampling point set. Then, the sampling points corresponding to the fifth MR sampling data collected in each of the first m monitoring cycles of the nth monitoring cycle are clustered to obtain a third sampling point set. The ratio of the number of sampling points in each sampling point set to the total number of sampling points is determined, and the sampling point set with the largest decrease in ratio is selected. The fault location is determined based on the MR sampling data corresponding to the sampling points in this sampling point set.

[0106] It is understandable that clustering is performed once within a monitoring cycle.

[0107] It should be noted that the difference between the average of the second ratio and the corresponding first ratio is the average of the second ratio minus the value of the first ratio.

[0108] In some embodiments, the fifth MR sampling data may also include frequency points and physical cell identifiers, and the data format is standardized according to the following data structure, wherein the indoor distribution level and macro station level are aggregated in intervals of 5dB to reduce the complexity of sampling point combination.

[0109] As an example, when the target macrocell area includes three locations, the resulting fourth set of sampling points can be represented in a combined form, such as date1 = (-75~-70, 504990, 122, -80~-75, 504990, 134, -85~-80, 504990, 139, -100~-95). Here, -75~-70 represents the indoor distribution level, -80~-75, -85~-80, and -100~-95 represent the macrocell levels; 504990 represents the frequency point; and 122, 134, and 139 represent the physical cell identifiers. The proportion of each combination in all data is calculated, and combinations with a decrease in proportion exceeding 0.5% are selected and denoted as Combi_1~z. The MR sampling data of the sampling points corresponding to these z combinations are used as the first MR sampling data. Z can be 10.

[0110] In some embodiments, the first MR sampling data is stored in a database.

[0111] In this way, for the third terminal device in the indoor distribution area of ​​the suspected faulty passive device, the first terminal device that reported a decrease in sampling points is selected from it, and it is determined that the macro station area used by the first terminal device was originally a terminal device in the indoor distribution area, thereby determining the location of the fault.

[0112] Based on this, in some embodiments, the target macro station region includes a first target macro station region, a second target macro station region, and a third target macro station region; from the second MR sampling data, filtering out the third MR sampling data that matches the first MR sampling data includes:

[0113] Compare the first MR sampling data of the first terminal device in the first target macro station area with the second MR sampling data of the first target macro station area, the first MR sampling data of the first terminal device in the second target macro station area with the second MR sampling data of the second target macro station area, and the first MR sampling data of the first terminal device in the third target macro station area with the second MR sampling data of the third target macro station area.

[0114] From the second MR sampling data, select the third MR sampling data that completely matches the first MR sampling data of the first terminal device in the first target macro station area with the second MR sampling data of the first target macro station area, the first MR sampling data of the first terminal device in the second target macro station area with the second MR sampling data of the second target macro station area, and the first MR sampling data of the first terminal device in the third target macro station area with the second MR sampling data of the third target macro station area.

[0115] In some embodiments, the first MR sampling data includes a first voltage level, a first frequency point, and a first physical cell identifier; the second MR sampling data includes a second voltage level, a second frequency point, and a second physical cell identifier. For example... Figure 6 As shown, the diagram compares the first and second voltage levels of the first terminal device in the first target macro base station region, the first and second frequency points of the first terminal device in the second target macro base station region, the first and second physical cell identifiers of the first terminal device in the second target macro base station region, the first and second voltage levels of the first terminal device in the second target macro base station region, the first and second frequency points of the first terminal device in the third target macro base station region, the first and second physical cell identifiers of the first terminal device in the third target macro base station region, and the first and second voltage levels of the first terminal device in the third target macro base station region. The meanings of the symbols representing the indoor sampling points in the diagram are shown in Table 2, which is as follows.

[0116] Table 2

[0117]

[0118]

[0119] The meanings of the symbols representing the macro-station sampling points in the figure are shown in Table 3, which is as follows.

[0120] Table 3

[0121]

[0122] From the second MR sampling data, select the third MR sampling data where all the following match: the first level of the first terminal device in the first target macro base station region and the second level of the first target macro base station region; the first frequency point of the first terminal device in the second target macro base station region and the second frequency point of the first terminal device in the second target macro base station region; the first physical cell identifier of the first terminal device in the second target macro base station region and the second physical cell identifier of the first terminal device in the second target macro base station region; the first level of the first terminal device in the second target macro base station region and the second level of the second target macro base station region; the first frequency point of the first terminal device in the third target macro base station region and the second frequency point of the third target macro base station region; the first physical cell identifier of the first terminal device in the third target macro base station region and the second physical cell identifier of the first terminal device in the third target macro base station region; and the first level of the first terminal device in the third target macro base station region and the second level of the third target macro base station region.

[0123] It should be noted that the first target macro station area is the strongest neighboring cell of the target indoor distribution area, the second target macro station area is the second strongest neighboring cell of the target indoor distribution area, and the third target macro station area is the third strongest neighboring cell of the target indoor distribution area.

[0124] In this way, based on the level, frequency point, and physical cell identifier, the third MR sampling data that matches the first MR sampling data in the macro base station area can be more accurately determined. The strongest neighboring cell in the indoor distribution sampling point is equivalent to the macro base station area. At the same time, the second strongest neighboring cell in the indoor distribution is matched with the strongest neighboring cell in the macro base station, and the third strongest neighboring cell in the indoor distribution is matched with the second strongest neighboring cell in the macro base station. This allows for more accurate screening of the sampling points that the macro base station takes over after a passive device failure occurs in the indoor distribution area, thereby improving the accuracy of fault location determination.

[0125] Based on this, in some embodiments, the third MR sampling data includes the horizontal angle, vertical angle and distance of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area;

[0126] Obtain the sampling point location information corresponding to the sampling points of the third MR sampling data, including:

[0127] Triangulation transformation is performed on the horizontal angle, vertical angle, and distance to obtain the sampling point location information of the sampling point corresponding to the third MR sampling data.

[0128] In some embodiments, the sampling point is initially located by the distance S + horizontal angle reported value hAOA + vertical angle reported value dAOA relative to the base station in the target macro base station area. The straight-line distance S from the sampling point to the base station in the macro base station area is calculated using a time advance NRScTadv, where S = NRScTadv * 39. 39 can be understood as a fixed propagation speed.

[0129] In some embodiments, the horizontal angle of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area is determined by the horizontal angle reporting value hAOA. Figure 7 This is a top view of the horizontal angle of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area. α represents the horizontal angle between the sampling point and the antenna coverage normal direction, that is, the horizontal angle of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area.

[0130] Specifically, the horizontal angle of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area is determined by the horizontal angle reported value hAOA. This includes: determining the horizontal angle interval of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area based on the correspondence between the horizontal angle reported value hAOA and the horizontal angle interval of the sampling point relative to the base station in the target macro base station area, and taking the midpoint of the interval as the horizontal angle of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area. The correspondence between the horizontal angle reported value hAOA and the horizontal angle interval of the sampling point relative to the base station in the target macro base station area is shown in Table 4.

[0131] Table 4

[0132] hAOA reported value Horizontal angle range 0 0 ≤ horizontal angle < 0.5 1 0.5 ≤ horizontal angle < 1.0 2 1.0 ≤ horizontal angle < 1.5 … … 717 358.5 ≤ horizontal angle < 359.0 718 359.0 ≤ horizontal angle < 359.5 719 359.5 ≤ horizontal angle < 360

[0133] In some embodiments, the vertical angle of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area is calculated using the vertical angle reported value dAOA. Figure 8 This is a side view of the vertical angle of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro station area. γ represents the vertical angle between the sampling point and the antenna coverage normal direction. For ease of calculation, γ + the antenna elevation angle is denoted as β, where β is the angle between the sampling point and the horizontal plane.

[0134] Specifically, the vertical angle of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area is determined by the vertical angle reported value dAOA. This includes: determining the vertical angle interval of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area based on the correspondence between the vertical angle reported value dAOA and the vertical angle interval of the sampling point relative to the base station in the target macro base station area; and taking the middle value of the interval as the vertical angle of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area. The correspondence between the vertical angle reported value dAOA and the vertical angle interval of the sampling point relative to the base station in the target macro base station area is shown in Table 5.

[0135] Table 5

[0136] dAOA reported value Vertical angle interval 0 0≤perpendicular angle<1 1 1≤perpendicular angle<2 2 2≤perpendicular angle<3 … … 357 357 ≤ vertical angle < 358 358 358 ≤ vertical angle < 359 359 359 ≤ vertical angle < 360

[0137] In some embodiments, such as Figure 9As shown, by summarizing the horizontal angle, vertical angle, and distance of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area, triangulation can be performed on the horizontal angle, vertical angle, and distance to obtain the sampling point location information corresponding to the third MR sampling data. Specifically, by using the distance S of the sampling point from the antenna, the angle α between the sampling point and the antenna normal direction, and the angle β between the sampling point and the horizontal plane, the sampling point is located through a second triangulation algorithm. Combined with the latitude and longitude information of the base station, the final sampling point location information is converted into a three-dimensional geographic coordinate (x, y, z), where x is longitude, y is latitude, and z is altitude.

[0138] In this way, the sampling location information of the sampling point can be determined by the MR sampling data reported by the sampling point, that is, by the horizontal angle, vertical angle and distance of the sampling point relative to the base station in the target macro base station area, and then the location of the passive device fault can be determined.

[0139] Based on this, in some embodiments, the third MR sampling data further includes a beam ID; before clustering the sampling points corresponding to the third MR sampling data based on the sampling point location information to obtain at least one set of sampling points, the method further includes:

[0140] Obtain the beam direction angle, horizontal beamwidth, beam downtilt angle, and vertical beamwidth corresponding to the beam ID;

[0141] Based on the beam direction angle, horizontal lobe width, beam downtilt angle and vertical lobe width corresponding to the beam ID, and the horizontal and vertical angles of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro station area, determine the sixth MR sampling data in the third MR sampling data whose beam angle meets the preset conditions.

[0142] Based on the sampling point location information, the sampling points corresponding to the third MR sampling data are clustered to obtain at least one set of sampling points, including:

[0143] Based on the sampling point location information, the sampling points corresponding to the sixth MR sampling data are clustered to obtain at least one set of sampling points.

[0144] Here, the sixth MR sampling data is the valid sampling point.

[0145] In some embodiments, radio waves are affected by obstacles and refracted when they are transmitted in the air. In order to ensure the accuracy of fault location, the sampling point position is calibrated by the downtilt angle and azimuth angle of the beam ID corresponding to the sampling point synchronization signal (SSB) beam, and sampling points with large deviations are eliminated.

[0146] Specifically, such as Figure 10 As shown in the figure, the beam angle corresponding to the beam ID in the third MR sampling data is illustrated, where X is the beam ID in the third MR sampling data. The beam direction angle α_x, horizontal beamwidth x_h, beam downtilt angle β_x, and vertical beamwidth x_d corresponding to the beam ID are obtained. If the horizontal angle of the sampling point satisfies α-α_x>2*x_h or β-β_x>2*x_d, then the deviation between the sampling point position and the beam angle corresponding to the beam ID in the third MR sampling data is too large, and this sampling point is considered an unreliable sampling point, thus its data is discarded. After SSB beam angle calibration, valid sampling points are retained. Based on the sampling point position information of the valid sampling points, the valid sampling points are clustered to obtain at least one set of sampling points.

[0147] In this way, by calibrating the sampling point positions, that is, by eliminating sampling points with large deviations and removing the interference of sampling points with large deviations, the fault location of passive devices can be located more accurately.

[0148] In the embodiments provided in this application, by combining MR data from macro base stations and indoor distribution systems, and leveraging the precise positioning characteristics of macro base station beam-level MR, accurate location of faults in indoor distribution system passive devices is achieved. Compared to traditional methods that rely on MR to identify faults but not to pinpoint their location, this method achieves precise fault location. It allows for rapid analysis and location of faults in indoor distribution system passive devices without adding additional components. Fault location for passive devices can be achieved without Wi-Fi or OTT (Over-The-Top) data, making the troubleshooting process simpler and faster. It can be completed independently without cross-departmental coordination of Wi-Fi or OTT data. It can operate intelligently with minimal manual intervention, saving significant manpower.

[0149] The embodiments provided in this application use information such as frequency point, level, physical cell identifier, beam ID, horizontal angle of arrival, vertical angle of arrival, and distance in MR data to locate faults in indoor distributed antenna systems (DAS) passive devices. It can accurately identify areas where passive device faults exist, and can also accurately locate indoor DAS fault locations through macro-micro collaboration, ultimately outputting a list of fault locations.

[0150] In the embodiments provided in this application, by utilizing the changes in the number of indoor distributed MR sampling points, the fault area of ​​indoor distributed passive devices can be identified. At the same time, by combining the macro base station SSB beam positioning fault location, the fault location of indoor distributed passive devices can be quickly identified and located in batches. This can promptly and effectively detect the faults of passive devices in the existing network, guide on-site fault handling, and avoid the impact of passive device faults that cannot be detected by conventional methods on the network user's perception.

[0151] Based on the fault location determination method provided in the above embodiments, this application also provides specific implementations of the fault location determination device. Please refer to the following embodiments.

[0152] First see Figure 11 The fault location determination device 300 provided in this application embodiment includes:

[0153] The acquisition module 310 is used to acquire the first MR sampling data of the first terminal device in the target macro station area within the target indoor distribution area, and the second MR sampling data of the target macro station area. The target macro station area is the macro station area adjacent to the target indoor distribution area, and is determined based on the level of the first terminal device.

[0154] The filtering module 320 is used to filter out the third MR sampling data that matches the first MR sampling data from the second MR sampling data;

[0155] The acquisition module 310 is also used to acquire the sampling point location information of the sampling point corresponding to the third MR sampling data;

[0156] Clustering module 330 is used to cluster the sampling points corresponding to the third MR sampling data based on the sampling point location information to obtain at least one set of first sampling points;

[0157] The determination module 340 is used to determine the center position of all sampling points in each first sampling point set, which is the location of the passive device fault within the target indoor distribution area;

[0158] The sampling point represents the location of the terminal device.

[0159] Based on this, in some embodiments, the device 300 may further include:

[0160] The acquisition module is used to acquire fourth MR sampling data of multiple second terminal devices in the target macro station area at preset intervals in each monitoring cycle before acquiring the first MR sampling data of the first terminal device in the target indoor distribution area. The second terminal devices include the first terminal device.

[0161] The determination module 340 is also used to determine, for each indoor distribution area, the first number of sampling points corresponding to the fourth MR sampling data collected in the nth monitoring cycle, and the second number of sampling points corresponding to the fourth MR sampling data collected in the first m monitoring cycles of the nth monitoring cycle, where n and m are positive integers, and n≥m;

[0162] The determination module 340 is also used to determine the indoor distribution area where the difference between the average of the second quantity and the first quantity is greater than the first threshold as the target indoor distribution area.

[0163] Based on this, in some embodiments, the acquisition module 310 can be specifically used for:

[0164] Within each monitoring cycle, the fifth MR sampling data of the third terminal device in the target indoor distribution area is collected at preset intervals. The fifth MR sampling data includes the indoor distribution level and the macro station level of the third terminal device in the target macro station area.

[0165] Based on the indoor distribution level and macro station level, the sampling points corresponding to the fifth MR sampling data collected in the nth monitoring cycle are clustered to obtain the second sampling point set. Then, the sampling points corresponding to the fifth MR sampling data collected in each of the first m monitoring cycles of the nth monitoring cycle are clustered to obtain the third sampling point set. Here, n and m are positive integers, and n≥m.

[0166] Determine a first ratio of the number of sampling points in each second sampling point set to the total number of sampling points corresponding to the fifth MR sampling data, and a second ratio of the number of sampling points in each third sampling point set to the total number of sampling points corresponding to the fifth MR sampling data;

[0167] From the second set of sampling points, select a fourth set of sampling points where the difference between the average of the second ratio and the corresponding first ratio is greater than the second threshold.

[0168] From the fifth MR sampling data, select the first MR sampling data corresponding to each sampling point in the fourth sampling point set.

[0169] Based on this, in some embodiments, the target macro station region includes a first target macro station region, a second target macro station region, and a third target macro station region; the filtering module 320 can specifically be used for:

[0170] Compare the first MR sampling data of the first terminal device in the first target macro station area with the second MR sampling data of the first target macro station area, the first MR sampling data of the first terminal device in the second target macro station area with the second MR sampling data of the second target macro station area, and the first MR sampling data of the first terminal device in the third target macro station area with the second MR sampling data of the third target macro station area.

[0171] From the second MR sampling data, select the third MR sampling data that completely matches the first MR sampling data of the first terminal device in the first target macro station area with the second MR sampling data of the first target macro station area, the first MR sampling data of the first terminal device in the second target macro station area with the second MR sampling data of the second target macro station area, and the first MR sampling data of the first terminal device in the third target macro station area with the second MR sampling data of the third target macro station area.

[0172] Based on this, in some embodiments, the third MR sampling data includes the horizontal angle, vertical angle and distance of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area;

[0173] Module 310 can be specifically used for:

[0174] Triangulation transformation is performed on the horizontal angle, vertical angle, and distance to obtain the sampling point location information of the sampling point corresponding to the third MR sampling data.

[0175] Based on this, in some embodiments, the third MR sampling data further includes a beam ID; the device 300 may also include:

[0176] The acquisition module 310 is also used to acquire the beam direction angle, horizontal beam width, beam downtilt angle and vertical beam width corresponding to the beam ID before clustering the sampling points corresponding to the third MR sampling data based on the sampling point location information to obtain at least one set of sampling points.

[0177] The determination module 340 is also used to determine the sixth MR sampling data in the third MR sampling data whose beam angle meets the preset conditions based on the beam direction angle, horizontal beam width, beam downtilt angle and vertical beam width corresponding to the beam ID, and the horizontal and vertical angles of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro station area.

[0178] Clustering module 330 can be specifically used for:

[0179] Based on the sampling point location information, the sampling points corresponding to the sixth MR sampling data are clustered to obtain at least one set of sampling points.

[0180] Each module of the fault location determination device provided in this application embodiment can realize the functions of each step of the fault location determination method provided above, and can achieve its corresponding technical effects. For the sake of brevity, it will not be described in detail here.

[0181] Based on the same inventive concept, embodiments of this application also provide an electronic device.

[0182] Figure 12 A schematic diagram of the hardware structure of the electronic device provided in an embodiment of this application is shown.

[0183] An electronic device may include a processor 401 and a memory 402 storing computer program instructions.

[0184] Specifically, the processor 401 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0185] Memory 402 may include mass storage for data or instructions. For example, and not limitingly, memory 402 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 402 may include removable or non-removable (or fixed) media. Where appropriate, memory 402 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 402 is non-volatile solid-state memory.

[0186] Memory may include read-only memory (ROM), random access memory (RAM), disk storage media devices, optical storage media devices, flash memory devices, and electrical, optical, or other physical / tangible memory storage devices. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0187] The processor 401 reads and executes computer program instructions stored in the memory 402 to implement any of the fault location determination methods in the above embodiments.

[0188] In one example, the electronic device may also include a communication interface 403 and a bus 410. For example, Figure 12 As shown, the processor 401, memory 402, and communication interface 403 are connected through bus 410 and complete communication with each other.

[0189] The communication interface 403 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0190] Bus 410 includes hardware, software, or both, that couples components of an electronic device together. For example, and not limitingly, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Linear Predictive Coding (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (Peripheral Component Interconnect-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VESA Local Bus, VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 410 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application contemplates any suitable bus or interconnection. The electronic device can perform the fault location determination method in the embodiments of the present invention, thereby implementing the fault location determination method described above.

[0191] Furthermore, in conjunction with the fault location determination method in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the fault location determination methods in the above embodiments.

[0192] This application also provides a computer program product in which the instructions, when executed by the processor of an electronic device, cause the electronic device to perform various processes implementing any of the above-described embodiments of the fault location determination method.

[0193] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0194] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memory (ROM), flash memory, erasable read-only memory (EROM), floppy disks, compact disc read-only memory (CD-ROM), optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0195] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0196] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0197] The above are merely specific embodiments of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for determining the location of a fault, characterized in that, include: Acquire first MR sampling data of a first terminal device in a target macro station area within a target indoor distribution area, and second MR sampling data of the target macro station area, wherein the target macro station area is a macro station area adjacent to the target indoor distribution area, and is determined based on the voltage level of the first terminal device; From the second MR sampling data, third MR sampling data that matches the first MR sampling data is selected. The third MR sampling data includes the horizontal and vertical angles of the sampling points corresponding to the third MR sampling data relative to the base station in the target macro base station area. The third MR sampling data also includes the beam ID. Obtain the sampling point location information of the sampling point corresponding to the third MR sampling data; Obtain the beam direction angle, horizontal lobe width, beam downtilt angle, and vertical lobe width corresponding to the beam ID; Based on the beam direction angle, horizontal lobe width, beam downtilt angle and vertical lobe width corresponding to the beam ID, and the horizontal and vertical angles of the sampling points corresponding to the third MR sampling data relative to the base station in the target macro base station area, the sixth MR sampling data in the third MR sampling data that meets the preset conditions is determined, and the sixth MR sampling data is the MR sampling data of the valid sampling points; Based on the sampling point location information, the sampling points corresponding to the third MR sampling data are clustered to obtain at least one set of first sampling points; Based on the sampling point location information, the sampling points corresponding to the third MR sampling data are clustered to obtain at least one set of sampling points, including: Based on the sampling point location information, the sampling points corresponding to the sixth MR sampling data are clustered to obtain at least one set of sampling points. Determine the center position of all sampling points in each first sampling point set as the location of the passive device fault within the target indoor distribution area; The sampling point represents the location of the terminal device.

2. The method for determining the fault location according to claim 1, characterized in that, Before acquiring the first MR sampling data of the first terminal device in the target macro station area within the target indoor distribution area, the method further includes: Within each monitoring cycle, fourth MR sampling data of second terminal devices in multiple indoor distribution areas are collected at preset intervals, wherein the second terminal devices include the first terminal devices. For each indoor distribution area, determine the first number of sampling points corresponding to the fourth MR sampling data collected in the nth monitoring cycle, and the second number of sampling points corresponding to the fourth MR sampling data collected in the first m monitoring cycles of the nth monitoring cycle, where n and m are positive integers, and nm; The target indoor distribution area is defined as the indoor distribution area where the difference between the average of the second quantity and the first quantity is greater than a first threshold.

3. The method for determining the fault location according to claim 1, characterized in that, The acquisition of the first MR sampling data of the first terminal device in the target macro station area within the target indoor distribution area includes: Within each monitoring cycle, the fifth MR sampling data of the third terminal device in the target indoor distribution area is collected at preset intervals. The fifth MR sampling data includes the indoor distribution level and the macro station level of the third terminal device in the target macro station area. Based on the indoor distribution level and the macro station level, the sampling points corresponding to the fifth MR sampling data collected in the nth monitoring cycle are clustered to obtain a second sampling point set, and the sampling points corresponding to the fifth MR sampling data collected in each of the first m monitoring cycles of the nth monitoring cycle are clustered to obtain a third sampling point set, where n and m are positive integers, and nm; Determine a first ratio of the number of sampling points in each second sampling point set to the total number of sampling points corresponding to the fifth MR sampling data, and a second ratio of the number of sampling points in each third sampling point set to the total number of sampling points corresponding to the fifth MR sampling data; From the second set of sampling points, select a fourth set of sampling points where the difference between the average of the second ratio and the corresponding first ratio is greater than a second threshold. From the fifth MR sampling data, select the first MR sampling data corresponding to each sampling point in the fourth sampling point set.

4. The method for determining the fault location according to claim 1, characterized in that, The target macro station area includes a first target macro station area, a second target macro station area, and a third target macro station area; The step of filtering out third MR sampling data that matches the first MR sampling data from the second MR sampling data includes: Compare the first MR sampling data of the first terminal device in the first target macro station area with the second MR sampling data of the first target macro station area, the first MR sampling data of the first terminal device in the second target macro station area with the second MR sampling data of the second target macro station area, and the first MR sampling data of the first terminal device in the third target macro station area with the second MR sampling data of the third target macro station area. From the second MR sampling data, select the third MR sampling data that completely matches the first MR sampling data of the first terminal device in the first target macro station area with the second MR sampling data of the first target macro station area, the first MR sampling data of the first terminal device in the second target macro station area with the second MR sampling data of the second target macro station area, and the first MR sampling data of the first terminal device in the third target macro station area with the second MR sampling data of the third target macro station area.

5. The method for determining the fault location according to claim 1, characterized in that, The third MR sampling data includes the horizontal angle, vertical angle, and distance of the sampling point corresponding to the third MR sampling data relative to the base station in the target macro base station area; The step of obtaining the sampling point location information of the sampling point corresponding to the third MR sampling data includes: Triangulation is performed on the horizontal angle, vertical angle, and distance to obtain the sampling point location information of the sampling point corresponding to the third MR sampling data.

6. A device for determining the location of a fault, characterized in that, include: The acquisition module is used to acquire the first MR sampling data of the first terminal device in the target macro station area within the target indoor distribution area, and the second MR sampling data of the target macro station area, wherein the target macro station area is a macro station area adjacent to the target indoor distribution area, and is determined based on the level of the first terminal device; The filtering module is used to filter out third MR sampling data that matches the first MR sampling data from the second MR sampling data. The third MR sampling data includes the horizontal and vertical angles of the sampling points corresponding to the third MR sampling data relative to the base station in the target macro base station area. The third MR sampling data also includes the beam ID. The acquisition module is also used to acquire the sampling point location information of the sampling point corresponding to the third MR sampling data; and to acquire the beam direction angle, horizontal beam width, beam downtilt angle and vertical beam width corresponding to the beam ID; The determining module is used to determine, based on the beam direction angle, horizontal lobe width, beam downtilt angle and vertical lobe width corresponding to the beam ID, and the horizontal and vertical angles of the sampling points corresponding to the third MR sampling data relative to the base station in the target macro base station area, the sixth MR sampling data is the MR sampling data of the valid sampling points; The clustering module is used to cluster the sampling points corresponding to the third MR sampling data based on the sampling point location information to obtain at least one set of first sampling points; The step of clustering the sampling points corresponding to the third MR sampling data based on the sampling point location information to obtain at least one set of sampling points includes: clustering the sampling points corresponding to the sixth MR sampling data based on the sampling point location information to obtain at least one set of sampling points. The determination module is used to determine the center position of all sampling points in each first sampling point set, which is the location of the passive device fault within the target indoor distribution area; The sampling point represents the location of the terminal device.

7. An electronic device, characterized in that, The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the method for determining the fault location as described in any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the method for determining the fault location as described in any one of claims 1-5.

9. A computer program product, characterized in that, When the instructions in the computer program product are executed by the processor of the electronic device, the electronic device is able to perform the fault location determination method as described in any one of claims 1-5.

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