TAC flower arrangement base station identification method and device

Abstract

The invention discloses a TAC flower arrangement base station identification method and device. The method comprises the steps that firstly, whether TACs of all cells in a base station are the same or not is judged, the base station is divided into a first base station or a TAC flower arrangement base station, then intelligent clustering is conducted on the first base station through a density-based spatial clustering algorithm, a target cluster is constructed, noise points which are not matched with the TACs are screened out at the same time, and the TACs in the first base station and the TACs in the second base station are identified. The first noise points point to direct reflection of differences and similarities of the TACs in the clusters, and the second noise points identify the base stations isolated from all the clusters. Furthermore, the abnormal cluster and the normal cluster are accurately judged by evaluating the affiliation condition of the noise points between the target clusters, and finally, all the first base stations in the abnormal cluster, the first noise points with TAC differences in the normal cluster and all the first base stations which are not clustered are uniformly confirmed as the TAC flower arrangement base stations. According to the invention, technical problems of low efficiency and poor accuracy of TAC flower arrangement phenomenon identification of the base station in the prior art are solved.

Description

Technical Field

[0001] This application relates to the field of wireless communication technologies, and in particular, to a method and apparatus for identifying TAC interspersed base stations. Background Art

[0002] In the actual laying process of a wireless network, due to reasons such as planning and equipment installation, there may be a phenomenon that some base stations are interspersed base stations, which may lead to an increase in the number of tracking area updates of user terminals, increasing the system load. The handover process between the interspersed base station and surrounding base stations becomes more complex, increasing the system load, resulting in a longer handover delay and a lower handover success rate, causing problems such as mobile phone call drops and data Internet disconnections and lags. Therefore, in the optimization work of a wireless communication network, it is necessary to identify these tracking area code (TAC) interspersed base stations and solve them.

[0003] Existing TAC interspersed identification methods mainly rely on graphical tools, such as QGIS to merge intersecting polygons, but this method is inefficient and requires manual intervention. When specifically implemented, it is necessary to manually distinguish the colors of different TACs on the map. Limited by the display size of the map software, only regional verification can be performed. When verifying the entire network, the workload is huge, and the underlying map needs to be dragged back and forth to observe the differences in the colors represented by the cell TACs, with low work efficiency and seriously affecting the accuracy of identifying TAC interspersed base stations.

[0004] In view of the above problems, no effective solution has been proposed yet. Summary of the Invention

[0005] Embodiments of this application provide a method and apparatus for identifying TAC interspersed base stations, so as to at least solve the technical problems of low efficiency and poor accuracy in identifying the TAC interspersed phenomenon of base stations in existing solutions.

[0006] According to one aspect of an embodiment of the present application, a method for identifying a TAC interlaced base station is provided, comprising: obtaining base station information of multiple base stations in a target area, wherein the base station information at least includes: a base station location, multiple cells corresponding to the base station, and a tracking area code TAC corresponding to each cell; for each base station, if the TACs of the multiple cells corresponding to the base station are the same, marking the base station as a first base station, and if the TACs of the multiple cells corresponding to the base station are different, determining that the base station is a TAC interlaced base station; performing spatial clustering on the multiple first base stations using a density-based spatial clustering algorithm to obtain multiple target clusters, a first noise point and a second noise point of each target cluster, Points, in the clustering process, for any first base station, when the density condition is met, only the density of other first base stations with the same TAC as the first base station in the neighborhood of the first base station is determined to be reachable, and other first base stations with different TAC from the first base station are determined to be the first noise points of the target cluster corresponding to the first base station, and the first base station that is not divided into any cluster after the clustering is completed is determined to be the second noise point; for each target cluster, if the first noise points corresponding to the target cluster all belong to another target cluster, the target cluster is determined to be an abnormal cluster, otherwise it is a normal cluster; it is determined that all the first base stations in the abnormal cluster, the first noise points of the normal cluster, and the first base stations corresponding to the second noise points are TAC inserted base stations.

[0007] Optionally, obtaining base station information of multiple base stations within the target area includes: obtaining cell information of multiple cells within the target area, wherein the cell information includes at least: the cell name, the physical site code corresponding to the cell, and the TAC; determining that cells with the same physical site code correspond to the same base station, and determining the base station position of the corresponding base station based on the physical site code.

[0008] Optionally, the cell information also includes a cell type. After acquiring the cell information of multiple cells in the target area, the method further includes: removing the cell information of the high-speed railway cell from the cell information of the multiple cells.

[0009] Optionally, use a density-based spatial clustering algorithm to perform spatial clustering on multiple first base stations to obtain multiple target clusters, the first noise points and second noise points of each target cluster, including: obtaining a preset first neighborhood radius and density threshold; for each first base station, respectively determining the distances between the first base station and other first base stations; determining, among the other first base stations whose distances from the first base station are less than the first neighborhood radius, the other first base stations with the same TAC as the first base station as second base stations, and the other first base stations with different TACs from the first base station as third base stations; if the number of second base stations is not less than the density threshold, determining that the first base station is density-reachable from each second base station, clustering the first base station and each second base station into the initial cluster corresponding to the first base station, and determining the third base stations as the first noise points of the initial cluster; if the number of second base stations is less than the density threshold, not processing the first base station; after clustering all the first base stations, aggregating the obtained multiple initial clusters according to the density-reachable relationship between each first base station to obtain multiple target clusters; for each target cluster, determining that the first noise points corresponding to the respective initial clusters corresponding to the target cluster are the first noise points corresponding to the target cluster; and determining the first base stations that are not assigned to any target cluster as second noise points.

[0010] Optionally, the base station location is the longitude and latitude of the base station. Respectively determining the distances between the first base station and other first base stations includes:

[0011] For any two first base stations, determine the distance between the two first base stations through the following formula:

[0012]

[0013] In the formula, L is the distance between base station 1 and base station 2, R is the radius of the earth, lat1 and lat2 are the latitudes of base station 1 and base station 2 respectively, and lon1 and lon2 are the longitudes of base station 1 and base station 2 respectively.

[0014] Optionally, after respectively determining the distances between the first base station and other first base stations, the method further includes: if there are no other first base stations whose distances from the first base station are less than the first neighborhood radius, obtaining a preset second neighborhood radius, where the second neighborhood radius is greater than the first neighborhood radius; determining, among the other first base stations whose distances from the first base station are less than the second neighborhood radius, the other first base stations with the same TAC as the first base station as fourth base stations, and the other first base stations with different TACs from the first base station as fifth base stations; if the number of fourth base stations is not less than the density threshold, determining that the first base station is density-reachable from each fourth base station, clustering the first base station and each fourth base station into the initial cluster corresponding to the first base station, and determining the fifth base stations as the first noise points of the initial cluster; if the number of fourth base stations is less than the density threshold, not processing the first base station.

[0015] Optionally, the obtained multiple initial clusters are aggregated according to the density reachability relationship between each first base station, including: for any two initial clusters, if the two initial clusters include a common first base station, determine that all first base stations in the two initial clusters are density reachable, and aggregate the two initial clusters into one cluster.

[0016] According to another aspect of the embodiment of the present application, a device for identifying a TAC interlaced base station is also provided, including: an acquisition module, used to acquire base station information of multiple base stations in a target area, wherein the base station information includes at least: the base station location, multiple cells corresponding to the base station, and the TAC corresponding to each cell; a first determination module, used to, for each base station, if the TACs of the multiple cells corresponding to the base station are the same, mark the base station as a first base station, and if the TACs of the multiple cells corresponding to the base station are different, determine that the base station is a TAC interlaced base station; a clustering module, used to perform spatial clustering on multiple first base stations using a density-based spatial clustering algorithm to obtain multiple target clusters, a first noise point and a second noise point of each target cluster. Point, in the clustering process, for any first base station, when the density condition is met, only the density of other first base stations with the same TAC as the first base station in the neighborhood of the first base station is determined to be reachable, and other first base stations with different TAC from the first base station are determined as the first noise points of the target cluster corresponding to the first base station, and the first base station that is not divided into any cluster after the clustering is completed is determined to be the second noise point; the second determination module is used for, for each target cluster, if the first noise points corresponding to the target cluster all belong to another target cluster, to determine that the target cluster is an abnormal cluster, otherwise it is a normal cluster; the third determination module is used to determine that all first base stations in the abnormal cluster, the first noise points of the normal cluster, and the first base stations corresponding to the second noise points are TAC interspersed base stations.

[0017] According to another aspect of an embodiment of the present application, a computer program product is also provided, the computer program product comprising: a computer program, wherein when the computer program is executed by a processor, the above-mentioned TAC flower arrangement base station identification method is implemented.

[0018] According to another aspect of an embodiment of the present application, an electronic device is also provided, which includes: a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to execute the above-mentioned TAC flower arrangement base station identification method through the computer program.

[0019] In an embodiment of the present application, after pre-processing the acquired base station information to achieve preliminary screening, a density-based spatial clustering algorithm is introduced, which lays the foundation for the subsequent identification and judgment of abnormal clusters. Therefore, not only can obvious TAC interspersed phenomena be identified, but also abnormal base stations hidden in dense areas can be discovered through clustering analysis, ensuring comprehensive coverage of identification results, thereby solving the technical problems of low efficiency and poor accuracy in the existing solutions for identifying the TAC interspersed phenomenon of base stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0021] Figure 1 is a schematic diagram of an optional TAC flower arrangement base station identification method according to an embodiment of the present application;

[0022] Figure 2 is a schematic diagram of TACs of different cells under an optional base station according to an embodiment of the present application;

[0023] Figure 3 is a schematic diagram of an optional base station neighborhood range according to an embodiment of the present application;

[0024] Figure 4 is a schematic diagram of an optional TAC flower arrangement base station identification device according to an embodiment of the present application;

[0025] Figure 5 It is a schematic diagram of an optional electronic device structure according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0027] It should be noted that the terms "first", "second", etc. in the specification, claims and drawings of the present application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] In order to better understand the embodiments of the present application, some nouns or terms that appear in the description of the embodiments of the present application are first translated and explained as follows:

[0029] TAC interlaced base station: refers to a situation in which the Tracking Area Code (TAC) of one or more base stations in a wireless communication network is different from the TAC of the surrounding adjacent base stations, and this difference is not based on reasonable network planning or geographical layout, but is caused by planning omissions, network adjustment errors, or the complexity of the geographical environment. This phenomenon may appear on the map as TAC areas of different colors interlaced or "interlaced" in distribution, hence the name "TAC interlaced base station".

[0030] Density reachability: In the field of data mining and cluster analysis, "density reachability" is a core concept, mainly used to describe the relationship between points in the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm. The concept of density reachability helps to identify clusters of data points and is particularly suitable for processing data sets containing noise. Specifically, density reachability means that under a given neighborhood radius (Eps) and a minimum point number threshold (MinPts), if starting from one point, you can reach another point along a series of points, and these points contain at least MinPts neighbor points in their neighborhood (that is, the density is not lower than a certain threshold), then the two points are density reachable.

[0031] Noise Points: In the field of data mining and machine learning, especially in cluster analysis, "noise points" refer to data points that neither belong to any cluster nor meet the conditions to be part of a cluster. Noise points usually represent outliers, outliers or patternless points in a data set, which are significantly different from other points in data distribution and do not follow the main trend or pattern of the data.

[0032] Example 1

[0033] According to an embodiment of the present application, a method for identifying a TAC flower-insertion base station is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] Figure 1 is a flow chart of a TAC flower arrangement base station identification method provided according to an embodiment of the present application, such as Figure 1 As shown, the method comprises the following steps:

[0035] Step S102, acquiring base station information of multiple base stations in the target area, wherein the base station information at least includes: a base station location, multiple cells corresponding to the base station, and a tracking area code TAC corresponding to each cell.

[0036] For each base station, a cell is a specific area within the base station coverage area, which can be regarded as a sub-area served by the base station. A base station can cover one or more cells, so when obtaining relevant information about a base station, it is necessary to obtain relevant information about the cells within its coverage area accordingly.

[0037] Step S104, for each base station, if the TACs of the multiple cells corresponding to the base station are the same, the base station is marked as the first base station; if the TACs of the multiple cells corresponding to the base station are different, the base station is determined to be a TAC interlaced base station.

[0038] The acquired base station information is first preprocessed, that is, whether the base station is a TAC-inserted base station is directly determined by whether the TACs of the cells within the base station coverage are the same. Each cell has its own specific tracking TAC. When all cells under a base station are assigned the same TAC, this means that these cells are regarded as part of the same location management area, which facilitates users to avoid unnecessary location updates when moving between these cells, thereby reducing the network load and improving user experience. However, if multiple cells under a base station are assigned different TACs, this may be due to planning omissions during network deployment and special requirements of the geographical environment.

[0039] The above-mentioned distinction method mainly depends on whether the TAC of the cells under the jurisdiction of each base station is the same. This simple logical judgment can efficiently screen out potential problem base stations and reduce the workload for subsequent further judgments, thereby optimizing the recognition efficiency of TAC interlaced base stations.

[0040] Step S106, use a density-based spatial clustering algorithm to spatially cluster multiple first base stations to obtain multiple target clusters, first noise points and second noise points of each target cluster. During the clustering process, for any first base station, when the density condition is met, only the density of other first base stations with the same TAC as the first base station in the neighborhood of the first base station is determined to be reachable, and other first base stations with different TAC from the first base station are determined to be the first noise points of the target cluster corresponding to the first base station, and the first base station that is not divided into any cluster after clustering is completed is determined to be the second noise point.

[0041] In the above clustering process, the satisfaction of the "density reachable" condition not only helps to form geographically and functionally consistent base station clusters, but also can effectively identify and separate those noise points that may destroy the clustering structure, thereby assisting the technical solution to accurately and efficiently identify and locate TAC base stations.

[0042] Step S108 : for each target cluster, if the first noise points corresponding to the target cluster all belong to another target cluster, the target cluster is determined to be an abnormal cluster, otherwise it is a normal cluster.

[0043] If the first noise points corresponding to the target cluster all belong to another target cluster, this indicates that the TACs of the base stations in this cluster overlap with those in another cluster, that is, geographically adjacent base stations are assigned different TACs, which is a direct manifestation of TAC interspersion. Therefore, all the first base stations in the abnormal cluster are naturally identified as TAC interspersion base stations because their TACs are inconsistent with those of the base stations in other clusters and they form a certain geographical clustering.

[0044] Step S110, determining that all first base stations in the abnormal cluster, first noise points in the normal cluster, and first base stations corresponding to second noise points are TAC interlaced base stations.

[0045] Normal clusters are those that do not show TAC interleaving characteristics during clustering. However, even in normal clusters, there may be first noise points whose TACs are different from the TACs of most base stations in the cluster. Although these noise points may be geographically close to other base stations in the normal cluster, due to their TAC differences, these points actually reveal local TAC interleaving. Therefore, the first base station corresponding to the first noise point is also marked as a TAC interleaving base station.

[0046] The following describes each step of the TAC flower arrangement base station identification method in conjunction with a specific implementation process.

[0047] When acquiring base station information of multiple base stations in a target area, it is usually necessary to acquire the base station location, multiple cells corresponding to the base station, and a tracking area code TAC corresponding to each cell.

[0048] Specifically, when obtaining base station information, one must first obtain cell-related information, which usually includes: cell name, physical site code corresponding to the cell, and TAC; after obtaining the cell-related information, it is determined that cells with the same physical site code correspond to the same base station, and the base station location of the corresponding base station is determined based on the physical site code.

[0049] Assume that the information of these cells is as follows: Cell name: JXNN-01001-A, physical site code: 01001, TAC: 64145; Cell name: JXNN-01001-B, physical site code: 01001, TAC: 64146; Cell name: JXNN-01002-C, physical site code: 01002, TAC: 64147. In this scenario: JXNN-01001-A and JXNN-01001-B both have the same physical site code 01001, which indicates that they belong to the same physical base station. The physical site code is like a geographical marker of a base station, which is used to distinguish different physical base stations.

[0050] The TAC patchwork identification algorithm is mainly applicable to base stations in conventional urban and rural areas, where the base station layout is relatively scattered and is more likely to have TAC patchwork due to planning, equipment installation and other issues. If the high-speed rail cell is included in the TAC patchwork identification algorithm in the conventional area, the TAC layout along the high-speed rail (usually linear and continuous) may be mistakenly identified as a patchwork base station. Therefore, after obtaining the cell information, in order to eliminate the influence of the cell information of the high-speed rail cell on the subsequent TAC patchwork base station identification, the cell information of the high-speed rail cell needs to be removed from the cell information.

[0051] In the technical solution provided in step S104 of the embodiment of the present application, for each acquired base station, the TAC interspersed base stations can be firstly screened directly by whether the TACs of the cells governed by the base station are the same. If the TACs of the cells governed by the base station are the same, the status of the base station is pending and it is marked as the first base station. A secondary judgment of the first base station is required later. If the TACs of multiple cells under the current base station are different, the current base station is directly determined to be a TAC interspersed base station.

[0052] Combination Figure 2 For example, from Figure 2 It can be seen that there are three cells under a certain base station. The TACs of cells A, B, and C are 61552, 61553, and 61553 respectively. Since the TACs of the three cells under the base station are different, the base station is determined to be a TAC interlaced base station.

[0053] In the technical solution provided in step S106 of the embodiment of the present application, for each first base station, a density-based spatial clustering algorithm can be used to perform spatial clustering on the base station to obtain multiple target clusters, a first noise point and a second noise point of each target cluster. This can be specifically achieved in the following way: obtain a preset first neighborhood radius and a density threshold, assuming that the first neighborhood radius is set to r1 and the density threshold is set to ρ. For each base station, the longitude and latitude corresponding to the base station are used as the location of the base station, and each group (lat, lon) can uniquely identify the location of a base station.

[0054] For each first base station, the distance between the first base station and other first base stations is determined respectively by the following formula:

[0055]

[0056] where L is the distance between base station 1 and base station 2, R is the radius of the earth, lat1 and lat2 are the latitudes of base station 1 and base station 2 respectively, and lon1 and lon2 are the longitudes of base station 1 and base station 2 respectively.

[0057] For each first base station, it is determined whether there are other first base stations whose distances from the first base station are less than the neighborhood radius r1. Based on the judgment, the following two situations will occur:

[0058] When there are other first base stations whose distances from the first base station are less than the neighborhood radius r1, the other first base stations whose distances from the first base station are less than the neighborhood radius r1 and have the same TAC as the first base station are determined as the second base stations, and the other first base stations whose distances from the first base station are less than the neighborhood radius r1 and have different TACs from the first base station are determined as the third base stations.

[0059] After determining the second base stations, it is necessary to judge the relationship between the number of second base stations and the density threshold ρ. Specifically: if the number of second base stations is not less than the density threshold, it is determined that the first base station and each second base station are density-reachable, the first base station and each second base station are clustered into the initial cluster corresponding to the first base station, and the third base stations are determined as the first noise points of the initial cluster. If the number of second base stations is less than the density threshold, no processing is performed on the first base station.

[0060] As Figure 3 shown, assuming that point A is an urban area base station, when the distance L < r1 from the surrounding points is satisfied and there are N points with the same TAC, it is represented by the set α

[0061] α = {P1, P2, P3,..., Pn}

[0062] When N ≥ ρ, it can be said that the density from point A to P1, A to P2,..., A to Pn is directly reachable.

[0063] In the above process, it can be seen that when clustering into the initial cluster, the density threshold condition needs to be satisfied. When there are not enough base stations around the first base station to meet the condition of forming a "density-reachable" relationship. In this case, the first base station cannot be regarded as a core point.

[0064] Considering that the base stations in some remote areas are relatively scattered, executing the above steps may result in the number of other base stations in the neighborhood of these base stations being zero, and the base stations in normal operation will be mistakenly identified as TAC flower-inserted base stations. In order to avoid misjudgment, it is necessary to increase the neighborhood radius r1 corresponding to the base station in a targeted manner to facilitate more accurate clustering of the base station in the later stage.

[0065] As an optional implementation, when there are no other first base stations whose distance from the first base station is less than the neighborhood radius r1, a preset second neighborhood radius is obtained, wherein the second neighborhood radius is greater than the first neighborhood radius. This can be specifically achieved in the following manner: among the other first base stations whose distance from the first base station is less than the second neighborhood radius, it is determined that the other first base stations with the same TAC as the first base station are the fourth base station, and the other first base stations with different TAC from the first base station are the fifth base station; if the number of fourth base stations is not less than the density threshold, it is determined that the density of the first base station and each fourth base station is reachable, the first base station and each fourth base station are clustered into an initial cluster corresponding to the first base station, and the fifth base station is determined as the first noise point of the initial cluster; if the number of fourth base stations is less than the density threshold, the first base station is not processed.

[0066] In the above process, an extreme situation that may occur is that the neighborhood radius is expanded multiple times, and the number of other base stations included in the neighborhood range of the base station is still zero. At this time, an upper limit T on the number of times the neighborhood radius is changed can be set. After trying to expand the neighborhood radius T times, if the number of other base stations included in the neighborhood range of the base station is still zero, the neighborhood radius will no longer be expanded, and the first base station will not be processed further.

[0067] After clustering of all first base stations is completed in the above manner, the multiple initial clusters obtained are aggregated according to the density reachability relationship between each first base station to obtain multiple target clusters; for each target cluster, it is determined that the first noise points corresponding to each initial cluster corresponding to the target cluster are all the first noise points corresponding to the target cluster; and the first base station that is not divided into any target cluster is determined to be the second noise point.

[0068] Based on the above determination of the relationship between the first base stations, assuming that when N surrounding base stations Pn (n=1, 2, 3...) with the same TAC as point A appear in the neighborhood with point A as the core point, the density from A to Pn is reachable; when X surrounding base stations Bn (n=1, 2, 3...) with the same TAC as point P appear with Pn as the core point, the relationship from P to B is direct, and it can be said that the density from A to B is reachable.

[0069] Aggregating the initial clusters into larger clusters means reducing the number of clusters that need to be processed individually, simplifying subsequent network optimization work. For optimizers, processing a small number of large clusters is more efficient than processing a large number of small clusters, because they can focus on identifying and solving TAC flower-splitting problems in a wider area, rather than analyzing and adjusting each small cluster individually.

[0070] For each target cluster, if the first noise points corresponding to the target cluster all belong to another target cluster, the target cluster is determined to be an abnormal cluster, otherwise it is a normal cluster;

[0071] After clustering is completed, for each target cluster, it is necessary to further check whether the first noise point in this cluster has a consistent configuration with another target cluster in terms of TAC. If the TACs of all the first noise points in a target cluster consistently belong to another target cluster (i.e., there is a density connection), then this indicates that the two clusters should be geographically adjacent or partially overlapping, but due to differences in TAC configuration, they are mistakenly divided into different clusters. This inconsistent configuration is abnormal, because the ideal TAC configuration should avoid assigning different TACs to geographically adjacent or overlapping areas, so it is marked as an abnormal cluster.

[0072] The next step of obtaining the relevant information through the above process is to identify the TAC flower-inserting base station, which can be determined in the following way: determine that all the first base stations in the abnormal cluster, the first noise points and the first base stations corresponding to the second noise points in the normal cluster are all TAC flower-inserting base stations.

[0073] Through the above steps, the acquired base station information is first preprocessed to achieve preliminary screening, and then the density-based spatial clustering algorithm is introduced to lay the foundation for the subsequent identification and judgment of abnormal clusters. In this way, not only can obvious TAC interspersed phenomena be identified, but also abnormal base stations hidden in dense areas can be discovered through clustering analysis, ensuring comprehensive coverage of identification results, thereby solving the technical problems of low efficiency and poor accuracy in the existing solutions for identifying TAC interspersed phenomena in base stations.

[0074] Example 2

[0075] According to an embodiment of the present application, a TAC flower arrangement base station identification device for implementing the TAC flower arrangement base station identification method in Example 1 is also provided, such as Figure 4 As shown, the identification device of the TAC flower arrangement base station at least includes: an acquisition module 41, a first determination module 42, a clustering module 43, a second determination module 44 and a third determination module 45, wherein:

[0076] The acquisition module 41 is used to acquire base station information of multiple base stations in the target area, wherein the base station information at least includes: a base station location, multiple cells corresponding to the base station, and a TAC corresponding to each cell;

[0077] A first determination module 42 is configured to, for each base station, mark the base station as a first base station if the TACs of the multiple cells corresponding to the base station are the same, and determine the base station as a TAC interlaced base station if the TACs of the multiple cells corresponding to the base station are different;

[0078] A clustering module 43 is used to perform spatial clustering on multiple first base stations using a density-based spatial clustering algorithm to obtain multiple target clusters, a first noise point and a second noise point of each target cluster. In the clustering process, for any first base station, when the density condition is met, only other first base stations with the same TAC as the first base station in the neighborhood of the first base station are determined to be reachable, other first base stations with different TACs from the first base station are determined to be the first noise points of the target cluster corresponding to the first base station, and first base stations that are not divided into any cluster after clustering are determined to be the second noise points;

[0079] A second determination module 44 is used for, for each target cluster, if the first noise points corresponding to the target cluster all belong to another target cluster, determining the target cluster as an abnormal cluster, otherwise it is a normal cluster;

[0080] The third determination module 45 is used to determine that all first base stations in the abnormal cluster and first base stations corresponding to the first noise points and second noise points in the normal cluster are TAC interlaced base stations.

[0081] The functions of each module of the identification device of the TAC flower arrangement base station are explained below in conjunction with a specific implementation process.

[0082] Optionally, when acquiring the base station information of multiple base stations within the target area, the acquisition module needs to at least acquire the cell information of multiple cells within the target area, wherein the cell information includes at least: the cell name, the physical site code corresponding to the cell, and the TAC; determine that cells with the same physical site code correspond to the same base station, and determine the base station position of the corresponding base station based on the physical site code.

[0083] Optionally, in addition to the above-mentioned cell name, the physical site code and TAC corresponding to the cell, the cell information acquired by the acquisition module also includes the cell type. After acquiring the cell information of multiple cells in the target area, the method also includes: eliminating the cell information of the high-speed rail cell from the cell information of multiple cells.

[0084] Optionally, the clustering module uses a density-based spatial clustering algorithm to perform spatial clustering on multiple first base stations. The obtaining of multiple target clusters, the first noise points and the second noise points of each target cluster can be achieved in the following manner: obtain a preset first neighborhood radius and density threshold; for each first base station, respectively determine the distances between the first base station and other first base stations; among the other first base stations whose distances from the first base station are less than the first neighborhood radius, determine the other first base stations with the same TAC as the first base station as second base stations, and the other first base stations with different TACs from the first base station as third base stations; if the number of second base stations is not less than the density threshold, determine that the first base station and each second base station are density-reachable, cluster the first base station and each second base station into the initial cluster corresponding to the first base station, and determine the third base stations as the first noise points of the initial cluster; if the number of second base stations is less than the density threshold, do not process the first base station; after clustering all the first base stations, aggregate the obtained multiple initial clusters according to the density-reachable relationship between the first base stations to obtain multiple target clusters; for each target cluster, determine that the first noise points corresponding to the respective initial clusters corresponding to the target cluster are the first noise points corresponding to the target cluster; determine the first base stations not assigned to any target cluster as second noise points.

[0085] Optionally, when determining the distances between the first base station and other first base stations, the clustering module uses the longitude and latitude of the base station as the location of the base station. For any two first base stations, the distance between the two first base stations is determined by the following formula:

[0086]

[0087] where L is the distance between base station 1 and base station 2, R is the radius of the earth, lat1 and lat2 are the latitudes of base station 1 and base station 2 respectively, and lon1 and lon2 are the longitudes of base station 1 and base station 2 respectively.

[0088] Optionally, after respectively determining the distances between the first base station and other first base stations, if there are no other first base stations whose distances from the first base station are less than the first neighborhood radius, obtain a preset second neighborhood radius, where the second neighborhood radius is greater than the first neighborhood radius; among the other first base stations whose distances from the first base station are less than the second neighborhood radius, determine the other first base stations with the same TAC as the first base station as fourth base stations, and the other first base stations with different TACs from the first base station as fifth base stations; if the number of fourth base stations is not less than the density threshold, determine that the first base station and each fourth base station are density-reachable, cluster the first base station and each fourth base station into the initial cluster corresponding to the first base station, and determine the fifth base stations as the first noise points of the initial cluster; if the number of fourth base stations is less than the density threshold, do not process the first base station.

[0089] Optionally, the clustering module can aggregate the multiple initial clusters obtained according to the density reachability relationship between the first base stations in the following manner: for any two initial clusters, if the two initial clusters include a common first base station, determine that all first base stations in the two initial clusters are density reachable, and aggregate the two initial clusters into one cluster.

[0090] It should be noted that each module in the identification device of the TAC flower arrangement base station in the embodiment of the present application corresponds one by one to each implementation step of the identification method of the TAC flower arrangement base station in Example 1. Since a detailed description has been given in Example 1, some details not reflected in this embodiment can be referred to Example 1 and will not be repeated here.

[0091] Example 3

[0092] According to an embodiment of the present application, a computer program product is also provided, which includes a computer program, wherein when the computer program is executed by a processor, the TAC flower arrangement base station identification method in Example 1 is implemented.

[0093] According to an embodiment of the present application, a non-volatile storage medium is also provided, which includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the TAC flower arrangement base station identification method in Example 1 by running the computer program.

[0094] According to an embodiment of the present application, a processor is also provided, which is used to run a computer program, wherein the TAC flower arrangement base station identification method in Example 1 is executed when the computer program is running.

[0095] According to an embodiment of the present application, an electronic device is also provided, which includes: a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to execute the TAC flower arrangement base station identification method in Example 1 through the computer program.

[0096] Specifically, when the computer program is running, the following steps are performed:

[0097] The base station information of multiple base stations in the target area is obtained, wherein the base station information at least includes: the base station location, multiple cells corresponding to the base station, and the tracking area code TAC corresponding to each cell; for each base station, if the TACs of the multiple cells corresponding to the base station are the same, the base station is marked as the first base station, and if the TACs of the multiple cells corresponding to the base station are different, the base station is determined to be a TAC interspersed base station; a density-based spatial clustering algorithm is used to perform spatial clustering on multiple first base stations to obtain multiple target clusters, a first noise point and a second noise point of each target cluster; in the clustering process, for any first base station, when the density condition is met, only other first base stations with the same TAC as the first base station in the neighborhood of the first base station are determined to be reachable in density, other first base stations with different TACs from the first base station are determined to be the first noise points of the target cluster corresponding to the first base station, and the first base stations that are not divided into any cluster after the clustering is completed are determined to be the second noise points; for each target cluster, if the first noise points corresponding to the target cluster all belong to another target cluster, the target cluster is determined to be an abnormal cluster, otherwise it is a normal cluster; it is determined that all first base stations in the abnormal cluster and the first noise points and the first noise points of the normal cluster correspond to the TAC interspersed base stations.

[0098] As an optional implementation, the electronic device may be in the form of a mobile terminal, a computer terminal or a similar computing device. Figure 5 The hardware structure block diagram of an electronic device for implementing a TAC flower arrangement base station identification method is shown. Figure 5 As shown, the electronic device 50 may include one or more (502a, 502b, ..., 502n are used to illustrate) processors 502 (the processor 502 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 504 for storing data, and a transmission device 506 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 5 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 5 More or fewer components as shown, or with Figure 5 Different configurations are shown.

[0099] It should be noted that one or more of the above-mentioned processors 502 and / or other data processing circuits can generally be referred to as "data processing circuits" herein. The data processing circuit can be embodied in software, hardware, firmware, or any combination thereof, in whole or in part. In addition, the data processing circuit can be a single independent processing module, or be incorporated in whole or in part into any one of the other components in the electronic device 50. As involved in the embodiments of the present application, the data processing circuit is a kind of processor control (such as the selection of a variable resistor terminal path connected to an interface).

[0100] The memory 504 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the identification method of the TAC flower arranging base station in the embodiments of the present application. The processor 502 executes various functional applications and data processing by running the software programs and modules stored in the memory 504, that is, implements the vulnerability detection method of the above-mentioned application program. The memory 504 can include a high-speed random access memory, and can also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some instances, the memory 504 can further include a memory remotely set relative to the processor 502, and these remote memories can be connected to the electronic device 50 through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0101] The transmission device 506 is used to receive or send data via a network. Specific examples of the above-mentioned network can include the wireless network provided by the communication provider of the electronic device 50. In one instance, the transmission device 506 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station and thus can communicate with the Internet. In one instance, the transmission device 506 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0102] The display can be, for example, a touch-screen liquid crystal display (LCD), which enables the user to interact with the user interface of the electronic device 50.

[0103] The above-mentioned embodiment numbers are only for description and do not represent the advantages or disadvantages of the embodiments.

[0104] In the above embodiments of the present application, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0105] In several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of units can be a logical function division. In actual implementation, there can be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections between each other can be through some interfaces. The indirect couplings or communication connections of units or modules can be in electrical or other forms.

[0106] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0107] In addition, in each embodiment of this application, each functional unit can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0108] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of this application. The foregoing storage medium includes: various media such as USB flash drives, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), mobile hard disks, magnetic disks, or optical discs that can store program codes.

[0109] The above is only the preferred embodiment of this application. It should be noted that for those of ordinary skill in the art, without departing from the principle of this application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of this application.

Claims

1. A method for identifying a TAC flower-arranging base station, characterized in that, include: Acquire base station information of multiple base stations in the target area, wherein the base station information at least includes: a base station location, multiple cells corresponding to the base station, and a tracking area code TAC corresponding to each cell; For each base station, if the TACs of the multiple cells corresponding to the base station are the same, the base station is marked as the first base station; if the TACs of the multiple cells corresponding to the base station are different, the base station is determined to be a TAC interlaced base station; A density-based spatial clustering algorithm is used to spatially cluster the multiple first base stations to obtain multiple target clusters, first noise points and second noise points of each target cluster. In the clustering process, for any first base station, when the density condition is met, only other first base stations with the same TAC as the first base station in the neighborhood of the first base station are determined to be reachable in density, other first base stations with different TACs from the first base station are determined to be the first noise points of the target cluster corresponding to the first base station, and the first base stations that are not divided into any cluster after clustering are determined to be the second noise points; For each target cluster, if the first noise points corresponding to the target cluster all belong to another target cluster, the target cluster is determined to be an abnormal cluster, otherwise it is a normal cluster; It is determined that all first base stations in the abnormal cluster, the first noise points in the normal cluster, and the first base stations corresponding to the second noise points are TAC interlaced base stations.

2. The method according to claim 1, characterized in that Get base station information of multiple base stations in the target area, including: Acquire cell information of multiple cells in the target area, wherein the cell information at least includes: a cell name, a physical site code corresponding to the cell, and a TAC; It is determined that cells with the same physical site address code correspond to the same base station, and the base station position of the corresponding base station is determined according to the physical site address code.

3. The method according to claim 2, wherein The cell information also includes a cell type. After acquiring the cell information of multiple cells in the target area, the method further includes: The cell information of the high-speed rail community is eliminated from the cell information of multiple communities.

4. The method according to claim 1, characterized in that, The plurality of first base stations are spatially clustered using a density-based spatial clustering algorithm to obtain a plurality of target clusters, a first noise point and a second noise point of each target cluster, including: Get the preset first neighborhood radius and density threshold; For each first base station, respectively determine the distance between the first base station and other first base stations; Determine that among other first base stations whose distances to the first base station are less than the first neighborhood radius, the other first base stations having the same TAC as the first base station are second base stations, and the other first base stations having different TACs from the first base station are third base stations; If the number of the second base stations is not less than the density threshold, determine that the first base station and each of the second base stations are density-reachable, cluster the first base station and each of the second base stations into an initial cluster corresponding to the first base station, and determine the third base station as a first noise point of the initial cluster; If the number of the second base stations is less than the density threshold, the first base station is not processed; After clustering all the first base stations, aggregating the obtained multiple initial clusters according to the density reachability relationship between the first base stations to obtain multiple target clusters; For each target cluster, determining that the first noise points corresponding to each initial cluster corresponding to the target cluster are all the first noise points corresponding to the target cluster; A first base station that is not classified into any target cluster is determined as a second noise point.

5. The method according to claim 4, characterized in that, The base station location is the latitude and longitude of the base station, and the distances between the first base station and other first base stations are determined respectively, including: For any two first base stations, the distance between the two first base stations is determined by the following formula: Where L is the distance between base station 1 and base station 2, R is the radius of the earth, lat1 and lat2 are the latitudes of base station 1 and base station 2, and lon1 and lon2 are the longitudes of base station 1 and base station 2.

6. The method according to claim 4, characterized in that After respectively determining the distances between the first base station and other first base stations, the method further includes: If there is no other first base station whose distance from the first base station is less than the first neighborhood radius, obtaining a preset second neighborhood radius, wherein the second neighborhood radius is greater than the first neighborhood radius; Determine that among other first base stations whose distances to the first base station are less than the second neighborhood radius, the other first base stations having the same TAC as the first base station are fourth base stations, and the other first base stations having different TACs from the first base station are fifth base stations; If the number of the fourth base stations is not less than the density threshold, determine that the first base station and each of the fourth base stations are density-reachable, cluster the first base station and each of the fourth base stations into an initial cluster corresponding to the first base station, and determine the fifth base station as a first noise point of the initial cluster; If the number of the fourth base stations is less than the density threshold, the first base station is not processed.

7. The method according to claim 4, characterized in that, Aggregating the obtained multiple initial clusters according to the density reachability relationship between the first base stations includes: For any two initial clusters, if the two initial clusters include a common first base station, it is determined that all first base stations in the two initial clusters are density-reachable, and the two initial clusters are aggregated into one cluster.

8. An identification device for a TAC flower-arranging base station, characterized in that, include: An acquisition module, configured to acquire base station information of multiple base stations in a target area, wherein the base station information at least includes: a base station location, multiple cells corresponding to the base station, and a TAC corresponding to each cell; A first determination module is used for, for each base station, if the TACs of the multiple cells corresponding to the base station are the same, marking the base station as a first base station; if the TACs of the multiple cells corresponding to the base station are different, determining the base station as a TAC interlaced base station; A clustering module, used for spatially clustering the plurality of first base stations using a density-based spatial clustering algorithm to obtain a plurality of target clusters, a first noise point and a second noise point of each target cluster. In the clustering process, for any first base station, when a density condition is met, only other first base stations with the same TAC as the first base station in the neighborhood of the first base station are determined to be density-reachable, other first base stations with different TACs from the first base station are determined to be the first noise points of the target cluster corresponding to the first base station, and first base stations that are not divided into any cluster after clustering are determined to be the second noise points; A second determination module is used for, for each target cluster, if the first noise points corresponding to the target cluster all belong to another target cluster, determining the target cluster as an abnormal cluster, otherwise it is a normal cluster; The third determination module is used to determine that all the first base stations in the abnormal cluster, the first noise points in the normal cluster, and the first base stations corresponding to the second noise points are TAC interlaced base stations.

9. A computer program product, characterized in that, include: A computer program, wherein when the computer program is executed by a processor, the method for identifying the TAC flower arrangement base station according to any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that, include: A memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the TAC flower arrangement base station identification method according to any one of claims 1 to 7 through the computer program.

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