A cross-operator neighboring cell missing configuration detection method and device, electronic equipment and medium

Abstract

This invention discloses a method, apparatus, electronic device, and medium for detecting missing neighbor cell configurations across operators. The method includes: continuously acquiring call detail record (CDR) information from the core network and storing it in a target database; extracting historical CDR data for a first preset period from the target database, sorting each CDR in the historical CDR data according to number identifier and access time to obtain a CDR list; performing difference matching on access time, release time, and cell identifier for adjacent CDRs with the same number identifier in the CDR list, and statistically analyzing missing neighbor cell pairs based on the difference matching results; and determining the missing neighbor cell configuration problem for each cell based on the statistical distribution of the missing neighbor cell pairs. This invention locates missing neighbor cell configuration problems based on CDR information. Even in the absence of neighbor cell handover and MR information from the other operator, it can promptly detect the problem of the other operator missing neighbor cell configurations, thereby promoting the optimization of missing neighbor cell configurations by all operators. It can be widely applied in the field of communication data processing technology.

Description

Technical Field

[0001] This invention relates to the field of communication data processing technology, and in particular to a method, apparatus, electronic device, and medium for detecting missing data configurations in neighboring cells across operators. Background Technology

[0002] As multi-operator joint construction and sharing of networks deepens, the scale of shared networks is gradually expanding. However, due to the inconsistent network scale among different operators, the problems of site sharing and cross-vendor sharing still exist. Initially, cross-operator configuration was not considered at all, including whether all parties were from the same vendor or whether the boundaries between different vendors were unified. Site sharing was entirely within the same area and scope, with base stations from each party distributed in a completely scattered manner. Creating neighboring cells for network switching between the two parties is a complex and labor-intensive task, prone to misconfiguration issues.

[0003] Within the same operator, neighbor cell configuration information, MR (Measurement Report) information, and base station latitude and longitude information are easily obtained. Missing neighbor cell configurations can be detected using traditional methods such as distance and MR data statistics, or neighbor cells can be added using the network management SON (Signaling System) function. However, when operating across different operators, the SON function cannot handle adding neighbor cells in cross-operator scenarios. Furthermore, without the neighbor cell configuration information and MR data of the other party, traditional methods for detecting missing neighbor cell configurations become ineffective. In other words, the current operator can only detect neighbor cells that it has missed configuring in the other party, but cannot promptly detect neighbor cells that the other party has missed configuring in its own. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in related technologies. To this end, this invention proposes a method, apparatus, electronic device, and medium for detecting missing data in neighboring cells across different operators.

[0005] On one hand, embodiments of the present invention provide a cross-operator neighboring cell missing configuration detection method, including:

[0006] Continuously obtain call detail records (CDRs) from the core network and store them in the target database;

[0007] The call detail record (CDR) information includes number identifier, access time, release time, and cell identifier; the cell identifier data consists of base station identifier and location identifier, and the core network shares base station communication connections with different operator networks;

[0008] Extract historical call detail records (CDRs) for the first preset period from the target database, sort the CDR information in the historical CDRs according to the number identifier and access time, and obtain a CDR list.

[0009] For adjacent call records with the same number identifier in the call record list, the access time, release time and cell identifier are matched for differences. Based on the results of the difference matching, the missing cell pairs in the neighboring cells are counted.

[0010] Based on the statistical distribution of missing neighbor cell pairs, the missing neighbor cell problem in each cell is determined.

[0011] Optionally, call detail record (CDR) information can be continuously obtained from the core network, including:

[0012] Based on a multi-operator core network, call detail records (CDRs) determined by shared base stations across various operator networks are continuously obtained from the core network.

[0013] The multi-operator core network includes multiple different operator networks. Each operator network consists of a core network and a shared base station. The core network of each operator network is connected to the shared base station of all operator networks.

[0014] Optionally, the method further includes:

[0015] Call detail records (CDRs) are determined based on call signals from mobile terminals.

[0016] The number identifier includes the local number of the mobile terminal and the remote number of the caller; the access time is determined by the initiation time of the call signal and the release time is determined by the interruption time of the call signal; the cell identifier includes the access cell identifier and the release cell identifier. The access cell identifier is determined by the shared base station connected after the call signal is initiated and the release cell identifier is determined by the shared base station connected before the call signal is interrupted.

[0017] Optionally, the call detail records (CDRs) are sorted according to the number identifier and access time in the historical CDR data to obtain a CDR list, including:

[0018] Using the number identifier as the first sorting field, the call detail records in the call detail record history data are sorted first.

[0019] Using access time as the second sorting field, the call detail records (CDRs) in the historical CDR data after the first sort are sorted again to obtain a list of CDRs.

[0020] Optionally, adjacent call detail records (CDRs) include first CDR information and second CDR information, where the access time of the first CDR information is earlier than that of the second CDR information. For adjacent CDRs with the same number identifier in the CDR list, differences in access time, release time, and cell identifier are matched. Based on the results of the difference matching, missing neighbor cell pairs are statistically analyzed, including:

[0021] The time interval is obtained by calculating the time difference between the release time of the first call detail record (CDR) and the access time of the second CDR.

[0022] Based on the release cell identifier of the first call detail record (CDR) and the access cell identifier of the second CDR, the base station identifier is matched to obtain the matching result.

[0023] When the time interval is less than the second preset period and the matching result of the base station identifier is inconsistent, the missing neighbor cell pair is recorded according to the release cell identifier of the first call detail record and the access cell identifier of the second call detail record.

[0024] Iterate through all adjacent call detail records in the call detail record list and count the number of missing cell pairs in the neighboring cells.

[0025] Optionally, based on the statistical distribution of missing neighbor cell pairs, the missing neighbor cell problem for each cell can be determined, including:

[0026] Based on the statistical distribution of missing neighbor cell pairs, target missing neighbor cell pairs are obtained based on preset screening conditions.

[0027] Among them, the target neighbor cell missing cell pair represents the neighbor cell relationship between the first cell and the second cell. The neighbor cell relationship includes positive neighbor cell relationship and / or negative neighbor cell relationship; the neighbor cell distance of the neighbor cell relationship is determined by the location identifier of the cell identifier corresponding to the first cell and the second cell.

[0028] Based on neighboring cell relationships, identify the missing allocation issue in the first neighboring cell;

[0029] Among them, the first neighbor cell mismatch problem includes one-way neighbor cell mismatch and two-way neighbor cell mismatch; when the neighbor relationship represented by the target neighbor cell mismatch cell pair is a positive neighbor relationship or a negative neighbor relationship between the first cell and the second cell, the first neighbor cell mismatch problem is determined to be a one-way neighbor cell mismatch; when the target neighbor cell mismatch cell pair simultaneously contains both positive and negative neighbor relationships representing the first cell and the second cell, the first neighbor cell mismatch problem is determined to be a two-way neighbor cell mismatch.

[0030] Optionally, the method further includes:

[0031] Based on the cell identifiers corresponding to the first cell and the second cell, the base station identifiers are matched to determine the operator relationship between the first cell and the second cell;

[0032] The issue of missing configuration in the second neighboring cell was determined based on the operator relationship;

[0033] Among them, the problem of missing neighboring cells includes missing neighboring cells within the same operator and missing neighboring cells across operators.

[0034] On the other hand, embodiments of the present invention provide a cross-carrier neighbor cell missing configuration detection device, comprising:

[0035] The first module is used to continuously obtain call detail records (CDRs) from the core network and store them in the target database;

[0036] The call detail record (CDR) information includes number identifier, access time, release time, and cell identifier; the cell identifier data consists of base station identifier and location identifier, and the core network shares base station communication connections with different operator networks;

[0037] The second module extracts historical call detail records (CDRs) for a first preset period from the target database, sorts the CDR information in the historical CDRs according to the number identifier and access time, and obtains a CDR list.

[0038] The third module performs difference matching on adjacent call records with the same number identifier in the call record list, matching the differences in access time, release time and cell identifier, and statistically analyzes the missing cell pairs in the neighboring cells based on the difference matching results.

[0039] The fourth module determines the neighboring cell missing pairing problem for each cell based on the statistical distribution of neighboring cell missing pairings.

[0040] Optionally, the first module is specifically used for:

[0041] Based on a multi-operator core network, call detail records (CDRs) determined by shared base stations across various operator networks are continuously obtained from the core network.

[0042] The multi-operator core network includes multiple different operator networks. Each operator network consists of a core network and a shared base station. The core network of each operator network is connected to the shared base station of all operator networks.

[0043] Optionally, the system also includes:

[0044] The fifth module is used to determine call detail records (CDRs) based on call signals from mobile terminals.

[0045] The number identifier includes the local number of the mobile terminal and the remote number of the caller; the access time is determined by the initiation time of the call signal and the release time is determined by the interruption time of the call signal; the cell identifier includes the access cell identifier and the release cell identifier. The access cell identifier is determined by the shared base station connected after the call signal is initiated and the release cell identifier is determined by the shared base station connected before the call signal is interrupted.

[0046] Optionally, the second module is specifically used for:

[0047] Using the number identifier as the first sorting field, the call detail records in the call detail record history data are sorted first.

[0048] Using access time as the second sorting field, the call detail records (CDRs) in the historical CDR data after the first sort are sorted again to obtain a list of CDRs.

[0049] Optionally, adjacent call detail records (CDRs) include first CDR information and second CDR information, where the access time of the first CDR information is earlier than the access time of the second CDR information. The third module is specifically used for:

[0050] The time interval is obtained by calculating the time difference between the release time of the first call detail record (CDR) and the access time of the second CDR.

[0051] Based on the release cell identifier of the first call detail record (CDR) and the access cell identifier of the second CDR, the base station identifier is matched to obtain the matching result.

[0052] When the time interval is less than the second preset period and the matching result of the base station identifier is inconsistent, the missing neighbor cell pair is recorded according to the release cell identifier of the first call detail record and the access cell identifier of the second call detail record.

[0053] Iterate through all adjacent call detail records in the call detail record list and count the number of missing cell pairs in the neighboring cells.

[0054] Optionally, the fourth module is specifically used for:

[0055] Based on the statistical distribution of missing neighbor cell pairs, target missing neighbor cell pairs are obtained based on preset screening conditions.

[0056] Among them, the target neighbor cell missing cell pair represents the neighbor cell relationship between the first cell and the second cell. The neighbor cell relationship includes positive neighbor cell relationship and / or negative neighbor cell relationship; the neighbor cell distance of the neighbor cell relationship is determined by the location identifier of the cell identifier corresponding to the first cell and the second cell.

[0057] Based on neighboring cell relationships, identify the missing allocation issue in the first neighboring cell;

[0058] Among them, the first neighbor cell mismatch problem includes one-way neighbor cell mismatch and two-way neighbor cell mismatch; when the neighbor relationship represented by the target neighbor cell mismatch cell pair is a positive neighbor relationship or a negative neighbor relationship between the first cell and the second cell, the first neighbor cell mismatch problem is determined to be a one-way neighbor cell mismatch; when the target neighbor cell mismatch cell pair simultaneously contains both positive and negative neighbor relationships representing the first cell and the second cell, the first neighbor cell mismatch problem is determined to be a two-way neighbor cell mismatch.

[0059] Optionally, the system also includes:

[0060] The sixth module is used to match base station identifiers based on the cell identifiers corresponding to the first cell and the second cell, and to determine the operator relationship between the first cell and the second cell.

[0061] The issue of missing configuration in the second neighboring cell was determined based on the operator relationship;

[0062] Among them, the problem of missing neighboring cells includes missing neighboring cells within the same operator and missing neighboring cells across operators.

[0063] On the other hand, embodiments of the present invention provide an electronic device, including: a processor and a memory; the memory is used to store a program; the processor executes the program to implement the above-described cross-operator neighbor cell missing configuration detection method.

[0064] On the other hand, embodiments of the present invention provide a computer storage medium storing a processor-executable program, which, when executed by a processor, is used to implement the above-described cross-carrier neighbor cell missing configuration detection method.

[0065] This invention first continuously acquires call detail record (CDR) information from the core network and stores it in a target database. The CDR information includes number identifier, access time, release time, and cell identifier. The cell identifier consists of a base station identifier and a location identifier, and the core network shares a base station communication connection with different operator networks. Historical CDR data for a first preset period is extracted from the target database. The CDR information in the historical CDR data is sorted according to the number identifier and access time to obtain a CDR list. Adjacent CDRs with the same number identifier in the CDR list are matched for differences in access time, release time, and cell identifier. Based on the results of the difference matching, missing neighbor cell pairs are statistically analyzed. Based on the statistical distribution of missing neighbor cell pairs, the missing neighbor cell matching problem for each cell is determined. This invention acquires CDR information through a shared base station. Based on the characteristics of CDRs formed by call behavior, and through the sorting and difference matching of information identifiers in the CDRs, it can promptly detect the problem of missing neighbor cells by the other operator, even in the absence of neighbor cell handover information or MR information from the other operator, thereby promoting the optimization of neighbor cell matching by all operators. Attached Figure Description

[0066] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0067] Figure 1 This is a schematic diagram of an implementation environment for cross-operator neighbor cell missing configuration detection provided in an embodiment of the present invention;

[0068] Figure 2 This is a flowchart illustrating a cross-operator neighbor cell missing configuration detection method provided in an embodiment of the present invention;

[0069] Figure 3 A schematic diagram illustrating the architecture principle of a multi-operator core network provided in an embodiment of the present invention;

[0070] Figure 4 A flowchart illustrating the process of statistically analyzing missing neighbor cell pairs provided in an embodiment of the present invention;

[0071] Figure 5 This is a schematic diagram illustrating the framework principle of extracting missing neighbor cell pairs from a call detail record (CDR) list according to an embodiment of the present invention.

[0072] Figure 6 This is a schematic diagram illustrating the framework principle for organizing data on missing neighboring cells provided in an embodiment of the present invention;

[0073] Figure 7 A schematic diagram of the workflow for the cross-operator neighbor cell missing configuration detection method provided in an embodiment of the present invention;

[0074] Figure 8 This is a schematic diagram of a cross-carrier neighbor cell missing configuration detection device provided in an embodiment of the present invention;

[0075] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention;

[0076] Figure 10 A computer system architecture block diagram suitable for implementing electronic devices according to embodiments of the present invention is provided. Detailed Implementation

[0077] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0078] It should be noted that although functional modules are divided in the system diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first / S100," "second / S200," etc., in the specification, claims, and the aforementioned figures are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0079] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0080] It is understood that the cross-carrier neighbor cell missing configuration detection method provided in this embodiment of the invention can be applied to any computer device with data processing and computing capabilities, and this computer device can be various types of terminals or servers. When the computer device in the embodiment is a server, the server is an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. Optionally, the terminal can be a smartphone, tablet, laptop, or desktop computer, but it is not limited to these.

[0081] like Figure 1 The diagram shown is a schematic representation of an implementation environment provided by an embodiment of the invention. (Refer to...) Figure 1 The implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be connected via a network, either wirelessly or via a wired connection, to complete data transmission and exchange.

[0082] Server 101 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0083] Additionally, server 101 can also be a node server in a blockchain network. Blockchain is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms.

[0084] Terminal 102 can be a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. Terminal 102 and server 101 can be directly or indirectly connected via wired or wireless communication, and this embodiment of the invention does not impose any limitations.

[0085] Exemplary based on Figure 1 The implementation environment shown in this embodiment of the invention provides a cross-carrier neighbor cell missing configuration detection method. The following description uses the application of this cross-carrier neighbor cell missing configuration detection method in server 101 as an example. It can be understood that this cross-carrier neighbor cell missing configuration detection method can also be applied to terminal 102.

[0086] Reference Figure 2 , Figure 2 This is a flowchart illustrating a cross-carrier neighbor cell missing configuration detection method for servers provided in an embodiment of the present invention. The executing entity of this cross-carrier neighbor cell missing configuration detection method can be any of the aforementioned computer devices. (Refer to...) Figure 2 The method includes the following steps:

[0087] S100 continuously obtains call detail records (CDRs) from the core network and stores them in the target database;

[0088] It should be noted that the call detail record (CDR) information includes the number identifier, access time, release time, and cell identifier; the cell identifier data consists of the base station identifier and the location identifier, and the core network shares base station communication connections with different operator networks.

[0089] In some embodiments, step S100 may include: continuously obtaining call detail records (CDRs) determined by shared base stations of various operator networks from the core network based on the multi-operator core network; wherein the multi-operator core network includes multiple different operator networks, each operator network includes a core network and a shared base station, and the core network of each operator network is communicatively connected to the shared base station of all operator networks.

[0090] In this method, a call detail record (CDR) is obtained based on a single call. The CDR can be determined by the interaction data between the mobile terminal's call signal and the shared base station during the call. In some embodiments, the method may further include: determining the CDR based on the mobile terminal's call signal; wherein, the number identifier includes the mobile terminal's local number and the outgoing call number; the access time is determined by the call signal initiation time, and the release time is determined by the call signal interruption time; the cell identifier includes an access cell identifier and a release cell identifier, wherein the access cell identifier is determined by the shared base station connected after the call signal is initiated, and the release cell identifier is determined by the shared base station connected before the call signal is interrupted.

[0091] Specifically, in some specific embodiments, the acquisition of call detail record (CDR) information can be achieved through the following steps:

[0092] First, it should be noted that for deep cooperation among multiple operators, the MOCN (Multi-Operator Core Network) approach is adopted, such as... Figure 3 As shown, different operators (Operator 1 and Operator 2) only share the RAN (Radio Access Network), while the core network remains independent. Base station sharing: A single base station can simultaneously function as a base station for both China Unicom and China Telecom, serving users of both operators (users of Operator 1 and users of Operator 2).

[0093] Based on the characteristics of shared networks, the current shared network only involves the base station side. Shared base stations need to connect to the core networks of both operators. For one core network, both base stations fall under its jurisdiction, so the core network can record base station information from different networks. Specifically, the call detail records (CDRs) reported by the shared base stations are an internal process within the communication system (operator network). Therefore, CDRs cannot be directly obtained from the shared base stations. In other words, the CDRs reported by the shared base stations to the core network are a reference for core CDR generation, not the final output CDRs. Therefore, CDRs cannot be directly obtained from the base stations. Thus, the specific process for obtaining CDR information in this embodiment of the invention may include: each operator's shared base station initially determines CDR information based on communication signals. Since each operator's core network connects to all shared base stations of all operator networks, the core network can continuously receive CDRs determined by each operator's shared base station. Finally, this embodiment of the invention continuously obtains CDR information from the core network.

[0094] This invention requires six fields from the VoLTE core network call detail record (CDR): user number (i.e., local number), peer number, access time, release time, access cell, and release cell. For the user number and peer number, only the same number needs to use the same identifier; the user's real number is not required. The user identifier can be formed using MD5 encryption or other encryption algorithms (separately or jointly on the local and peer numbers) to protect user privacy. The access time is the time the user dials the call, the release time is the time the user hangs up (when the call is dropped), the access cell is the cell the user accesses when dialing, and the release cell is the cell where the user interacts with the network before hanging up. The format of both the access cell and release cell is converted from ECI to enodeid_cellid (i.e., cell identifier), composed of enodebid (base station identifier) ​​+ cellid (location identifier). It contains 28 bits of information (the first 20 bits represent enodebid, and the last 8 bits represent cellid). Both parties share enodebid and can use it to determine the operator affiliation of the access cell and release cell. Furthermore, the database storing call detail records (CDRs) is updated in real time based on the CDRs continuously transmitted from the VoLTE core network.

[0095] S200: Extract historical call detail records (CDRs) for the first preset period from the target database, sort the CDR information in the historical CDRs according to the number identifier and access time, and obtain a CDR list.

[0096] It should be noted that in some embodiments, step S200 may include: sorting each call detail record (CDR) information in the call detail record history data by using the number identifier as the first sorting field; and sorting each CDR information in the first sorted CDR history data by using the access time as the second sorting field to obtain a call detail record list.

[0097] Specifically, in some specific embodiments, the call detail record (CDR) list can be obtained through the following steps: extract VoLTE CDRs for one week (depending on the system's computing power, the longer the time period, the more accurate the statistics, generally not exceeding one month), extract 6 fields (user number, peer number, access time, release time, access cell, release cell), sort them by user number as the first sorting field (ascending or descending order is acceptable), and sort them by access time as the second sorting field, thus obtaining the CDR list.

[0098] S300: For adjacent call records with the same number identifier in the call record list, the access time, release time and cell identifier are matched for differences. Based on the results of the difference matching, the missing cell pairs in the neighboring cells are counted.

[0099] It should be noted that adjacent call detail records (CDRs) include first CDR information and second CDR information, and the access time of the first CDR information is earlier than the access time of the second CDR information.

[0100] In some embodiments, such as Figure 4 As shown, step S300 may include: S301, calculating the time difference based on the release time of the first call detail record (CDR) information and the access time of the second CDR information to obtain a time interval; S302, matching the base station identifier based on the release cell identifier of the first CDR information and the access cell identifier of the second CDR information to obtain a matching result; S303, when the time interval is less than a second preset period and the matching result of the base station identifier is inconsistent, recording the missing neighbor cell pairs based on the release cell identifier of the first CDR information and the access cell identifier of the second CDR information; S304, traversing all adjacent CDRs in the CDR list and counting the recorded missing neighbor cell pairs.

[0101] Specifically, in some specific embodiments, counting missing neighbor cell pairs can be achieved through the following steps:

[0102] First, it should be noted that this embodiment of the invention uses the characteristic of capturing dropped calls (call drops) through user behavior to achieve neighbor cell pair mismatch statistics. Typically, when a user is making a VoLTE voice call and the signal is very poor, making it difficult to hear the other party, they will actively hang up the phone and redial the same user's number. This characteristic can be used to initially determine if a user has dropped a call, and neighbor cell mismatch is one such scenario.

[0103] Normally, if a dropped call is caused by a missing neighbor cell, the mobile terminal returns to an idle state and searches for a network again. It will then wait on the best available cell. When the user dials again, it will use the best available cell, and the dropped call will usually not occur again.

[0104] By extracting user behavior data, the cell where the user disconnects and the cell where the user reconnects can be used as a neighbor cell for identification. If the two cells belong to different operators, it can be counted as a suspected cross-operator neighbor cell misconfiguration record. Accumulating these records can effectively support the discovery of cross-operator neighbor cell misconfiguration issues.

[0105] Based on the aforementioned user behavior characteristics for capturing dropped calls, such as Figure 5 As shown, the missing neighbor cell pairs are extracted from the call detail record (CDR) list: Starting from the first CDR in the CDR list, the records are traversed sequentially. If two consecutive CDRs belong to the same user and have the same peer number, and the difference between the release time of the previous record and the access time of the next record is within 20 seconds, and the release cell A in the previous record is different from the access cell B in the next record, then a suspected handover drop record from A to B is recorded. If it is suspected that A is not a neighbor cell of B, the count of the A->B cell pair is incremented by 1. After traversing the CDRs for one week, the statistical count of all missing neighbor cell pairs is obtained.

[0106] S400. Based on the statistical distribution of missing neighbor cell pairs, determine the missing neighbor cell problem for each cell.

[0107] It should be noted that in some embodiments, step S400 may include: obtaining target neighboring cell pairs with missing configurations based on preset screening conditions according to the statistical distribution of neighboring cell pairs with missing configurations; wherein, the target neighboring cell pairs with missing configurations represent the neighboring cell relationship between the first cell and the second cell, and the neighboring cell relationship includes a positive neighboring cell relationship and / or a reverse neighboring cell relationship; the neighboring cell distance of the neighboring cell relationship is determined by the positioning identifier of the cell identifiers corresponding to the first cell and the second cell; determining the first neighboring cell missing configuration problem according to the neighboring cell relationship; wherein, the first neighboring cell missing configuration problem includes one-way neighboring cell missing configuration and two-way neighboring cell missing configuration; when the neighboring cell relationship represented in the target neighboring cell pairs with missing configurations is a positive neighboring cell relationship or a reverse neighboring cell relationship between the first cell and the second cell, the first neighboring cell missing configuration problem is determined to be a one-way neighboring cell missing configuration; when the target neighboring cell pairs with missing configurations simultaneously contain both a positive neighboring cell relationship and a reverse neighboring cell relationship representing the first cell and the second cell, the first neighboring cell missing configuration problem is determined to be a two-way neighboring cell missing configuration.

[0108] In some embodiments, the method may further include: matching base station identifiers according to the cell identifiers corresponding to the first cell and the second cell to determine the operator relationship between the first cell and the second cell; determining the second neighbor cell mismatch problem according to the operator relationship; wherein the second neighbor cell mismatch problem includes mismatch of neighbor cells within the same operator and mismatch of neighbor cells across operators.

[0109] Specifically, in some specific embodiments, determining the neighbor cell missing configuration problem of each cell can be achieved through the following steps:

[0110] First, organize the neighboring cell missing match relationship table, such as Figure 6 As shown, the neighbor cell pairs with missing configurations counted in the aforementioned steps are sorted and organized. For cell pairs A->B, where A is the source cell and B is the neighbor cell, the number of suspected handover dropped calls is counted for A->B. Combined with the existing neighbor cell relationships, a neighbor cell missing configuration relationship organization table is obtained, consisting of source cell, source cell operator, source cell name, neighbor cell, neighbor cell operator, neighbor cell name, whether there is a positive neighbor cell relationship, whether there is a negative neighbor cell relationship, number of suspected positive handover dropped calls, sorted by the number of suspected positive handover dropped calls, sorted by the number of suspected negative handover dropped calls, and the distance between the source cell and the neighbor cell.

[0111] The source cell operator, neighboring cell operator, source cell name, and neighboring cell name can be determined based on the cell operation parameters exchanged between the two parties. When the exchange of cell operation parameters is not timely, resulting in missing information, the cell operator can be distinguished using the enodebid portion of the cell. Since the enodebid is used within a scope agreed upon by both parties and does not repeat within the same province, the cell operator affiliation can be determined based on the enodebid segmentation. If the cell name is missing, it can be left blank.

[0112] The number of suspected handover dropped calls is the number of suspected handover dropped calls from the source cell to the neighboring cell (A->B).

[0113] The number of suspected handover dropped calls in the reverse direction is the number of suspected handover dropped calls from the neighboring cell to the source cell (B->A).

[0114] The forward suspected handover dropped call count sorting is the reverse order of the suspected handover dropped call count from the same source cell to the neighboring cell (i.e., A->B).

[0115] The reverse sorting of suspected handover dropped calls is based on the number of suspected handover dropped calls when the neighboring cell is the source cell and the source cell is the neighboring cell (i.e., B->A), sorted in reverse order among B's neighboring cells.

[0116] The fields for "Whether there is a positive neighbor relationship" and "Whether there is a negative neighbor relationship" are all set to "Yes", "No", or "Unknown". If there is a relationship, set it to "Yes"; if there is no relationship, set it to "No"; if it cannot be determined, set it to "Unknown". Because neighbor data between the two parties cannot be exchanged in batches via the interface, we cannot confirm whether the other operator has created a neighbor cell for us, so we must set it to "Unknown". However, if the source cell is our own cell, and our neighbor relationships are known, we can determine whether the neighbor relationship is "Yes" or "No".

[0117] The distance between the source cell and neighboring cells can be calculated using the latitude and longitude of the source cell and neighboring cells. When the data is missing, it can be set to "unknown".

[0118] Furthermore, based on the above-mentioned analysis of missing neighbor cell relationships, a diagnosis of missing neighbor cell issues is performed:

[0119] Neighbor cell misconfiguration is categorized into cross-operator one-way neighbor cell misconfiguration, cross-operator two-way neighbor cell misconfiguration, intra-operator one-way neighbor cell misconfiguration, and intra-operator two-way neighbor cell misconfiguration. Based on actual network optimization work, the top 40 neighbor cell handover relationships with the highest number of suspected call drops have a significant impact on call drops. This embodiment of the invention temporarily uses the top 40 as the threshold for neighbor cell misconfiguration analysis. This threshold can be increased or decreased based on actual optimization configuration. The judgment rules are described below:

[0120] (1) Cross-carrier one-way neighbor cell mismatch

[0121] Here, "one-way neighbor cell misconfiguration" refers to the situation where we configure the neighbor cells of the other party, but the other party does not configure our neighbor cells, which is called situation 1. Or, the situation where the other party configures our neighbor cells, but we do not configure the neighbor cells of the other party, which is called situation 2.

[0122] Scenario 1 Filtering: The source cell operator is our side, the neighboring cell operator is the other side, select the positive neighbor cell relationship as "yes", the top 40 in the number of suspected reverse handover dropped calls, the number of suspected reverse handover dropped calls is more than twice the number of suspected positive dropped calls, the neighbor cell distance is within 3 kilometers or the neighbor cell relationship is "unknown".

[0123] Scenario 2 Filtering: The source cell operator is our side, and the neighboring cell operator is the other side. Select neighboring cell relationships where the positive neighboring cell relationship is "No", the top 40 neighboring cell relationships with the most suspected positive handover dropped calls, and the number of suspected positive handover dropped calls is more than twice the number of suspected negative handover dropped calls. Neighboring cell relationships with a distance of less than 3 kilometers or "Unknown".

[0124] (2) Missed configuration of two-way neighboring cells across operators

[0125] The source cell operator is our side, and the neighboring cell operator is the other party. Select neighboring cell relationships with "No" for positive neighboring relationships, and the top 40 neighboring cell relationships with the most suspected positive handover dropped calls. Select neighboring cell relationships with the most suspected positive handover dropped calls. Neighboring cell relationships with a distance of less than 3 kilometers or "Unknown" are suspected of not being configured with two-way neighboring cell configuration.

[0126] (3) Missed neighboring cell configuration by this operator

[0127] Here, "one-way neighbor cell mismatch" refers to the situation where both the source cell and the neighbor cell operators are our operators. Forward neighbor cell mismatch is situation 1, and reverse neighbor cell mismatch is situation 2.

[0128] Case 1 Filtering: Select positive neighbor cell relationship as "No", positive neighbor cell relationship as "Yes", the top 40 positive suspected handover dropped calls, positive suspected handover dropped calls more than twice the number of negative suspected dropped calls, neighbor cell distance within 3 kilometers or "Unknown" neighbor cell relationship.

[0129] Scenario 2 Filtering: Select "Yes" for positive neighbor relationships and "No" for negative neighbor relationships. The top 40 cells with the most suspected reverse handover dropped calls, where the number of suspected reverse handover dropped calls is more than twice the number of suspected positive handover dropped calls. Neighbor relationships with a distance of less than 3 kilometers or "Unknown" are also considered.

[0130] (4) Missed configuration of two-way neighboring cells by this operator

[0131] Both the source and neighboring cell operators are our company. We selected neighboring cell relationships with both forward and reverse neighboring cell relationships marked "No" and those ranking among the top 40 in terms of suspected handover call drops for both forward and reverse relationships. Neighboring cell relationships with a distance of less than 3 kilometers or marked "Unknown" are suspected of being missing bidirectional neighboring cell configurations.

[0132] To explain in detail the principle of the technical solution of the present invention, the overall process of the present invention will be described below with reference to some specific embodiments. It is easy to understand that the following is an explanation of the technical principle of the present invention and should not be regarded as a limitation of the present invention.

[0133] like Figure 7 As shown, the cross-carrier neighbor cell missing configuration detection method of this invention can be implemented through the following steps:

[0134] First, obtain VoLTE call detail records, neighbor cell relationships within the local network, and latitude and longitude information of cells within the local network and other networks;

[0135] Subsequently, the VoLTE call detail records were analyzed to obtain cell pairs with missing neighbor cell configuration characteristics.

[0136] Then, using the neighbor cell missing match characteristics, the relationship between neighbor cells in this network, and the latitude and longitude information of cells in this network and other networks, a neighbor cell missing match judgment relationship matrix is ​​compiled.

[0137] Finally, the neighbor cell misconfiguration judgment rules are used to output the diagnostic results of neighbor cell misconfiguration for both the local network and cross-operator networks.

[0138] In summary, existing technologies address the issue that traditional methods for detecting missing neighbor cell configurations fail when there is a lack of neighbor cell handover information and MR information from the other operator. Currently, determining missing neighbor cell configurations requires obtaining neighbor cell information from the other party. However, since the information exchanged between the two parties in the current shared network does not include neighbor cell information, traditional methods encounter the following problems:

[0139] 1. Traditional distance-based methods require manual verification of neighbor cell configuration when neighbor cell information cannot be obtained. This involves a large scope of verification, and verifying neighbor cell information requires logging into the other party's network management system to check frequency and neighbor cell configurations. It is not possible to specifically check for missing configuration issues in certain neighbor cells, resulting in a large workload for manual verification and difficulties in cross-operator neighbor cell verification.

[0140] 2. The traditional method of using the number of handover requests as a basis for neighbor cell determination is labor-intensive to manually calculate and export, and cannot be automatically obtained by the system. Moreover, when a frequency point is missing, the system will not record the handover request, so it is impossible to count the number of handover requests and detect the problem of missing neighbor cell configuration.

[0141] Therefore, this invention provides an implementation method for cross-carrier neighbor cell misconfiguration detection. By using the first and last cell codes used in VoLTE call records, and considering the characteristic that users typically dial the same number within a short period after a dropped call, records are filtered out where the interval between the current and next call is within 20 seconds, and the second access cell is from a different carrier than the first release cell. This yields short-interval cross-carrier cell pairs, and the top cell pairs with the highest number of cell pairs are identified to investigate missing neighbor cell configuration issues. Compared to existing technologies, this invention has the following advantages and effects:

[0142] 1. It can greatly reduce the scope of cross-operator neighbor cell mismatch verification, and only verify neighbor cell mismatch relationships with significant impact, thereby improving the efficiency of neighbor cell verification.

[0143] 2. This paper is the first to propose using user behavior analysis after a dropped call to locate the problem of missing neighbor cell configuration.

[0144] 3. Even in the case of missing frequency points, the problem of missing neighboring cells can still be determined through user behavior, which solves the drawbacks of traditional handover request statistics.

[0145] On the other hand, such as Figure 8As shown, this embodiment of the invention provides a cross-operator neighbor cell mismatch detection device 800, comprising: a first module 810, used to continuously obtain call detail record (CDR) information from the core network and store it in a target database; wherein, the CDR information includes number identifier, access time, release time, and cell identifier; the cell identifier data composition includes base station identifier and location identifier, and the core network shares a base station communication connection with different operator networks; a second module 820, used to extract historical CDR data for a first preset period from the target database, sort the CDR information in the historical CDR data according to the number identifier and access time, and obtain a CDR list; a third module 830, used to perform difference matching of access time, release time, and cell identifier on adjacent CDRs with the same number identifier in the CDR list, and statistically analyze neighbor cell mismatch cell pairs based on the difference matching results; and a fourth module 840, used to determine the neighbor cell mismatch problem of each cell according to the statistical distribution of neighbor cell mismatch cell pairs.

[0146] It should be noted that some embodiments also include the following modules:

[0147] The fifth module is used to determine call detail records (CDRs) based on the call signals of the mobile terminal. The number identifier includes the local number of the mobile terminal and the outgoing number of the call. The access time is determined by the initiation time of the call signal, and the release time is determined by the interruption time of the call signal. The cell identifier includes the access cell identifier and the release cell identifier. The access cell identifier is determined by the shared base station connected after the call signal is initiated, and the release cell identifier is determined by the shared base station connected before the call signal is interrupted.

[0148] The sixth module is used to match base station identifiers based on the cell identifiers corresponding to the first cell and the second cell to determine the operator relationship between the first cell and the second cell; and to determine the second neighbor cell mismatch problem based on the operator relationship; wherein the second neighbor cell mismatch problem includes the mismatch of neighbor cells within the same operator and the mismatch of neighbor cells across operators.

[0149] On the other hand, embodiments of the present invention provide an electronic device, including: a processor and a memory; the memory is used to store a program; the processor executes the program to implement the above-described cross-operator neighbor cell missing configuration detection method.

[0150] The content of the method embodiments of the present invention is applicable to the system embodiments. The specific functions implemented in the system embodiments are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0151] On the other hand, such as Figure 9 As shown, this embodiment of the invention also provides an electronic device 900, which includes at least one processor 910 and at least one memory 920 for storing at least one program; taking one processor 910 and one memory 920 as an example.

[0152] The processor 910 and memory 920 can be connected via a bus or other means.

[0153] Memory 920, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory 920 may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory 920 may optionally include memory remotely located relative to the processor, and this remote memory can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0154] The electronic device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0155] Specifically, Figure 10 A schematic block diagram of a computer system architecture for implementing an electronic device according to embodiments of the present invention is shown.

[0156] It should be noted that, Figure 10 The computer system 1000 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0157] like Figure 10 As shown, the computer system 1000 includes a central processing unit (CPU) 1001, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 1002 or programs loaded from storage section 1008 into random access memory (RAM). The RAM 1003 also stores various programs and data required for system operation. The CPU 1001, ROM 1002, and RAM 1003 are interconnected via a bus 1004. An input / output interface 1005 (I / O interface) is also connected to the bus 1004.

[0158] The following components are connected to the input / output interface 1005: an input section 1006 including a keyboard, mouse, etc.; an output section 1007 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a local area network card, modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the input / output interface 1005 as needed. A removable medium 1011, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 1010 as needed so that computer programs read from it can be installed into the storage section 1008 as needed.

[0159] In particular, according to embodiments of the present invention, the processes described in the various method flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1009, and / or installed from removable medium 1011. When the computer program is executed by central processing unit 1001, it performs various functions defined in the system of the present invention.

[0160] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, wherein computer-readable program code is carried. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0161] The content of the method embodiments of the present invention is applicable to the system embodiments. The specific functions implemented in the system embodiments are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0162] Another aspect of this invention provides a computer-readable storage medium storing a program that is executed by a processor to implement the method described above.

[0163] The content of the method embodiments of the present invention is applicable to the computer-readable storage medium embodiments. The specific functions implemented by the computer-readable storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above methods.

[0164] This invention also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform the aforementioned method.

[0165] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0166] It should be noted that although several modules for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0167] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, portable hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of the present invention.

[0168] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order shown in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously, or the blocks may sometimes be executed in reverse order. Furthermore, the embodiments presented and described in the flowcharts of this invention are provided by way of example to provide a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and sub-operations described as part of a larger operation are executed independently.

[0169] Furthermore, although the invention has been described in the context of functional modules, it should be understood that, unless otherwise stated, one or more of the functions and / or features may be integrated into a single physical device and / or software module, or one or more functions and / or features may be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the invention. Rather, given the properties, functions, and internal relationships of the various functional modules in the apparatus disclosed herein, the actual implementation of the module will be understood within the scope of conventional skill of an engineer. Therefore, those skilled in the art can implement the invention as set forth in the claims using ordinary techniques without excessive experimentation. It is also understood that the specific concepts disclosed are merely illustrative and not intended to limit the scope of the invention, which is determined by the full scope of the appended claims and their equivalents.

[0170] If a function is implemented as 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 invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0171] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution means, apparatus, or device (such as a computer-based device, a processor-including device, or other means that can fetch and execute instructions from, or in conjunction with, an instruction execution means, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution means, apparatus, or device.

[0172] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which programs can be printed, because programs can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0173] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution device. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0174] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0175] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

[0176] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of the present invention.

Claims

1. A cross-operator neighbor cell misconfiguration detection method, characterized in that, include: Continuously obtain call detail records (CDRs) from the core network and store them in the target database; The call detail record (CDR) information includes number identifier, access time, release time, and cell identifier; the cell identifier data includes base station identifier and location identifier; and the core network communicates with shared base stations of different operator networks. Extract historical call detail records (CDRs) for a first preset period from the target database, and sort the CDR information in the historical CDRs according to the number identifier and the access time to obtain a CDR list; For adjacent call records with the same number identifier in the call record list, perform difference matching on the access time, release time and cell identifier, and count the missing cell pairs in the neighboring cells based on the result of the difference matching; Based on the statistical distribution of the missing neighbor cell pairs, the missing neighbor cell problem for each cell is determined; The step of determining the neighboring cell mismatch problem for each cell based on the statistical distribution of the neighboring cell mismatch pairs includes: Based on the statistical distribution of the missing neighbor cell pairs, target missing neighbor cell pairs are obtained based on preset screening conditions; The target neighbor cell missing match cell pair represents the neighbor cell relationship between the first cell and the second cell, and the neighbor cell relationship includes a positive neighbor cell relationship and / or a negative neighbor cell relationship; the neighbor cell distance of the neighbor cell relationship is determined by the location identifier of the cell identifier corresponding to the first cell and the second cell; Based on the neighbor cell relationships, the first neighbor cell missing configuration issue is determined; The first neighbor cell mismatch problem includes one-way neighbor cell mismatch and two-way neighbor cell mismatch. When the neighbor cell relationship represented in the target neighbor cell mismatch cell pair is a positive neighbor cell relationship or a negative neighbor cell relationship between the first cell and the second cell, the first neighbor cell mismatch problem is determined to be a one-way neighbor cell mismatch. When the target neighbor cell mismatch cell pair simultaneously contains both a positive neighbor cell relationship and a negative neighbor cell relationship representing the first cell and the second cell, the first neighbor cell mismatch problem is determined to be a two-way neighbor cell mismatch.

2. The cross-operator neighboring cell misconfiguration detection method of claim 1, wherein, The continuous acquisition of call detail records (CDRs) from the core network includes: Based on the multi-operator core network, call detail records (CDRs) determined by shared base stations through each operator's network are continuously obtained from the core network; The multi-operator core network includes multiple different operator networks, each operator network including a core network and a shared base station, and the core network of each operator network is communicatively connected to the shared base station of all operator networks.

3. The cross-operator neighboring cell misconfiguration detection method of claim 1, wherein, The method also includes: The call detail record (CDR) information is determined based on the call signals from the mobile terminal. The number identifier includes the local number of the mobile terminal and the remote number of the caller; the access time is determined by the initiation time of the call signal, and the release time is determined by the interruption time of the call signal; the cell identifier includes an access cell identifier and a release cell identifier, the access cell identifier is determined by the shared base station connected after the call signal is initiated, and the release cell identifier is determined by the shared base station connected before the call signal is interrupted.

4. The cross-operator neighboring cell misconfiguration detection method of claim 1, wherein, The step of sorting each call detail record (CDR) entry in the historical CDR data according to the number identifier and the access time to obtain a CDR list includes: Using the number identifier as the first sorting field, the call detail records in the historical call detail records are sorted in the first sorting; Using the access time as the second sorting field, the call detail records (CDRs) in the first sorted historical data are sorted again to obtain a CDR list.

5. The cross-operator neighboring cell misconfiguration detection method of claim 3, wherein, The adjacent call detail records (CDRs) include first CDR information and second CDR information, wherein the access time of the first CDR information is earlier than the access time of the second CDR information; the step of performing difference matching on the access time, release time, and cell identifier of adjacent CDRs with the same number identifier in the CDR list, and statistically analyzing the missing neighbor cell pairs based on the result of the difference matching, includes: Based on the release time of the first call detail record (CDR) information and the access time of the second CDR information, a time difference calculation is performed to obtain the time interval. Based on the release cell identifier in the first call detail record (CDR) information and the access cell identifier in the second CDR information, the base station identifier is matched to obtain a matching result; When the time interval is less than the second preset period and the matching result of the base station identifier is inconsistent, the missing neighbor cell pair is recorded according to the release cell identifier of the first call detail record and the access cell identifier of the second call detail record. Iterate through all the adjacent call detail records in the call detail record list and count the number of missing cell pairs in the neighboring cells.

6. The cross-operator neighboring cell misconfiguration detection method of claim 1, wherein, The method further includes: Based on the cell identifiers corresponding to the first cell and the second cell, the base station identifiers are matched to determine the operator relationship between the first cell and the second cell; Based on the aforementioned operator relationships, the issue of missing configuration in the second neighboring cell was identified; The second neighbor cell misconfiguration problem includes misconfiguration of neighbor cells within the same operator and misconfiguration of neighbor cells across operators.

7. A cross-operator neighboring cell misconfiguration detection apparatus, characterized in that, include: The first module is used to continuously obtain call detail records (CDRs) from the core network and store them in the target database; The call detail record (CDR) information includes number identifier, access time, release time, and cell identifier; the cell identifier data includes base station identifier and location identifier; and the core network communicates with shared base stations of different operator networks. The second module extracts historical call detail records (CDRs) for a first preset period from the target database, sorts each CDR information in the historical CDRs according to the number identifier and the access time, and obtains a CDR list. The third module performs difference matching on adjacent call records with the same number identifier in the call record list, matching the access time, release time and cell identifier, and counts the missing cell pairs in the neighboring cells based on the result of the difference matching. The fourth module determines the neighbor cell mismatch problem for each cell based on the statistical distribution of the neighbor cell mismatched cell pairs. The step of determining the neighboring cell mismatch problem for each cell based on the statistical distribution of the neighboring cell mismatch pairs includes: Based on the statistical distribution of the missing neighbor cell pairs, target missing neighbor cell pairs are obtained based on preset screening conditions; The target neighbor cell missing match cell pair represents the neighbor cell relationship between the first cell and the second cell, and the neighbor cell relationship includes a positive neighbor cell relationship and / or a negative neighbor cell relationship; the neighbor cell distance of the neighbor cell relationship is determined by the location identifier of the cell identifier corresponding to the first cell and the second cell; Based on the neighbor cell relationships, the first neighbor cell missing configuration issue is determined; The first neighbor cell mismatch problem includes one-way neighbor cell mismatch and two-way neighbor cell mismatch. When the neighbor cell relationship represented in the target neighbor cell mismatch cell pair is a positive neighbor cell relationship or a negative neighbor cell relationship between the first cell and the second cell, the first neighbor cell mismatch problem is determined to be a one-way neighbor cell mismatch. When the target neighbor cell mismatch cell pair simultaneously contains both a positive neighbor cell relationship and a negative neighbor cell relationship representing the first cell and the second cell, the first neighbor cell mismatch problem is determined to be a two-way neighbor cell mismatch.

8. An electronic device, comprising: Including the processor and memory; The memory is used to store programs; The processor executes the program to implement the method as described in any one of claims 1 to 6.

9. A computer storage medium storing a processor-executable program, characterized in that, The processor-executable program, when executed by the processor, is used to implement the method as described in any one of claims 1 to 6.

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