WO2021031761A1 - 异常终端的处理方法、网管设备及计算机可读介质 - Google Patents

异常终端的处理方法、网管设备及计算机可读介质 Download PDF

Info

Publication number
WO2021031761A1
WO2021031761A1 PCT/CN2020/102816 CN2020102816W WO2021031761A1 WO 2021031761 A1 WO2021031761 A1 WO 2021031761A1 CN 2020102816 W CN2020102816 W CN 2020102816W WO 2021031761 A1 WO2021031761 A1 WO 2021031761A1
Authority
WO
WIPO (PCT)
Prior art keywords
abnormal
base station
terminal
protection table
terminal type
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2020/102816
Other languages
English (en)
French (fr)
Inventor
田文凯
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
ZTE Corp
Original Assignee
ZTE Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by ZTE Corp filed Critical ZTE Corp
Priority to JP2022512327A priority Critical patent/JP2022545498A/ja
Priority to EP20855185.3A priority patent/EP4017072A4/en
Publication of WO2021031761A1 publication Critical patent/WO2021031761A1/zh
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports

Definitions

  • the present disclosure belongs to the field of communication technology, and specifically relates to a processing method of an abnormal terminal, a network management device, an electronic device, and a computer-readable medium.
  • MDT Minimization Drive Test
  • the network analyzes the coverage, handover, access, interference and other conditions of the existing network according to the measurements reported by the terminal, finds problems and solves the problems of coverage, handover, access, and interference in the network.
  • the present disclosure aims to solve at least one of the technical problems existing in some situations and provide a method for handling abnormal terminals.
  • an embodiment of the present disclosure provides a method for processing an abnormal terminal, which includes: according to the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type obtained when the drive test minimization task is performed by each base station, Generate a first protection table; upload the first protection table to a cloud server so that the cloud server summarizes the first protection table uploaded by each network management device to generate a second protection table; receive all the protection tables issued by the cloud server The second protection table, and at least part of the corresponding relationship between the abnormal terminal type identification and the abnormal behavior type in the second protection table is issued to the base station, so that the base station controls the terminal with the abnormal terminal type identification Terminate the task of minimizing drive test.
  • the embodiments of the present disclosure provide a network management device, including: a generation module, configured to obtain the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type when performing the minimizing drive test task uploaded by each base station , Generate a first protection table; upload module, used to upload the first protection table to a cloud server, so that the cloud server summarizes the first protection table uploaded by each network management device to generate a second protection table; control The module is used to receive the second protection table issued by the cloud server, and send the correspondence between at least part of the abnormal terminal type identifiers and the abnormal behavior types in the second protection table to the base station, so that The base station controls the terminal with the abnormal terminal type identifier to terminate the task of minimizing drive test.
  • a generation module configured to obtain the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type when performing the minimizing drive test task uploaded by each base station , Generate a first protection table
  • upload module used to upload the first protection table to a cloud server, so that the cloud server summarizes the first
  • an embodiment of the present disclosure provides an electronic device, which includes: one or more processors; a storage device, on which one or more programs are stored, when the one or more programs are A plurality of processors execute, so that the one or more processors implement the method described in any one of the foregoing.
  • an embodiment of the present disclosure provides a computer-readable medium having a computer program stored thereon, and the program is executed by a processor to implement the method described in any one of the above.
  • FIG. 1 is a flowchart of a method for processing an abnormal terminal according to an embodiment of the disclosure
  • FIG. 2 is a flowchart of step S0 in an embodiment of the disclosure
  • step S3 is a flowchart of steps S31-S35 in step S3 in the embodiment of the disclosure.
  • FIG. 5 is a structural block diagram of a network management device according to an embodiment of the disclosure.
  • FIG. 6 is another structural block diagram of a network management device according to an embodiment of the disclosure.
  • FIG. 7 is a structural block diagram of a control module of a network management device according to an embodiment of the disclosure.
  • FIG. 8 is another structural block diagram of the control module of the network management device of the embodiment of the disclosure.
  • FIG. 9 is a structural diagram of an electronic device according to an embodiment of the disclosure.
  • the base station sends the delay information measurement to the terminal, the Global Navigation Satellite System (GNSS) information measurement, the Wireless Local Area Network (WLAN) information measurement, the Bluetooth information measurement, the idle state MDT (Logged MDT) measurement, etc., due to the defect of the measurement capability of the problem terminal, the disconnection, re-establishment, and handover fail; the base station sends the idle state MDT (Logged MDT) to the terminal, and the radio link fails MDT (Radio Link Failure; RLF MDT) ), Radio Resource Control Connection Establishment Failure; RCEF MDT) task, the terminal does not clear the data cache after reporting the measurement data in accordance with the provisions of the protocol, which leads to the phenomenon of unlimited reporting of measurement data. Analysis creates tremendous pressure.
  • GNSS Global Navigation Satellite System
  • WLAN Wireless Local Area Network
  • Bluetooth Bluetooth information measurement
  • the idle state MDT (Logged MDT) measurement etc.
  • the method for processing an abnormal terminal uses a network management device as an execution subject.
  • a network management device as an execution subject.
  • the cloud server can interact with multiple network management devices, and each network management device interacts with multiple base stations within its jurisdiction.
  • the so-called learning strategy in the following embodiments refers to a specific method for obtaining the corresponding relationship between the common terminal type identifier and the abnormal behavior type.
  • Fig. 1 is a flowchart of a method for processing an abnormal terminal according to an embodiment of the disclosure.
  • an embodiment of the present disclosure provides a method for processing an abnormal terminal, which includes the following steps:
  • the first protection table is only a form for storing the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type, and is not a table in a strict sense.
  • the terminal type identification can be any of the feature group indication FGI, International Mobile Equipment Identity Code IMEI, International Mobile Equipment Identity Code-Model Authentication Code IMEI-TAC, International Mobile Equipment Identity Code-Software Version IMEI-SV;
  • the characteristic group indication FGI is taken as an example for description.
  • the network management device detects that the performance index used for network maintenance is abnormal, parameters such as the call drop rate of the base station and the usage rate of the data analysis server are greater than the preset reference value.
  • the network management equipment will control the base station to adopt corresponding learning strategies and protection strategies for the terminal according to the type of abnormal behavior.
  • the following examples illustrate:
  • the type of abnormal behavior is an increase in the call drop rate; specifically, when network maintenance personnel find that some terminals will enter the idle state for data measurement after receiving Logged MD. If the logged MDT data is carried after the next access, There will be a reconfiguration timeout phenomenon; the network management equipment issues the learning strategy and protection strategy adopted by the base station to the terminal, as follows:
  • S011 Control the base station to issue a Logged MDT measurement task to the accessed terminal.
  • the base station records the terminal carrying the Logged MDT data and the reconfiguration timeout occurs according to the terminal type identifier FGI to form a record table.
  • the base station adopts a protection strategy for the terminal with the abnormal terminal type identifier FGI according to the first protection table.
  • the specific protection strategy is that when abnormal behaviors that increase the call drop rate occur in the later period, the base station will no longer issue a Logged MDT measurement task to the terminal with the abnormal terminal type identifier FGI.
  • the second type the usage rate of the data analysis server is greater than the preset value; specifically, when network maintenance personnel find that some terminals report Logged MDT data without restriction, and the reporting is frequent, which causes great pressure on the data analysis server, the network management equipment sends it to the base station
  • the learning strategies and protection strategies adopted for the terminal are as follows:
  • S022 Calculate the maximum number of measurements according to the measurement duration and measurement interval of the Logged MDT task.
  • S023 Determine whether the number of times the terminal reports Logged MDT data each time is greater than the maximum number of measurements calculated in step S022. Since the terminal reports at least one measurement each time the Logged MDT data is reported; theoretically the maximum number of reports of the terminal does not exceed the maximum number of measurements; if the number of times the terminal reports Logged MDT data each time is greater than the maximum number of measurements, these FGIs are recorded as abnormal terminals
  • the type identification FGI, and the corresponding relationship between the abnormal terminal type identification FGI and the type of abnormal behavior is stored, and the first protection table is generated. Among them, the corresponding relationship between the abnormal terminal type identifier FGI and the abnormal behavior type can be represented by ⁇ FGI, abnormal behavior type ⁇ . S024.
  • the base station adopts a protection strategy for the terminal with the abnormal terminal type identifier FGI according to the first protection table.
  • the specific protection strategy is that when abnormal behaviors that increase the call drop rate occur later, the base station will no longer issue Logged MDT measurement tasks to terminals with abnormal terminal type identification FGI; at the same time, the base station will no longer request those with abnormal terminal type identification FGI.
  • the terminal reports Logged MDT data.
  • the network management device may receive the first protection table obtained by each base station according to the above steps.
  • both the above-mentioned learning strategies adopted by the base station according to the first or the second abnormal behavior are periodic, and the above description only describes the specific method of the first learning cycle.
  • the base station will no longer learn the identifiers of the abnormal terminal types that have been identified, and only learn the identifiers of the unidentified abnormal terminal types to achieve incremental learning; because the identifiers of abnormal terminal types are limited, Continuously learning the identifiers of unidentified abnormal terminal types, the learning results also tend to converge, and the incremental learning method ensures the convergence of the learning process; the way the base station recognizes the identifier of the abnormal terminal type can rely on its own base station to learn and recognize. It can also be recognized by obtaining learning information shared by other base stations.
  • the second protection table is only a form for storing the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type, and is not a table in a strict sense.
  • step S2 the network management equipment summarizes the received first protection tables uploaded by each base station, and summarizes the correspondence between different abnormal terminal type identifiers and abnormal behavior types in each first protection table into a second protection Table; the cloud server then issues the second protection table to each network management device, so that the learning results of each base station connected to different network management devices are shared, so that the overall learning is more effective.
  • step S3 the network management device receives the second protection list issued from the cloud server; then, according to the number of correspondences between the abnormal terminal type identification and the abnormal behavior type that the base station can receive, the received second protection table
  • the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type in the table is issued to the corresponding base station, so that the base station controls the terminal with the abnormal terminal type identifier to terminate the execution of the MDT task.
  • the second protection table is collected by each network management device from the first protection table uploaded by each base station, and then the different abnormal terminal type identifiers and abnormal behavior types in each first protection table are summarized. The corresponding relationship is summarized into the second protection table.
  • the learning results of each base station connected to different network management equipment are shared, so that the overall learning is more effective, so that the protection range of each base station is wider, and the performance of the base station is improved. Lower consumption.
  • FIG. 2 is a flowchart of step S0 in an embodiment of the disclosure.
  • step S0 is further included before step S1 in the above-mentioned embodiment of the present disclosure; step S0 may specifically include the following steps:
  • S01 According to the type of abnormal behavior, determine whether the base station has activated the related function corresponding to the abnormal behavior.
  • step S01 the network management device needs to determine whether the base station has enabled the related function corresponding to the abnormal behavior according to the abnormal behavior type corresponding to the performance index detected by the network maintenance personnel. Because only the base station has enabled the corresponding function, the network device is allowed to control the learning strategy of the base station to perform abnormal behavior, thereby ensuring the accuracy of the opening range of the learning strategy.
  • the learning strategy is, for example, the learning strategy corresponding to the first and second abnormal behavior types in the foregoing embodiment. If it is determined in step S01 that the base station has activated the relevant function corresponding to the abnormal behavior, step S02 is executed; if it is determined that the base station has not activated the relevant function corresponding to the abnormal behavior, the method is terminated.
  • the network management device obtains corresponding performance indicators according to the type of abnormal behavior of the base station.
  • the performance indicators detected by the network management equipment may be parameters such as the call drop rate of the base station and the usage rate of the data analysis server.
  • step S3 the network management device determines whether the performance index for network maintenance detected in step S02 is greater than a first threshold, for example, the call drop rate of the base station, the usage rate of the data analysis server and other parameters are greater than the preset Reference. If it is determined that the performance index is greater than the first threshold. Step S04 is executed; if it is determined that the performance index is less than or equal to the first threshold, then step S02 is returned.
  • a first threshold for example, the call drop rate of the base station, the usage rate of the data analysis server and other parameters are greater than the preset Reference. If it is determined that the performance index is greater than the first threshold.
  • Step S04 is executed; if it is determined that the performance index is less than or equal to the first threshold, then step S02 is returned.
  • the control base station obtains the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type according to the type of abnormal behavior caused.
  • step S04 when the network management device detects that the performance index used for network maintenance is abnormal, parameters such as the call drop rate of the base station and the usage rate of the data analysis server are greater than the preset reference value.
  • the network management equipment will control the base station to adopt corresponding learning strategies and protection strategies for the terminal according to the type of abnormal behavior.
  • the specific learning strategy and protection strategy may be the same as steps S011 to S014 and steps S021 to S024 in the foregoing embodiment, and therefore will not be described in detail.
  • the network management equipment controls the learning of the base station (that is, the process of obtaining the correspondence between the normal terminal type identification and the abnormal behavior type) is periodic. Therefore, the base station no longer identifies the identified abnormal terminal type. For learning, only learn unrecognized abnormal terminal type identifications to achieve incremental learning; because abnormal terminal type identifications are limited, with continuous learning of unrecognized abnormal terminal type identifications, the learning results tend to converge and increase
  • the learning method ensures the convergence of the learning process; among them, the method for the base station to identify the abnormal terminal type identification can rely on its own learning and identification, or it can rely on the acquisition of learning information shared by other base stations.
  • Fig. 3 is a flowchart of steps S31-S35 in step S3 in an embodiment of the disclosure.
  • step S3 in the above embodiment may specifically include the following steps:
  • step S31 the network management device receives the second protection table issued by the cloud server.
  • the second protection table includes a plurality of correspondences between abnormal terminal type identifiers and abnormal behavior types.
  • step S32 the network management device obtains the number of different abnormal terminal type identifiers in the second protection table, denoted as M; and obtains the number of different abnormal terminal type identifiers that the base station can receive, denoted as N.
  • M the number of different abnormal terminal type identifiers in the second protection table
  • N the number of different abnormal terminal type identifiers that the base station can receive
  • the abnormal terminal type identifiers are the same, that is, ⁇ FGI-1, abnormal behavior type 1 ⁇ and ⁇ FGI-1 , The type of abnormal behavior 2 ⁇ .
  • step S33 if the network management device determines that M>N, it will execute step S34; if the network management device determines that M ⁇ N, it will execute step S35.
  • the network management device may sort the correspondence between the M different abnormal terminal type identifiers and the abnormal behavior types in the second protection table, and deliver the first N of them to the base station, or in the M N of the correspondences between different abnormal terminal type identifiers and abnormal behavior types are randomly selected and sent to the base station.
  • the second protection table is issued to the base station, so that the base station controls the terminal with the abnormal terminal type identifier to terminate the execution of the MDT task.
  • the network management device may issue the correspondence between all abnormal terminal type identifiers and abnormal behavior types in the second protection table to the base station, so that the base station controls the termination of the terminal with the abnormal terminal type identifier. Perform MDT tasks.
  • Fig. 4 is a flowchart of steps S36-S37 in step S3 in the embodiment of the disclosure.
  • step S34 the following steps may be further included after step S34 in the foregoing embodiment:
  • the replacement request includes: the base station periodically detects the number of protection times for the terminal corresponding to the abnormal terminal type identifier, and sends a request when a terminal with a protection number of 0 appears.
  • the base station when the base station periodically detects the protection times of the terminal corresponding to the abnormal terminal type identifier, and if it finds that the protection times of the terminal corresponding to an abnormal terminal type identifier is 0, then it sends a replacement request to the network management device.
  • the network management device determines the number of protections to be 0 based on the corresponding relationship between the abnormal terminal type identification and the abnormal behavior type in the second protection table that has not been issued to the base station.
  • the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type corresponding to the terminal is replaced.
  • the network management equipment summarizes the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type uploaded by the base station connected to it, to obtain the first protection table, and upload it to the cloud Server, the cloud server then aggregates the first protection table uploaded by each network management device connected to it to generate a second protection table.
  • the corresponding relationship between the abnormal terminal type identification and the abnormal behavior type in the second protection table is The corresponding relationship between the abnormal terminal type identification and the abnormal behavior type uploaded for the base stations connected to multiple network management equipment is summarized.
  • the network management equipment receives the second protection table issued by the cloud server, and adds the information in the second protection table At least part of the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type is issued to the base station, so that the base station controls the terminal with the abnormal terminal type identifier to terminate the execution of the MDT task.
  • the learning results of various base stations connected to different network management equipment are shared, so that the overall learning is more effective, so that the protection range of each base station is wider, and the performance consumption of the base station is lower.
  • Figure 5 is a structural block diagram of a network management device according to an embodiment of the disclosure.
  • an embodiment of the present disclosure provides a network management device, which can be used to execute the abnormal terminal processing method in any of the foregoing embodiments.
  • the network management equipment specifically includes: a generating module 1, an uploading module 2, and a control module 3.
  • the generating module 1 is configured to generate the first protection table according to the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type that are obtained when the MDT task is executed and uploaded by each base station.
  • the upload module 3 is used to upload the first protection table to the cloud server, so that the cloud server summarizes the first protection table uploaded by each network management device to generate a second protection table.
  • the control module 3 is configured to receive the second protection list issued by the cloud server, and issue the correspondence between at least part of the abnormal terminal type identification and the abnormal behavior type in the second protection list to the base station, so that the base station controls the abnormal terminal The terminal identified by the type terminates the execution of the MDT task.
  • the generation module 1 in the embodiment of the present disclosure can be used to perform step S1 in the above embodiment; the upload module 2 can be used to perform step S2 in the above embodiment; the control module 3 can be used to perform step S2 in the above embodiment. ⁇ S3.
  • Fig. 6 is another structural block diagram of a network management device according to an embodiment of the disclosure.
  • the network management device not only includes the above structure, but may also include: a first judgment module 4, a detection module 5, a second judgment module 6, and a first acquisition module 7.
  • the first judging module 4 is used to judge whether the base station turns on the related function corresponding to the abnormal behavior according to the type of the abnormal behavior.
  • the detecting module 5 is configured to detect the performance index of the base station corresponding to the abnormal behavior when the first determining module 4 determines that the base station has activated the related function corresponding to the abnormal behavior.
  • the second judgment module 6 is used to judge whether the detected performance index is greater than the first threshold.
  • the obtaining module 7 is used to control the base station to obtain the corresponding relationship between the abnormal terminal type identifier and the abnormal behavior type according to the type of abnormal behavior caused when the second determining module 6 determines that the detected performance index is greater than the first threshold.
  • the first judgment module 4 in the embodiment of the present disclosure can be used to execute step S01 in the above embodiment; the detection module 5 can be used to execute step S02 in the above embodiment; the second judgment module 6 can be used to execute Step S03 in the foregoing embodiment; the acquisition module 7 can be used to execute step S04 in the foregoing embodiment.
  • Fig. 7 is a structural block diagram of a control module of a network management device according to an embodiment of the disclosure.
  • control module may include: a first receiving unit 31, an acquiring unit 32, a judgment unit 33, and a control unit 34.
  • the first receiving unit 31 is configured to receive the second protection list issued by the cloud server.
  • the obtaining unit 32 is used to obtain the number of different abnormal terminal type identifiers in the second protection table, denoted as M; and obtain the number of different abnormal terminal type identifiers that can be received by the base station, denoted as N.
  • the judging unit 33 is used to judge whether M is greater than N.
  • the control unit 34 is configured to, when the judgment unit 33 judges that M>N, send the correspondence between the N different abnormal terminal type identifiers and the abnormal behavior types in the second protection table to the base station, so that The base station controls the terminal with the abnormal terminal type identifier to terminate the execution of the MDT task; and, when the determining unit 33 determines that if M ⁇ N, the second protection table is issued to the base station so that the base station can control The terminal with the abnormal terminal type identifier terminates the execution of the MDT task.
  • the first receiving unit 31 in the embodiment of the present disclosure can be used to perform step S31 in the above embodiment; the obtaining unit 32 can be used to perform step S32 in the above embodiment; the judgment unit 33 can be used to perform the above implementation Step S33 in the example; the control unit 34 can be used to execute steps S34 and S35 in the above embodiment.
  • FIG. 8 is another structural block diagram of the control module of the network management device according to the embodiment of the disclosure.
  • the foregoing control module not only includes the foregoing structure, but may also include: a second receiving unit 35 and a replacement unit 36.
  • the second receiving unit 35 is configured to receive a replacement request sent by the base station; the replacement request includes: the base station periodically detects the number of protection times for the terminal corresponding to the abnormal terminal type identifier, and the occurrence of a terminal whose protection number is 0 When the request is sent.
  • the replacement unit 36 is configured to, according to the replacement request, use the corresponding relationship between the abnormal terminal type identification and the abnormal behavior type in the second protection table that has not been sent to the base station, and combine the abnormal terminal type identification corresponding to the terminal whose protection times are 0 and The corresponding relationship of the type of abnormal behavior is replaced.
  • the second receiving unit 35 in the embodiment of the present disclosure can be used to execute step S36 in the above embodiment; the replacement unit 36 can be used to execute step S37 in the above embodiment.
  • the network management equipment provided in the embodiments of the present disclosure can adopt the method for processing abnormal terminals in the above-mentioned embodiments, that is, the network management equipment summarizes the correspondence between the abnormal terminal type identification and the abnormal behavior type uploaded by the base station connected to the network management equipment, Obtain the first protection table and upload it to the cloud server. The cloud server then aggregates the first protection table uploaded by each network management device connected to it to generate a second protection table. At this time, the abnormal terminal type in the second protection table
  • the corresponding relationship between the identifier and the type of abnormal behavior is a summary of the corresponding relationship between the abnormal terminal type identifier and the type of abnormal behavior uploaded by the base station to which multiple network management devices are connected.
  • the network management device receives the second protection issued by the cloud server
  • the corresponding relationship between at least part of the abnormal terminal type identifier and the abnormal behavior type in the second protection table is issued to the base station, so that the base station controls the terminal with the abnormal terminal type identifier to terminate the execution of the MDT task.
  • the learning results of various base stations connected to different network management equipment are shared, so that the overall learning is more effective, so that the protection range of each base station is wider, and the performance consumption of the base station is lower.
  • an electronic device which includes:
  • One or more processors 91 One or more processors 91;
  • the storage device 92 has one or more programs stored thereon. When the one or more programs are executed by the one or more processors 91, the one or more processors 91 implement any one of the above-mentioned abnormal terminal processing methods.
  • embodiments of the present disclosure provide a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, any one of the above-mentioned processing methods for abnormal terminals is implemented.
  • Such software may be distributed on a computer-readable medium, and the computer-readable medium may include a computer storage medium (or a non-transitory medium) and a communication medium (or a transitory medium).
  • the term computer storage medium includes volatile and non-volatile data implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Flexible, removable and non-removable media.
  • Computer storage media include but are not limited to RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassette, tape, magnetic disk storage or other magnetic storage device, or Any other medium used to store desired information and that can be accessed by a computer.
  • communication media usually contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as carrier waves or other transmission mechanisms, and may include any information delivery media .

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

一种异常终端的处理方法、网管设备、电子设备及计算机可读介质，属于通信技术领域。本公开实施例的异常终端的处理的方法，包括：根据各个基站上传的在执行最小化路测任务时，所获取到的异常终端类型标识和异常行为的类型的对应关系，生成第一防护表(S1)；将所述第一防护表上传至云服务器，以使所述云服务器对各个网管设备上传的第一防护表进行汇总，生成第二防护表(S2)；接收云服务器下发的所述第二防护表，并将所述第二防护表中的至少部分异常终端类型标识和异常行为类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行最小化路测任务(S3)。

Description

异常终端的处理方法、网管设备及计算机可读介质
相关申请的交叉引用
本申请基于申请号为201910776929.6、申请日为2019年8月22日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本公开属于通信技术领域，具体涉及一种异常终端的处理方法、网管设备、电子设备及计算机可读介质。
背景技术
在无线通讯领域，随着移动通信的普及和移动终端的广泛应用，移动市场下充斥着各种各样类型的终端；在众多终端类型中，存在部分异常终端，由于硬件缺陷或者没严格按照协议实现业务行为，导致在做特定业务时，出现掉线、接入失败、切换失败或测量数据频繁上报基站等异常现象，严重影响网络的掉线率、重建率、接入成功率、切换成功率等关键指标，给整个网络的维测造成了极大困难。
最小化路测(Minimization Drive Test；MDT)就是让现网的商用终端代替人工做路测，进行相关量的测量并上报。网络根据终端上报的测量对现网覆盖、切换、接入、干扰等情况进行分析，发现问题并解决网络中存在覆盖问题、切换问题、接入问题以及干扰等问题。
发明内容
本公开旨在至少解决一些情形中存在的技术问题之一，提供一种异常终端的处理的方法。
第一方面，本公开实施例提供一种异常终端的处理的方法，包括：根据各个基站上传的在执行最小化路测任务时，所获取的异常终端类型标识和异常行为的类型的对应关系，生成第一防护表；将所述第一防护表上传至云服务器，以使所述云服务器对各个网管设备上传的第一防护表进行汇总，生成第二防护表；接收云服务器下发的所述第二防护表，并将所述第二防护表中的至少部分异常终端类型标识和异常行为类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行最小化路测任务。
第二方面，本公开实施例提供一种网管设备，包括：生成模块，用于根据各个基站上传的在执行最小化路测任务时，所获取的异常终端类型标识和异常行为的类型的对应关系，生成第一防护表；上传模块，用于将所述第一防护表上传至云服务器，以使所述云服务器对各个网管设备上传的第一防护表进行汇总，生成第二防护表；控制模块，用于接收云服务器下发的所述第二防护表，并将所述第二防护表中的至少部分异常终端类型标识和异常行为类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端 终止执行最小化路测任务。
第三方面，本公开实施例提供一种电子设备，其包括：一个或多个处理器；存储装置，其上存储有一个或多个程序，当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现上述所谓任意一项所述的方法。
第四方面，本公开实施例提供一种计算机可读介质，其上存储有计算机程序，所述程序被处理器执行时实现上述的任意一项所述的方法。
附图说明
图1为本公开实施例的异常终端的处理方法的流程图；
图2为本公开实施例的步骤S0的流程图；
图3为本公开实施例中的步骤S3中的步骤S31-S35流程图；
图4为本公开实施例中的步骤S3中的步骤S36-S37流程图；
图5为本公开实施例的网管设备的一种结构框图；
图6为本公开实施例的网管设备的另一种结构框图；
图7为本公开实施例的网管设备的控制模块的一种结构框图；
图8为本公开实施例的网管设备的控制模块的另一种结构框图；
图9为本公开实施例的电子设备的结构图。
具体实施方式
为使本领域的技术人员更好地理解本公开的技术方案，下面结合附图对本公开提供的异常终端的处理方法、网管设备、电子设备及计算机可读介质进行详细描述。
在下文中将参考附图更充分地描述示例实施例，但是所述示例实施例可以以不同形式来体现且不应当被解释为限于本文阐述的实施例。反之，提供这些实施例的目的在于使本公开透彻和完整，并将使本领域技术人员充分理解本公开的范围。
如本文所使用的，术语“和/或”包括一个或多个相关列举条目的任何和所有组合。
本文所使用的术语仅用于描述特定实施例，且不意欲限制本公开。如本文所使用的，单数形式“一个”和“该”也意欲包括复数形式，除非上下文另外清楚指出。还将理解的是，当本说明书中使用术语“包括”和/或“由……制成”时，指定存在所述特征、整体、步骤、操作、元件和/或组件，但不排除存在或添加一个或多个其它特征、整体、步骤、操作、元件、组件和/或其群组。
本文所述实施例可借助本公开的理想示意图而参考平面图和/或截面图进行描述。因此，可根据制造技术和/或容限来修改示例图示。因此，实施例不限于附图中所示的实施例，而是包括基于制造工艺而形成的配置的修改。因此，附图中例示的区具有示意性属性，并且图中所示区的形状例示了元件的区的具体形状，但并不旨在是限制性的。
除非另外限定，否则本文所用的所有术语(包括技术和科学术语)的含义与本领域普通技术人员通常理解的含义相同。还将理解，诸如那些在常用字典中限定的那些术语应当被 解释为具有与其在相关技术以及本公开的背景下的含义一致的含义，且将不解释为具有理想化或过度形式上的含义，除非本文明确如此限定。
在一些情形中，基站给终端下发时延信息测量，全球卫星定位系统(Global Navigation Satellite System；GNSS)信息测量，无线局域网(Wireless Local Area Network；WLAN)信息测量，蓝牙信息测量，空闲态MDT(Logged MDT)测量等，由于问题终端的测量能力缺陷，出现掉线，重建，切换失败现象；基站给终端下发空闲态MDT(Logged MDT)，无线链路失败MDT(Radio Link Failure；RLF MDT)，无线资源控制连接建立失败MDT(Radio Resource Control Connection Establishment Failure；RCEF MDT)任务时，终端没有按照协议规定，在上报测量数据后清除数据缓存，导致无限制上报测量数据现象，对后端数据解析形成巨大压力。
本公开实施例所提供的异常终端的处理方法是以网管设备作为执行主体。通过网管设备、基站、云服务器之间进行信息的交互，以实现树状的共享机制。其中，云服务器与多个网管设备能够进行信息的交互，每个网管设备与其所管辖范围内的多个基站之间信息的交互。
在此需要说明的是，在下述实施例中所谓的学习策略是指：获取常终端类型标识和异常行为的类型的对应关系的具体方法。
图1为本公开实施例的异常终端的处理方法的流程图。
第一方面，参照图1，本公开实施例提供一种异常终端的处理方法，包括如下步骤：
S1、根据各个基站上传的执行MDT任务时，所获取的异常终端类型标识和异常行为的类型的对应关系，生成第一防护表。
在此需要说明的是，在本公开实施例中第一防护表只是用于存储异常终端类型标识和异常行为的类型的对应关系的一种形式，并非严格意义上的表格。
其中，终端类型标识可以为特性群指示FGI、国际移动设备识别码IMEI、国际移动设备识别码-型号认证码IMEI-TAC、国际移动设备识别码-软件版本IMEI-SV中的任意一种；在本实施例中以特性群指示FGI为例进行说明。
具体的，当网管设备检测到用以对网络维护的性能指标发生异常时，例如基站的掉话率、数据解析服务器的使用率等参数大于预设的参考值。网管设备将根据异常行为的类型，控制基站对终端采取相应的学习策略和防护策略。以下举例进行说明：
第一种：异常行为的类型为掉话率增加；具体的，当网络维护人员发现部分终端在接收到Logged MD后，会进入空闲态进行数据测量，下次接入后如果携带Logged MDT数据，会出现重配超时现象；网管设备下发给基站对终端所采取的学习策略和防护策略，具体如下：
S011、控制基站给接入的终端下发Logged MDT测量任务。
S012、基站对携带Logged MDT数据，并出现重配超时的终端按照终端类型标识FGI 进行记录，形成记录表。
S013、统计记录表中各个终端按照终端类型标识FGI出现的次数，获取出现次数大于预设值的终端类型标识FGI，并将这些FGI记作异常终端类型标识FGI，并将异常终端类型标识FGI与异常行为的类型的对应关系进行存储，生成第一防护表。其中，异常终端类型标识FGI与异常行为的类型的对应关系可以用{FGI，异常行为的类型}表示。S014、基站根据第一防护表对具有异常终端类型标识FGI的终端采取防护策略。具体防护策略为，在后期出现掉话率增加的异常行为时，基站出不再向具有异常终端类型标识FGI的终端下发Logged MDT测量任务。
第二种：数据解析服务器的使用率大于预设值；具体的当网络维护人员发现部分终端无限制上报Logged MDT数据，且上报频繁，给数据解析服务器造成巨大压力时，网管设备下发给基站对终端所采取的学习策略和防护策略，具体如下：
S021、控制基站给接入的终端下发Logged MDT测量任务。
S022、根据Logged MDT任务的测量时长和测量间隔，算出最大测量次数。
S023、判断终端每次上报Logged MDT数据的次数，是否大于步骤S022中计算得到的最大测量次数。由于终端每次上报Logged MDT数据中至少包含一次测量；理论上终端的最大上报次数不超过最大测量次数；若终端每次上报Logged MDT数据的次数大最大测量次数，则将这些FGI记作异常终端类型标识FGI，并将异常终端类型标识FGI与异常行为的类型的对应关系进行存储，生成第一防护表。其中，异常终端类型标识FGI与异常行为的类型的对应关系可以用{FGI，异常行为的类型}表示。S024、基站根据第一防护表对具有异常终端类型标识FGI的终端采取防护策略。具体防护策略为，在后期出现掉话率增加的异常行为时，基站出不再向具有异常终端类型标识FGI的终端下发Logged MDT测量任务；同时基站也不再请求具有异常终端类型标识FGI的终端上报Logged MDT数据。在步骤S1中，网管设备可以接收各个基站按照上述步骤所获取的第一防护表。
在需要说明的是，无论是上述的基站根据第一种还是第二种异常行为所采用的学习策略均为周期性的，上述描述只是描述了第一个学习周期的具体方法。而对于之后的学习，基站则对已经识别出的异常终端类型的标识不再进行学习，只学习未识别的异常终端类型的标识，实现增量学习；因为异常终端类型的标识是有限的，随着不断地对未识别异常终端类型的标识学习，学习结果也趋于收敛，增量的学习方式保证了学习过程的收敛性；其中基站识别异常终端类型的标识的方式可以依靠自身基站学习识别，也可以依靠获取其他基站分享的学习信息识别。
S2、将接收的各个基站上传的第一防护表上传至云服务器，以使云服务器对各个网管设备上传的第一防护表进行汇总，生成第二防护表。
在此需要说明的是，在本公开实施例中第二防护表只是用于存储异常终端类型标识和异常行为的类型的对应关系的一种形式，并非严格意义上的表格。
在步骤S2中，网管设备将其所接收到的各个基站上传的第一防护表进行汇总，将各个第一防护表中不同的异常终端类型标识与异常行为的类型的对应关系汇总成第二防护表；云服务器将第二防护表再下发至各个网管设备，这样一来，实现连接不同网管设备的各个基站的学习结果共享，以使总体的学习更加有效。
S3、接收云服务器下发的第二防护表，并将第二防护表中的至少部分异常终端类型标识和异常行为类型的对应关系下发至基站，以使基站控制具有异常终端类型标识的终端终止执行MDT任务。
在步骤S3中，网管设备接收来自云服务器下发的第二防护表；之后，再根据基站所能够接收的异常终端类型标识和异常行为类型的对应关系的数量，将所接收到的第二防护表中相应数量的异常终端类型标识和异常行为类型的对应关系下发至相应的基站，以使所述基站控制具有异常终端类型标识的终端终止执行MDT任务。
同时，由于第二防护表是由各个网管设备将其所接收到的各个基站上传的第一防护表中进行汇总，再将各个第一防护表中不同的异常终端类型标识与异常行为的类型的对应关系汇总成第二防护表，这样一来，实现连接不同网管设备的各个基站的学习结果共享，以使总体的学习更加有效，从而使得每个基站的防护范围更加广泛，同时使得基站性能的消耗更低。
图2为本公开实施例的步骤S0的流程图。
在一些实施例中，参照图2，在本公开上述实施例的步骤S1之前还包括步骤S0；步骤S0具体可以包括如下步骤：
S01、根据异常行为类型，判断基站是否开启了引起异常行为所对应的相关功能。
在步骤S01中，网管设备需要根据其所接收到网络维护人员所检测的性能指标所对应的异常行为类型，判断基站是否开启了引起异常行为所对应的相关功能。因为只有基站开启了相应功能，才允许网络设备控制该基站进行异常行为的学习策略，从而可以保证学习策略开启范围的准确性。其中，学习策略也即例如上述实施例中第一种和第二种异常行为类型所对应的学习策略。若在步骤S01中判断出基站开启了引起异常行为对应的相关功能，则执行步骤S02；若判断出基站没有开启引起异常行为对应的相关功能，则终止该方法。
S02、检测基站对应异常行为的性能指标。
在步骤S02中，网管设备根据基站根据异常行为的类型，获取相应的性能指标。具体的，网管设备所检测的性能指标可以是基站的掉话率、数据解析服务器的使用率等参数。
S03、判断所检测的性能指标是否大于第一阈值。
在步骤S3中，网管设备判断在步骤S02中所检测到的、用以对网络维护的性能指标是否大于第一阈值，例如基站的掉话率、数据解析服务器的使用率等参数大于预设的参考值。若判断出该性能指标大于第一阈值。则执行步骤S04；若判断出该性能指标小于等于第一阈值，则返回步骤S02。
S04、控制基站根据所引起的异常行为的类型，获取异常终端类型标识和异常行为的类型的对应关系。
在步骤S04中，当网管设备检测到用以对网络维护的性能指标发生异常时，例如基站的掉话率、数据解析服务器的使用率等参数大于预设的参考值。网管设备将根据异常行为的类型，控制基站对终端采取相应的学习策略和防护策略。具体的学习策略和防护策略可以与上述实施例中步骤S011～S014，以及步骤S021～S024相同，因此不再详细描述。
在此需要说明的是，网管设备控制基站的学习(也就是获取常终端类型标识和异常行为的类型的对应关系的过程)是周期性的，因此，基站对已识别的异常终端类型标识不再进行学习，只学习未识别的异常终端类型标识，实现增量学习；因为异常终端类型标识是有限的，随着不断地对未识别异常终端类型标识学习，学习结果也趋于收敛，增量的学习方式保证了学习过程的收敛性；其中，基站识别异常终端类型标识的方式可以依靠自身学习识别，也可以依靠获取其他基站分享的学习信息识别。
图3为本公开实施例中的步骤S3中的步骤S31-S35流程图。
在一些实施例，参照图3，上述实施例中的步骤S3，具体可以包括如下步骤：
S31、接收云服务器下发的第二防护表。
在步骤S31中，网管设备接收云服务器下发的第二防护表。其中，第二防护表包括多个异常终端类型标识和异常行为类型的对应关系。
S32、获取第二防护表中不同的异常终端类型标识的个数，记作M；以及获取基站能够接收的不同的异常终端类型标识的个数，记作N。
在步骤S32中，网管设备获取第二防护表中不同的异常终端类型标识的个数，记作M；以及获取基站能够接收的不同的异常终端类型标识的个数，记作N。在此需要说明的是，第二防护表中不同的异常终端类型标识的个数并不等于，第二防护表中异常终端类型标识和异常行为的类型的对应关系的数量；因为在第二防护表中，有可能存在两个异常终端类型标识和异常行为的类型的对应关系中，异常终端类型标识是相同的情况，也即存在{FGI-1，异常行为的类型1}和{FGI-1，异常行为的类型2}。
S33，判断M是否大于N。
在步骤S33中，网管设备若判断出M＞N，则执行步骤S34；网管设备若判断出M≤N，则执行步骤S35。
S34、将第二防护表中N个不同的异常终端类型标识和异常行为的类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行MDT任务。
在步骤S34中，网管设备可以将第二防护表的M个不同的异常终端类型标识和异常行为的类型的对应关系进行排序，将其中的前N个下发至所述基站，也可以在M个不同的异常终端类型标识和异常行为的类型的对应关系中随机抽取N个下发至所述基站。
S35、将第二防护表下发至所述基站，以使所述基站控制具有异常终端类型标识的终 端终止执行MDT任务。
在步骤S34中，网管设备可以将第二防护表中所有的异常终端类型标识和异常行为的类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行MDT任务。
图4为本公开实施例中的步骤S3中的步骤S36-S37流程图。
在一些实施例中，参照图4，在上述实施例中的步骤S34之后还可以包括以下步骤：
S36、接收基站发送的替换请求；所述替换请求包括：基站在周期性的检测对异常终端类型标识所对应的终端的防护次数，且在出现防护次数为0的终端时发送的请求。
具体的，当基站周期性的检测对异常终端类型标识所对应的终端的防护次数，若发现某一异常终端类型标识所对应的终端的防护次数为0，此时则向网管设备发送替换请求。
S37、根据所述替换请求，通过所述第二防护表中未被下发至基站的异常终端类型标识和异常行为的类型的对应关系，将防护次数为0的终端所对应的异常终端类型标识和异常行为的类型的对应关系进行替换。
具体的，网管设备在接收到基站所下发的替换请求后，则通过第二防护表中未被下发至基站的异常终端类型标识和异常行为的类型的对应关系，将防护次数为0的终端所对应的异常终端类型标识和异常行为的类型的对应关系进行替换。
本公开实施例所提供的异常终端的处理方法，通过网管设备将与之连接的基站所上传的异常终端类型标识和异常行为的类型的对应关系进行汇总，得到第一防护表，并上传至云服务器，之后云服务器再对与之连接各个网管设备所上传的第一防护表进行汇总生成第二防护表，此时，第二防护表中的异常终端类型标识和异常行为的类型的对应关系，为多个网管设备所连接的基站上传的异常终端类型标识和异常行为的类型的对应关系汇总，最后，网管设备接收云服务器下发的所述第二防护表，并将第二防护表中的至少部分异常终端类型标识和异常行为类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行MDT任务。这样一来，实现连接不同网管设备的各个基站的学习结果共享，以使总体的学习更加有效，从而使得每个基站的防护范围更加广泛，同时使得基站性能的消耗更低。
图5为本公开实施例的网管设备的一种结构框图。
第二方面，参照图5，本公开实施例提供一种网管设备，其可用于执行上述任一实施例中的异常终端的处理方法。该网管设备具体包括：生成模块1、上传模块2和控制模块3。
具体的，生成模块1用于根据各个基站上传的在执行MDT任务时，所获取的异常终端类型标识和异常行为的类型的对应关系，生成第一防护表。
上传模块3用于将第一防护表上传至云服务器，以使云服务器对各个网管设备上传的第一防护表进行汇总，生成第二防护表。
控制模块3用于接收云服务器下发的第二防护表，并将第二防护表中的至少部分异常终端类型标识和异常行为类型的对应关系，下发至基站，以使基站控制具有异常终端类型标识的终端终止执行MDT任务。
在需要说明的是，本公开实施例中的生成模块1可用于执行上述实施例中的步骤S1；上传模块2可用于执行上述实施例中的步骤S2；控制模块3可用于执行上述实施例中的步骤S3。
图6为本公开实施例的网管设备的另一种结构框图。
在一些实施例中，参照图6，该网管设备不仅包括上述结构，还可以包括：第一判断模块4、检测模块5、第二判断模块6、第一获取模块7。
具体的，第一判断模块4用于根据异常行为类型，判断基站是否开启引起异常行为所对应的相关功能。
检测模块5用于当所述第一判断模块4判断出基站开启了引起异常行为对应的相关功能时，检测所述基站对应该异常行为的性能指标。
第二判断模块6用于判断所检测的性能指标是否大于第一阈值。
获取模块7用于当第二判断模块6判断出所检测的性能指标大于第一阈值时，控制基站根据所引起的异常行为的类型，获取异常终端类型标识和异常行为的类型的对应关系。
在此需要说明的，本公开实施例中的第一判断模块4可用于执行上述实施例中的步骤S01；检测模块5可用于执行上述实施例中的步骤S02；第二判断模块6可用于执行上述实施例中的步骤S03；获取模块7可用于执行上述实施例中的步骤S04。
图7为本公开实施例的网管设备的控制模块的一种结构框图。
在一些实施例中，参照图7，上述的控制模块可以包括：第一接收单元31、获取单元32、判断单元33、控制单元34。
具体的，第一接收单元31用于接收云服务器下发的第二防护表。
获取单元用32于获取所述第二防护表中不同的异常终端类型标识的个数，记作M；以及获取基站能够接收的不同的异常终端类型标识的个数，记作N。
判断单元33用于判断M是否大于N。
控制单元34用于在判断单元33判断出M＞N时，将所述第二防护表中N个不同的异常终端类型标识和异常行为的类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行MDT任务；以及，在判断单元33判断出若判断出M≤N时，将第二防护表下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行MDT任务。
在此需要说明的，本公开实施例中的第一接收单元31可用于执行上述实施例中的步骤S31；获取单元32可用于执行上述实施例中的步骤S32；判断单元33可用于执行上述实施例中的步骤S33；控制单元34可用于执行上述实施例中的步骤S34和S35。
图8为本公开实施例的网管设备的控制模块的另一种结构框图。
在一些实施例中，参照图8，上述的控制模块不仅包括上述结构，还可以包括：第二接收单元35和替换单元36。
具体的，第二接收单元35用于接收基站发送的替换请求；该替换请求包括：基站在周期性的检测对异常终端类型标识所对应的终端的防护次数，且在出现防护次数为0的终端时发送的请求。
替换单元36用于根据替换请求，通过第二防护表中未被下发至基站的异常终端类型标识和异常行为的类型的对应关系，将防护次数为0的终端所对应的异常终端类型标识和异常行为的类型的对应关系进行替换。
在此需要说明的，本公开实施例中的第二接收单元35可用于执行上述实施例中的步骤S36；替换单元36可用于执行上述实施例中的步骤S37。
本公开实施例所提供的网管设备可以采用上述的实施例中异常终端的处理方法，即通过网管设备将与之连接的基站所上传的异常终端类型标识和异常行为的类型的对应关系进行汇总，得到第一防护表，并上传至云服务器，之后云服务器再对与之连接各个网管设备所上传的第一防护表进行汇总生成第二防护表，此时，第二防护表中的异常终端类型标识和异常行为的类型的对应关系，为多个网管设备所连接的基站上传的异常终端类型标识和异常行为的类型的对应关系汇总，最后，网管设备接收云服务器下发的所述第二防护表，并将第二防护表中的至少部分异常终端类型标识和异常行为类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行MDT任务。这样一来，实现连接不同网管设备的各个基站的学习结果共享，以使总体的学习更加有效，从而使得每个基站的防护范围更加广泛，同时使得基站性能的消耗更低。
第三方面，参考图9，本公开实施例提供一种电子设备，其包括：
一个或多个处理器91；
存储装置92，其上存储有一个或多个程序，当一个或多个程序被一个或多个处理器91执行，使得一个或多个处理器91实现上述任意一种异常终端的处理方法。
第四方面，本公开实施例提供一种计算机可读介质，其上存储有计算机程序，程序被处理器执行时实现上述任意一种异常终端的处理方法。
本领域普通技术人员可以理解，上文中所公开方法中的全部或某些步骤、系统、装置中的功能模块/单元可以被实施为软件、固件、硬件及其适当的组合。在硬件实施方式中，在以上描述中提及的功能模块/单元之间的划分不一定对应于物理组件的划分；例如，一个物理组件可以具有多个功能，或者一个功能或步骤可以由若干物理组件合作执行。某些物理组件或所有物理组件可以被实施为由处理器，如中央处理器、数字信号处理器或微处理器执行的软件，或者被实施为硬件，或者被实施为集成电路，如专用集成电路。这样的软件可以分布在计算机可读介质上，计算机可读介质可以包括计算机存储介质(或非暂时性 介质)和通信介质(或暂时性介质)。如本领域普通技术人员公知的，术语计算机存储介质包括在用于存储信息(诸如计算机可读指令、数据结构、程序模块或其它数据)的任何方法或技术中实施的易失性和非易失性、可移除和不可移除介质。计算机存储介质包括但不限于RAM、ROM、EEPROM、闪存或其它存储器技术、CD-ROM、数字多功能盘(DVD)或其它光盘存储、磁盒、磁带、磁盘存储或其它磁存储装置、或者可以用于存储期望的信息并且可以被计算机访问的任何其它的介质。此外，本领域普通技术人员公知的是，通信介质通常包含计算机可读指令、数据结构、程序模块或者诸如载波或其它传输机制之类的调制数据信号中的其它数据，并且可包括任何信息递送介质。
本文已经公开了示例实施例，并且虽然采用了具体术语，但它们仅用于并仅应当被解释为一般说明性含义，并且不用于限制的目的。在一些实例中，对本领域技术人员显而易见的是，除非另外明确指出，否则可单独使用与特定实施例相结合描述的特征、特性和/或元素，或可与其它实施例相结合描述的特征、特性和/或元件组合使用。因此，本领域技术人员将理解，在不脱离由所附的权利要求阐明的本公开的范围的情况下，可进行各种形式和细节上的改变。
可以理解的是，以上实施方式仅仅是为了说明本公开的原理而采用的示例性实施方式，然而本公开并不局限于此。对于本领域内的普通技术人员而言，在不脱离本公开的精神和实质的情况下，可以做出各种变型和改进，这些变型和改进也视为本公开的保护范围。

Claims (11)

  1. 一种异常终端的处理的方法，包括：
    根据各个基站上传的在执行最小化路测任务时，所获取的异常终端类型标识和异常行为的类型的对应关系，生成第一防护表；
    将所述第一防护表上传至云服务器，以使所述云服务器对各个网管设备上传的第一防护表进行汇总，生成第二防护表；
    接收云服务器下发的所述第二防护表，并将所述第二防护表中的至少部分异常终端类型标识和异常行为类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行最小化路测任务。
  2. 根据权利要求1所述的异常终端的处理方法，其中，在所述根据各个基站上传的在执行最小化路测任务时，所获取的异常终端类型标识和异常行为类型的对应关系，生成第一防护表之前，还包括：
    根据异常行为类型，判断基站是否开启引起异常行为所对应的相关功能；
    若判断出基站开启了引起异常行为对应的相关功能，检测所述基站对应该异常行为的性能指标；
    判断所检测的性能指标是否大于第一阈值；
    若判断出大于第一阈值，则控制基站根据所引起的异常行为的类型，获取异常终端类型标识和异常行为的类型的对应关系。
  3. 根据权利要求1所述的异常终端的处理方法，其中，所述接收云服务器下发的所述第二防护表，并将所述第二防护表中的至少部分异常终端类型标识和异常行为类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行最小化路测任务，包括：
    接收云服务器下发的第二防护表；
    获取所述第二防护表中不同的异常终端类型标识的个数，记作M；以及获取基站能够接收的不同的异常终端类型标识的个数，记作N；
    判断M是否大于N；
    若判断出M＞N，则将所述第二防护表中N个不同的异常终端类型标识和异常行为的类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行最小化路测任务；
    若判断出若判断出M≤N，则将第二防护表下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行最小化路测任务。
  4. 根据权利要求3所述的异常终端的处理方法，其中，所述若判断出M＞N，则将所述第二防护表中N个不同的异常终端类型标识和异常行为的类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行最小化路测任务之后，还 包括：
    接收基站发送的替换请求；所述替换请求包括：基站在周期性的检测对异常终端类型标识所对应的终端的防护次数，且在出现防护次数为0的终端时发送的请求；
    根据所述替换请求，通过所述第二防护表中未被下发至基站的异常终端类型标识和异常行为的类型的对应关系，将防护次数为0的终端所对应的异常终端类型标识和异常行为的类型的对应关系进行替换。
  5. 根据权利要求1所述的异常终端的处理方法，其中，所述异常终端类型标识包括：特性群指示、国际移动设备识别码、国际移动设备识别码-型号认证码、国际移动设备识别码-软件版本中的任意一种。
  6. 一种网管设备，包括：
    生成模块，用于根据各个基站上传的在执行最小化路测任务时，所获取的异常终端类型标识和异常行为的类型的对应关系，生成第一防护表；
    上传模块，用于将所述第一防护表上传至云服务器，以使所述云服务器对各个网管设备上传的第一防护表进行汇总，生成第二防护表；
    控制模块，用于接收云服务器下发的所述第二防护表，并将所述第二防护表中的至少部分异常终端类型标识和异常行为类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行最小化路测任务。
  7. 根据权利要求6所述的网管设备，其中，还包括：
    第一判断模块，用于根据异常行为类型，判断基站是否开启引起异常行为所对应的相关功能；
    检测模块，用于当所述第一判断模块判断出基站开启了引起异常行为对应的相关功能时，检测所述基站对应该异常行为的性能指标；
    第二判断模块，用于判断所检测的性能指标是否大于第一阈值；
    获取模块，用于当第二判断模块判断出所检测的性能指标大于第一阈值时，控制基站根据所引起的异常行为的类型，获取异常终端类型标识和异常行为的类型的对应关系。
  8. 根据权利要求6所述的网管设备，其中，所述控制模块包括：
    第一接收单元，用于接收云服务器下发的第二防护表；
    获取单元，用于获取所述第二防护表中不同的异常终端类型标识的个数，记作M；以及获取基站能够接收的不同的异常终端类型标识的个数，记作N；
    判断单元，用于判断M是否大于N；
    控制单元，用于在判断单元判断出M＞N时，将所述第二防护表中N个不同的异常终端类型标识和异常行为的类型的对应关系，下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止执行最小化路测任务；以及，在判断单元判断出若判断出M≤N时，将第二防护表下发至所述基站，以使所述基站控制具有异常终端类型标识的终端终止 执行最小化路测任务。
  9. 根据权利要求8所述的网管设备，其中，所述控制模块还包括：
    第二接收单元，用于接收基站发送的替换请求；所述替换请求包括：基站在周期性的检测对异常终端类型标识所对应的终端的防护次数，且在出现防护次数为0的终端时发送的请求；
    替换单元，用于根据所述替换请求，通过所述第二防护表中未被下发至基站的异常终端类型标识和异常行为的类型的对应关系，将防护次数为0的终端所对应的异常终端类型标识和异常行为的类型的对应关系进行替换。
  10. 一种电子设备，其包括：
    一个或多个处理器；
    存储装置，其上存储有一个或多个程序，其中，当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现权利要求1-5中任意一项所述的方法。
  11. 一种计算机可读介质，其上存储有计算机程序，其中，所述程序被处理器执行时实现权利要求1-5中任意一项所述的方法。
PCT/CN2020/102816 2019-08-22 2020-07-17 异常终端的处理方法、网管设备及计算机可读介质 Ceased WO2021031761A1 (zh)

Priority Applications (2)

Application Number Priority Date Filing Date Title
JP2022512327A JP2022545498A (ja) 2019-08-22 2020-07-17 異常端末の処理方法、ネットワーク管理機器、及びコンピュータ読み取り可能な媒体
EP20855185.3A EP4017072A4 (en) 2019-08-22 2020-07-17 METHOD FOR HANDLING ABNORMAL TERMINAL, NETWORK MANAGEMENT DEVICE AND COMPUTER READABLE MEDIA

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201910776929.6A CN112423315B (zh) 2019-08-22 2019-08-22 异常终端的处理方法、网管设备及计算机可读介质
CN201910776929.6 2019-08-22

Publications (1)

Publication Number Publication Date
WO2021031761A1 true WO2021031761A1 (zh) 2021-02-25

Family

ID=74659928

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2020/102816 Ceased WO2021031761A1 (zh) 2019-08-22 2020-07-17 异常终端的处理方法、网管设备及计算机可读介质

Country Status (4)

Country Link
EP (1) EP4017072A4 (zh)
JP (1) JP2022545498A (zh)
CN (1) CN112423315B (zh)
WO (1) WO2021031761A1 (zh)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102476700B1 (ko) * 2021-05-13 2022-12-12 서울대학교산학협력단 비정상 단말을 포함하는 무선 분산 학습 시스템 및 그의 동작 방법
CN115544502B (zh) * 2022-03-07 2024-04-23 荣耀终端有限公司 终端软件管控方法、电子设备及存储介质
CN114596297A (zh) * 2022-03-16 2022-06-07 深圳市恒天伟业科技有限公司 一种pcb的制造方法以及pcb制造系统

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20180086593A (ko) * 2017-01-23 2018-08-01 주식회사 엘지유플러스 무선 네트워크 전용망 설정 장치 및 그 방법
CN108668318A (zh) * 2018-06-06 2018-10-16 奇酷互联网络科技（深圳）有限公司 小区测量报告的处理方法、装置和移动终端
CN109391933A (zh) * 2017-08-04 2019-02-26 中兴通讯股份有限公司 工作异常终端处理、工作异常终端识别方法及装置
CN109818770A (zh) * 2017-11-22 2019-05-28 维沃移动通信有限公司 一种最小化路测异常配置处理方法和装置

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101998463B (zh) * 2009-08-11 2013-04-24 电信科学技术研究院 一种最小化路测方法及系统
EP3661256A1 (en) * 2009-10-30 2020-06-03 Telefonaktiebolaget LM Ericsson (publ) User equipment reporting of connection loss
KR101660818B1 (ko) * 2010-02-16 2016-09-28 삼성전자주식회사 이동통신 시스템에서 채널 측정 정보의 전송 방법 및 장치
KR20120037602A (ko) * 2010-10-12 2012-04-20 주식회사 팬택 이동통신 단말 및 이동통신 단말의 엠디티 관련 데이터 관리 방법
CN102761863B (zh) * 2011-04-29 2015-08-19 华为技术有限公司 最小化人工路测方法、收集终端信息方法、终端及网元
US9271169B2 (en) * 2012-02-23 2016-02-23 Ace Incorporated Method of reporting link failure
CN103369581B (zh) * 2012-04-05 2016-12-14 华为技术有限公司 一种获取终端最小化路测数据的方法和装置
US9565203B2 (en) * 2014-11-13 2017-02-07 Cyber-Ark Software Ltd. Systems and methods for detection of anomalous network behavior
CN106162708A (zh) * 2015-04-10 2016-11-23 中兴通讯股份有限公司 一种最小化路测方法及装置
CN106162709B (zh) * 2015-04-10 2021-05-07 中兴通讯股份有限公司 丢失率的最小化路测mdt的方法及装置
IL249816B (en) * 2016-12-28 2019-03-31 Gross Amit System and methods for diagnosing and repairing a smart mobile device by neutralization

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20180086593A (ko) * 2017-01-23 2018-08-01 주식회사 엘지유플러스 무선 네트워크 전용망 설정 장치 및 그 방법
CN109391933A (zh) * 2017-08-04 2019-02-26 中兴通讯股份有限公司 工作异常终端处理、工作异常终端识别方法及装置
CN109818770A (zh) * 2017-11-22 2019-05-28 维沃移动通信有限公司 一种最小化路测异常配置处理方法和装置
CN108668318A (zh) * 2018-06-06 2018-10-16 奇酷互联网络科技（深圳）有限公司 小区测量报告的处理方法、装置和移动终端

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP4017072A4 *

Also Published As

Publication number Publication date
CN112423315B (zh) 2024-07-19
CN112423315A (zh) 2021-02-26
EP4017072A1 (en) 2022-06-22
JP2022545498A (ja) 2022-10-27
EP4017072A4 (en) 2022-10-26

Similar Documents

Publication Publication Date Title
US12511186B2 (en) Using user equipment data clusters and spatial temporal graphs of abnormalities for root cause analysis
CN101800675B (zh) 故障监控方法、监控设备及通信系统
CN104105114B (zh) 数据传输方法、装置及终端
US20140219107A1 (en) Technique for Determining Correlated Events in a Communication System
CN103220695A (zh) 网元状态的处理方法及装置
CN101925101A (zh) 一种用户呼叫过程信息采集及统计分析的方法及装置
US12143452B2 (en) Method and apparatus for signaling session terminations in a communication network
US20120089876A1 (en) Method, apparatus and system for flexible user tracing in mobile networks
WO2020151699A1 (zh) 信息上报方法、接收方法、装置及设备
CN103701625A (zh) 家庭网关wlan 网络故障定位方法及网管系统
CN106454926A (zh) 链路覆盖问题确定方法、装置与系统
CN107182051B (zh) 一种用于cbtc的终端状态跟踪方法
WO2016045418A1 (zh) 一种参考信号接收质量上报方法及装置
EP4017072A1 (en) Method for processing abnormal terminal, network management device and computer-readable medium
WO2019024939A1 (zh) 工作异常终端处理、工作异常终端识别方法及装置
WO2022149149A1 (en) Artificial intelligence with dynamic causal model for failure analysis in mobile communication network
KR102333866B1 (ko) 이동 통신 네트워크 이상 진단 장치 및 방법
CN120416879A (zh) 网络质量的调整方法、系统及计算机设备
CN111263389B (zh) 一种Volte语音质量问题的自动化定位的方法及装置
WO2020063050A1 (zh) 数据传输方法及装置
EP2982162B1 (en) Technique for aggregating minimization of drive test, mdt, measurements in a component of an operating and maintenance, oam, system
CN103167537A (zh) 一种上行干扰测量方法、系统及装置
CN107920360A (zh) 一种定位网络问题的方法、装置及系统
CN104581804B (zh) 物联网中固定终端状态检测的方法
CN109756384A (zh) 数据源状态判定方法及装置

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20855185

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2022512327

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 2020855185

Country of ref document: EP

Effective date: 20220314