Abnormal cell determination method and device, data cutoff processing method and device, medium and chip

Abstract

The invention relates to an abnormal cell determination method and device, a data cutoff processing method and device, a medium and a chip, and belongs to the technical field of communication, and the abnormal cell determination method comprises the steps: determining a first weight corresponding to each type of network abnormal event for each type of network abnormal event generated by a plurality of terminals; determining a second weight corresponding to the type of network exception event according to the first weight of the type of network exception event and a second number proportion of the type of network exception event occurring in the target terminal for each type of network exception event occurring in the plurality of cells of any target terminal, and determining a second weight corresponding to the type of network exception event according to the first weight of the type of network exception event and the second number proportion of the type of network exception event occurring in the target terminal, the plurality of cells are cells detected by the target terminal; and for any cell, determining whether the cell is an abnormal cell of the target terminal according to the second weight of each type of network abnormal event of the target terminal in the cell. The accuracy of the finally determined abnormal cell can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a method, device, medium and chip for determining abnormal cells and processing data interruption. Background Art

[0002] In the network connection, there will be some abnormal cells, which may cause the terminal device to be unable to obtain services, slow Internet access, and freezes. In the related art, abnormal cells can be determined so that the user's terminal device can avoid abnormal cells to ensure normal communication or data services of the terminal device. However, the information used to determine abnormal cells in the related art is single, resulting in the abnormal cells determined to be inaccurate. Summary of the invention

[0003] In order to overcome the problems existing in the related art, the present disclosure provides a method, device, medium and chip for determining abnormal cells and processing data interruption.

[0004] According to a first aspect of an embodiment of the present disclosure, a method for determining an abnormal cell is provided, the method comprising:

[0005] For each type of network abnormal event occurring at each of the multiple terminals, determine a first weight corresponding to each type of network abnormal event, wherein the first weight of each type of network abnormal event is related to a first quantity ratio of the type of network abnormal event to all network abnormal events occurring at the multiple terminals;

[0006] For each type of network abnormal event occurring in a plurality of cells for any target terminal, determining a second weight corresponding to the type of network abnormal event according to the first weight of the type of network abnormal event and a second number ratio of the type of network abnormal event occurring in the target terminal, wherein the plurality of cells are cells detected by the target terminal;

[0007] For any cell, whether the cell is an abnormal cell of the target terminal is determined according to the second weight of each type of network abnormal event occurring in the cell by the target terminal.

[0008] In some embodiments, the first weight of each type of network abnormal event is negatively correlated with the first quantity ratio of the type of network abnormal event.

[0009] In some embodiments, the first weight of each type of network abnormal event is obtained based on the difference between a preset value and the first quantity proportion of the type of network abnormal event, and the preset value is 1.

[0010] In some embodiments, for each type of network abnormal event occurring in a plurality of cells for any target terminal, determining a second weight corresponding to the type of network abnormal event according to the first weight of the type of network abnormal event and a second number ratio of the type of network abnormal event occurring in the target terminal includes:

[0011] For each type of network abnormal event occurring in multiple cells for any target terminal, the function value of a preset exponential function is determined according to the second number proportion of this type of network abnormal event occurring in the target terminal and a preset attenuation parameter, and the second weight of this type of network abnormal event is determined according to the first weight of this type of network abnormal event and the function value.

[0012] In some embodiments, for any cell, determining whether the cell is an abnormal cell of the target terminal according to the second weight of each type of network abnormal event occurring in the cell by the target terminal includes:

[0013] For any cell, determining an anomaly score of the cell according to the second weight of each type of network anomaly event occurring in the cell by the target terminal;

[0014] When the abnormality score is greater than a preset threshold, the cell is determined as the abnormal cell of the target terminal.

[0015] In some embodiments, the abnormal cell determination method further includes:

[0016] Generate an abnormal cell list of the target terminal according to the abnormal cell of the target terminal; if any abnormal cell in the abnormal cell list of the target terminal is detected and no network abnormal event of any type occurs within a preset time period, delete the abnormal cell from the abnormal cell list.

[0017] According to a second aspect of an embodiment of the present disclosure, a data interruption processing method is provided, the data interruption processing method comprising:

[0018] When a data interruption occurs at a target terminal, obtaining a target cell currently accessed by the target terminal;

[0019] Matching the target cell and the abnormal cell to obtain a matching result, wherein the abnormal cell is obtained according to the abnormal cell determination method;

[0020] If the matching result reflects that the target cell is the abnormal cell, disabling the target cell and detecting a normal cell;

[0021] Control the target terminal to access the normal cell.

[0022] According to a third aspect of an embodiment of the present disclosure, a device for determining an abnormal cell is provided, the device for determining an abnormal cell comprising:

[0023] A first determination module is configured to determine, for each type of network abnormal event occurring at each of the multiple terminals, a first weight corresponding to each type of network abnormal event, wherein the first weight of each type of network abnormal event is related to a first quantity ratio of the type of network abnormal event to all network abnormal events occurring at the multiple terminals;

[0024] A second determination module is configured to determine, for each type of network abnormal event occurring in a plurality of cells for any target terminal, a second weight corresponding to the type of network abnormal event according to the first weight of the type of network abnormal event and a second number ratio of the type of network abnormal event occurring in the target terminal, wherein the plurality of cells are cells detected by the target terminal;

[0025] The third determination module is configured to determine, for any cell, whether the cell is an abnormal cell of the target terminal according to the second weight of each type of network abnormal event occurring in the cell by the target terminal.

[0026] In some embodiments, the first weight of each type of network abnormal event is negatively correlated with the first quantity ratio of the type of network abnormal event.

[0027] In some embodiments, the first weight of each type of network abnormal event is obtained based on the difference between a preset value and the first quantity proportion of the type of network abnormal event, and the preset value is 1.

[0028] In some embodiments, the second determining module is further configured to:

[0029] For each type of network abnormal event occurring in multiple cells for any target terminal, the function value of a preset exponential function is determined according to the second number proportion of this type of network abnormal event occurring in the target terminal and a preset attenuation parameter, and the second weight of this type of network abnormal event is determined according to the first weight of this type of network abnormal event and the function value.

[0030] In some embodiments, the third determination module is further configured to:

[0031] For any cell, determining an anomaly score of the cell according to the second weight of each type of network anomaly event occurring in the cell by the target terminal;

[0032] When the abnormality score is greater than a preset threshold, the cell is determined as the abnormal cell of the target terminal.

[0033] In some embodiments, the abnormal cell determination device further includes:

[0034] A generating module, configured to generate an abnormal cell list of the target terminal according to the abnormal cells of the target terminal;

[0035] The deleting module is configured to, when any abnormal cell in the abnormal cell list of the target terminal is detected and no network abnormal event of any type occurs within a preset time period, delete the abnormal cell from the abnormal cell list.

[0036] According to a fourth aspect of an embodiment of the present disclosure, a data interruption processing device is provided, the data interruption processing device comprising:

[0037] An acquisition module is configured to acquire a target cell currently accessed by the target terminal when detecting that data flow interruption occurs in the target terminal;

[0038] a matching module configured to match the target cell and the abnormal cell to obtain a matching result, wherein the abnormal cell is obtained according to the abnormal cell determination method;

[0039] a disabling module configured to disable the target cell and detect a normal cell if the matching result reflects that the target cell is the abnormal cell;

[0040] The access module is configured to control the target terminal to access the normal cell.

[0041] According to a fifth aspect of an embodiment of the present disclosure, a device for determining an abnormal cell is provided, including:

[0042] processor;

[0043] a memory for storing processor-executable instructions;

[0044] Wherein, the processor is configured to:

[0045] For each type of network abnormal event occurring at each of the multiple terminals, determine a first weight corresponding to each type of network abnormal event, wherein the first weight of each type of network abnormal event is related to a first quantity ratio of the type of network abnormal event to all network abnormal events occurring at the multiple terminals;

[0046] For each type of network abnormal event occurring in a plurality of cells for any target terminal, determining a second weight corresponding to the type of network abnormal event according to the first weight of the type of network abnormal event and a second number ratio of the type of network abnormal event occurring in the target terminal, wherein the plurality of cells are cells detected by the target terminal;

[0047] For any cell, whether the cell is an abnormal cell of the target terminal is determined according to the second weight of each type of network abnormal event occurring in the cell by the target terminal.

[0048] According to a sixth aspect of an embodiment of the present disclosure, a data interruption processing device is provided, including:

[0049] processor;

[0050] a memory for storing processor-executable instructions;

[0051] Wherein, the processor is configured to:

[0052] When a data interruption occurs at a target terminal, obtaining a target cell currently accessed by the target terminal;

[0053] Matching the target cell and the abnormal cell to obtain a matching result, wherein the abnormal cell is obtained according to the abnormal cell determination method;

[0054] If the matching result reflects that the target cell is the abnormal cell, disabling the target cell and detecting a normal cell;

[0055] Control the target terminal to access the normal cell.

[0056] According to a seventh aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided, on which computer program instructions are stored. When the program instructions are executed by a processor, the steps of the method described in any one of the first aspect and the second aspect of the present disclosure are implemented.

[0057] According to an eighth aspect of an embodiment of the present disclosure, a chip is provided, comprising a processor and an interface; the processor is used to read instructions to execute any one of the methods of the first aspect and the second aspect.

[0058] The technical solution provided by the embodiments of the present disclosure may include the following beneficial effects: in the process of determining whether a cell is an abnormal cell of a target terminal, a second weight determined according to a second number proportion of each type of network abnormal event occurring in the target terminal is utilized, that is, the network abnormal event information of the target terminal itself is utilized, so that the abnormal cell finally selected is more in line with the communication environment and network requirements of the target terminal itself, thereby improving the accuracy of the abnormal cell finally determined, and making the determined abnormal cell more meet the personalized requirements of the user.

[0059] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0061] Figure 1 The figure is a flowchart of a method for determining an abnormal cell according to an exemplary embodiment.

[0062] Figure 2 The figure is a flow chart of a method for processing data interruption according to an exemplary embodiment.

[0063] Figure 3 The figure is a block diagram showing a device for determining an abnormal cell according to an exemplary embodiment.

[0064] Figure 4 The invention is a block diagram of a data interruption processing device according to an exemplary embodiment.

[0065] Figure 5 The present invention is a block diagram of an abnormal cell determination device or a data interruption processing device according to an exemplary embodiment. DETAILED DESCRIPTION

[0066] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0067] As mentioned in the background technology, in network connections, such as 4G network connections or 5G network connections, there will be some abnormal cells, which may cause the terminal device to be unable to obtain services, slow Internet access, and freezes. In related technologies, abnormal cells can be determined so that the user's terminal device avoids abnormal cells to ensure normal communication or data services of the terminal device.

[0068] For example, the relevant technology can determine abnormal cells in the following ways: 1) using cloud technology to train an abnormal cell detection model, identifying abnormal cell characteristics through the abnormal cell detection model, thereby detecting abnormal cell data, and sending the abnormal cell data to the user's terminal device; 2) the user's terminal device uses an abnormal cell detection algorithm to detect abnormal cells.

[0069] However, the abnormal cell information used in the related art to determine abnormal cells is single, and does not take into account the abnormal cell information of the user's terminal device. However, different users are located in different areas or have different requirements for the network, and the abnormal cell information corresponding to different user living environments is also different. Therefore, the abnormal cells determined in the related art are not accurate, causing the user's terminal device to still reside in the abnormal cell after network switching or cell reselection, causing the user's terminal device to be unable to restore good network services for a long time, affecting the user experience.

[0070] In addition, when users encounter network problems such as no service in the current cell network, data freeze or network congestion during the use of terminal devices, the terminal devices will generally switch networks or cells. In this process, there are some cells with normal signal quality but still abnormal services, such as congested cells in crowded places, which will also be used as candidate cells for cell switching. However, after staying in such abnormal cells, the terminal devices still cannot obtain good network services, and thus the network switching or cell reselection process will be carried out again, causing users to be unable to restore good network services for a long time, affecting user experience.

[0071] In view of this, the present disclosure proposes a method, device, medium and chip for determining abnormal cells and processing data interruption.

[0072] Figure 1 It is a flowchart of an abnormal cell determination method according to an exemplary embodiment. It is worth noting that the present disclosure does not impose any restrictions on the execution subject of the abnormal cell determination method. For example, the abnormal cell determination method can be executed by a network device or by a target terminal. The network device may include a computer, which may be a remote computer deployed in the cloud. The target terminal may be any terminal among multiple terminals. The network device may be connected to multiple terminals in communication and receive any information sent by multiple terminals.

[0073] like Figure 1 As shown, the abnormal cell determination method may include the following steps.

[0074] Step 110: for each type of network abnormal event occurring at each of the multiple terminals, determine a first weight corresponding to each type of network abnormal event, wherein the first weight of each type of network abnormal event is related to a first quantity ratio of the type of network abnormal event to all network abnormal events occurring at the multiple terminals.

[0075] It can be understood that when the abnormal cell determination method of the present invention is executed by a network device, the network device can execute steps 110-130 and send the determined abnormal cell to the target terminal. When the abnormal cell determination method of the present invention is executed by a target terminal, since the target terminal cannot obtain all network abnormal events occurring in multiple terminals, step 110 can be executed by the network device, and the network device sends the determined first weight corresponding to each type of network abnormal event to the target terminal, thereby the target terminal determines the first weight corresponding to each type of network abnormal event.

[0076] In some embodiments, each of the multiple terminals can obtain its own network abnormality event through modem data embedding, and send its own network abnormality event to the network device. Therefore, the network device can obtain all network abnormality events occurring in the multiple terminals.

[0077] In some embodiments, multiple terminals belong to the same model. Since the network configurations of terminals of different models are different, such as different antenna configurations, abnormal cells are determined by utilizing all network abnormal events occurring in multiple terminals of the same model, so that the abnormal cells determined subsequently better meet the network requirements of the target terminal.

[0078] Network abnormal events may include multiple types, that is, multiple types of network abnormal events. In some embodiments, the type of network abnormal event may be specifically determined according to actual needs, for example, the type of network abnormal event may include NAS registration rejection, high downlink data block error rate, and random access failure.

[0079] In some embodiments, the first weight corresponding to each type of network abnormal event can be obtained in a variety of ways. For example, the first weight of each type of network abnormal event can be preset. For another example, the first weight of each type of network abnormal event can be determined based on the first number ratio of the type of network abnormal event in all network abnormal events occurring on multiple terminals.

[0080] In some embodiments, the first weight of each type of network abnormal event is negatively correlated with the first quantity ratio of the type of network abnormal event. It is understandable that the larger the first quantity ratio of the type of network abnormal event, the smaller the first weight of the type of network abnormal event, and the smaller the first quantity ratio of the type of network abnormal event, the larger the first weight of the type of network abnormal event.

[0081] The first quantity proportion of each type of network abnormal events can reflect the probability of occurrence of each type of network abnormal events. Since the network abnormal events with a high first quantity proportion or a high probability of occurrence have a great influence on the determination result of the abnormal cell, it is impossible to highlight the influence of the network abnormal events with a small first quantity proportion or a low probability of occurrence on the determination result of the abnormal cell. The present disclosure determines the first weight of each type of network abnormal event as being negatively correlated with the first quantity proportion of the type of network abnormal event, so that the first weight of the network abnormal events with a large first quantity proportion or a high probability of occurrence is small, and the first weight of the network abnormal events with a small first quantity proportion or a low probability of occurrence is large, thereby avoiding the situation where the network abnormal events with a large first quantity proportion or a high probability of occurrence play an absolute role in the determination result of the abnormal cell, and enhancing the influence of the network abnormal events with a small first quantity proportion or a low probability of occurrence on the determination result of the abnormal cell.

[0082] In some embodiments, the first weight of each type of network abnormal event can be obtained based on the difference between a preset value and a first quantity ratio of the type of network abnormal event, and the preset value is 1.

[0083] In some embodiments, the first quantity ratio of each type of network abnormal event in all network abnormal events occurring at multiple terminals may be obtained based on the ratio of the number of network abnormal events of that type to the number of all network abnormal events. For example, taking all network abnormal events including A, A, B, C, D and E as an example, the first quantity ratio of type A network abnormal events may be 2 / 6=0.33, and the first quantity ratios of type B network abnormal events, type C network abnormal events, type D network abnormal events and type E network abnormal events are each 1 / 6=0.17.

[0084] In some embodiments, the first weight of each type of network abnormal event can be obtained according to the following formula (1):

[0085] W a =1-P a (1)

[0086] Among them, W a Represents the first weight of each type of network abnormal event, P a Indicates the first number and proportion of each type of network abnormal events.

[0087] The present disclosure obtains a first weight that is negatively correlated with the first number ratio of this type of network abnormal events based on the difference between a preset value and the first number ratio of this type of network abnormal events. The method for determining the first weight is simple and convenient, and can improve the efficiency of subsequent determination of abnormal cells.

[0088] Step 120, for each type of network abnormality event occurring in multiple cells for any target terminal, determine a second weight corresponding to the type of network abnormality event based on the first weight of the type of network abnormality event and the second number ratio of the type of network abnormality event occurring in the target terminal, and the multiple cells are cells detected by the target terminal.

[0089] In some embodiments, the target terminal can obtain network abnormal events that occur in the target terminal through modem data embedding. In some embodiments, after determining the first weight, the target terminal can determine each type of network abnormal event that occurs in the target terminal in multiple cells based on all network abnormal events that occur in the target time period. The target time period can be specifically determined according to actual needs. For example, the target time period can be 3 months or 6 months, etc., and the present disclosure does not impose any restrictions on this.

[0090] The second number ratio of the target terminal to the type of network abnormal events may be obtained based on the ratio between the number of the type of network abnormal events that occur in the target terminal and the number of all network abnormal events that occur in the target terminal in multiple cells. For example, taking all network abnormal events that occur in multiple cells of the target terminal as A, A, A, and B, it can be determined that the second number ratio of type A network abnormal events is 3 / 4=0.75, and the second number ratio of type B network abnormal events is 1 / 4=0.25.

[0091] In some embodiments, for each type of network abnormal event occurring in multiple cells for any target terminal, a second weight corresponding to the type of network abnormal event is determined based on a first weight of the type of network abnormal event and a second number ratio of the type of network abnormal event occurring in the target terminal, including: for each type of network abnormal event occurring in multiple cells for any target terminal, a function value of a preset exponential function is determined based on the second number ratio of the type of network abnormal event occurring in the target terminal and a preset attenuation parameter, and a second weight of the type of network abnormal event is determined based on the first weight and function value of the type of network abnormal event.

[0092] In some embodiments, the preset exponential function may be an exponential function with the natural constant e as the base. The value of the natural constant e is approximately 2.718281828459045. For example, the second weight of each type of network abnormal event may be obtained based on the following formula (2):

[0093] W ai =W a ·exp(-∝·P ai ) (2)

[0094] Among them, W ai Represents the second weight of each type of network abnormal event, W arepresents the first weight of each type of network abnormal event, exp represents the exponential function with the natural constant e as the base, ∝ represents the preset attenuation parameter, and P ai Indicates the second number ratio of each type of network abnormal events. Among them, exp(-∝·P ai ) can represent the function value of an exponential function with the natural constant e as the base.

[0095] In some embodiments, the preset attenuation parameter is a positive parameter used to control the attenuation speed of the second weight. The preset attenuation parameter may be an empirical value or a test value, for example, the preset attenuation parameter may be 0.7 or 0.8.

[0096] The present disclosure determines the function value of a preset exponential function according to the second number proportion of the type of network abnormal events occurring in the target terminal and the preset attenuation parameter for each type of network abnormal event occurring in a plurality of cells for any target terminal, and determines the second weight of the type of network abnormal event according to the first weight and function value of the type of network abnormal event, so that the second weight of the high-probability network abnormal event gradually decreases as the second number proportion decreases, and the second weight of the low-probability network abnormal event gradually increases as the second number proportion increases. The abnormal cell determined by the second weight will better match the abnormal cell characteristics of the target terminal, so that the abnormal cell obtained subsequently is more in line with the communication environment or network requirements of the target terminal, and the accuracy of the abnormal cell is improved.

[0097] Step 130: for any cell, determine whether the cell is an abnormal cell of the target terminal according to the second weight of each type of abnormal network event occurring in the cell by the target terminal.

[0098] In some embodiments, for any cell, whether the cell is an abnormal cell of the target terminal is determined based on the second weight of each type of network abnormal event occurring in the cell by the target terminal, including: for any cell, determining the abnormality score of the cell based on the second weight of each type of network abnormal event occurring in the cell by the target terminal; when the abnormality score is greater than a preset threshold, determining the cell as an abnormal cell of the target terminal.

[0099] In some embodiments, determining the abnormality score of the cell according to the second weight of each type of network abnormality event that occurs in the cell for the target terminal may include: performing a weighted sum operation according to the second weight of each type of network abnormality event that occurs in the cell for the target terminal to determine the abnormality score of the cell. For example, taking multiple cells including cells 1-3 as an example, if the network abnormality events that occur in cell 1 for the target terminal include A, A, A, and B, the second weight of the network abnormality event of type A is a, and the second weight of the network abnormality event of type B is b, then for cell 1, the abnormality score of cell 1 can be determined in the following manner: a+b.

[0100] In some embodiments, the abnormality score of the cell is determined according to the second weight of each type of network abnormal event occurring in the cell by the target terminal, and it may also include: performing a sum operation according to the second weight of each type of network abnormal event and the remainder parameter to determine the abnormality score of the cell. The remainder parameter can be specifically determined according to actual needs and is used to control the range of the abnormality score within a preset range. For example, still taking the above example as an example, the abnormality score of cell 1 can be determined in the following manner: a+b+δ.

[0101] In the process of determining whether a cell is an abnormal cell of the target terminal, the embodiment of the present disclosure utilizes a second weight determined according to a second number proportion of each type of network abnormal event occurring in the target terminal, that is, utilizing the target terminal's own network abnormal event information, so that the abnormal cell finally selected is more in line with the target terminal's own communication environment and network requirements, thereby improving the accuracy of the abnormal cell finally determined, and making the determined abnormal cell more meet the user's personalized requirements.

[0102] In some embodiments, the preset threshold value may be specifically determined according to actual needs, for example, the preset threshold value may be 0.9 or 0.95, etc. Since cells with occasional abnormalities have fewer network abnormal events, the abnormality score of the cell is small. The present disclosure determines cells with abnormality scores greater than the preset threshold value as abnormal cells, which is equivalent to setting the lowest abnormality score threshold, and can prevent cells with occasional abnormalities from being identified as abnormal cells.

[0103] In some embodiments, the abnormal cell determination method may further include: generating an abnormal cell list of the target terminal based on the abnormal cells of the target terminal; when any abnormal cell in the abnormal cell list of the target terminal is detected, if no type of network abnormal event occurs within a preset time period, deleting the abnormal cell from the abnormal cell list.

[0104] In some embodiments, the abnormal cell determination method may further include: detecting network abnormal events occurring in each of a plurality of cells of a target terminal within a preset time period, and updating an event label of the corresponding cell when a network abnormal event is detected; and determining a cell whose event label has not been updated within the preset time period as an abnormal cell in which no type of network abnormal event has occurred within the preset time period.

[0105] The present disclosure can avoid that a cell that has returned to normal is still identified as an abnormal cell by deleting the cell that has not experienced any type of network abnormal event within a preset time period.

[0106] In some embodiments, generating an abnormal cell list of the target terminal according to the abnormal cells of the target terminal may include: sorting the abnormal cells according to the abnormal scores of the abnormal cells to obtain the abnormal cell list.

[0107] In some embodiments, the abnormal cells may be sorted in descending order or ascending order according to their abnormal scores, that is, the abnormal scores are sorted from high to low, or from low to high. By sorting the abnormal cells to obtain an abnormal cell list, it is convenient to manage the abnormal cells.

[0108] In some embodiments, the abnormal cell determination method may further include: storing the data of the abnormal cell, or the abnormal cell list, in a database of the target terminal. In some embodiments, the data of the abnormal cell, or the abnormal cell list, may be stored in the database of the target terminal by calling the SharedPreferences interface of the target terminal. By storing the data of the abnormal cell or the abnormal cell list in the database of the target terminal, it is possible to achieve shutdown without loss and persistence of abnormal cell statistical data.

[0109] In some embodiments, the abnormal cell determination method may further include: performing the aforementioned steps 110 to 130 at preset time intervals. The first weight corresponding to each type of network abnormal event may be statistical data within a period of time. The present disclosure can update the abnormal cells by performing the aforementioned steps 110 to 130 at preset time intervals.

[0110] In some embodiments, when the abnormal cell determination method is executed by the target terminal, the abnormal cell determination method may further include: receiving, through an adjustment interface in the target terminal, a first weight corresponding to each type of network abnormal event sent by a network device at preset time intervals.

[0111] When the abnormal cell determination method is executed by the target terminal, the network device determines the first weight corresponding to each type of network abnormal event, and the first weight may be statistical data within a period of time. Therefore, the first weight determined by the network device through the network abnormal event data in different time periods is different. The present disclosure adjusts the interface to receive the first weight corresponding to each type of network abnormal event sent by the network device at preset time intervals, and can receive the first weight determined by the network device according to each type of network abnormal event occurring in multiple terminals within the preset time interval, and can adjust the first weight every preset time interval, thereby ensuring the accuracy and real-time performance of the first weight.

[0112] In some embodiments, when the abnormal cell determination method is executed by a network device, the abnormal cell determination method may further include: obtaining each type of network abnormal event occurring at each of the multiple terminals at a preset time interval, and determining a first weight corresponding to each type of network abnormal event according to each type of network abnormal event occurring at each of the multiple terminals. By determining the first weight at a preset time interval by the network device, the first weight can be adjusted at a preset time interval, thereby ensuring the accuracy and real-time performance of the first weight.

[0113] Figure 2 1 is a flow chart of a data interruption processing method according to an exemplary embodiment. It is worth noting that the present disclosure does not impose any restrictions on the execution subject of the data interruption processing method. For example, the data interruption processing method can be executed by a network device or a target terminal. For specific details about the network device and the target terminal, please refer to the above Figure 1 And the related description will not be repeated here. Figure 2 As shown, the data interruption method may include the following steps:

[0114] Step 210: When it is detected that data flow interruption occurs in the target terminal, the target cell currently accessed by the target terminal is obtained.

[0115] In some embodiments, data interruption may refer to a sudden interruption of Internet access data of the target terminal, and no data flow. For example, a web page cannot be loaded when browsing, and network delay increases. In some embodiments, a data interruption detection algorithm in the target terminal may be used to detect whether data interruption occurs in the target terminal.

[0116] Step 220, matching is performed according to the target cell and the abnormal cell to obtain a matching result, wherein the abnormal cell is obtained according to the abnormal cell determination method.

[0117] The abnormal cell can be any abnormal cell determination method described in any of the specific embodiments of the present disclosure. For specific details of the abnormal cell determination method, please refer to Figure 1 And the related description will not be repeated here.

[0118] The abnormal cell determination method disclosed in the present invention, in the process of determining whether a cell is an abnormal cell of a target terminal, utilizes a second weight determined according to a second quantity proportion of each type of network abnormal event occurring in the target terminal, that is, utilizes the network abnormal event information of the target terminal itself, so that the abnormal cell finally selected is more in line with the communication environment and network requirements of the target terminal itself, improves the accuracy of the abnormal cell finally determined, and makes the determined abnormal cell more meet the personalized requirements of the user.

[0119] In some embodiments, a match result may be obtained by matching the target cell identifier and the abnormal cell identifier, and the identifier may include an Absolute Radio Frequency Channel Number (ARFCN) and a Physical Cell Identifier (PCI).

[0120] Step 230: If the matching result shows that the target cell is an abnormal cell, the target cell is disabled and a normal cell is detected.

[0121] Step 240: Control the target terminal to access a normal cell.

[0122] It can be understood that when the data interruption processing method disclosed in the present invention is executed by a network device, the network device can execute steps 210-230, and controlling the target terminal to access the normal cell can include: sending the determined normal cell to the target terminal so that the target terminal accesses the normal cell. When the data interruption processing method disclosed in the present invention is executed by a target terminal, the target terminal can execute steps 210-240.

[0123] In some embodiments, a normal cell may refer to a cell with a normal network. The present disclosure matches an abnormal cell according to the currently connected target cell when a data interruption occurs to the target terminal. If the match is successful, it means that the target cell is a cell where the user frequently experiences abnormalities, and then disables the second target cell, so that the target terminal directly attempts to reside on other networks or normal cells and attempts data reconnection, thereby reducing the waiting time on high-frequency abnormal cells and accelerating data service recovery.

[0124] Figure 3 FIG. 1 is a block diagram of a device for determining an abnormal cell according to an exemplary embodiment. Figure 3 , the abnormal cell determination device 300 includes:

[0125] The first determination module 310 is configured to determine, for each type of network abnormal event occurring in each of the multiple terminals, a first weight corresponding to each type of network abnormal event, wherein the first weight of each type of network abnormal event is related to a first quantity ratio of the type of network abnormal event in all network abnormal events occurring in the multiple terminals;

[0126] The second determination module 320 is configured to determine, for each type of network abnormal event occurring in a plurality of cells for any target terminal, a second weight corresponding to the type of network abnormal event according to the first weight of the type of network abnormal event and a second number ratio of the type of network abnormal event occurring in the target terminal, wherein the plurality of cells are cells detected by the target terminal;

[0127] The third determination module 330 is configured to determine, for any cell, whether the cell is an abnormal cell of the target terminal according to the second weight of each type of network abnormal event occurring in the cell by the target terminal.

[0128] In some embodiments, the first weight of each type of network abnormal event is negatively correlated with the first quantity ratio of the type of network abnormal event.

[0129] In some embodiments, the first weight of each type of network abnormal event is obtained based on the difference between a preset value and the first quantity proportion of the type of network abnormal event, and the preset value is 1.

[0130] In some embodiments, the second determining module 320 is further configured to:

[0131] For each type of network abnormal event occurring in multiple cells for any target terminal, the function value of a preset exponential function is determined according to the second number proportion of this type of network abnormal event occurring in the target terminal and a preset attenuation parameter, and the second weight of this type of network abnormal event is determined according to the first weight of this type of network abnormal event and the function value.

[0132] In some embodiments, the third determination module 330 is further configured to:

[0133] For any cell, determining an anomaly score of the cell according to the second weight of each type of network anomaly event occurring in the cell by the target terminal;

[0134] When the abnormality score is greater than a preset threshold, the cell is determined as the abnormal cell of the target terminal.

[0135] In some embodiments, the abnormal cell determination device further includes:

[0136] A generating module, configured to generate an abnormal cell list of the target terminal according to the abnormal cells of the target terminal;

[0137] The deleting module is configured to, when any abnormal cell in the abnormal cell list of the target terminal is detected and no network abnormal event of any type occurs within a preset time period, delete the abnormal cell from the abnormal cell list.

[0138] Regarding the abnormal cell determination device 300 in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the abnormal cell determination method, and will not be elaborated here.

[0139] Figure 4 FIG. 1 is a block diagram of a data interruption processing device according to an exemplary embodiment. Figure 4 As shown, the data interruption processing device 400 includes:

[0140] The acquisition module 410 is configured to acquire a target cell currently accessed by the target terminal when detecting that data flow interruption occurs in the target terminal;

[0141] A matching module 420 is configured to match the target cell with an abnormal cell to obtain a matching result, wherein the abnormal cell is obtained according to an abnormal cell determination method;

[0142] A disabling module 430 is configured to disable the target cell and detect a normal cell if the matching result reflects that the target cell is the abnormal cell;

[0143] The access module 440 is configured to control the target terminal to access the normal cell.

[0144] Regarding the data interruption processing device 400 in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the data interruption processing method, and will not be elaborated here.

[0145] The present disclosure also provides a computer-readable storage medium having computer program instructions stored thereon. When the program instructions are executed by a processor, the steps of the abnormal cell determination method and the data interruption processing method provided by the present disclosure are implemented.

[0146] Figure 5 1 is a block diagram of an abnormal cell determination device or a data interruption processing device according to an exemplary embodiment. For example, the device 500 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0147] Reference Figure 5 , the device 500 may include one or more of the following components: a processing component 502 , a memory 504 , a power component 506 , a multimedia component 508 , an audio component 510 , an input / output interface 512 , a sensor component 514 , and a communication component 516 .

[0148] The processing component 502 generally controls the overall operation of the device 500, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 502 may include one or more processors 520 to execute instructions to complete all or part of the steps of the above-mentioned abnormal cell determination method, or complete all or part of the steps of the above-mentioned data interruption processing method. In addition, the processing component 502 may include one or more modules to facilitate the interaction between the processing component 502 and other components. For example, the processing component 502 may include a multimedia module to facilitate the interaction between the multimedia component 508 and the processing component 502.

[0149] The memory 504 is configured to store various types of data to support operations on the device 500. Examples of such data include instructions for any application or method operating on the device 500, contact data, phone book data, messages, pictures, videos, etc. The memory 504 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0150] The power supply component 506 provides power to the various components of the device 500. The power supply component 506 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device 500.

[0151] The multimedia component 508 includes a screen that provides an output interface between the device 500 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 508 includes a front camera and / or a rear camera. When the device 500 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0152] The audio component 510 is configured to output and / or input audio signals. For example, the audio component 510 includes a microphone (MIC), and when the device 500 is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 504 or sent via the communication component 516. In some embodiments, the audio component 510 also includes a speaker for outputting audio signals.

[0153] The input / output interface 512 provides an interface between the processing component 502 and the peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0154] The sensor assembly 514 includes one or more sensors for providing various aspects of status assessment for the device 500. For example, the sensor assembly 514 can detect the open / closed state of the device 500, the relative positioning of components, such as the display and keypad of the device 500, the sensor assembly 514 can also detect the position change of the device 500 or a component of the device 500, the presence or absence of user contact with the device 500, the orientation or acceleration / deceleration of the device 500, and the temperature change of the device 500. The sensor assembly 514 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 514 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 514 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0155] The communication component 516 is configured to facilitate wired or wireless communication between the device 500 and other devices. The device 500 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 516 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 516 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0156] In an exemplary embodiment, the apparatus 500 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned abnormal cell determination method or data interruption processing method.

[0157] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 504 including instructions, and the instructions can be executed by the processor 520 of the device 500 to complete the above-mentioned abnormal cell determination method or data interruption processing method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0158] In addition to being an independent electronic device, the abnormal cell determination device or data interruption processing device can also be a part of an independent electronic device. For example, in one embodiment, the device can be an integrated circuit (IC) or a chip, wherein the integrated circuit can be an IC or a collection of multiple ICs; the chip can include but is not limited to the following types: GPU (Graphics Processing Unit), CPU (Central Processing Unit), FPGA (Field Programmable Gate Array), DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), SOC (System on Chip, SoC, system on chip or system-level chip), etc. The above-mentioned integrated circuit or chip can be used to execute executable instructions (or codes) to implement the above-mentioned abnormal cell determination method or data interruption processing method. The executable instructions can be stored in the integrated circuit or chip, or can be obtained from other devices or equipment, such as the integrated circuit or chip includes a processor, a memory, and an interface for communicating with other devices. The executable instruction can be stored in the memory, and when the executable instruction is executed by the processor, the above-mentioned abnormal cell determination method or data interruption processing method is implemented; alternatively, the integrated circuit or chip can receive the executable instruction through the interface and transmit it to the processor for execution, so as to implement the above-mentioned abnormal cell determination method or data interruption processing method.

[0159] In another exemplary embodiment, a computer program product is also provided, which includes a computer program that can be executed by a programmable device, and the computer program has a code portion for executing the above-mentioned abnormal cell determination method or data interruption processing method when executed by the programmable device.

[0160] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the present disclosure. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered as exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

[0161] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for determining an abnormal cell, characterized in that: The abnormal cell determination method comprises: For each type of network abnormal event occurring at each of the multiple terminals, determine a first weight corresponding to each type of network abnormal event, wherein the first weight of each type of network abnormal event is related to a first quantity ratio of the type of network abnormal event to all network abnormal events occurring at the multiple terminals; For each type of network abnormal event occurring in a plurality of cells for any target terminal, determining a second weight corresponding to the type of network abnormal event according to the first weight of the type of network abnormal event and a second number ratio of the type of network abnormal event occurring in the target terminal, wherein the plurality of cells are cells detected by the target terminal; For any cell, whether the cell is an abnormal cell of the target terminal is determined according to the second weight of each type of network abnormal event occurring in the cell by the target terminal.

2. The abnormal cell determination method according to claim 1, characterized in that: The first weight of each type of network abnormal event is negatively correlated with the first quantity ratio of the type of network abnormal event.

3. The abnormal cell determination method according to claim 1, characterized in that: The first weight of each type of network abnormal event is obtained based on the difference between a preset value and the first quantity proportion of the type of network abnormal event, and the preset value is 1.

4. The abnormal cell determination method according to claim 1, characterized in that: The determining, for each type of network abnormal event occurring in a plurality of cells for any target terminal, a second weight corresponding to the type of network abnormal event according to the first weight of the type of network abnormal event and a second number ratio of the type of network abnormal event occurring in the target terminal, includes: For each type of network abnormal event occurring in multiple cells for any target terminal, the function value of a preset exponential function is determined according to the second number proportion of this type of network abnormal event occurring in the target terminal and a preset attenuation parameter, and the second weight of this type of network abnormal event is determined according to the first weight of this type of network abnormal event and the function value.

5. The abnormal cell determination method according to claim 1, characterized in that: The determining, for any cell, whether the cell is an abnormal cell of the target terminal according to the second weight of each type of network abnormal event occurring in the cell by the target terminal includes: For any cell, determining an anomaly score of the cell according to the second weight of each type of network anomaly event occurring in the cell by the target terminal; When the abnormality score is greater than a preset threshold, the cell is determined as the abnormal cell of the target terminal.

6. The abnormal cell determination method according to any one of claims 1 to 5, characterized in that: The abnormal cell determination method further includes: generating an abnormal cell list of the target terminal according to the abnormal cell of the target terminal; When any abnormal cell in the abnormal cell list of the target terminal is detected and no network abnormal event of any type occurs within a preset time period, the abnormal cell is deleted from the abnormal cell list.

7. A data interruption processing method, characterized in that: The data interruption processing method comprises: When a data interruption occurs at a target terminal, obtaining a target cell currently accessed by the target terminal; Matching the target cell and the abnormal cell to obtain a matching result, wherein the abnormal cell is obtained by the abnormal cell determination method according to any one of claims 1 to 6; If the matching result reflects that the target cell is the abnormal cell, disabling the target cell and detecting a normal cell; Control the target terminal to access the normal cell.

8. An abnormal cell determination device, characterized in that: The abnormal cell determining device comprises: A first determination module is configured to determine, for each type of network abnormal event occurring at each of the multiple terminals, a first weight corresponding to each type of network abnormal event, wherein the first weight of each type of network abnormal event is related to a first quantity ratio of the type of network abnormal event to all network abnormal events occurring at the multiple terminals; A second determination module is configured to determine, for each type of network abnormal event occurring in a plurality of cells for any target terminal, a second weight corresponding to the type of network abnormal event according to the first weight of the type of network abnormal event and a second number ratio of the type of network abnormal event occurring in the target terminal, wherein the plurality of cells are cells detected by the target terminal; The third determination module is configured to determine, for any cell, whether the cell is an abnormal cell of the target terminal according to the second weight of each type of network abnormal event occurring in the cell by the target terminal.

9. A data interruption processing device, characterized in that: The data interruption processing device comprises: An acquisition module is configured to acquire a target cell currently accessed by the target terminal when detecting that data flow interruption occurs in the target terminal; a matching module, configured to match the target cell and the abnormal cell to obtain a matching result, wherein the abnormal cell is obtained by the abnormal cell determination method according to any one of claims 1 to 6; a disabling module configured to disable the target cell and detect a normal cell if the matching result reflects that the target cell is the abnormal cell; The access module is configured to control the target terminal to access the normal cell.

10. An abnormal cell determination device, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to: For each type of network abnormal event occurring at each of the multiple terminals, determine a first weight corresponding to each type of network abnormal event, wherein the first weight of each type of network abnormal event is related to a first quantity ratio of the type of network abnormal event to all network abnormal events occurring at the multiple terminals; For each type of network abnormal event occurring in a plurality of cells for any target terminal, determining a second weight corresponding to the type of network abnormal event according to the first weight of the type of network abnormal event and a second number ratio of the type of network abnormal event occurring in the target terminal, wherein the plurality of cells are cells detected by the target terminal; For any cell, whether the cell is an abnormal cell of the target terminal is determined according to the second weight of each type of network abnormal event occurring in the cell by the target terminal.

11. A data interruption processing device, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to: When a data interruption occurs at a target terminal, obtaining a target cell currently accessed by the target terminal; Matching the target cell and the abnormal cell to obtain a matching result, wherein the abnormal cell is obtained by the abnormal cell determination method according to any one of claims 1 to 6; If the matching result reflects that the target cell is the abnormal cell, disabling the target cell and detecting a normal cell; Control the target terminal to access the normal cell.

12. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the program instructions are executed by a processor, the steps of the method described in any one of claims 1 to 7 are implemented.

13. A chip, characterized in that: The method comprises a processor and an interface; the processor is used to read instructions to execute the method according to any one of claims 1 to 7.

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