Network prediction method and terminal device, server and communication system thereof

Abstract

The present application provides a network prediction method and its terminal device, server and communication system, the method comprising: the server matches the possible cell switching relationship of the terminal device on the subsequent moving route from the cell association information library according to the information of the N cells continuously accessed by the terminal device, and then calculates the network prediction result in combination with the stuck cell contained in the cell switching relationship, and sends the network prediction result to the terminal device. The network prediction result includes but is not limited to: the estimated time for the terminal device to arrive at the stuck cell, the residence time in the stuck cell, the probability corresponding to the estimated time to arrive at the stuck cell, and the probability corresponding to the residence time in the stuck cell, etc. In this way, the user can be prompted to take relevant Internet access measures in advance, or it can be used to control the terminal device to automatically take relevant Internet access measures to avoid Internet access problems such as stuck Internet access to the user during the process of the terminal device accessing the stuck cell.

Description

Technical Field

[0001] The present application relates to the field of terminals, and in particular to a network prediction method and its terminal equipment, server and communication system. Background Art

[0002] In the existing network configuration, due to poor construction of some cells or improper data configuration, problems may arise in the data services and call services carried by these cells, which in turn may cause problems such as Internet access lag, call failures, and poor call quality for terminal devices accessing these cells.

[0003] How to solve the above problems is an urgent problem to be solved. Summary of the invention

[0004] The present application provides a network prediction method and its terminal device, server and communication system, the method comprising: the server matches the possible cell switching relationship of the terminal device on the subsequent moving route from the cell association information library according to the information of N cells continuously accessed by the terminal device, and then calculates the network prediction result in combination with the stuck cells included in the cell switching relationship, and sends the network prediction result to the terminal device. In this way, the user can be prompted to take relevant Internet access measures in advance, or it can be used to control the terminal device to automatically take relevant Internet access measures, so as to avoid Internet access stuck problems for the user when the terminal device accesses the stuck cell.

[0005] In a first aspect, the present application provides a network prediction method, which is applied to a server, and the method includes: the server receives first cell information sent by a first device, and the first cell information includes information of multiple cells continuously accessed by the first device; the server generates a network prediction result based on the first cell information, and the network prediction result indicates that the first device is about to access a stuck cell; the server sends the network prediction result to the first device; the network prediction result is used to instruct the first device to output prompt information and / or adjust an Internet access strategy.

[0006] After implementing the method provided in the first aspect, the server can perform network prediction for the first device in real time based on the cell information reported by the first device, so as to prompt the user or control the first device to pre-adjust Internet access measures according to the network prediction results, thereby ensuring that the Internet access experience of the user of the first device is not affected by the network environment.

[0007] In combination with the method provided in the first aspect, the network prediction result is used to instruct the first device to adjust the Internet access strategy, specifically including: instructing the first device to cache network content, and / or reducing the clarity of viewing network content.

[0008] In this way, the first device can automatically adjust the Internet access strategy according to the network prediction results. When the first device enters a stuck cell with a poor network environment, it can still ensure that the user can watch network content normally without being aware of the network environment, thereby improving the user's Internet experience.

[0009] In combination with the method provided in the first aspect, the network prediction result includes information of the first stuck cell, and the information of the first stuck cell includes any one or more of the following: the first time required for the first device to access the first stuck cell, the first probability of the first device accessing the first stuck cell within the first time, the second time of staying in the first stuck cell, and the second probability of staying in the first stuck cell for the second time.

[0010] In this way, accurate network prediction results can be obtained, so that users can decide whether to adjust relevant Internet access strategies and how to adjust strategies based on network results and the probability of occurrence of the results.

[0011] In combination with the method provided in the first aspect, the first duration and the first probability are determined by the server based on the probability distribution of the residence time of multiple devices in the corresponding cell; the second duration and the second probability are determined by the server based on the probability distribution of the residence time of multiple devices in the first stuck cell.

[0012] In this way, the probability distribution of the residence time in each cell can be accurately counted based on the collected big data, and then more accurate network prediction results can be obtained based on the probability distribution, ensuring the accuracy of the network prediction results and improving the user experience.

[0013] In combination with the method provided in the first aspect, the first stuck cell includes: a cell belonging to the stuck cell among the multiple cells that the terminal device is about to access in sequence; the multiple cells that the terminal device is about to access in sequence include: a cell in a cell association information library that matches the first cell information; wherein the cell association information library contains multiple cell switching relationships, and each cell switching relationship includes: the order in which multiple cells are switched in sequence.

[0014] In this way, the corresponding route can be matched first according to the cells continuously accessed by the first device, and then the cell switching relationship on the route can be determined, and then the stuck cell of the cell switching relationship can be obtained.

[0015] In combination with the method provided in the first aspect, the relevant information of the first stuck cell is stored in a stuck cell information database. The stuck cell information database is used by the server to obtain multiple cells that the first device is about to access in sequence from the cell association information database according to the first cell information, and then determine whether the multiple cells include a cell belonging to the stuck cell information database. If so, it is the first stuck cell.

[0016] In combination with the method provided in the first aspect, the first stuck cell includes: a cell that is a stuck cell at a current time or a current time period among the multiple cells that the terminal device is about to access in sequence;

[0017] In this way, the network results can be predicted based on the tidal effect of the stuck cell, avoiding the prediction of the cell whose stuck time is different from the time when the first device passes through the cell as the stuck cell, that is, the stuck cell during the non-stuck time will not be predicted as the stuck cell, thereby avoiding the problem of misjudgment of network prediction. The tidal effect includes that the terminal devices on the subway, high-speed rail, car and other driving routes during peak hours are more than those during non-peak hours, so the business stuck phenomenon will occur.

[0018] In combination with the method provided in the first aspect, before the server generates a network prediction result based on the first cell information, the method also includes: the server receives second cell information sent by the second device, and the second cell information is information of multiple cells continuously accessed by the second device; the server fills the second cell information into the skeleton data to update the cell association information library; the skeleton data includes the switching relationship of the cells laid out on multiple routes.

[0019] In this way, a more comprehensive cell-related information database can be generated by collecting big data, thereby obtaining accurate network prediction results.

[0020] In combination with the method provided in the first aspect, the information of the multiple cells continuously accessed by the second device specifically includes: an identifier of each cell, an access time and a residence time of each cell.

[0021] In combination with the method provided in the first aspect, before the server generates a network prediction result based on the first cell information, the method also includes: the second device sends third cell information to the server, and the third cell information indicates the service quality of the cell accessed by the second device; the server determines the stuck cell based on the service quality.

[0022] In addition, the above-mentioned third cell information can also include the time period corresponding to the cell accessed by the second device, such as access time, residence time, etc., which is used by the server to judge whether the cell is stuck and whether the stuck cell has a tidal effect based on the service quality of the cell in the corresponding time period.

[0023] In this way, a more comprehensive information database of stuck cells can be generated by collecting big data, and accurate network prediction results can be obtained.

[0024] In a second aspect, the present application provides a network prediction method, which is applied to a first device, and the method includes: the first device sends first cell information to a server, and the first cell information includes information of multiple cells continuously accessed by the first device; the first cell information is used by the server to generate a network prediction result, and the network prediction result indicates that the first device is about to access a stuck cell; the first device receives the network prediction result sent by the server; the first device outputs prompt information according to the network prediction result, and / or adjusts the Internet access strategy.

[0025] After implementing the method provided in the second aspect, the first device can report cell information to the server, which is used by the server to perform network prediction on the first device in real time, so as to prompt the user or control the first device to pre-adjust Internet access measures according to the network prediction results, thereby ensuring that the Internet access experience of the user of the first device is not affected by the network environment.

[0026] In combination with the method provided in the second aspect, the first device adjusts the Internet access strategy according to the network prediction result specifically including: the first device caches network content, and / or reduces the clarity of viewing network content.

[0027] In this way, the first device can automatically adjust the Internet access strategy according to the network prediction results. When the first device enters a stuck cell with a poor network environment, it can still ensure that the user can watch network content normally without being aware of the network environment, thereby improving the user's Internet experience.

[0028] In combination with the method provided in the second aspect, the network prediction result includes information of the first stuck cell, and the information of the first stuck cell includes any one or more of the following: the first time required for the first device to access the first stuck cell, the first probability of the first device accessing the first stuck cell within the first time, the second time of staying in the first stuck cell, and the second probability of staying in the first stuck cell for the second time.

[0029] In this way, accurate network prediction results can be obtained, so that users can decide whether to adjust relevant Internet access strategies and how to adjust strategies based on network results and the probability of occurrence of the results.

[0030] In combination with the method provided in the second aspect, the first duration and the first probability are determined by the server based on the probability distribution of the residence time of multiple devices in the corresponding cell; the second duration and the second probability are determined by the server based on the probability distribution of the residence time of multiple devices in the first stuck cell.

[0031] In this way, the probability distribution of the residence time in each cell can be accurately counted based on the collected big data, and then more accurate network prediction results can be obtained based on the probability distribution, ensuring the accuracy of the network prediction results and improving the user experience.

[0032] In combination with the method provided in the second aspect, the first stuck cell includes: a cell belonging to the stuck cell among the multiple cells that the terminal device is about to access in sequence; the multiple cells that the terminal device is about to access in sequence include: a cell in a cell association information library that matches the first cell information; wherein the cell association information library contains multiple cell switching relationships, and each cell switching relationship includes: the order in which multiple cells are switched in sequence.

[0033] In combination with the method provided in the second aspect, the relevant information of the first stuck cell is stored in a stuck cell information database. The stuck cell information database is used by the server to obtain multiple cells that the first device is about to access in sequence from the cell association information database according to the first cell information, and then determine whether the multiple cells include a cell belonging to the stuck cell information database. If so, it is the first stuck cell.

[0034] In this way, the corresponding route can be matched first according to the cells continuously accessed by the first device, and then the cell switching relationship on the route can be determined, and then the stuck cell of the cell switching relationship can be obtained.

[0035] In combination with the method provided in the second aspect, the first stuck cell includes: a cell that is a stuck cell at the current time and time period among the multiple cells that the terminal device is about to access in sequence.

[0036] In this way, the network results can be predicted based on the tidal effect of the stuck cell, avoiding the prediction of the cell whose stuck time is different from the time when the first device passes through the cell as the stuck cell, that is, the stuck cell during the non-stuck time will not be predicted as the stuck cell, thereby avoiding the problem of misjudgment of network prediction. The tidal effect includes that the terminal devices on the subway, high-speed rail, car and other driving routes during peak hours are more than those during non-peak hours, so the business stuck phenomenon will occur.

[0037] In combination with the method provided in the second aspect, before the first device sends the first cell information to the server, the method also includes: the first device recognizes that it is in a scene of subway, high-speed rail or car driving.

[0038] In this way, since in these scenarios, the first device will frequently switch cells due to rapid movement, it is very likely to switch to a stuck cell, causing the user to experience stuck Internet access, etc., so this type of scenario is taken as the focus of network prediction.

[0039] In a third aspect, the present application provides a network prediction method, which is applied to a communication system including a first device and a server, and the method includes: the first device sends first cell information to the server, and the first cell information includes information of multiple cells continuously accessed by the first device; the server generates a network prediction result based on the first cell information, and the network prediction result indicates that the first device is about to access a stuck cell; the server sends the network prediction result to the first device; the first device outputs prompt information according to the network prediction result, and / or adjusts the Internet access strategy.

[0040] After implementing the method provided in the third aspect, the server can perform network prediction for the first device in real time based on the cell information reported by the first device, so as to prompt the user or control the first device to pre-adjust Internet access measures according to the network prediction results, thereby ensuring that the Internet access experience of the user of the first device is not affected by the network environment.

[0041] In combination with the method provided in the third aspect, the first device adjusts the Internet access strategy according to the network prediction result, specifically including caching network content, and / or reducing the clarity of viewing network content.

[0042] In this way, the first device can automatically adjust the Internet access strategy according to the network prediction results. When the first device enters a stuck cell with a poor network environment, it can still ensure that the user can watch network content normally without being aware of the network environment, thereby improving the user's Internet experience.

[0043] In combination with the method provided in the third aspect, the network prediction result includes information of the first stuck cell, and the information of the first stuck cell includes: the first time required for the first device to access the first stuck cell, the first probability of the first device accessing the first stuck cell within the first time, the second time of staying in the first stuck cell, and the second probability of staying in the first stuck cell for the second time.

[0044] In this way, accurate network prediction results can be obtained, so that users can decide whether to adjust relevant Internet access strategies and how to adjust strategies based on network results and the probability of occurrence of the results.

[0045] In combination with the method provided in the third aspect, the first duration and the first probability are determined by the server based on the probability distribution of the residence time of multiple devices in the corresponding cell; the second duration and the second probability are determined by the server based on the probability distribution of the residence time of multiple devices in the first stuck cell.

[0046] In this way, the probability distribution of the residence time in each cell can be accurately counted based on the collected big data, and then more accurate network prediction results can be obtained based on the probability distribution, ensuring the accuracy of the network prediction results and improving the user experience.

[0047] In combination with the method provided in the third aspect, the first stuck cell includes: a cell belonging to the stuck cell among the multiple cells that the terminal device is about to access in sequence; the multiple cells that the terminal device is about to access in sequence include: a cell in a cell association information library that matches the first cell information; wherein the cell association information library contains multiple cell switching relationships, and each cell switching relationship includes: the order in which multiple cells are switched in sequence.

[0048] In combination with the method provided in the third aspect, the relevant information of the first stuck cell is stored in a stuck cell information database. The stuck cell information database is used by the server to obtain multiple cells that the first device is about to access in sequence from the cell association information database according to the first cell information, and then determine whether the multiple cells include a cell belonging to the stuck cell information database. If so, it is the first stuck cell.

[0049] In this way, the corresponding route can be matched first according to the cells continuously accessed by the first device, and then the cell switching relationship on the route can be determined, and then the stuck cell of the cell switching relationship can be obtained.

[0050] In combination with the method provided in the third aspect, the first stuck cell includes: a cell that is a stuck cell at the current moment among the multiple cells that the terminal device is about to access in sequence;

[0051] In this way, the network results can be predicted based on the tidal effect of the stuck cell, avoiding the prediction of the cell whose stuck time is different from the time when the first device passes through the cell as the stuck cell, that is, the stuck cell during the non-stuck time will not be predicted as the stuck cell, thereby avoiding the problem of misjudgment of network prediction. The tidal effect includes that the terminal devices on the subway, high-speed rail, car and other driving routes during peak hours are more than those during non-peak hours, so the business stuck phenomenon will occur.

[0052] In combination with the method provided in the third aspect, the communication system also includes one or more second devices. Before the server generates a network prediction result based on the first cell information, the method also includes: the second device sends second cell information to the server, and the second cell information is information of multiple cells continuously accessed by the second device; the server fills the second cell information into the skeleton data to update the cell association information library; the skeleton data includes the switching relationship of the cells laid out on multiple routes.

[0053] In this way, a more comprehensive cell-related information database can be generated by collecting big data, thereby obtaining accurate network prediction results.

[0054] In combination with the method provided in the third aspect, the information of the multiple cells continuously accessed by the second device specifically includes: an identifier of each cell, an access time and a residence time of each cell.

[0055] In combination with the method provided in the third aspect, before the server generates a network prediction result based on the first cell information, the method also includes: the second device sends third cell information to the server, and the third cell information indicates the service quality of the cell accessed by the second device; the server determines the stuck cell based on the service quality.

[0056] In addition, the above-mentioned third cell information can also include the time period corresponding to the cell accessed by the second device, such as access time, residence time, etc., which is used by the server to judge whether the cell is stuck and whether the stuck cell has a tidal effect based on the service quality of the cell in the corresponding time period.

[0057] In this way, a more comprehensive information database of stuck cells can be generated by collecting big data, and accurate network prediction results can be obtained.

[0058] In combination with the method provided in the third aspect, before the first device sends the first cell information to the server, the method also includes: the first device recognizes that it is in a scene of subway, high-speed rail or car driving.

[0059] In this way, since in these scenarios, the first device will frequently switch cells due to rapid movement, it is very likely to switch to a stuck cell, causing the user to experience stuck Internet access, etc., so this type of scenario is taken as the focus of network prediction.

[0060] In a fourth aspect, the present application provides a server, comprising a memory and one or more processors; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code comprises computer instructions, and the one or more processors call the computer instructions to cause the server to execute a method as described in any one of the first aspects.

[0061] In a fifth aspect, the present application provides a terminal device, comprising a memory and one or more processors; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code comprises computer instructions, and the one or more processors call the computer instructions so that the terminal device executes a method as described in any one of the second aspects.

[0062] In a sixth aspect, the present application provides a chip, which is applied to an electronic device, and the chip includes one or more processors, and the processor is used to call computer instructions so that the electronic device executes the method described in any one of the first aspect or the second aspect.

[0063] In a seventh aspect, the present application provides a computer-readable storage medium, which includes instructions. When the instructions are executed on an electronic device, the electronic device executes the method described in any one of the first aspect or the second aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application;

[0065] Figure 2A A hardware architecture diagram of a terminal device 100 provided in an embodiment of the present application;

[0066] Figure 2B A software architecture diagram of a terminal device 100 provided in an embodiment of the present application;

[0067] Figure 3A A hardware architecture diagram of a server 200 provided in an embodiment of the present application;

[0068] Figure 3B A software architecture diagram of a server 200 provided in an embodiment of the present application;

[0069] Figure 4 A flow chart of a network prediction method provided in an embodiment of the present application;

[0070] Figure 5 A schematic diagram of the principle of establishing a cell association information database provided in an embodiment of the present application;

[0071] Figure 6 A schematic diagram of a cell association information database storage model provided in an embodiment of the present application;

[0072] Figure 7 A network prediction architecture diagram provided for an embodiment of the present application. DETAILED DESCRIPTION

[0073] The technical solutions in the embodiments of the present application will be described clearly and in detail below in conjunction with the accompanying drawings. In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B; "and / or" in the text is only a description of the association relationship of the associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0074] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0075] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0076] The term "user interface (UI)" in the following embodiments of the present application refers to a medium interface for interaction and information exchange between an application or operating system and a user, which realizes the conversion between the internal form of information and the form acceptable to the user. The user interface is a source code written in a specific computer language such as Java and extensible markup language (XML). The interface source code is parsed and rendered on the terminal device, and finally presented as content that the user can recognize. The commonly used form of user interface is the graphical user interface (GUI), which refers to a user interface related to computer operation that is displayed in a graphical manner. It can be a visual interface element such as text, icons, buttons, menus, tabs, text boxes, dialog boxes, status bars, navigation bars, widgets, etc. displayed on the display screen of a terminal device.

[0077] refer to Figure 1 , Figure 1 A schematic diagram of an application scenario provided by the present application is exemplified.

[0078] like Figure 1 As shown, the network prediction method provided by the present application is applicable to the application scenario of a communication system deployed on a route including but not limited to: a subway, a high-speed railway, and a car. The communication system includes one or more terminal devices, one or more servers, and one or more network-side devices. Figure 1 The terminal device 100, the server 200, the network side device 301 and the network side device 302 are shown as examples.

[0079] The communication system provided in the present application can be any one of the following: global system for mobile communications (GSM) system, code division multiple access (CDMA) system, wideband code division multiple access (WCDMA) system, general packet radio service (GPRS), long term evolution (LTE) system, LTE frequency division duplex (FDD) system, LTE time division duplex (TDD), universal mobile telecommunication system (UMTS), world wide interoperability for microwave access (WiMAX) communication system, fifth generation (5G) system or new radio (NR), etc.

[0080] The terminal device 100 provided in the present application can be a mobile phone, a tablet computer, a handheld computer, an ultra-mobile personal computer (UMPC), a netbook, a cellular phone, a personal digital assistant (PDA), a wearable device, a vehicle-mounted device, etc., and the embodiments of the present application are not limited to this.

[0081] The server 200 provided in the present application may be a server that provides network prediction calculation and application services for one or more applications in the terminal device 100. The server 200 may be one or more servers provided by the developer or provider of the terminal device 100.

[0082] The network side device 301 and the network side device 302 provided in the present application are devices for communicating with the terminal device. The network side device 301 and the network side device 302 can be a base station (base transceiverstation, BTS) in a GSM system or a CDMA system, a base station (NodeB, NB) in a WCDMA system, an evolved base station (evolved NodeB, eNodeB) in an LTE system, and a next-generation base station (new Generation NodeB, gNodeB) in a 5G system, etc., and the embodiments of the present application are not limited thereto.

[0083] In the embodiment of the present application, all areas or part of the areas covered by the network side device may be divided into a cell, for example, the area covered by the network side device 301 includes cell A, cell B and cell C, and the area covered by the network side device 300-2 includes cell D. The network side device 301 and the network side device 302 may allocate transmission resources for the cells under their jurisdiction. Under normal circumstances, when the terminal device 100 is in the area covered by the network side device 301 and the network side device 302, the terminal device 100 may communicate with the network side device by accessing the wireless channel resources of the corresponding cell, or communicate with other terminal devices, the server 200, etc. through the network side device.

[0084] However, in some special cases, such as when a cell is overloaded, or the base station to which the cell belongs is poorly constructed or improperly configured, the terminal device 100 may not be able to access the cell, or after accessing the cell, due to congestion of transmission resources, the terminal device 100 may suffer from problems such as Internet access lag, call failure, poor call quality, etc. Especially on some subway / high-speed rail / car routes, as the terminal device 100 carried by the user moves quickly, the terminal device 100 will frequently switch to different cells, and it is also very easy to access a lag cell, which will bring a bad experience.

[0085] In order to solve the above problems, the present application provides a network prediction method and its terminal device, server and communication system, the method comprising: the server 200 matches the possible cell switching relationship of the terminal device 100 on the subsequent moving route from the cell association information library according to the information of the N cells continuously accessed by the terminal device 100, and then calculates the network prediction result in combination with the stuck cell included in the cell switching relationship, and sends the network prediction result to the terminal device 100. The network prediction result includes but is not limited to: the estimated time for the terminal device 100 to arrive at the stuck cell, the residence time in the stuck cell, the probability corresponding to the estimated time to arrive at the stuck cell, and the probability corresponding to the residence time in the stuck cell, etc. In this way, it can be used to prompt the user to take relevant Internet access measures in advance, or to control the terminal device 100 to automatically take relevant Internet access measures, so as to avoid Internet access stuck problems such as Internet access stuck to the user during the process of the terminal device 100 accessing the stuck cell.

[0086] In the embodiment of the present application, N in the information of N cells can be any integer greater than or equal to 2. When the value of N is larger, the server 200 can more accurately match the cell switching relationship that may exist on the subsequent moving route for the terminal device 100, and thus accurately predict the quality of the network environment in which it will be located; when the value of N is smaller, the server 200 can more quickly match the cell switching relationship that may exist on the subsequent moving route for the terminal device 100, and thus achieve the purpose of real-time prediction of the network environment.

[0087] In the embodiment of the present application, the terminal device 100 may also be referred to as a first device, and the information of N cells sent by the terminal device 100 to the server 200 may also be referred to as first cell information.

[0088] In an embodiment of the present application, the cell association information database is a cell association information database established by the server 200 in advance on the basis of manually input skeleton data, combined with information of multiple continuously accessed cells (also referred to as second cell information) reported by multiple terminal devices (also referred to as second devices). The cell association information database includes: cell switching relationships arranged on the routes of transportation vehicles such as subways, high-speed railways, and cars. The cell switching relationship may specifically include: the probability of the previous cell switching to the next cell, and the probability distribution of the residence time of each cell, etc. For the specific establishment process of the cell association information database, please refer to the description at S401 of the method flow below, and for the storage model of the cell association information database, please refer to the following text. Figure 6 The description of is not repeated here.

[0089] Next, the software and hardware architecture of the terminal device 100 and the server 200 involved in this application will be introduced in turn.

[0090] refer to Figure 2A , Figure 2A The hardware architecture diagram of the terminal device 100 is shown as an example.

[0091] like Figure 2A As shown, the terminal device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a button 190, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a touch sensor 180B, an acceleration sensor 180C, or may also include an air pressure sensor, a magnetic sensor, a distance sensor, a proximity light sensor, a fingerprint sensor, a temperature sensor, a gyroscope sensor, an ambient light sensor, a bone conduction sensor, etc., which are not shown.

[0092] It is to be understood that the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on the terminal device 100. In other embodiments of the present application, the terminal device 100 may include more or fewer components than shown in the figure, or combine some components, or split some components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0093] The processor 110 may include one or more processing units, for example, the processor 110 may include an application processor (AP), a modem processor, a graphics processor (GPU), an image signal processor (ISP), a controller, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

[0094] The controller can generate operation control signals according to the instruction operation code and timing signal to complete the control of instruction fetching and execution.

[0095] The processor 110 may also be provided with a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. The memory may store instructions or data that the processor 110 has just used or cyclically used. If the processor 110 needs to use the instruction or data again, it may be directly called from the memory. This avoids repeated access, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0096] In some embodiments, the processor 110 may include one or more interfaces. The interface may include an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, an external memory interface 120, and / or a universal serial bus (USB) interface, etc.

[0097] The external memory interface 120 can be used to connect to an external non-volatile memory to expand the storage capacity of the terminal device 100. The external non-volatile memory communicates with the processor 110 through the external memory interface 120 to implement a data storage function. For example, files such as music and videos are stored in the external non-volatile memory.

[0098] The terminal device 100 may further include an internal memory 121 , which may include one or more random access memories (RAM) and one or more non-volatile memories (NVM).

[0099] The random access memory may include static random-access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM, for example, the fifth generation DDR SDRAM is generally referred to as DDR5 SDRAM), etc. The random access memory may be directly read and written by the processor 110, and may be used to store executable programs (such as machine instructions) of an operating system or other running programs, and may also be used to store user and application data, etc.

[0100] Non-volatile memory can include disk storage devices and flash memory. Flash memory can be divided into NOR FLASH, NAND FLASH, 3D NAND FLASH, etc. according to the operating principle, single-level cell (SLC), multi-level cell (MLC), triple-level cell (TLC), quad-level cell (QLC), etc. according to the potential level of the storage cell, and universal flash storage (UFS), embedded multi media card (eMMC), etc. according to the storage specification.

[0101] In the embodiment of the present application, the external non-volatile memory connected to the external memory interface 120 and the non-volatile memory in the internal memory 121 can also be generally referred to as the external memory of the terminal device. These non-volatile memories can be used to store executable programs, user and application data, etc. Before the terminal device runs an application, that is, when the terminal device receives an operation for opening the application and starts the application, the application needs to perform data initialization, read and write databases, and load data resources, that is, the application needs to load the executable programs, user and application data stored in the non-volatile memory into the random access memory in advance for direct reading and writing by the processor 110.

[0102] The USB interface 130 is an interface that complies with the USB standard specification, and can be a Mini USB interface, a Micro USB interface, a USB Type C interface, etc. The USB interface 130 can be used to connect a charger to charge the terminal device 100, and can also be used to transfer data between the terminal device 100 and peripheral devices. It can also be used to connect headphones to play audio through the headphones. The interface can also be used to connect other terminal devices, such as a mouse, a keyboard, or an AR device.

[0103] It is understandable that the interface connection relationship between the modules illustrated in the embodiment of the present invention is only a schematic illustration and does not constitute a structural limitation on the terminal device 100. In other embodiments of the present application, the terminal device 100 may also adopt different interface connection methods in the above embodiments, or a combination of multiple interface connection methods.

[0104] The charging management module 140 is used to receive charging input from a charger. The charger may be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 may receive charging input from a wired charger through the USB interface 130. In some wireless charging embodiments, the charging management module 140 may receive wireless charging input through a wireless charging coil of the terminal device 100. While the charging management module 140 is charging the battery 142, it may also power the terminal device through the power management module 141.

[0105] The power management module 141 is used to connect the battery 142, the charging management module 140 and the processor 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140, and supplies power to the processor 110, the internal memory 121, the display screen 194, the camera 193, and the wireless communication module 160. The power management module 141 can also be used to detect parameters such as battery capacity, battery cycle number, battery health status (leakage, impedance), etc. In some other embodiments, the power management module 141 can also be set in the processor 110. In other embodiments, the power management module 141 and the charging management module 140 can also be set in the same device.

[0106] The wireless communication function of the terminal device 100 can be implemented through the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor and the baseband processor.

[0107] Antenna 1 and antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in terminal device 100 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve the utilization of antennas. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In some other embodiments, the antenna can be used in combination with a tuning switch.

[0108] The mobile communication module 150 can provide solutions for wireless communications including 2G / 3G / 4G / 5G applied to the terminal device 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a low noise amplifier (LNA), etc. The mobile communication module 150 can receive electromagnetic waves from the antenna 1, and filter, amplify, and process the received electromagnetic waves, and transmit them to the modulation and demodulation processor for demodulation. The mobile communication module 150 can also amplify the signal modulated by the modulation and demodulation processor, and convert it into electromagnetic waves for radiation through the antenna 1. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the processor 110. In some embodiments, at least some of the functional modules of the mobile communication module 150 can be set in the same device as at least some of the modules of the processor 110.

[0109] The modem processor may include a modulator and a demodulator. Among them, the modulator is used to modulate the low-frequency baseband signal to be sent into a medium-high frequency signal. The demodulator is used to demodulate the received electromagnetic wave signal into a low-frequency baseband signal. The demodulator then transmits the demodulated low-frequency baseband signal to the baseband processor for processing. After the low-frequency baseband signal is processed by the baseband processor, it is passed to the application processor. The application processor outputs a sound signal through an audio device (not limited to a speaker 170A, a receiver 170B, etc.), or displays an image or video through a display screen 194. In some embodiments, the modem processor may be an independent device. In other embodiments, the modem processor may be independent of the processor 110 and be set in the same device as the mobile communication module 150 or other functional modules.

[0110] The wireless communication module 160 can provide wireless communication solutions including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (IR), etc., which are applied to the terminal device 100. The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via an antenna, modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110. The wireless communication module 160 can also receive the signal to be sent from the processor 110, modulate the frequency, amplify it, and convert it into electromagnetic waves for radiation through the antenna.

[0111] In some embodiments, the antenna of the terminal device 100 is coupled to the wireless communication module 160, so that the terminal device 100 can communicate with the network and other devices through wireless communication technology. The wireless communication technology may include global system for mobile communications (GSM), general packet radio service (GPRS), code division multiple access (CDMA), wideband code division multiple access (WCDMA), time division code division multiple access (TD-SCDMA), long term evolution (LTE), BT, GNSS, WLAN, NFC, FM, and / or IR technology, etc. The GNSS may include global positioning system (GPS), global navigation satellite system (GLONASS), Beidou navigation satellite system (BDS), quasi-zenith satellite system (QZSS) and / or satellite based augmentation system (SBAS).

[0112] The terminal device 100 implements the display function through a GPU, a display screen 194, and an application processor. The GPU is a microprocessor for image processing, which connects the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor 110 may include one or more GPUs, which execute program instructions to generate or change display information.

[0113] The display screen 194 is used to display images, videos, etc. The display screen 194 includes a display panel. The display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode or an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), Miniled, MicroLed, Micro-oLed, a quantum dot light-emitting diode (QLED), etc. In some embodiments, the terminal device 100 may include 1 or N display screens 194, where N is a positive integer greater than 1.

[0114] The pressure sensor 180A is used to sense the pressure signal and can convert the pressure signal into an electrical signal. In some embodiments, the pressure sensor 180A can be set on the display screen 194. There are many types of pressure sensors 180A, such as resistive pressure sensors, inductive pressure sensors, capacitive pressure sensors, etc. The capacitive pressure sensor can be a parallel plate including at least two conductive materials. When a force acts on the pressure sensor 180A, the capacitance between the electrodes changes. The terminal device 100 determines the intensity of the pressure according to the change in capacitance. When a touch operation acts on the display screen 194, the terminal device 100 detects the touch operation intensity according to the pressure sensor 180A. The terminal device 100 can also calculate the touch position according to the detection signal of the pressure sensor 180A. In some embodiments, touch operations acting on the same touch position but with different touch operation intensities can correspond to different operation instructions. For example: when a touch operation with a touch operation intensity less than the first pressure threshold acts on the short message application icon, an instruction to view the short message is executed. When a touch operation with a touch operation intensity greater than or equal to the first pressure threshold acts on the short message application icon, an instruction to create a new short message is executed.

[0115] The touch sensor 180B is also called a "touch control device". The touch sensor 180B can be arranged on the display screen 194, and the touch sensor 180B and the display screen 194 form a touch screen, also called a "touch control screen". The touch sensor 180B is used to detect touch operations acting on or near it. The touch sensor can pass the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through the display screen 194. In other embodiments, the touch sensor 180B can also be arranged on the surface of the terminal device 100, which is different from the position of the display screen 194.

[0116] The acceleration sensor 180C can detect the magnitude of the acceleration of the terminal device 100 in various directions (generally three axes). When the terminal device 100 is stationary, the magnitude and direction of gravity can be detected. It can also be used to identify the posture of the electronic device and is applied to applications such as horizontal and vertical screen switching and pedometers.

[0117] In other embodiments of the present application, the above-mentioned sensors, such as the pressure sensor 180A and the touch sensor 180B, can be set in the display screen 194 of the terminal device 100, or can also be set in the touch panel area at the keyboard of the terminal device 100 to receive the operation input by the user. Specifically, the pressure sensor 180A can detect the operation of the user clicking the touch panel with a finger or a stylus, and then the pressure sensor 180A can generate corresponding pressure information according to the operation input by the user, and send the pressure information to the processor 110. The processor 110 can obtain the coordinate information of the user acting on the display screen according to the pressure information, and finally perform the corresponding operation according to the coordinate information.

[0118] In the embodiment of the present application, the processor 110 can determine that the user is in a scene of taking a subway / high-speed rail / car through the data detected by the acceleration sensor 180C, and report the information of the N cells continuously accessed by the mobile communication module 150 to the server 200 through the mobile communication module 150 / wireless communication module 160, so that the server 200 can determine the cell switching relationship that may exist on the subsequent moving route of the terminal device 100 based on the information of the N cells continuously accessed, and then calculate the network prediction result in combination with the stuck cells included in the cell switching relationship, and send the network prediction result to the terminal device 100. Afterwards, the processor 110 can control the display screen 194 to display the prompt information of the network prediction result, which is used to prompt the user to collect the prompt information of the relevant Internet access measures in advance, or to control the APP installed in the terminal device 100 to automatically take relevant Internet access measures, such as pre-caching content, or reducing the definition of network video, etc., so as to avoid the problem of Internet access stuck to the user during the process of the terminal device 100 accessing the stuck cell.

[0119] The terminal device 100 may be equipped with Or portable devices with other operating systems, the software system of the terminal device 100 can adopt a layered architecture, an event-driven architecture, a micro-kernel architecture, a micro-service architecture, or a cloud architecture. Taking the system as an example, the software structure of the terminal device 100 is exemplified.

[0120] refer to Figure 2B , Figure 2B The software architecture diagram of the terminal device 100 is shown as an example.

[0121] like Figure 2B As shown, the layered architecture divides the software into several layers, each with clear roles and division of labor. The layers communicate with each other through software interfaces. In some embodiments, the Android system is divided into four layers, from top to bottom, namely, the application layer, the application framework layer, the Android runtime (Android runtime) and the system library, and the kernel layer.

[0122] The application layer can include a series of application packages. For example, an application package can include camera, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music APP, video APP and other applications.

[0123] Among them, the music APP and the video APP can be system APP or third-party APP, which is not limited in the present embodiment. However, such APP can provide users with services of downloading and caching music or videos from the network through the mobile communication module.

[0124] The application framework layer provides an application programming interface (API) and a programming framework for applications in the application layer. The application framework layer includes some predefined functions.

[0125] like Figure 2B As shown, the application framework layer may include a window manager, a content provider, a view system, a phone manager, a resource manager, a notification manager, and the like.

[0126] The window manager is used to manage window programs. The window manager can obtain the display screen size, determine whether there is a status bar, lock the screen, capture the screen, etc.

[0127] Content providers are used to store and retrieve data and make it accessible to applications. The data may include videos, images, audio, calls made and received, browsing history and bookmarks, phone books, etc.

[0128] The view system includes visual controls, such as controls for displaying text, controls for displaying images, etc. The view system can be used to build applications. A display interface can be composed of one or more views. For example, a display interface including a text notification icon can include a view for displaying text and a view for displaying images.

[0129] The phone manager is used to provide communication functions of the terminal device 100, such as management of call status (including connection, disconnection, etc.).

[0130] The resource manager provides various resources for applications, such as localized strings, icons, images, layout files, video files, and so on.

[0131] The notification manager enables applications to display notification information in the status bar. It can be used to convey notification-type messages and can disappear automatically after a short stay without user interaction. For example, the notification manager is used to notify download completion, message reminders, etc. The notification manager can also be a notification that appears in the system top status bar in the form of a chart or scroll bar text, such as notifications of applications running in the background, or a notification that appears on the screen in the form of a dialog window. For example, a text message is displayed in the status bar, a prompt sound is emitted, the terminal device vibrates, the indicator light flashes, etc.

[0132] Android Runtime includes core libraries and virtual machines. Android runtime is responsible for scheduling and management of the Android system.

[0133] The core library consists of two parts: one is the function that needs to be called by the Java language, and the other is the Android core library.

[0134] The application layer and the application framework layer run in a virtual machine. The virtual machine executes the Java files of the application layer and the application framework layer as binary files. The virtual machine is used to perform functions such as object life cycle management, stack management, thread management, security and exception management, and garbage collection.

[0135] The system library may include multiple functional modules, such as surface manager, media library, 3D graphics processing library (such as OpenGL ES), 2D graphics engine (such as SGL), etc.

[0136] The surface manager is used to manage the display subsystem and provide the fusion of 2D and 3D layers for multiple applications.

[0137] The media library supports playback and recording of a variety of commonly used audio and video formats, as well as static image files, etc. The media library can support a variety of audio and video encoding formats, such as: MPEG4, H.264, MP3, AAC, AMR, JPG, PNG, etc.

[0138] The 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing.

[0139] A 2D graphics engine is a drawing engine for 2D drawings.

[0140] The kernel layer is the layer between hardware and software. The kernel layer contains at least display driver, camera driver, audio driver, and sensor driver.

[0141] The following is an illustrative description of the software and hardware workflow of the terminal device 100 in conjunction with the capture and photo shooting scene.

[0142] When the touch sensor 180B receives a touch operation, the corresponding hardware interrupt is sent to the kernel layer. The kernel layer processes the touch operation into an original input event (including touch coordinates, timestamp of the touch operation, and other information). The original input event is stored in the kernel layer. The application framework layer obtains the original input event from the kernel layer and identifies the control corresponding to the input event. For example, if the touch operation is a touch single-click operation and the control corresponding to the single-click operation is a control of the camera application icon, the camera application calls the interface of the application framework layer to start the camera application, and then starts the camera driver by calling the kernel layer to capture static images or videos through the camera 193.

[0143] refer to Figure 3A , Figure 3A The hardware architecture diagram of the server 200 is exemplarily shown.

[0144] like Figure 3A As shown, the server 200 may include: one or more processors 201, a memory 202, a communication interface 203, a transmitter 205, a receiver 206, a coupler 207 and an antenna 208. These components may be connected via a bus 204 or other means. Figure 3A Take bus connection as an example.

[0145] In the embodiment of the present application, the processor 201 can be used to read and execute computer-readable instructions. Specifically, the processor 201 can be used to call a program stored in the memory 202, such as a method provided in an embodiment of the present application, which determines the future movement route of the terminal device 100 based on the information of the N cells continuously accessed by the terminal device 100, and the stuck cells that can be accessed in the movement route, and sends the estimated arrival time of the stuck cell and the residence time in the stuck cell to the terminal device 100. Related information, such as the implementation program on the server 200 side, and executes the instructions contained in the program.

[0146] The memory 202 is coupled to the processor 201 and is used to store various software programs and / or multiple sets of instructions. Specifically, the memory 202 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more disk storage devices, flash memory devices or other non-volatile solid-state storage devices.

[0147] The memory 202 can store an operating system (hereinafter referred to as system), such as embedded operating systems such as uCOS, VxWorks, RTLinux, etc. The memory 202 can also store a network communication program, which can be used to communicate with the terminal device 100 and other terminal devices.

[0148] The communication interface 203 can be used for the server 200 to communicate with other communication devices, such as the terminal device 100. Specifically, the communication interface 203 can be a 3G communication interface, a long-term evolution (LTE) (4G) communication interface, a 5G communication interface, a WLAN communication interface, a WAN communication interface, etc. Not limited to a wireless communication interface, the server 200 can also be configured with a wired communication interface 203 to support wired communication, for example, the link between the server 200 and other servers can be a wired communication connection.

[0149] In some embodiments of the present application, the transmitter 205 and the receiver 206 can be regarded as a wireless modem. The transmitter 205 can be used to transmit and process the signal output by the processor 201. The receiver 206 can be used to receive the signal. In the server 200, the number of the transmitter 205 and the receiver 206 can be one or more. The antenna 208 can be used to convert the electromagnetic energy in the transmission line into electromagnetic waves in the free space, or to convert the electromagnetic waves in the free space into electromagnetic energy in the transmission line. The coupler 207 can be used to divide the mobile communication signal into multiple paths and distribute it to multiple receivers 206. It can be understood that the antenna 208 of the network device can be implemented as a large-scale antenna array.

[0150] In the embodiment of the present application, the memory 202 of the server 200 may store: a cell association information library, information about the stuck cell, a network prediction algorithm, and a prediction information database. For a detailed introduction to the cell association information library, information about the stuck cell, and the network prediction algorithm, please refer to the description of the method embodiment below, which will not be repeated here.

[0151] The prediction information database refers to the relevant information of the network environment that each terminal device may be in during the subsequent movement route obtained by the server 200 through the network prediction algorithm. The relevant information of the network environment includes, but is not limited to: the estimated time when the terminal device arrives at the stuck cell, the residence time in the stuck cell, the probability corresponding to the estimated time to arrive at the stuck cell, and the probability corresponding to the residence time in the stuck cell, etc.

[0152] When the server 200 receives the area information that the target user has visited and the time he / she has stayed in the area sent by the server 200 through the communication interface 203 , the server 200 can send it to the electronic device that logs in the tracking application.

[0153] Need to explain, Figure 3A The server 200 shown is only one implementation of the embodiment of the present application. In actual applications, the server 200 may also include more or fewer components, which is not limited here.

[0154] refer to Figure 3B , Figure 3B The software architecture diagram of the server 200 is exemplarily shown.

[0155] like Figure 3B As shown, the server 200 may include the following modules: a cell association information library, a stuck cell information library, a network prediction algorithm, and a network prediction information database.

[0156] The cell association information base module includes: the cell switching relationship arranged on the travel routes of transportation vehicles such as subways, high-speed railways, and cars. The cell switching relationship may specifically include: the probability of switching from the previous cell to the next cell, and the probability distribution of the residence time of each cell. For the specific establishment process of the cell association information base, please refer to the description at S401 of the method flow below, and for the storage model of the cell association information base, please refer to the following Figure 6 The description of is not repeated here.

[0157] The Caton cell information database is used to store information of one or more Caton cells, including but not limited to the identification of the Caton campus, the probability distribution of the dwell time of the Caton cell, etc.

[0158] The network prediction algorithm module is used to calculate the network prediction result based on the information of N continuously accessed cells reported by the terminal device, the cell association information library and the stuck cell.

[0159] The network prediction information database module is used to store the relevant information (i.e., prediction results) of the network environment that each terminal device may be in during its subsequent movement route, obtained by the server 200 through the network prediction algorithm, and to send the prediction results to the corresponding terminal device.

[0160] Need to explain, Figure 3B The server 200 shown is only one implementation of the embodiment of the present application. In actual applications, the server 200 may also include more or fewer modules, which is not limited here.

[0161] Based on the above description of the embodiments of the communication system, terminal device 100, server 200 and other devices involved in the present application, Figure 4 The method flow shown is used to introduce the network prediction method provided by this application in detail.

[0162] like Figure 4 As shown, the method comprises the following steps:

[0163] Phase 1 (S401): Server initialization phase.

[0164] S401, the server 200 pre-stores a cell association information database, a stuck cell information database and a network prediction algorithm.

[0165] Specifically, the server 200 needs to pre-store information required for network prediction of the terminal device, including but not limited to: a cell association information library, a stuck cell information library, and a network prediction algorithm. The cell association information library and the stuck cell information library can also be integrated into one database.

[0166] The cell association information base includes multiple cell switching relationships, and each cell switching relationship includes: the order in which multiple cells are switched in sequence. In addition, it can also include the probability of switching from the previous cell to the next cell and the residence time of each cell. Among them, the residence time of each cell can be characterized by statistically analyzing the probability distribution (e.g., normal distribution) of the residence time of multiple terminal devices in the cell.

[0167] The cell association information database may be established in any of the following three ways, or the method for establishing the cell association information database may also be established in other ways, which are not limited in this application:

[0168] (1) Developers collect all the cell switching relationships and cell residence time on the routes of transportation vehicles such as subways, high-speed trains, and cars to establish a cell association information database;

[0169] (2) Based on the manually collected skeleton data (the main / partial cell handover relationships on the routes of transportation vehicles such as subways, high-speed trains, and cars), the server 200 combines the information of multiple cells continuously accessed by each terminal device (also known as the second device) reported by a large number of terminal devices (also known as the second device) when moving on the routes of subways, high-speed trains, cars, etc. (including the identification of each cell, access time, and residence time, etc.), and then obtains a more comprehensive and accurate cell association information database through route direction recognition (for example, using time series DTW algorithm, dynamic time warping, LCSS algorithm) and cell handover relationship aggregation. The cell association information database almost covers the cell information corresponding to all base stations arranged on the routes of subways, high-speed trains, cars, etc.;

[0170] (3) Based on the ticket purchase information or base station location information reported by the collected terminal devices (also called the second device), the server 200 combines the information of multiple cells continuously accessed by each terminal device reported by a large number of terminal devices when moving on the subway, high-speed rail, bus and other routes, and then obtains a more comprehensive and accurate cell association information database through route direction recognition (for example, using the cosine similarity algorithm), cell switching relationship aggregation, and time correlation algorithm. The cell association information database almost covers the cell information corresponding to all base stations deployed on the subway, high-speed rail, bus and other routes.

[0171] refer to Figure 5 , Figure 5 The schematic diagram exemplarily shows the principle of establishing a cell association information database. Figure 5 This is a schematic diagram of the principle of generating a cell association information database using method (2) or method (3) as described above.

[0172] like Figure 5 As shown, the principle of establishing a cell association information database specifically includes the following steps:

[0173] Step 1: Manually collect skeleton data. The skeleton data includes, but is not limited to: the association information of the cells corresponding to the main base stations arranged on the routes of subways, high-speed railways, and buses, for example, the manually collected cell layout information of subway line 1 from the museum to the airport is: cell 1, cell 2, cell 3 and cell 4; for another example, the manually collected cell layout information of the high-speed railway from city A to city B is: cell 1, cell 2, cell 3 and cell 4; or the skeleton data can also include more routes, and more cells on each route, which is not limited in the embodiments of the present application.

[0174] Among them, the manually collected skeleton data can be the main / partial cell switching relationship arranged on the travel routes of transportation tools such as subways, high-speed railways, and cars in the previous method (2), or it can be the ticket purchase information or base station location information reported by the terminal device in method (3).

[0175] Step 2: Match the route according to the data reported by the terminal device and fill in the cell-related information. Specifically, after the server 200 collects from the terminal device the information of multiple cells that are continuously accessed during the movement on the subway, high-speed rail, bus and other routes, it can match the multiple cells that are continuously accessed with the related information of the cells on each existing route. For example, the cell information collected by the server 200 from the terminal device is: cell 1, cell 5, cell 2 and cell 3. When it is, it can be matched to the cell-related route corresponding to the subway line 1 from the museum in city A to the airport, and by comparison, it can be known that cell 5 is a new cell between cell 1 and cell 2, so cell 5 is filled between cell 1 and cell 2.

[0176] Step 3: Continue to match the route and fill in the cell association information according to the data reported by the terminal device until the reported cell is not a cell that is not included in the existing cell association information.

[0177] Specifically, when the cell information collected by server 200 from the terminal device is: cell 1, cell 6, cell 2, cell 3 and cell 4 in sequence, it can be matched to the cell-associated route corresponding to Metro Line 1 from the museum in City A to the airport, and by comparison, it can be known that cell 6 is a newly added cell between cell 1 and cell 2, so cell 6 is filled between cell 1 and cell 2.

[0178] It is worth noting that, in the process of establishing the cell association information database, the server 200 will also count the residence time of each cell and the transfer probability of the previous cell and the next cell according to the information of multiple cells continuously accessed reported by each terminal device.

[0179] Specifically, when the server 200 receives the information of the multiple cells that are continuously accessed reported by each terminal device, the information of the cell will also carry the access time, the residence time, or the disconnection time, the information related to the network coverage status, the location information obtained by the global positioning system (GPS) module, etc. The server 200 can count the residence time of the terminal device in each cell according to the access time, the residence time, or the opening time, for example, using a normal distribution function to characterize the residence time. In addition, the server 200 can also determine the information of the stuck cell according to the information related to the network coverage status, or the server 200 can also determine the subway, high-speed rail, and car route where the terminal device is located according to the location information. In addition, when there are multiple cells connected to the next cell in the information of the multiple cells that are continuously accessed reported by multiple terminals, the server 200 can also count the probability of the previous cell transferring to a different cell.

[0180] Understandably, Figure 5 The principle of establishing a cell association information database is shown only by taking the skeleton data on two routes as an example. In other examples of the present application, the skeleton data may include more. The number of cells contained in the skeleton data on each route may be more or less, and the switching relationship between each cell may also be other. The embodiments of the present application do not limit this.

[0181] refer to Figure 6 , Figure 6 The following is a schematic diagram showing an exemplary storage model of a cell association information database.

[0182] like Figure 6 As shown, Figure 6 The cell association information database in the example only shows the cell association information corresponding to Line 1 from the museum to the airport and the high-speed rail from city A to city B, as well as the residence time of each cell and the probability of the previous cell transferring to the later cell. In addition, the cell association information may also include cell association information corresponding to more routes, and the switching relationship between cells on each route may also be other, which is not limited in the embodiments of the present application.

[0183] The stuck cell information database includes: information of one or more stuck cells, such as cell identification, cell residence time, etc., or may also include the stuck time period of the cell, etc. Among them, the cell identification includes but is not limited to: the name, location, model, etc. of the cell. The residence time of the cell includes the time between the terminal accessing the cell and disconnecting from the cell. The stuck time period of the cell refers to the time corresponding to the service quality of the cell not meeting the preset conditions. The reasons for the stuck cell include but are not limited to poor construction / improper data configuration, or overload of access equipment, etc. Among them, the reasons for poor construction / data configuration may cause the cell to be stuck continuously (regardless of time period), and overload of access equipment usually has a tidal effect, that is, the access equipment of the cell is overloaded only during peak time periods, which causes the cell to be stuck only during peak time periods.

[0184] The stuck cell information database may be generated in any of the following three ways, or the cell association information database may be generated in other ways, which is not limited in this application:

[0185] (1) The developer determines the information of the stuck community through on-site testing or by collecting information from the public and then inputs it into the server 200;

[0186] (2) The server 200 generates the cell information by acquiring the cell information reported by the network side device, wherein the cell information includes information indicating the call service and data service quality of the cell accessed by the terminal device, or also includes information such as access time and residence time;

[0187] (3) The server 200 generates the cell information by acquiring the cell information reported by the terminal device, wherein the cell information includes information indicating the quality of call services and data services of the cell accessed by the terminal device, or also includes information such as access time and residence time.

[0188] In the embodiment of the present application, the cell information reported by the terminal device and collected by the server 200 when generating the stuck cell information database can also be referred to as the third cell information.

[0189] When the stuck cell information base is generated by adopting method (2) or method (3), specifically, the server 200 can regard the cell with quality lower than the threshold as the stuck cell according to the quality of the access cell, or can also analyze the specific stuck time of the stuck cell by analyzing whether the cell is stuck in different time periods. When a cell is stuck only in a specific time period and has periodic stuck, it is confirmed that the cell has a tidal effect. Accordingly, when the server 200 performs network prediction for the terminal device later, the stuck cell in the non-stuck time will not be predicted as the stuck cell, thereby avoiding the problem of network prediction misjudgment. The tidal effect refers to the fact that the terminal devices on the subway, high-speed rail, car and other driving routes during the peak time period are more than those during the non-peak time period, so the business stuck phenomenon will occur.

[0190] The network prediction algorithm can be preset by the developer, or it can be an algorithm updated through real-time training through learning iteration based on the initial algorithm preset by the developer. In the embodiment of the present application, the network prediction algorithm can achieve:

[0191] (1) According to the information of N consecutively accessed cells reported by the terminal device, a possible cell handover relationship that matches the future movement route of the terminal device is matched from the cell association information database;

[0192] (2) Obtaining information about the stuck cells in the matched cell handover relationship;

[0193] (3) Calculate the estimated time from the cell currently accessed by the terminal device to the stuck cell and the probability corresponding to the time, and calculate the retention time in the stuck cell and the corresponding probability.

[0194] For the specific calculation method of the network prediction algorithm, please refer to the description of S404 below, which will not be described here.

[0195] Phase 2 (S402-S403): The terminal device 100 reports the information of the cell it has accessed to the server 200.

[0196] S402, the terminal device 100 detects a scenario that meets the network prediction.

[0197] Specifically, the terminal device 100 can determine whether the terminal device is in a scene that meets the network prediction by detecting the mobile acceleration of the terminal device through the acceleration sensor; or, it can also determine whether the terminal device is in a scene that meets the network prediction by obtaining information that the terminal device 100 uses NFC or an electronic boarding code to board a bus. Alternatively, it can also determine whether the terminal device is in a scene that meets the network prediction by positioning or booking tickets online.

[0198] Among them, the scenarios that meet the network prediction include but are not limited to the scenarios where the terminal device moves on the routes of subways, high-speed railways, cars, etc. In these scenarios, the terminal device will frequently switch cells due to the rapid movement of the location, and it is very likely to switch to a stuck cell, which will bring users the experience of Internet stuck, so such scenarios are taken as the focus of network prediction. However, in some other embodiments, the scenarios that meet the network prediction may also include other scenarios, which are not limited in the embodiments of the present application.

[0199] In the embodiment of the present application, S402 is an optional step, that is, no matter what scenario the terminal device is in, it can report the information of the cell it is connected to to the server 200, and the server 200 will further screen the information of these cells or perform network prediction, etc.

[0200] S403, the terminal device 100 sends information of multiple cells that are continuously accessed to the server 200.

[0201] Specifically, after detecting that the network prediction scenario is met, the terminal device 100 will report the information of the N cells that it has continuously accessed to the server 200. The information of the N cells can be reported N times in the access order, or it can be reported at one time after being packaged in the access order. Among them, the information of the multiple / N cells that the terminal device 100 reports to the server 200 that it has continuously accessed can also be called the first cell information.

[0202] The cell information includes, but is not limited to: the cell identifier, the time of accessing the cell, the residence time in the cell, and the like.

[0203] Phase 3 ( S404 ): The server 200 performs network prediction on the environment that the terminal device 100 is about to arrive at.

[0204] S404, the server 200 performs network prediction based on the information of the cell accessed by the terminal device 100.

[0205] Specifically, the server 200 has stored a network prediction algorithm, a cell association information library, and a stuck cell. After receiving information about N cells, the network prediction algorithm in the server 200 can match the cell switching relationship that may exist in the subsequent mobile route of the terminal device from the cell association information library according to the information of the N consecutively accessed cells, and obtain the information of the stuck cell in the matched cell switching relationship, and finally calculate the network prediction result. The network prediction result includes: the estimated time from the cell currently accessed by the terminal device to the stuck cell and the probability corresponding to the time, as well as the calculated residence time in the stuck cell and the corresponding probability.

[0206] Optionally, when some stuck cells have tidal effects, when receiving the information of the continuously accessed cells reported by the terminal device during the non-tidal time period, when performing network prediction on them, the stuck cells with tidal effects are considered not to be stuck cells, that is, such cells are not included in the network prediction range. The tidal effect means that some cells will only experience service stuck during the morning and evening peak hours, while the cell services are normal during other time periods.

[0207] Next, we will use a specific example to introduce the specific calculation process of the network prediction result:

[0208] When the N cells received by the server 200 are: cell A, cell B and cell C, then Figure 6 The cell association information database shown matches the cell switching relationship on the high-speed rail route from city A to city B. The cell switching relationship specifically includes the following three cell switching routes. The 34 switching routes are all switching behaviors that the terminal device 100 will have in the next driving route:

[0209] The switching order of switching route 1 is: cell A, cell B, cell C, cell D, cell F;

[0210] The switching order of switching route 2 is: cell A, cell B, cell C, cell D, cell G and cell H;

[0211] The switching order of switching route 3 is: cell A, cell B, cell C, cell E, cell G and cell H.

[0212] Among them, the cell G is a stuck cell. In the embodiment of the present application, the cell G can also be called the first stuck cell.

[0213] In addition, the cell association information database also records the probability of switching from the previous cell to the next cell. For example, the probability of switching from cell C to cell D is 70%, the probability of switching from cell D to cell G is 60%, the probability of switching from cell C to cell E is 30%, and the probability of switching from cell E to cell G is 100%.

[0214] In addition, the cell association information database will also record the residence time of each cell. The residence time can be the mean directly obtained by the server based on statistical data, or it can be a period of time within a certain probability range. The statistical data can be a normal distribution function of the residence time. For example, the mean of the probability distribution of cell C is 20 seconds, the standard deviation is 2 seconds, and the variance is 4 seconds. The probability that the residence time of cell C is within (20-4, 20+4) seconds is 95%; the mean of the probability distribution of cell D is 30 seconds, the standard deviation is 2 seconds, and the variance is 4 seconds. The probability that the residence time of cell D is within (30-4, 30+4) seconds is 95%; the mean of the probability distribution of cell E is 20 seconds, the standard deviation is 4 seconds, and the variance is 16 seconds. The probability that the residence time of cell D is within (20-16, 20+16) seconds is 68%.

[0215] Finally, the method for calculating the time when the terminal device arrives at the stuck cell includes any of the following:

[0216] (1) Calculation rule 1 (only using the mean):

[0217] The probability of taking switching route 2 to enter the stuck cell G is 70%*60%=42%, and the time required is 20+30=50 seconds;

[0218] The probability of taking switching route 3 to enter the stuck cell G is 30%*100%=30%, and the time required is 20+20=40 seconds;

[0219] In total, the terminal device will access the stuck cell G after 40-50 seconds with a probability of 42%+30%=72%.

[0220] (2) Calculation rule 2 (using probability transfer + mean):

[0221] The probability of taking switching route 2 or switching route 3 to enter the stuck cell G is: 70%*60%+30%*100%=72%, and the time required is: 42% / 72%(20+30)+30% / 72%(20+20)=29.2+16.7=45.9;

[0222] In total, the terminal device will access the stuck cell G after 45.9 seconds with a 72% probability.

[0223] (3) Calculation rule 3 (using probability transfer + variance):

[0224] The probability of taking switching route 2 to enter the stuck cell G is 95%*70%*95%*60%=37.905%, and the time required is between 20-4+30-4=42 seconds and 20+4+30+4=58 seconds;

[0225] The probability of taking switching route 3 to enter the stuck cell G is 95%*30%*68%*100%=19.38%, and the time required is between 20-4+20-16=12 seconds and 20+4+20+16=60 seconds;

[0226] Total: The probability of taking switching route 2 or 3 to enter the stuck cell G is 37.905%+19.38%=57.285%, and the time required is between 12 seconds and 60 seconds.

[0227] Among the prediction results obtained by the above three calculation methods, the probability of entering the stuck cell G can be called the first probability, and the time required to enter the stuck cell G under the first probability can also be called the first duration, the probability of staying in the stuck cell G is the second probability, and the duration of staying in the cell G under the second probability can also be called the second probability.

[0228] It is understandable that the calculation method of the network prediction results described above is only an example. In other examples of this application, when the information of N cells is other, the matched cell switching relationship may be other, or the information of the stuck cell may be other, so the calculated network prediction results may be different, but the calculation principle is the same, and the calculation method can still be referred to the above example. In addition, when taking the value of the cell residence time according to the probability distribution of the residence time of each cell, in addition to taking the mean and taking the time period within the range of the mean to the variance, it can also be used to take the time period within the range of the mean to the standard deviation, or take other time periods for calculation. The only difference is that the residence probabilities corresponding to different time periods are different, but the calculation principle is the same, and it will not be elaborated here.

[0229] Phase 4 ( S405 - S406 ): The server 200 pushes the network prediction result to the terminal device 100 .

[0230] S405 , the server 200 sends the network prediction result to the terminal device 100 .

[0231] Specifically. The network prediction results include but are not limited to: information about the stuck cell, the time required to reach the stuck cell and the corresponding probability, and the residence time in the stuck cell and the corresponding probability. Among them, the calculation rule for the time required to reach the stuck cell can be any of the examples in S404, and the residence time of the stuck cell can use the mean value or the time within the variance range, which is not limited in the embodiment of the present application.

[0232] S406, the terminal device 100 outputs the network prediction result, and / or adjusts Internet access measures according to the network prediction result.

[0233] The content of the prompt information may be, for example, the time required to reach the stuck cell and the corresponding probability, and the residence time in the stuck cell and the corresponding probability, and the prompting method includes but is not limited to SMS, notification, card, voice broadcast, etc. In this way, the user can be prompted to take relevant measures in advance according to the network prediction results, such as caching network content in advance or reducing the clarity of viewing network content, so as to avoid the phenomenon that the user cannot access the Internet after entering the stuck cell.

[0234] Among them, controlling the terminal device 100 to adjust the Internet access measures includes, for example, caching network content in advance and / or reducing the clarity of viewing network content. The measure can be related to the user's Internet access behavior, for example, the network content cached in advance and / or reducing the clarity of viewing network content is the content provided by the APP that the user is currently using, or the content provided by the APP that the user frequently uses. The APP can be a system APP or a third-party APP. In this way, the user can take relevant Internet access measures in advance without the user's perception, so that the user can still watch the network content unimpeded after entering the stuck cell.

[0235] For example, do not answer calls, cache or download online content in advance, or reduce the definition of online videos, etc. And / or, the terminal device 100 can also control the installed APP to automatically take relevant online measures, such as caching or downloading online content in advance, or reducing the definition of online videos, etc.

[0236] Finally, combine Figure 7 The network prediction architecture diagram shown is used to introduce the network prediction method provided by the present application in detail.

[0237] like Figure 7 As shown, the network prediction mainly includes four parts: cell information reporting, cell association information database establishment, network prediction and network prediction result push. Among them, cell information reporting and network prediction result push are performed by the terminal device 100, and cell association information database establishment and network prediction are performed by the server 200. The detailed execution process is as follows:

[0238] 1. Report community information.

[0239] When the scene recognition module in the terminal device 100 recognizes a scene that meets the network prediction (such as taking the subway, high-speed rail, car, etc.), it will notify the cell information reporting module to report the information of the N cells that it has continuously accessed to the cell information module or network prediction algorithm module of the server 200. Among them, the information of the N cells reported to the cell information module is used for the server 200 to establish a cell association information library, and the information of the N cells reported to the network prediction algorithm module is used for the server 200 to generate network prediction results. The former is executed in the process of the server 200 establishing a cell association information library or updating a cell association information library, and the latter is executed after the server 200 has successfully established a cell association information library.

[0240] 2. Establishment of community-related information database.

[0241] The cell information module in the server 200 can receive manually input cell information (ie, the skeleton data mentioned above), as well as cell information reported by multiple terminal devices, and then establish and update the cell-related information after data processing to obtain a cell-related information database.

[0242] The data processing process includes but is not limited to steps such as data cleaning, route direction identification, cell switching relationship aggregation, and time correlation analysis. Data cleaning is an optional processing process, which refers to deleting information of cells that are continuously accessed by less than N cells received from the terminal device. For a detailed introduction to cell switching relationship aggregation and time correlation analysis, please refer to the description of S401 in the previous method flow, which will not be repeated here.

[0243] 3. Network prediction.

[0244] After each time the network prediction algorithm module in the server 200 receives the information of N continuously accessed cells reported by the terminal device 100, it will match them from the cell association information library according to the information of the N continuously accessed cells. When matching the cell switching relationship that may exist on the driving route of the terminal device 100, it will combine the stuck cell existing in the cell switching relationship, and then calculate the time when the terminal device is about to arrive at the stuck cell, and the time it stays in the stuck cell, or it will also calculate: the probability corresponding to the time of reaching the stuck cell, and the probability corresponding to the time of staying in the stuck cell, etc., and finally output the calculated prediction result to the network prediction information library.

[0245] 4. Push of network prediction results.

[0246] After receiving the network prediction results sent by the network prediction information library of the server 200, the network prediction push module in the terminal device 100 can control the display screen 194, audio module 170, etc. of the terminal device 100 to output the network prediction results, which are used to prompt the user to take relevant measures next, such as not answering calls, caching or downloading online content in advance, or reducing the clarity of online videos, etc. And / or, the network prediction push module can also control the video APP and game APP installed in the terminal device to automatically take relevant online measures, such as caching or downloading online content in advance, or reducing the clarity of online videos, etc. Alternatively, the online strategy can also be formulated by the provider or developer of the third-party APP according to the network prediction results, and the embodiments of the present application are not limited to this.

[0247] To sum up, after the implementation of this application, it can be used to predict the environment in which the terminal device will be located and the network quality corresponding to the environment, to prompt the user to take relevant Internet access measures in advance, or to control the terminal device to automatically take relevant Internet access measures, so as to avoid Internet access freezes and other problems for users when the terminal device accesses a freeze cell.

[0248] In addition, the network prediction results include but are not limited to: the time when the terminal device is expected to arrive at the stuck cell, the residence time in the stuck cell, the probability corresponding to the time of arrival at the stuck cell, and the probability corresponding to the residence time in the stuck cell. In this way, the user can be prompted to take relevant Internet access measures in advance, or it can be used to control the terminal device to automatically take relevant Internet access measures to avoid Internet access problems such as stuck Internet access for the user during the process of the terminal device accessing the stuck cell. In this way, the user can decide whether to adjust the relevant Internet access strategy and how to adjust the strategy according to the network result and the probability of the result. Or the APP installed in the terminal is divided into Internet access adjustment strategies according to the network result and the probability of the result. For example, when the probability of entering the stuck cell is greater, or the time of entering the stuck cell is shorter, or the residence time in the stuck cell is longer, the corresponding Internet access strategy is more stringent, such as the lower the definition of watching network content, or the more network content is pre-downloaded / cached, etc.

[0249] It should be understood that each step in the above method embodiment provided by the present application can be completed by an integrated logic circuit of hardware in a processor or by instructions in the form of software. The method steps disclosed in the embodiments of the present application can be directly embodied as being executed by a hardware processor, or by a combination of hardware and software modules in a processor.

[0250] The present application also provides a terminal device, which may include: a memory and a processor. The memory may be used to store a computer program; the processor may be used to call the computer program in the memory, so that the terminal device executes the method in any one of the above embodiments.

[0251] The present application also provides a chip system, which includes at least one processor for implementing the functions involved in the method executed by the terminal device in any of the above embodiments.

[0252] In one possible design, the chip system also includes a memory, which is used to store program instructions and data, and the memory is located inside or outside the processor.

[0253] The chip system may be composed of the chip, or may include the chip and other discrete devices.

[0254] Optionally, the processor in the chip system may be one or more. The processor may be implemented by hardware or by software. When implemented by hardware, the processor may be a logic circuit, an integrated circuit, etc. When implemented by software, the processor may be a general-purpose processor implemented by reading software code stored in a memory.

[0255] Optionally, the memory in the chip system may also be one or more. The memory may be integrated with the processor or may be separately arranged with the processor, which is not limited in the embodiments of the present application. Exemplarily, the memory may be a non-transient processor, such as a read-only memory ROM, which may be integrated with the processor on the same chip or may be arranged on different chips respectively. The embodiments of the present application do not specifically limit the type of memory and the arrangement of the memory and the processor.

[0256] Exemplarily, the chip system can be a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on chip (SoC), a central processor unit (CPU), a network processor (NP), a digital signal processor (DSP), a microcontroller unit (MCU), a programmable logic device (PLD) or other integrated chips.

[0257] The present application also provides a computer program product, which includes: a computer program (also referred to as code, or instruction), which, when executed, enables a computer to execute the method executed by a terminal device in any one of the above embodiments.

[0258] The present application also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program (also referred to as code or instruction). When the computer program is executed, the computer executes the method executed by the terminal device in any of the above embodiments.

[0259] The various implementation modes of the present application can be combined arbitrarily to achieve different technical effects.

[0260] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in this application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) mode. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integration. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk Solid State Disk), etc.

[0261] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

[0262] In short, the above description is only an embodiment of the technical solution of the present invention, and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made according to the disclosure of the present invention shall be included in the protection scope of the present invention.

Claims

1. A network prediction method, characterized in that: The method is applied to a server, and the method comprises: The server receives, from the first device, information about a plurality of historical cells that the first device sequentially accesses; The server matches a first cell switching route including the historical cell from a preset cell association information database; The server determines that the first cell switching route includes a first stuck cell located after the historical cell, and generates a network prediction result, wherein the network prediction result includes: a first duration required for the first device to access the first stuck cell, a first probability of accessing the first stuck cell within the first duration, a second duration of residence in the first stuck cell, and a second probability of residence in the first stuck cell for the second duration; The server sends the network prediction result to the first device; The network prediction result is used to instruct the first device to perform one or more of the following: outputting prompt information, caching network content, and reducing the definition of viewing network content.

2. The method according to claim 1, characterized in that The first duration and the first probability are determined by the server based on the probability distribution of the residence time of the plurality of devices in the corresponding cell obtained; The second duration and the second probability are determined by the server according to the acquired probability distribution of the residence time of multiple devices in the first freeze cell.

3. The method according to claim 1 or 2, characterized in that: Before the server generates a network prediction result, the method further includes: The server receives second cell information sent by the second device, where the second cell information is information of multiple cells continuously accessed by the second device; The server fills the second cell information into the skeleton data to update the cell association information library; The skeleton data includes the switching relationship between cells arranged on multiple routes.

4. The method according to claim 3, characterized in that The information of the multiple cells continuously accessed by the second device specifically includes: an identifier of each cell, an access time and a residence time of each cell.

5. The method according to claim 1 or 2, characterized in that: The first stuck cell includes: a cell belonging to the stuck cell among the multiple cells that the terminal device is about to access in sequence; The multiple cells that the terminal device is about to access in sequence include: cells in the cell association information database that match the first cell switching route; The cell association information database includes multiple cell switching relationships, and each cell switching relationship includes: the order in which multiple cells are switched in sequence.

6. The method according to claim 5, characterized in that The first freeze cell includes: The cell that belongs to the stuck cell at the current moment or the current time period among the multiple cells that the terminal device is about to access in sequence.

7. The method according to claim 5, characterized in that Before the server generates a network prediction result, the method further includes: The server receives third cell information sent by the second device, where the third cell information indicates service quality of a cell accessed by the second device; The server determines the stuck cell according to the service quality.

8. A network prediction method, characterized in that: The method is applied to a first device, and the method includes: Information of a plurality of historical cells sequentially accessed by the first device, sent by the first device to the server; The information of the multiple historical cells is used by the server to match a first cell switching route including the historical cell from a preset cell association information database, determine that the first cell switching route includes a first stuck cell located after the historical cell, and generate a network prediction result, the network prediction result including: a first duration required for the first device to access the first stuck cell, a first probability of accessing the first stuck cell within the first duration, a second duration of residence in the first stuck cell, and a second probability of residence in the first stuck cell for the second duration; The first device receives the network prediction result sent by the server; The first device performs one or more of the following according to the network prediction result: outputting prompt information, caching network content, and reducing the definition of viewing network content.

9. The method according to claim 8, characterized in that The first duration and the first probability are determined by the server based on the probability distribution of the residence time of the plurality of devices in the corresponding cell obtained; The second duration and the second probability are determined by the server according to the acquired probability distribution of the residence time of multiple devices in the first freeze cell.

10. The method according to claim 8 or 9, characterized in that: The first freeze cell includes: A cell that is a stuck cell among multiple cells that the terminal device is about to access in sequence; The multiple cells that the terminal device is about to access in sequence include: cells in the cell association information database that match the first cell switching route; The cell association information database includes multiple cell switching relationships, and each cell switching relationship includes: the order in which multiple cells are switched in sequence.

11. The method according to claim 10, characterized in that The first freeze cell includes: The cell that is a stuck cell at the current time or current time period among the multiple cells that the terminal device is about to access in sequence.

12. The method according to claim 8, characterized in that Before the first device sends information about a plurality of historical cells sequentially accessed by the first device to the server, the method further includes: The first device recognizes that it is in a scene of a subway, a high-speed train or a car.

13. A network prediction method, characterized in that: The method is applied to a communication system including a first device and a server, and the method includes: The first device sends, to the server, information about a plurality of historical cells accessed sequentially by the first device; The server matches a first cell switching route including the historical cell from a preset cell association information database; The server determines that the first cell switching route includes a first stuck cell located after the historical cell, and generates a network prediction result, wherein the network prediction result includes: a first duration required for the first device to access the first stuck cell, a first probability of accessing the first stuck cell within the first duration, a second duration of residence in the first stuck cell, and a second probability of residence in the first stuck cell for the second duration; The server sends the network prediction result to the first device; The first device performs one or more of the following according to the network prediction result: outputting prompt information, caching network content, and reducing the definition of viewing network content.

14. A server, characterized in that: The server includes a memory and one or more processors; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the server to execute the method described in any one of claims 1-7.

15. A terminal device, characterized in that: The terminal device includes a memory and one or more processors; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the terminal device to execute the method as described in any one of claims 8-12.

16. A chip, applied to electronic equipment, characterized in that: The chip includes one or more processors, and the processor is used to call computer instructions to enable the electronic device to execute the method as described in any one of claims 1-12.

17. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on an electronic device, the electronic device is caused to execute the method as claimed in any one of claims 1 to 12.

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