WO2024174641A1 - 网络预测方法及其终端设备、服务器和通信系统 - Google Patents

网络预测方法及其终端设备、服务器和通信系统 Download PDF

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Publication number
WO2024174641A1
WO2024174641A1 PCT/CN2023/134657 CN2023134657W WO2024174641A1 WO 2024174641 A1 WO2024174641 A1 WO 2024174641A1 CN 2023134657 W CN2023134657 W CN 2023134657W WO 2024174641 A1 WO2024174641 A1 WO 2024174641A1
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WIPO (PCT)
Prior art keywords
cell
information
server
terminal device
network prediction
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PCT/CN2023/134657
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English (en)
French (fr)
Inventor
杜旭阳
孙伟光
宋昊
魏珍荣
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Honor Device Co Ltd
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Honor Device Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/06—Testing, supervising or monitoring using simulated traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/147—Network analysis or design for predicting network behaviour
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/08—Reselecting an access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]

Definitions

  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the first device can automatically adjust the Internet access strategy according to the network prediction results.
  • the first device enters a slow 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.
  • the network prediction result includes information of the first stuck cell
  • the information of the first stuck cell includes any one or more of the following: a first duration required for the first device to access the first stuck cell, a first probability of the first device accessing the first stuck cell within the first duration, a second probability of the first device residing in the first stuck cell, duration, and a second probability of the first stuck cell staying for a second duration.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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;
  • 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 the peak time are more than those during the non-peak time, so the business stuck phenomenon will occur.
  • the method 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.
  • 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.
  • the method 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.
  • the third cell information may also include the time period corresponding to the cell accessed by the second device, such as the access time. Time, residence time, etc. are used by the server to determine whether the cell is stuck and whether the stuck cell has a tidal effect, etc. based on the service quality of the cell in the corresponding time period.
  • 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.
  • 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.
  • 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.
  • the first device can automatically adjust the Internet access strategy according to the network prediction results.
  • the first device enters a slow 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.
  • the network prediction result includes information of the first stuck cell
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the corresponding route can be matched according to the cells that the first device continuously accesses, and then the The cell switching relationship can then be used to obtain the stuck cell in the cell switching relationship.
  • 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.
  • 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 the peak time are more than those during the non-peak time, so the business stuck phenomenon will occur.
  • the method 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.
  • 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.
  • 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.
  • 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.
  • the first device can automatically adjust the Internet access strategy according to the network prediction results.
  • the first device enters a slow 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.
  • the network prediction result includes information of the first stuck cell
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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;
  • 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 the peak time are more than those during the non-peak time, so the business stuck phenomenon will occur.
  • the communication system also includes one or more second devices.
  • 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.
  • 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.
  • the method 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.
  • 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.
  • the method 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.
  • 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.
  • 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.
  • 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.
  • the present application provides a computer-readable storage medium, which includes instructions.
  • the 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.
  • FIG1 is a schematic diagram of an application scenario provided by an embodiment of the present application.
  • FIG2A is a hardware architecture diagram of a terminal device 100 provided in an embodiment of the present application.
  • FIG2B is a software architecture diagram of a terminal device 100 provided in an embodiment of the present application.
  • FIG3A is a hardware architecture diagram of a server 200 provided in an embodiment of the present application.
  • FIG3B is a software architecture diagram of a server 200 provided in an embodiment of the present application.
  • FIG4 is a flow chart of a network prediction method provided in an embodiment of the present application.
  • FIG5 is a schematic diagram of a principle for establishing a cell association information database provided by an embodiment of the present application.
  • FIG6 is a schematic diagram of a cell association information database storage model provided in an embodiment of the present application.
  • FIG. 7 is a diagram of a network prediction architecture provided in an embodiment of the present application.
  • 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.
  • 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.
  • GUI graphical user interface
  • FIG1 exemplarily shows a schematic diagram of an application scenario provided by the present application.
  • the network prediction method provided by the present application is applicable to a communication system deployed on a route including but not limited to: a subway, a high-speed railway, and a car, and the communication system includes one or more terminal devices, one or more servers, and one or more network-side devices.
  • FIG1 exemplarily shows a terminal device 100, a server 200, a network-side device 301, and a network-side device 302.
  • 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) system, universal mobile telecommunication system (UMTS), world-wide interoperability for microwave access (WiMAX) communication system, fifth generation (5G) system or new radio (NR), etc.
  • GSM global system for mobile communications
  • CDMA code division multiple access
  • WCDMA wideband code division multiple access
  • GPRS general packet radio service
  • LTE long term evolution
  • FDD frequency division duplex
  • TDD LTE time division duplex
  • UMTS universal mobile telecommunication system
  • WiMAX world-wide interoperability for microwave access
  • 5G fifth generation
  • NR new radio
  • 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.
  • UMPC ultra-mobile personal computer
  • PDA personal digital assistant
  • 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.
  • 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 transceiver station, 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.
  • all areas or part of the areas covered by the network side device can be divided into a cell.
  • the area covered by the network side device 301 includes cell A, cell B and cell C
  • the area covered by the network side device 300-2 includes cell A, cell B and cell C.
  • the area includes cell D.
  • the network side device 301 and the network side device 302 can 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 can 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.
  • 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.
  • 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.
  • N in the information of N cells can be any integer greater than or equal to 2.
  • 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 can 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 can achieve the purpose of real-time prediction of the network environment.
  • 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.
  • 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 reported by multiple terminal devices (also referred to as second devices) (also referred to as second cell information).
  • the cell association information database includes: cell switching relationships 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 the previous cell switching to the next cell, and the probability distribution of the residence time of each cell, etc.
  • 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 description of Figure 6 below, which will not be repeated here.
  • FIG. 2A exemplarily shows a hardware architecture diagram of the terminal device 100 .
  • 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, and a power management module 141, battery 142, antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, audio module 170, speaker 170A, receiver 170B, microphone 170C, headphone jack 170D, sensor module 180, button 190, indicator 192, camera 193, display screen 194, and subscriber identification module (SIM) card interface 195, etc.
  • SIM subscriber identification module
  • 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.
  • the structure illustrated in the embodiment of the present invention does not constitute a specific limitation on the terminal device 100.
  • 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.
  • 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.
  • AP application processor
  • GPU graphics processor
  • ISP image signal processor
  • DSP digital signal processor
  • NPU neural-network processing unit
  • Different processing units may be independent devices or integrated in one or more processors.
  • 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.
  • the processor 110 may also be provided with a memory for storing instructions and data.
  • 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.
  • 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.
  • I2C inter-integrated circuit
  • I2S inter-integrated circuit sound
  • PCM pulse code modulation
  • UART universal asynchronous receiver/transmitter
  • MIPI mobile industry processor interface
  • GPIO general-purpose input/output
  • SIM subscriber identity module
  • USB universal serial bus
  • 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.
  • 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).
  • RAM random access memories
  • NVM non-volatile memories
  • 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 The first generation DDR SDRAM is generally referred to as DDR5 SDRAM), etc.; the random access memory can be directly read and written by the processor 110, and can be used to store executable programs (such as machine instructions) of the operating system or other running programs, and can also be used to store user and application data, etc.
  • SRAM static random-access memory
  • DRAM dynamic random access memory
  • SDRAM synchronous dynamic random access memory
  • DDR SDRAM double data rate synchronous dynamic random access memory
  • DDR SDRAM double data rate synchronous dynamic random access memory
  • Non-volatile memory may include disk storage devices and flash memory.
  • Flash memory may include NOR FLASH, NAND FLASH, 3D NAND FLASH, etc. according to the operating principle. It may include 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 unit. It may include universal flash storage (UFS), embedded multi media card (eMMC), etc. according to the storage specification.
  • SLC single-level cell
  • MLC multi-level cell
  • TLC triple-level cell
  • QLC quad-level cell
  • UFS universal flash storage
  • eMMC embedded multi media card
  • 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.
  • the application Before the terminal device runs an application, that is, when the terminal device starts the application after receiving an operation for opening 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.
  • the USB interface 130 is an interface that complies with the USB standard specification, and specifically 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 transmit 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.
  • 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.
  • the terminal device 100 may also adopt different interface connection methods in the above embodiments, or a combination of multiple interface connection methods.
  • 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.
  • the charging management module 140 may receive charging input from a wired charger through the USB interface 130.
  • 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.
  • 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.
  • the power management module 141 can also be set in the processor 110.
  • the power management module 141 and the charging management module 140 can also be set in the same device.
  • 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.
  • 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.
  • antenna 1 can be reused as a diversity antenna for a wireless local area network.
  • the antenna can be used in combination with a tuning switch.
  • 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.
  • at least some of the functional modules of the mobile communication module 150 can be set in the processor 110.
  • 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.
  • the modem processor may include a modulator and a demodulator.
  • 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.
  • 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.
  • the modem processor may be an independent device.
  • 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.
  • the wireless communication module 160 can provide wireless communication solutions including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) network), bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (IR) and the like applied to the terminal device 100.
  • WLAN wireless local area networks
  • BT wireless fidelity
  • GNSS global navigation satellite system
  • FM frequency modulation
  • NFC near field communication
  • IR infrared
  • 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 of the signal, amplify the signal, and convert it into electromagnetic waves for radiation via the antenna.
  • 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.
  • the GNSS may include a global positioning system (GPS), a global navigation satellite system (GLONASS), a Beidou navigation satellite system (BDS), a quasi-zenith satellite system (QZSS) and/or a satellite based augmentation system (SBAS).
  • GPS global positioning system
  • GLONASS global navigation satellite system
  • BDS Beidou navigation satellite system
  • QZSS quasi-zenith satellite system
  • SBAS satellite based augmentation system
  • 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 that execute program instructions to generate or change display information.
  • 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), Active-matrix organic light emitting diode or active-matrix organic light emitting diode (AMOLED), flexible light-emitting diode (FLED), Miniled, MicroLed, Micro-oLed, quantum dot light emitting diodes (QLED), etc.
  • the terminal device 100 may include 1 or N display screens 194, where N is a positive integer greater than 1.
  • the pressure sensor 180A is used to sense the pressure signal and can convert the pressure signal into an electrical signal.
  • the pressure sensor 180A can be set on the display screen 194.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the above-mentioned sensors 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.
  • 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.
  • 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.
  • 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.
  • relevant Internet access measures such as pre-caching content, or reducing the definition of network video, etc.
  • 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.
  • FIG. 2B exemplarily shows a software architecture diagram of the terminal device 100 .
  • 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.
  • 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 system library, and the kernel layer.
  • the application layer can include a series of application packages.
  • an application package can include camera, gallery, calendar, call, map, navigation, WLAN, Bluetooth, music APP, video APP and other applications.
  • the music APP and the video APP can be system APP or third-party APP, which is not limited in the present embodiment.
  • this type of APP can provide users with services of downloading and caching music or videos from the network through the mobile communication module.
  • the application framework layer provides application programming interface (API) and programming framework for applications in the application layer.
  • API application programming interface
  • the application framework layer includes some predefined functions.
  • the application framework layer may include a window manager, a content provider, a view system, a telephony manager, a resource manager, a notification manager, and the like.
  • 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.
  • 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.
  • 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.
  • a display interface including a text notification icon can include a view for displaying text and a view for displaying images.
  • the phone manager is used to provide communication functions of the terminal device 100, such as management of call status (including connection, disconnection, etc.).
  • the resource manager provides various resources for applications, such as localized strings, icons, images, layout files, video files, and so on.
  • 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.
  • Android Runtime includes core libraries and virtual machines. Android Runtime is responsible for the scheduling and management of the Android system.
  • the core library consists of two parts: one part is the function that needs to be called by the Java language, and the other part is the Android core library.
  • the application layer and the application framework layer run in the 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 manage the object life cycle, stack management, thread Management, security and exception management, and garbage collection functions.
  • the system library can 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.
  • functional modules such as surface manager, media library, 3D graphics processing library (such as OpenGL ES), 2D graphics engine (such as SGL), etc.
  • the surface manager is used to manage the display subsystem and provide the fusion of 2D and 3D layers for multiple applications.
  • 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.
  • the 3D graphics processing library is used to implement 3D graphics drawing, image rendering, compositing, and layer processing.
  • a 2D graphics engine is a drawing engine for 2D drawings.
  • 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.
  • the following is an example of the workflow of the software and hardware of the terminal device 100 in conjunction with the capture and photo shooting scene.
  • 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 a static image or video through the camera 193.
  • FIG. 3A exemplarily shows a hardware architecture diagram of the server 200 .
  • 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, and FIG3A takes the connection via a bus as an example. Among them:
  • 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.
  • the memory 202 is coupled to the processor 201 and is used to store various software programs and/or multiple sets of instructions.
  • 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.
  • the memory 202 can store an operating system (hereinafter referred to as system), such as embedded operating systems such as uCOS, VxWorks, RTLinux, etc.
  • 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.
  • the communication interface 203 can be used for the server 200 to communicate with other communication devices, such as the terminal device 100.
  • 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.
  • LTE long-term evolution
  • the server 200 can also be configured with a wired communication interface 203 to support wired communication.
  • the link between the server 200 and other servers can be a wired communication interface. Line communication connection.
  • 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.
  • 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.
  • 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.
  • a cell association information library information about the stuck cell
  • a network prediction algorithm information about the stuck cell
  • a prediction information database information about the network prediction algorithm
  • 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 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.
  • the server 200 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.
  • server 200 shown in FIG. 3A 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.
  • FIG. 3B exemplarily shows a software architecture diagram of the server 200 .
  • 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.
  • the cell association information base module includes: the cell switching relationship arranged on the travel route of transportation vehicles such as subways, high-speed railways, and cars, and 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, etc.
  • 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 description of Figure 6 below, which will not be repeated here.
  • 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.
  • 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.
  • 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.
  • server 200 shown in FIG. 3B 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.
  • the method comprises the following steps:
  • Phase 1 Server initialization phase.
  • the server 200 pre-stores a cell association information database, a stuck cell information database and a network prediction algorithm.
  • 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.
  • 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.
  • 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:
  • the server 200 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 covers almost all the cell information corresponding to all base stations arranged on the routes of subways, high-speed trains, cars, etc.;
  • the server 200 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.
  • Figure 5 is a schematic diagram showing the principle of establishing a cell association information base.
  • Figure 5 is a schematic diagram showing the principle of generating a cell association information base using the above method (2) or method (3).
  • the principle of establishing a cell association information database specifically includes the following steps:
  • Step 1 Manually collect skeleton data.
  • the skeleton data includes, but is not limited to, the associated information of the cells corresponding to the main base stations arranged on the routes of subways, high-speed railways, and buses.
  • the manually collected cell layout information on the direction from the museum to the airport on Metro Line 1 is: Cell 1, Cell 2, Cell 3, and Cell 4;
  • the manually collected cell layout information on the direction from city A to city B on the high-speed railway is: Cell 1, Cell 2, Cell 3, and Cell 4; or the skeleton data may also include more routes, and more cells on each route, which is not limited in the embodiments of the present application.
  • the manually collected skeleton data can be the layout of subways, high-speed railways, cars and other transportation in the previous method (2).
  • the main/partial cell switching relationship on the tool's driving route can also be the ticket purchase information or base station location information reported by the terminal device in method (3).
  • Step 2 Match the route according to the data reported by the terminal device and fill in the cell-related information.
  • 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.
  • the cell information collected by the server 200 from the terminal device is: cell 1, cell 5, cell 2 and cell 3.
  • cell 5 is a new cell between cell 1 and cell 2, so cell 5 is filled between cell 1 and cell 2.
  • 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.
  • 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.
  • 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.
  • the server 200 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, information related to the network coverage status, and the location information obtained through 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.
  • 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.
  • the server 200 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.
  • the principle of establishing a cell association information database shown in Figure 5 is only introduced using the skeleton data on two routes as an example.
  • 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, and the embodiments of the present application do not limit this.
  • FIG6 exemplarily shows a schematic diagram of a cell association information database storage model.
  • the cell association information database in FIG6 only takes the cell association information corresponding to the two routes, Line 1 from the museum to the airport and the high-speed rail from city A to city B, as examples, as well as the residence time of each cell and the probability of the previous cell being transferred to the later cell.
  • the cell association information may also include cell association information corresponding to more routes, and the switching relationship between the cells on each route may also be other, which is not limited in the embodiments of the present application.
  • 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.
  • 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.
  • 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.
  • 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:
  • 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;
  • 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;
  • 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 the call service and data service of the cell accessed by the terminal device, or also includes information such as the access time and the residence time.
  • 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.
  • 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.
  • a cell is stuck only in a specific time period and has periodic stuck, it is confirmed that the cell has a tidal effect.
  • 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.
  • 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.
  • the network prediction algorithm can achieve:
  • Phase 2 (S402-S403): The terminal device 100 reports the information of the cell it has accessed to the server 200.
  • the terminal device 100 detects a scenario that meets the network prediction.
  • 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.
  • 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 rapid movement, 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.
  • the scenarios that meet the network prediction may also include other scenarios, which are not limited in the embodiments 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.
  • the terminal device 100 sends information of multiple cells that are continuously accessed to the server 200.
  • the terminal device 100 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.
  • 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.
  • 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.
  • Phase 3 ( S404 ): The server 200 performs network prediction on the environment that the terminal device 100 is about to arrive at.
  • the server 200 performs network prediction based on the information of the cell accessed by the terminal device 100.
  • the server 200 has stored a network prediction algorithm, a cell association information library, and a stuck cell.
  • 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.
  • the stuck cells with 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.
  • the cell switching relationship on the high-speed rail route from city A to city B can be matched from the cell association information library shown in FIG. 6 above.
  • the cell switching relationship specifically includes the following three cell switching routes.
  • the 34 switching routes are all
  • the switching behaviors that will exist in the next driving route are:
  • the switching order of switching route 1 is: cell A, cell B, cell C, cell D, cell F;
  • the switching order of switching route 2 is: cell A, cell B, cell C, cell D, cell G and cell H;
  • the switching order of switching route 3 is: cell A, cell B, cell C, cell E, cell G and cell H.
  • the cell G is a stuck cell.
  • the cell G can also be called the first stuck cell.
  • 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%.
  • 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%.
  • the method for calculating the time when the terminal device arrives at the stuck cell includes any of the following:
  • the terminal device will access the stuck cell G after 45.9 seconds with a 72% probability.
  • 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.
  • the calculation method of the network prediction result described above is only an example.
  • 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 you can still refer to the above.
  • the calculated network prediction results may be different, but the calculation principle is the same, and you can still refer to the above.
  • the calculation principle is the same, and you can still refer to the above.
  • when taking values of the cell dwell time according to the probability distribution of the dwell 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 dwell probabilities corresponding to different time periods are different, but the calculation principle is the same, which will not be elaborated here.
  • Phase 4 ( S405 - S406 ): The server 200 pushes the network prediction result to the terminal device 100 .
  • the server 200 sends the network prediction result to the terminal device 100 .
  • 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.
  • 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.
  • the terminal device 100 outputs the network prediction result, and/or adjusts Internet access measures according to the network prediction result.
  • 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.
  • 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 definition of viewing network content, so as to avoid the phenomenon of users being unable to access the Internet after entering the stuck cell.
  • 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.
  • 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.
  • 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:
  • the scene recognition module in the terminal device 100 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.
  • 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
  • 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.
  • 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.
  • cell information ie, the skeleton data mentioned above
  • 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.
  • 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.
  • the network prediction algorithm module in the server 200 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.
  • 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.
  • 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.
  • 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.
  • this application 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.
  • 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.
  • 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.
  • 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.
  • the APP installed in the terminal is divided into Internet access adjustment strategies according to the network result and the probability of the result.
  • 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.
  • each step in the above method embodiment provided in the present application can be implemented by the integrated logic of the hardware in the processor.
  • the method steps disclosed in the embodiments of the present application can be directly implemented as hardware processors, or can be implemented as a combination of hardware and software modules in the processor.
  • the present application also provides a terminal device, which may include: a memory and a processor, wherein the memory may be used to store a computer program; and 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.
  • 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.
  • 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.
  • the chip system may be composed of the chip, or may include the chip and other discrete devices.
  • the processor in the chip system may be one or more.
  • the processor may be implemented by hardware or by software.
  • the processor may be a logic circuit, an integrated circuit, etc.
  • the processor may be a general-purpose processor implemented by reading software code stored in a memory.
  • 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.
  • 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.
  • 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.
  • FPGA field programmable gate array
  • ASIC application specific integrated circuit
  • SoC system on chip
  • CPU central processor unit
  • NP network processor
  • DSP digital signal processor
  • MCU microcontroller unit
  • PLD programmable logic device
  • 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.
  • a computer program also referred to as code, or instruction
  • 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).
  • a computer program also referred to as code or instruction.
  • the computer program executes the method executed by the terminal device in any of the above embodiments.
  • all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof.
  • all or part of the embodiments may be implemented in the form of a computer program product.
  • the computer program product includes one or more computer instructions.
  • the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.
  • the computer instructions may 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 may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium.
  • the transmission can be performed from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means.
  • the computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media integrated therein.
  • the available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk).
  • the processes can be completed by a computer program to instruct the relevant hardware, and the program can be stored in a computer-readable storage medium.
  • the program When the program is executed, it can include the processes of the above-mentioned method embodiments.
  • the aforementioned storage medium includes: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

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Abstract

本申请提供了网络预测方法及其终端设备、服务器和通信系统，该方法包括：服务器根据终端设备连续接入的N个小区的信息，从小区关联信息库中匹配到该终端设备在之后的移动路线上可能存在的小区切换关系，然后结合该小区切换关系中包含的卡顿小区来计算网络预测结果，并将网络预测结果发送至终端设备。其中，网络预测结果包括但不限于：预计终端设备到达卡顿小区的时间，在该卡顿小区的驻留时间，预计到达卡顿小区的时间所对应的概率，以及在该卡顿小区的驻留时间所对应的概率等。这样，可以提示用户预先采取相关上网措施，或者用于控制终端设备自动采取相关上网措施，避免在终端设备接入卡顿小区过程中给用户带来上网卡顿等的问题。

Description

网络预测方法及其终端设备、服务器和通信系统
本申请要求于2023年02月20日提交中国专利局、申请号为202310183467.3、申请名称为“网络预测方法及其终端设备、服务器和通信系统”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及终端领域，尤其涉及一种网络预测方法及其终端设备、服务器和通信系统。
背景技术
在现网配置中，因为一些小区建设不周或数据配置不当的原因，会导致这些小区承载的数据业务和通话业务出现问题，进而给接入这些小区的终端设备带来例如上网卡顿、通话失败、通话质量差等的问题。
如何解决上述问题，则是亟待解决的问题。
发明内容
本申请提供了网络预测方法及其终端设备、服务器和通信系统，该方法包括：服务器根据终端设备连续接入的N个小区的信息，从小区关联信息库中匹配到该终端设备在之后的移动路线上可能存在的小区切换关系，然后结合该小区切换关系中包含的卡顿小区来计算网络预测结果，并将网络预测结果发送至终端设备。这样，可以提示用户预先采取相关上网措施，或者用于控制终端设备自动采取相关上网措施，避免在终端设备接入卡顿小区过程中给用户带来上网卡顿等的问题。
第一方面，本申请提供了一种网络预测方法，该方法应用于服务器，该方法包括：该服务器接收第一设备发送的第一小区信息，该第一小区信息包括该第一设备连续接入的多个小区的信息；该服务器基于该第一小区信息生成网络预测结果，该网络预测结果表征该第一设备即将接入至卡顿小区；该服务器向该第一设备发送该网络预测结果；该网络预测结果用于指示该第一设备输出提示信息，和/或，调整上网策略。
实施第一方面提供的方法后，服务器可以根据第一设备上报的小区信息，实时为第一设备进行网络预测，以达到提示用户或控制第一设备根据网络预测结果预先调整上网措施，保证第一设备的用户的上网体验不受网络环境的影响。
结合第一方面提供的方法，该网络预测结果用于指示该第一设备调整上网策略具体包括：指示该第一设备缓存网络内容，和/或，降低观看网络内容的清晰度。
这样，第一设备能够根据网络预测结果自动调整上网策略，在第一设备进入到网络环境恶劣的卡顿小区时，仍然能够保证用户对网络环境无感知的情况下正常观看网络内容，提高用户的上网体验。
结合第一方面提供的方法，该网络预测结果包括第一卡顿小区的信息，该第一卡顿小区的信息包括以下任一项或多项：该第一设备接入至第一卡顿小区所需的第一时长，该第一设备在该第一时长内接入至该第一卡顿小区的第一概率，在该第一卡顿小区驻留的第二 时长，该第一卡顿小区驻留的第二时长的第二概率。
这样，可以得到精确的网络预测结果，使得用户能够根据网络结果和该结果发生的概率决定是否调整相关上网策略以及如何调整策略等。
结合第一方面提供的方法，该第一时长和该第一概率为该服务器根获取计到的多个设备在相应小区驻留时间的概率分布而确定的；该第二时长和该第二概率为该服务器根据获取到的多个设备在该第一卡顿小区驻留时间的概率分布而确定的。
这样，可以根据收集到的大数据来准确统计各个小区驻留时间的概率分布，进而能够基于概率分布获取到更加精确的网络预测结果，保证网络预测结果的准确性，提升用户体验感。
结合第一方面提供的方法，该第一卡顿小区包括：该终端设备即将依次接入的多个小区中属于卡顿小区的小区；该终端设备即将依次接入的多个小区包括：小区关联信息库中与该第一小区信息匹配的小区；其中，该小区关联信息库包含多路小区切换关系，每路小区切换关系包括：多个小区依次切换的顺序。
这样，可以根据第一设备连续接入的小区先匹配到相应的路线，然后确定该路线上的小区切换关系，进而获取到小区切换关系的卡顿小区。
结合第一方面提供的方法，该第一卡顿小区的相关信息存储在卡顿小区信息库中，卡顿小区信息库用于服务器根据第一小区信息从小区关联信息库中获取第一设备即将依次接入的多个小区后，判断该多个小区中是否包含属于卡顿小区信息库的小区，若是，则为第一卡顿小区。
结合第一方面提供的方法，该第一卡顿小区包括：该终端设备即将依次接入的多个小区中在当前时刻或当前时段属于卡顿小区的小区；
这样，可以根据卡顿小区具备的潮汐效应来预测网络结果，避免将小区的卡顿时间与第一设备经过该小区的时间不同的小区作为卡顿小区进行网络预测，即不会将非卡顿时间内的卡顿小区作为卡顿小区进行预测，从而避免网络预测误判的问题。其中潮汐效应包括在高峰时间段内地铁、高铁、汽车等行驶路线上的终端设备是比非高峰时间端多的，因此会出现业务卡顿的现象。
结合第一方面提供的方法，在该服务器基于该第一小区信息生成网络预测结果之前，该方法还包括：该服务器接收第二设备发送的第二小区信息，该第二小区信息为该第二设备连续接入的多个小区的信息；该服务器将该第二小区信息填充至骨架数据，以更新得到该小区关联信息库；该骨架数据包括多个路线上布局的小区的切换关系。
这样，可以通过收集大数据来生成更加全面的小区关联信息库，进而获取到根据准确的网络预测结果。
结合第一方面提供的方法，该第二设备连续接入的多个小区的信息具体包括：每个小区的标识、每个小区的接入时间和驻留时间。
结合第一方面提供的方法，在该服务器基于该第一小区信息生成网络预测结果之前，该方法还包括：该第二设备向该服务器发送第三小区信息，该第三小区信息指示该第二设备接入的小区的业务质量；该服务器根据该业务质量确定该卡顿小区。
此外，上述第三小区信息还可以包括第二设备接入的小区所对应的时间段，例如接入 时间，驻留时间等，用于服务器根据小区在对应时间段的业务质量来判断小区是否卡顿以及该卡顿小区是否具备潮汐效应等。
这样，可以通过收集大数据来生成更加全面的卡顿小区信息库，进而获取到根据准确的网络预测结果。
第二方面，本申请提供了一种网络预测方法，该方法应用于第一设备，该方法包括：该第一设备向服务器发送第一小区信息，该第一小区信息包括该第一设备连续接入的多个小区的信息；该第一小区信息用于该服务器生成网络预测结果，该网络预测结果表征该第一设备即将接入至卡顿小区；第一设备接收该服务器发送的该网络预测结果；该第一设备根据该网络预测结果输出提示信息，和/或，调整上网策略。
实施第二方面提供的方法后，第一设备可以向服务器上报的小区信息，用于服务器实时对第一设备进行网络预测，以达到提示用户或控制第一设备根据网络预测结果预先调整上网措施，保证第一设备的用户的上网体验不受网络环境的影响。
结合第二方面提供的方法，该第一设备根据该网络预测结果调整上网策略具体包括：该第一设备缓存网络内容，和/或，降低观看网络内容的清晰度。
这样，第一设备能够根据网络预测结果自动调整上网策略，在第一设备进入到网络环境恶劣的卡顿小区时，仍然能够保证用户对网络环境无感知的情况下正常观看网络内容，提高用户的上网体验。
结合第二方面提供的方法，该网络预测结果包括第一卡顿小区的信息，该第一卡顿小区的信息包括以下任一项或多项：该第一设备接入至第一卡顿小区所需的第一时长，该第一设备在该第一时长内接入至该第一卡顿小区的第一概率，在该第一卡顿小区驻留的第二时长，该第一卡顿小区驻留的第二时长的第二概率。
这样，可以得到精确的网络预测结果，使得用户能够根据网络结果和该结果发生的概率决定是否调整相关上网策略以及如何调整策略等。
结合第二方面提供的方法，该第一时长和该第一概率为该服务器根获取计到的多个设备在相应小区驻留时间的概率分布而确定的；该第二时长和该第二概率为该服务器根据获取到的多个设备在该第一卡顿小区驻留时间的概率分布而确定的。
这样，可以根据收集到的大数据来准确统计各个小区驻留时间的概率分布，进而能够基于概率分布获取到更加精确的网络预测结果，保证网络预测结果的准确性，提升用户体验感。
结合第二方面提供的方法，该第一卡顿小区包括：该终端设备即将依次接入的多个小区中属于卡顿小区的小区；该终端设备即将依次接入的多个小区包括：小区关联信息库中与该第一小区信息匹配的小区；其中，该小区关联信息库包含多路小区切换关系，每路小区切换关系包括：多个小区依次切换的顺序。
结合第二方面提供的方法，该第一卡顿小区的相关信息存储在卡顿小区信息库中，卡顿小区信息库用于服务器根据第一小区信息从小区关联信息库中获取第一设备即将依次接入的多个小区后，判断该多个小区中是否包含属于卡顿小区信息库的小区，若是，则为第一卡顿小区。
这样，可以根据第一设备连续接入的小区先匹配到相应的路线，然后确定该路线上的 小区切换关系，进而获取到小区切换关系的卡顿小区。
结合第二方面提供的方法，该第一卡顿小区包括：该终端设备即将依次接入的多个小区中在当前时刻当前时段属于卡顿小区的小区。
这样，可以根据卡顿小区具备的潮汐效应来预测网络结果，避免将小区的卡顿时间与第一设备经过该小区的时间不同的小区作为卡顿小区进行网络预测，即不会将非卡顿时间内的卡顿小区作为卡顿小区进行预测，从而避免网络预测误判的问题。其中潮汐效应包括在高峰时间段内地铁、高铁、汽车等行驶路线上的终端设备是比非高峰时间端多的，因此会出现业务卡顿的现象。
结合第二方面提供的方法，在该第一设备向该服务器发送第一小区信息之前，该方法还包括：该第一设备识别到处于地铁、高铁或汽车行驶的场景。
这样，由于在这些场景中，第一设备因为快速移动位置会频繁的切换小区，很有可能切换到卡顿小区，给用户带来上网卡顿等的体验，因此将这类场景作为重点对象进行网络预测。
第三方面，本申请提供了一种网络预测方法，该方法应用于包含第一设备和服务器的通信系统，该方法包括：该第一设备向该服务器发送第一小区信息，该第一小区信息包括该第一设备连续接入的多个小区的信息；该服务器基于该第一小区信息生成网络预测结果，该网络预测结果表征该第一设备即将接入至卡顿小区；该服务器向该第一设备发送该网络预测结果；该第一设备根据该网络预测结果输出提示信息，和/或，调整上网策略。
实施第三方面提供的方法后，服务器可以根据第一设备上报的小区信息，实时为第一设备进行网络预测，以达到提示用户或控制第一设备根据网络预测结果预先调整上网措施，保证第一设备的用户的上网体验不受网络环境的影响。
结合第三方面提供的方法，该第一设备根据该网络预测结果调整上网策略具体包括缓存网络内容，和/或，降低观看网络内容的清晰度。
这样，第一设备能够根据网络预测结果自动调整上网策略，在第一设备进入到网络环境恶劣的卡顿小区时，仍然能够保证用户对网络环境无感知的情况下正常观看网络内容，提高用户的上网体验。
结合第三方面提供的方法，该网络预测结果包括第一卡顿小区的信息，该第一卡顿小区的信息包括：该第一设备接入至第一卡顿小区所需的第一时长，该第一设备在该第一时长内接入至该第一卡顿小区的第一概率，在该第一卡顿小区驻留的第二时长，该第一卡顿小区驻留的第二时长的第二概率。
这样，可以得到精确的网络预测结果，使得用户能够根据网络结果和该结果发生的概率决定是否调整相关上网策略以及如何调整策略等。
结合第三方面提供的方法，该第一时长和该第一概率为该服务器根据统计到的多个设备在相应小区驻留时间的概率分布而确定的；该第二时长和该第二概率为该服务器根据统计到的多个设备在该第一卡顿小区驻留时间的概率分布而确定的。
这样，可以根据收集到的大数据来准确统计各个小区驻留时间的概率分布，进而能够基于概率分布获取到更加精确的网络预测结果，保证网络预测结果的准确性，提升用户体验感。
结合第三方面提供的方法，该第一卡顿小区包括：该终端设备即将依次接入的多个小区中属于卡顿小区的小区；该终端设备即将依次接入的多个小区包括：小区关联信息库中与该第一小区信息匹配的小区；其中，该小区关联信息库包含多路小区切换关系，每路小区切换关系包括：多个小区依次切换的顺序。
结合第三方面提供的方法，该第一卡顿小区的相关信息存储在卡顿小区信息库中，卡顿小区信息库用于服务器根据第一小区信息从小区关联信息库中获取第一设备即将依次接入的多个小区后，判断该多个小区中是否包含属于卡顿小区信息库的小区，若是，则为第一卡顿小区。
这样，可以根据第一设备连续接入的小区先匹配到相应的路线，然后确定该路线上的小区切换关系，进而获取到小区切换关系的卡顿小区。
结合第三方面提供的方法，该第一卡顿小区包括：该终端设备即将依次接入的多个小区中在当前时刻属于卡顿小区的小区；
这样，可以根据卡顿小区具备的潮汐效应来预测网络结果，避免将小区的卡顿时间与第一设备经过该小区的时间不同的小区作为卡顿小区进行网络预测，即不会将非卡顿时间内的卡顿小区作为卡顿小区进行预测，从而避免网络预测误判的问题。其中潮汐效应包括在高峰时间段内地铁、高铁、汽车等行驶路线上的终端设备是比非高峰时间端多的，因此会出现业务卡顿的现象。
结合第三方面提供的方法，该通信系统还包括一个或多个第二设备，在该服务器基于该第一小区信息生成网络预测结果之前，该方法还包括：该第二设备向该服务器发送第二小区信息，该第二小区信息为该第二设备连续接入的多个小区的信息；该服务器将该第二小区信息填充至骨架数据，以更新该小区关联信息库；该骨架数据包括多个路线上布局的小区的切换关系。
这样，可以通过收集大数据来生成更加全面的小区关联信息库，进而获取到根据准确的网络预测结果。
结合第三方面提供的方法，该第二设备连续接入的多个小区的信息具体包括：每个小区的标识、每个小区的接入时间和驻留时间。
结合第三方面提供的方法，在该服务器基于该第一小区信息生成网络预测结果之前，该方法还包括：该第二设备向该服务器发送第三小区信息，该第三小区信息指示该第二设备接入的小区的业务质量；该服务器根据该业务质量确定该卡顿小区。
此外，上述第三小区信息还可以包括第二设备接入的小区所对应的时间段，例如接入时间，驻留时间等，用于服务器根据小区在对应时间段的业务质量来判断小区是否卡顿以及该卡顿小区是否具备潮汐效应等。
这样，可以通过收集大数据来生成更加全面的卡顿小区信息库，进而获取到根据准确的网络预测结果。
结合第三方面提供的方法，在该第一设备向该服务器发送第一小区信息之前，该方法还包括：该第一设备识别到处于地铁、高铁或汽车行驶的场景。
这样，由于在这些场景中，第一设备因为快速移动位置会频繁的切换小区，很有可能切换到卡顿小区，给用户带来上网卡顿等的体验，因此将这类场景作为重点对象进行网络 预测。
第四方面，本申请提供了一种服务器，该服务器包括存储器、一个或多个处理器；该存储器与该一个或多个处理器耦合，该存储器用于存储计算机程序代码，该计算机程序代码包括计算机指令，该一个或多个处理器调用该计算机指令以使得该服务器执行如第一方面中任一项描述的方法。
第五方面，本申请提供了一种终端设备，该终端设备包括存储器、一个或多个处理器；该存储器与该一个或多个处理器耦合，该存储器用于存储计算机程序代码，该计算机程序代码包括计算机指令，该一个或多个处理器调用该计算机指令以使得该终端设备执行如第二方面中任一项描述的方法。
第六方面，本申请提供了一种芯片，该芯片应用于电子设备，该芯片包括一个或多个处理器，该处理器用于调用计算机指令以使得该电子设备执行如第一方面或第二方面中任一项描述的方法。
第七方面，本申请提供了一种计算机可读存储介质，该计算机可读存储介质包括指令，当该指令在电子设备上运行时，使得该电子设备执行如第一方面或第二方面中任一项描述的方法。
附图说明
图1为本申请实施例提供的一种应用场景示意图；
图2A为本申请实施例提供的一种终端设备100的硬件架构图；
图2B为本申请实施例提供的一种终端设备100的软件架构图；
图3A为本申请实施例提供的一种服务器200的硬件架构图；
图3B为本申请实施例提供的一种服务器200的软件架构图；
图4为本申请实施例提供的一种网络预测方法流程图；
图5为本申请实施例提供的一种建立小区关联信息库的原理示意图；
图6为本申请实施例提供的一种小区关联信息库存储模型示意图；
图7为本申请实施例提供的一种网络预测架构图。
具体实施方式
下面将结合附图对本申请实施例中的技术方案进行清楚、详尽地描述。其中，在本申请实施例的描述中，除非另有说明，“/”表示或的意思，例如，A/B可以表示A或B；文本中的“和/或”仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。
以下，术语“第一”、“第二”仅用于描述目的，而不能理解为暗示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括一个或者更多个该特征，在本申请实施例的描述中，除非另有说明，“多个”的含义是两个或两个以上。
在本申请中提及“实施例”意味着，结合实施例描述的特定特征、结构或特性可以包含 在本申请的至少一个实施例中。在说明书中的各个位置出现该短语并不一定均是指相同的实施例，也不是与其它实施例互斥的独立的或备选的实施例。本领域技术人员显式地和隐式地理解的是，本申请所描述的实施例可以与其它实施例相结合。
本申请以下实施例中的术语“用户界面(user interface，UI)”，是应用程序或操作系统与用户之间进行交互和信息交换的介质接口，它实现信息的内部形式与用户可以接受形式之间的转换。用户界面是通过java、可扩展标记语言(extensible markup language，XML)等特定计算机语言编写的源代码，界面源代码在终端设备上经过解析，渲染，最终呈现为用户可以识别的内容。用户界面常用的表现形式是图形用户界面(graphic user interface，GUI)，是指采用图形方式显示的与计算机操作相关的用户界面。它可以是在终端设备的显示屏中显示的文本、图标、按钮、菜单、选项卡、文本框、对话框、状态栏、导航栏、Widget等可视的界面元素。
参考图1，图1示例性示出本申请提供的一种应用场景示意图。
如图1所示，本申请提供的网络预测方法适用的应用场景为，布局在包括但不限于：地铁、高铁、汽车的行驶路线上的通信系统，该通信系统包括一个或多个终端设备、一个或多个服务器，以及一个或多个网络侧设备。例如图1示例性示出的终端设备100、服务器200、网络侧设备301和网络侧设备302。
本申请提供的通信系统可以是以下任意一种：全球移动通信(global system for mobile communications，GSM)系统、码分多址接入(Code Division Multiple Access，CDMA)系统、宽带码分多址(Wideband Code Division Multiple Access，WCDMA)系统、通用分组无线业务(general packet radio service，GPRS)、长期演进(Long Term Evolution，LTE)系统、LTE频分双工(frequency division duplex，FDD)系统、LTE时分双工(time division duplex，TDD)、通用移动通信系统(Universal Mobile Telecommunication System，UMTS)、全球互联微波接入(Worldwide Interoperability for Microwave Access，WiMAX)通信系统、第五代(5th generation，5G)系统或新无线(new radio，NR)等。
本申请提供的终端设备100可以是手机、平板电脑、手持计算机、超级移动个人计算机(ultra-mobile personal computer，UMPC)、上网本，以及蜂窝电话、个人数字助理(personal digital assistant，PDA)、可穿戴式设备、车载设备等等，本申请实施例对此不作限制。
本申请提供的服务器200可以是为终端设备100中的一个或多个应用提供网络预测计算和应用服务的服务器。服务器200可以是由终端设备100的开发商或者是提供商所提供的一个或多个服务器。
本申请提供的网络侧设备301、网络侧设备302是用于与终端设备通信的设备，该网络侧设备301、网络侧设备302可以是GSM系统、CDMA系统中的基站(base transceiver station，BTS)，也可以是WCDMA系统中的基站(NodeB，NB)，还可以是LTE系统中的演进型基站(evolved NodeB，eNodeB)，以及还可以是5G系统中的下一代基站(new Generation NodeB，gNodeB)等等，本申请实施例并不限定。
在本申请实施例中，网络侧设备覆盖的所有区域或部分区域可以被划分为一个小区，例如网络侧设备301覆盖的区域包括小区A、小区B和小区C，网络侧设备300-2覆盖的 区域包括小区D。网络侧设备301、网络侧设备302可以为所管辖的小区分配传输资源，正常情况下，当终端设备100在网络侧设备301、网络侧设备302覆盖的区域内时，终端设备100可以通过接入对应小区的无线信道资源与网络侧设备进行通信，或者通过网络侧设备与其他终端设备、服务器200等进行通信。
但是，在一些特殊情况下，如某个小区业务负载超负荷、或者该小区所属基站建设不周、配置不当的情况下，终端设备100可能无法接入该小区，或者接入该小区后因传输资源拥堵，进而给终端设备100带来例如上网卡顿、通话失败、通话质量差等的问题。特别在一些地铁/高铁/汽车的行驶路线上，随着用户携带的终端设备100的快速移动，终端设备100会频繁切换到不同的小区，也极易因接入到卡顿小区，进而带来糟糕体验。
为了解决上述问题，本申请提供了网络预测方法及其终端设备、服务器和通信系统，该方法包括：服务器200根据终端设备100连续接入的N个小区的信息，从小区关联信息库中匹配到，该终端设备100在之后的移动路线上可能存在的小区切换关系，然后结合该小区切换关系中包含的卡顿小区来计算网络预测结果，并将网络预测结果发送至终端设备100。其中，网络预测结果包括但不限于：预计终端设备100到达卡顿小区的时间，在该卡顿小区的驻留时间，预计到达卡顿小区的时间所对应的概率，以及在该卡顿小区的驻留时间所对应的概率等。这样，可用于提示用户预先采取相关上网措施，或者用于控制终端设备100自动采取相关上网措施，避免在终端设备100接入卡顿小区过程中给用户带来上网卡顿等的问题。
在本申请实施例中，N个小区的信息中的N可以是大于或等于2的任意整数。当N值越大时，则服务器200可以更加精确的为终端设备100匹配到之后的移动路线上可能存在的小区切换关系，进而能够精准预测即将所处的网络环境的质量；当N值越小时，则服务器200可以更快的为终端设备100匹配到之后的移动路线上可能存在的小区切换关系，进而能够达到实时预测网络环境的目的。
在本申请实施例中，终端设备100还可以称为第一设备，终端设备100向服务器200发送的N个小区的信息还可以被称为第一小区信息。
在本申请实施例中，小区关联信息库为服务器200端预先在人工输入的骨架数据的基础上，结合多个终端设备(还可以称为第二设备)分别上报的连续接入的多个小区的信息(还可以称为第二小区信息)，建立而成的小区关联信息库。小区关联信息库包括：布局在地铁、高铁、汽车等交通工具的行驶路线上的小区切换关系，该小区切换关系具体可以包括：前一个小区切换到后一个小区的概率，以及每个小区的驻留时间的概率分布等。关于小区关联信息库的具体建立过程可以参考后文方法流程的S401处的描述，以及关于小区关联信息库的存储模型可以参考后文图6的描述，在此暂不赘述。
接下来，将依次介绍本申请涉及的终端设备100、服务器200的软硬件架构。
参考图2A，图2A示例性示出终端设备100的硬件架构图。
如图2A所示，终端设备100可以包括处理器110，外部存储器接口120，内部存储器121，通用串行总线(universal serial bus，USB)接口130，充电管理模块140，电源管理模块 141，电池142，天线1，天线2，移动通信模块150，无线通信模块160，音频模块170，扬声器170A，受话器170B，麦克风170C，耳机接口170D，传感器模块180，按键190，指示器192，摄像头193，显示屏194，以及用户标识模块(subscriber identification module，SIM)卡接口195等。其中传感器模块180可以包括压力传感器180A，触摸传感器180B，加速度传感器180C，或者还可以包括未示出的气压传感器，磁传感器，距离传感器，接近光传感器，指纹传感器，温度传感器，陀螺仪传感器，环境光传感器，骨传导传感器等。
可以理解的是，本发明实施例示意的结构并不构成对终端设备100的具体限定。在本申请另一些实施例中，终端设备100可以包括比图示更多或更少的部件，或者组合某些部件，或者拆分某些部件，或者不同的部件布置。图示的部件可以以硬件，软件或软件和硬件的组合实现。
处理器110可以包括一个或多个处理单元，例如：处理器110可以包括应用处理器(application processor，AP)，调制解调处理器，图形处理器(graphics processing unit，GPU)，图像信号处理器(image signal processor，ISP)，控制器，视频编解码器，数字信号处理器(digital signal processor，DSP)，基带处理器，和/或神经网络处理器(neural-network processing unit，NPU)等。其中，不同的处理单元可以是独立的器件，也可以集成在一个或多个处理器中。
控制器可以根据指令操作码和时序信号，产生操作控制信号，完成取指令和执行指令的控制。
处理器110中还可以设置存储器，用于存储指令和数据。在一些实施例中，处理器110中的存储器为高速缓冲存储器。该存储器可以保存处理器110刚用过或循环使用的指令或数据。如果处理器110需要再次使用该指令或数据，可从所述存储器中直接调用。避免了重复存取，减少了处理器110的等待时间，因而提高了系统的效率。
在一些实施例中，处理器110可以包括一个或多个接口。接口可以包括集成电路(inter-integrated circuit，I2C)接口，集成电路内置音频(inter-integrated circuit sound，I2S)接口，脉冲编码调制(pulse code modulation，PCM)接口，通用异步收发传输器(universal asynchronous receiver/transmitter，UART)接口，移动产业处理器接口(mobile industry processor interface，MIPI)，通用输入输出(general-purpose input/output，GPIO)接口，用户标识模块(subscriber identity module，SIM)接口，外部存储器接口120，和/或通用串行总线(universal serial bus，USB)接口等。
外部存储器接口120可以用于连接外部的非易失性存储器，实现扩展终端设备100的存储能力。外部的非易失性存储器通过外部存储器接口120与处理器110通信，实现数据存储功能。例如将音乐，视频等文件保存在外部的非易失性存储器中。
终端设备100还可以包括内部存储器121，内部存储器121可以包括一个或多个随机存取存储器(random access memory，RAM)和一个或多个非易失性存储器(non-volatile memory，NVM)。
随机存取存储器可以包括静态随机存储器(static random-access memory，SRAM)、动态随机存储器(dynamic random access memory，DRAM)、同步动态随机存储器(synchronous dynamic random access memory,SDRAM)、双倍资料率同步动态随机存取存储器(double data rate synchronous dynamic random access memory,DDR SDRAM，例如第五 代DDR SDRAM一般称为DDR5SDRAM)等；随机存取存储器可以由处理器110直接进行读写，可以用于存储操作系统或其他正在运行中的程序的可执行程序(例如机器指令)，还可以用于存储用户及应用程序的数据等。
非易失性存储器可以包括磁盘存储器件、快闪存储器(flash memory)。快闪存储器按照运作原理划分可以包括NOR FLASH、NAND FLASH、3D NAND FLASH等，按照存储单元电位阶数划分可以包括单阶存储单元(single-level cell,SLC)、多阶存储单元(multi-level cell,MLC)、三阶储存单元(triple-level cell,TLC)、四阶储存单元(quad-level cell,QLC)等，按照存储规范划分可以包括通用闪存存储(英文：universal flash storage，UFS)、嵌入式多媒体存储卡(embedded multi media Card，eMMC)等。
在本申请实施例中，外部存储器接口120所连接的外部的非易失性存储器和上述内部存储器121中的非易失性存储器通常还可以被称为终端设备的外存。这些非易失性存储器可用于存储可执行程序，用户及应用程序的数据等。在终端设备运行某一应用之前，即终端设备接收到用于打开该应用的操作后启动该应用的过程时，该应用需要执行数据初始化、读写数据库和加载数据资源，也就是说该应用需要将存储与非易失性存储器中的可执行程序，用户及应用程序的数据提前加载到随机存取存储器中，用于处理器110直接进行读写。
USB接口130是符合USB标准规范的接口，具体可以是Mini USB接口，Micro USB接口，USB Type C接口等。USB接口130可以用于连接充电器为终端设备100充电，也可以用于终端设备100与外围设备之间传输数据。也可以用于连接耳机，通过耳机播放音频。该接口还可以用于连接其他终端设备，例如鼠标、键盘或者AR设备等。
可以理解的是，本发明实施例示意的各模块间的接口连接关系，只是示意性说明，并不构成对终端设备100的结构限定。在本申请另一些实施例中，终端设备100也可以采用上述实施例中不同的接口连接方式，或多种接口连接方式的组合。
充电管理模块140用于从充电器接收充电输入。其中，充电器可以是无线充电器，也可以是有线充电器。在一些有线充电的实施例中，充电管理模块140可以通过USB接口130接收有线充电器的充电输入。在一些无线充电的实施例中，充电管理模块140可以通过终端设备100的无线充电线圈接收无线充电输入。充电管理模块140为电池142充电的同时，还可以通过电源管理模块141为终端设备供电。
电源管理模块141用于连接电池142，充电管理模块140与处理器110。电源管理模块141接收电池142和/或充电管理模块140的输入，为处理器110，内部存储器121，显示屏194，摄像头193，和无线通信模块160等供电。电源管理模块141还可以用于检测电池容量，电池循环次数，电池健康状态(漏电，阻抗)等参数。在其他一些实施例中，电源管理模块141也可以设置于处理器110中。在另一些实施例中，电源管理模块141和充电管理模块140也可以设置于同一个器件中。
终端设备100的无线通信功能可以通过天线1，天线2，移动通信模块150，无线通信模块160，调制解调处理器以及基带处理器等实现。
天线1和天线2用于发射和接收电磁波信号。终端设备100中的每个天线可用于覆盖单个或多个通信频带。不同的天线还可以复用，以提高天线的利用率。例如：可以将天线1复用为无线局域网的分集天线。在另外一些实施例中，天线可以和调谐开关结合使用。
移动通信模块150可以提供应用在终端设备100上的包括2G/3G/4G/5G等无线通信的解决方案。移动通信模块150可以包括至少一个滤波器，开关，功率放大器，低噪声放大器(low noise amplifier，LNA)等。移动通信模块150可以由天线1接收电磁波，并对接收的电磁波进行滤波，放大等处理，传送至调制解调处理器进行解调。移动通信模块150还可以对经调制解调处理器调制后的信号放大，经天线1转为电磁波辐射出去。在一些实施例中，移动通信模块150的至少部分功能模块可以被设置于处理器110中。在一些实施例中，移动通信模块150的至少部分功能模块可以与处理器110的至少部分模块被设置在同一个器件中。
调制解调处理器可以包括调制器和解调器。其中，调制器用于将待发送的低频基带信号调制成中高频信号。解调器用于将接收的电磁波信号解调为低频基带信号。随后解调器将解调得到的低频基带信号传送至基带处理器处理。低频基带信号经基带处理器处理后，被传递给应用处理器。应用处理器通过音频设备(不限于扬声器170A，受话器170B等)输出声音信号，或通过显示屏194显示图像或视频。在一些实施例中，调制解调处理器可以是独立的器件。在另一些实施例中，调制解调处理器可以独立于处理器110，与移动通信模块150或其他功能模块设置在同一个器件中。
无线通信模块160可以提供应用在终端设备100上的包括无线局域网(wireless local area networks，WLAN)(如无线保真(wireless fidelity，Wi-Fi)网络)，蓝牙(bluetooth，BT)，全球导航卫星系统(global navigation satellite system，GNSS)，调频(frequency modulation，FM)，近距离无线通信技术(near field communication，NFC)，红外技术(infrared，IR)等无线通信的解决方案。无线通信模块160可以是集成至少一个通信处理模块的一个或多个器件。无线通信模块160经由天线接收电磁波，将电磁波信号调频以及滤波处理，将处理后的信号发送到处理器110。无线通信模块160还可以从处理器110接收待发送的信号，对其进行调频，放大，经天线转为电磁波辐射出去。
在一些实施例中，终端设备100的天线和无线通信模块160耦合，使得终端设备100可以通过无线通信技术与网络以及其他设备通信。所述无线通信技术可以包括全球移动通讯系统(global system for mobile communications，GSM)，通用分组无线服务(general packet radio service，GPRS)，码分多址接入(code division multiple access，CDMA)，宽带码分多址(wideband code division multiple access，WCDMA)，时分码分多址(time-division code division multiple access，TD-SCDMA)，长期演进(long term evolution，LTE)，BT，GNSS，WLAN，NFC，FM，和/或IR技术等。所述GNSS可以包括全球卫星定位系统(global positioning system，GPS)，全球导航卫星系统(global navigation satellite system，GLONASS)，北斗卫星导航系统(beidou navigation satellite system，BDS)，准天顶卫星系统(quasi-zenith satellite system，QZSS)和/或星基增强系统(satellite based augmentation systems，SBAS)。
终端设备100通过GPU，显示屏194，以及应用处理器等实现显示功能。GPU为图像处理的微处理器，连接显示屏194和应用处理器。GPU用于执行数学和几何计算，用于图形渲染。处理器110可包括一个或多个GPU，其执行程序指令以生成或改变显示信息。
显示屏194用于显示图像，视频等。显示屏194包括显示面板。显示面板可以采用液晶显示屏(liquid crystal display，LCD)，有机发光二极管(organic light-emitting diode，OLED)， 有源矩阵有机发光二极体或主动矩阵有机发光二极体(active-matrix organic light emitting diode的，AMOLED)，柔性发光二极管(flex light-emitting diode，FLED)，Miniled，MicroLed，Micro-oLed，量子点发光二极管(quantum dot light emitting diodes，QLED)等。在一些实施例中，终端设备100可以包括1个或N个显示屏194，N为大于1的正整数。
压力传感器180A用于感受压力信号，可以将压力信号转换成电信号。在一些实施例中，压力传感器180A可以设置于显示屏194。压力传感器180A的种类很多，如电阻式压力传感器，电感式压力传感器，电容式压力传感器等。电容式压力传感器可以是包括至少两个具有导电材料的平行板。当有力作用于压力传感器180A，电极之间的电容改变。终端设备100根据电容的变化确定压力的强度。当有触摸操作作用于显示屏194，终端设备100根据压力传感器180A检测所述触摸操作强度。终端设备100也可以根据压力传感器180A的检测信号计算触摸的位置。在一些实施例中，作用于相同触摸位置，但不同触摸操作强度的触摸操作，可以对应不同的操作指令。例如：当有触摸操作强度小于第一压力阈值的触摸操作作用于短消息应用图标时，执行查看短消息的指令。当有触摸操作强度大于或等于第一压力阈值的触摸操作作用于短消息应用图标时，执行新建短消息的指令。
触摸传感器180B，也称“触控器件”。触摸传感器180B可以设置于显示屏194，由触摸传感器180B与显示屏194组成触摸屏，也称“触控屏”。触摸传感器180B用于检测作用于其上或附近的触摸操作。触摸传感器可以将检测到的触摸操作传递给应用处理器，以确定触摸事件类型。可以通过显示屏194提供与触摸操作相关的视觉输出。在另一些实施例中，触摸传感器180B也可以设置于终端设备100的表面，与显示屏194所处的位置不同。
加速度传感器180C可检测终端设备100在各个方向上(一般为三轴)加速度的大小。当终端设备100静止时可检测出重力的大小及方向。还可以用于识别电子设备姿态，应用于横竖屏切换，计步器等应用。
在本申请的另一些实施例中，上述传感器例如压力传感器180A，触摸传感器180B除了可以设置于终端设备100的显示屏194中，或者也可以设置于终端设备100的键盘处的触控板区域，用于接收用户输入的操作。具体的，压力传感器180A可以检测到用户通过手指或者触控笔来点击触控面板的操作，然后压力传感器180A可以根据用户输入的操作生成对应的压力信息，并将该压力信息发送至处理器110，处理器110可以根据压力信息获知用户作用于显示屏中的坐标信息，最后根据坐标信息执行相应的操作。
在本申请实施例中，处理器110可以在通过加速度传感器180C检测到的数据确定用户处于乘坐地铁/高铁/汽车的场景下，通过移动通信模块150/无线通信模块160向服务器200上报移动通信模块150连续接入的N个小区的信息，用于服务器200根据该连续接入的N个小区的信息确定终端设备100之后的移动路线上可能存在的小区切换关系，然后结合该小区切换关系中包含的卡顿小区来计算网络预测结果，并将网络预测结果发送至终端设备100。之后，处理器110可以控制显示屏194显示网络预测结果的提示信息，用于提示用户预先采集相关上网措施的提示信息，或者用于控制终端设备100中安装的APP自动采取相关上网措施，例如预先缓内容，或者降低网络视频清晰度等等，从而可以避免在终端设备100接入卡顿小区过程中给用户带来上网卡顿等的问题。
终端设备100可以是搭载或者其它操作系统的便携式设备，终端设备100的软件系统可以采用分层架构，事件驱动架构，微核架构，微服务架构，或云架构。本申请实施例以分层架构的系统为例，示例性说明终端设备100的软件结构。
参考图2B，图2B示例性示出终端设备100的软件架构图。
如图2B所示，分层架构将软件分成若干个层，每一层都有清晰的角色和分工。层与层之间通过软件接口通信。在一些实施例中，将Android系统分为四层，从上至下分别为应用程序层，应用程序框架层，安卓运行时(Android runtime)和系统库，以及内核层。
应用程序层可以包括一系列应用程序包。例如，应用程序包可以包括相机，图库，日历，通话，地图，导航，WLAN，蓝牙，音乐类APP，视频类APP等应用程序。
其中，音乐类APP和视频类APP可以是系统类APP，也可以是第三方APP，本申请实施例对此不作限制。但该类APP可以为用户提供通过移动通信模块从网络中下载、缓存音乐或视频的服务。
应用程序框架层为应用程序层中的应用程序提供应用编程接口(application programming interface，API)和编程框架。应用程序框架层包括一些预先定义的函数。
如图2B所示，应用程序框架层可以包括窗口管理器，内容提供器，视图系统，电话管理器，资源管理器，通知管理器等。
窗口管理器用于管理窗口程序。窗口管理器可以获取显示屏大小，判断是否有状态栏，锁定屏幕，截取屏幕等。
内容提供器用来存放和获取数据，并使这些数据可以被应用程序访问。所述数据可以包括视频，图像，音频，拨打和接听的电话，浏览历史和书签，电话簿等。
视图系统包括可视控件，例如显示文字的控件，显示图片的控件等。视图系统可用于构建应用程序。显示界面可以由一个或多个视图组成的。例如，包括短信通知图标的显示界面，可以包括显示文字的视图以及显示图片的视图。
电话管理器用于提供终端设备100的通信功能。例如通话状态的管理(包括接通，挂断等)。
资源管理器为应用程序提供各种资源，比如本地化字符串，图标，图片，布局文件，视频文件等等。
通知管理器使应用程序可以在状态栏中显示通知信息，可以用于传达告知类型的消息，可以短暂停留后自动消失，无需用户交互。比如通知管理器被用于告知下载完成，消息提醒等。通知管理器还可以是以图表或者滚动条文本形式出现在系统顶部状态栏的通知，例如后台运行的应用程序的通知，还可以是以对话窗口形式出现在屏幕上的通知。例如在状态栏提示文本信息，发出提示音，终端设备振动，指示灯闪烁等。
Android Runtime包括核心库和虚拟机。Android runtime负责安卓系统的调度和管理。
核心库包含两部分：一部分是java语言需要调用的功能函数，另一部分是安卓的核心库。
应用程序层和应用程序框架层运行在虚拟机中。虚拟机将应用程序层和应用程序框架层的java文件执行为二进制文件。虚拟机用于执行对象生命周期的管理，堆栈管理，线程 管理，安全和异常的管理，以及垃圾回收等功能。
系统库可以包括多个功能模块。例如：表面管理器(surface manager)，媒体库(Media Libraries)，三维图形处理库(例如：OpenGL ES)，二维(2D)图形引擎(例如：SGL)等。
表面管理器用于对显示子系统进行管理，并且为多个应用程序提供了2D和3D图层的融合。
媒体库支持多种常用的音频，视频格式回放和录制，以及静态图像文件等。媒体库可以支持多种音视频编码格式，例如:MPEG4，H.264，MP3，AAC，AMR，JPG，PNG等。
三维图形处理库用于实现三维图形绘图，图像渲染，合成，和图层处理等。
2D图形引擎是2D绘图的绘图引擎。
内核层是硬件和软件之间的层。内核层至少包含显示驱动，摄像头驱动，音频驱动，传感器驱动。
下面结合捕获拍照场景，示例性说明终端设备100软件以及硬件的工作流程。
当触摸传感器180B接收到触摸操作，相应的硬件中断被发给内核层。内核层将触摸操作加工成原始输入事件(包括触摸坐标，触摸操作的时间戳等信息)。原始输入事件被存储在内核层。应用程序框架层从内核层获取原始输入事件，识别该输入事件所对应的控件。以该触摸操作是触摸单击操作，该单击操作所对应的控件为相机应用图标的控件为例，相机应用调用应用框架层的接口，启动相机应用，进而通过调用内核层启动摄像头驱动，通过摄像头193捕获静态图像或视频。
参考图3A，图3A示例性示出服务器200的硬件架构图。
如图3A所示，服务器200可包括：一个或多个处理器201、存储器202、通信接口203、发射器205、接收器206、耦合器207和天线208。这些部件可通过总线204或者其他方式连接，图3A以通过总线连接为例。其中：
本申请实施例中，处理器201可用于读取和执行计算机可读指令。具体的，处理器201可用于调用存储于存储器202中的程序，例如本申请的实施例提供的，将根据终端设备100连续接入的N个小区的信息确定终端设备100之后的移动路线，和在该移动路线中可以能接入到的卡顿小区，并向终端设备100发送预计到达卡顿小区的时间以及在该卡顿小区中的驻留时间等相关信息的方法，在服务器200侧的实现程序，并执行该程序包含的指令。
存储器202与处理器201耦合，用于存储各种软件程序和/或多组指令。具体的，存储器202可包括高速随机存取的存储器，并且也可包括非易失性存储器，例如一个或多个磁盘存储设备、闪存设备或其他非易失性固态存储设备。
存储器202可以存储操作系统(下述简称系统)，例如uCOS、VxWorks、RTLinux等嵌入式操作系统。存储器202还可以存储网络通信程序，该网络通信程序可用于与终端设备100、以及其他终端设备等进行通信。
通信接口203可用于服务器200与其他通信设备，例如终端设备100等进行通信。具体的，通信接口203可以是3G通信接口、长期演进(LTE)(4G)通信接口、5G通信接口、WLAN通信接口、WAN通信接口等等。不限于无线通信接口，服务器200还可以配置有有线的通信接口203来支持有线通信，例如服务器200与其他服务器之间的链接可以是有 线通信连接。
在本申请的一些实施例中，发射器205和接收器206可看作一个无线调制解调器。发射器205可用于对处理器201输出的信号进行发射处理。接收器206可用于接收信号。在服务器200中，发射器205和接收器206的数量均可以是一个或者多个。天线208可用于将传输线中的电磁能转换成自由空间中的电磁波，或者将自由空间中的电磁波转换成传输线中的电磁能。耦合器207可用于将移动通信号分成多路，分配给多个的接收器206。可理解的，网络设备的天线208可以实现为大规模天线阵列。
在本申请实施例中，服务器200的存储器202中可以存储有：小区关联信息库、卡顿小区的信息、网络预测算法和预测信息数据库。关于小区关联信息库、卡顿小区的信息、网络预测算法的具体介绍可以参考后文方法实施例的描述，在此暂不赘述。
其中，预测信息数据库是指，服务器200通过网络预测算法得到的各个终端设备在之后的移动路线中可能处于的网络环境的相关信息。该网络环境的相关信息包括但不限于：预计终端设备到达卡顿小区的时间，在该卡顿小区的驻留时间，预计到达卡顿小区的时间所对应的概率，以及在该卡顿小区的驻留时间所对应的概率等。
当服务器200通过通信接口203接收到服务器200发送目标用户到达过的区域信息和在该区域的滞留时间后，服务器200可以将其发送至登陆追踪应用程序的电子设备中。
需要说明的，图3A所示的服务器200仅仅是本申请实施例的一种实现方式，实际应用中，服务器200还可以包括更多或更少的部件，这里不作限制。
参考图3B，图3B示例性示出服务器200的软件架构图。
如图3B所示，服务器200可包括以下模块：小区关联信息库、卡顿小区信息库、网络预测算法和网络预测信息数据库。
小区关联信息库模块包括：布局在地铁、高铁、汽车等交通工具的行驶路线上的小区切换关系，该小区切换关系具体可以包括：前一个小区切换到后一个小区的概率，以及每个小区的驻留时间的概率分布等。关于小区关联信息库的具体建立过程可以参考后文方法流程的S401处的描述，以及关于小区关联信息库的存储模型可以参考后文图6的描述，在此暂不赘述。
卡顿小区信息库用于存储一个或多个卡顿小区的信息，包括但不限于卡顿校区的标识，卡顿小区的驻留时间的概率分布等等。
网络预测算法模块用于，根据终端设备上报的N个连续接入的小区的信息、小区关联信息库和卡顿小区计算出网络预测结果。
网络预测信息数据库模块，用于存储服务器200通过网络预测算法得到的各个终端设备在之后的移动路线中可能处于的网络环境的相关信息(即预测结果)，以及用于将预测结果发送至相应的终端设备处。
需要说明的，图3B所示的服务器200仅仅是本申请实施例的一种实现方式，实际应用中，服务器200还可以包括更多或更少的模块，这里不作限制。
基于上文对本申请涉及的通信系统、终端设备100和服务器200等装置实施例的介绍， 接下来结合图4所示的方法流程来详细介绍本申请提供的网络预测方法。
如图4所示，该方法包括以下步骤：
阶段1(S401)：服务器初始化阶段。
S401，服务器200预存小区关联信息库、卡顿小区信息库以及网络预测算法。
具体的，服务器200需要预先存储用于对终端设备进行网络预测时所需的信息，包括但不限于：小区关联信息库、卡顿小区信息库以及网络预测算法。其中，小区关联信息库和卡顿小区信息库也可以是集合在一个数据库中。
小区关联信息库包含多路小区切换关系，每路小区切换关系包括：多个小区依次切换的顺序。此外，还可以包含前一小区切换至后一个小区的概率和每个小区的驻留时间。其中，每个小区的驻留时间可以是统计多个终端设备在该小区驻留时间的概率分布(例如正态分布)来表征。
小区关联信息库可以是通过以下三种方式中的任意方式建立而成的，或者小区关联信息库的建立方法还可以采用其他方式，本申请对此不作限制：
(1)开发人员通过采集到布局在地铁、高铁、汽车等交通工具的行驶路线上的所有小区切换关系，小区驻留时间建立而成的小区关联信息库；
(2)服务器200在人工采集的骨架数据的基础(布局在地铁、高铁、汽车等交通工具的行驶路线上的主要/部分小区切换关系)上，再结合大量的终端设备(又称第二设备)在地铁、高铁、汽车等行驶路线上移动时分别上报的各终端设备连续接入的多个小区的信息(包含每个小区的标识、接入时间和驻留时间等)，然后通过路线方向识别(例如采用时间序列DTW算法、动态时间规整、LCSS算法)、小区切换关系聚合得到的更加全面精准的小区关联信息库，该小区关联信息库几乎覆盖了地铁、高铁、汽车等行驶路线上布局的所有基站所对应的小区信息；
(3)服务器200在采集到的终端设备(又称第二设备)上报的购票信息或者基站位置信息的基础上，结合大量的终端设备在地铁、高铁、汽车等行驶路线上移动时分别上报的各终端设备连续接入的多个小区的信息，然后通过路线方向识别(例如使用余弦相似度算法)、小区切换关系聚合、时间相关性算法得到的更加全面精准的小区关联信息库，该小区关联信息库几乎覆盖了地铁、高铁、汽车等行驶路线上布局的所有基站所对应的小区信息。
参考图5，图5示例性示出建立小区关联信息库的原理示意图。图5是针对前文采用方式(2)或方式(3)的生成小区关联信息库的原理示意图。
如图5所示，建立小区关联信息库的原理具体包括以下步骤：
Step1：人工采集骨架数据。该骨架数据包括但不限于：地铁、高铁、汽车等行驶路线上布局的主要基站所对应的小区的关联信息，例如人工采集的地铁1号线上从博物馆开往机场方向上的小区布局信息依次为：小区1、小区2、小区3和小区4；又例如人工采集的高铁从城市A开往城市B方向上的小区布局信息依次为：小区1、小区2、小区3和小区4；或者该骨架数据还可以包括更多的路线，以及各个路线上更多的小区，本申请实施例对此不作限制。
其中，人工采集的骨架数据可以是前文方式(2)中的布局在地铁、高铁、汽车等交通 工具的行驶路线上的主要/部分小区切换关系，也可以是方式(3)中的端设备上报的购票信息或者基站位置信息。
Step2：根据终端设备上报的数据匹配路线并填充小区关联信息。具体的，服务器200从终端设备处收集到，其在地铁、高铁、汽车等行驶路线上移动的过程中连续接入的多个小区的信息后，可以将该连续接入的多个小区与已有的各个路线上的小区的关联信息进行匹配。例如，服务器200从终端设备处收集到的小区信息依次为：小区1、小区5、小区2和小区3。时，则可以将其匹配到城市A博物馆开往机场的地铁1号线对应的小区关联路线中，并且通过对比可知小区5是小区1和小区2之间新增的一个小区，因此将小区5填充至小区1和小区2之间。
Step3：继续根据终端设备上报的数据匹配路线并填充小区关联信息，直至上报的小区不是已有的小区关联信息中没有的小区为止。
具体的，当服务器200从终端设备处收集到的小区信息依次为：小区1、小区6、小区2、小区3和小区4时，则可以将其匹配到城市A博物馆开往机场的地铁1号线对应的小区关联路线中，并且通过对比可知小区6是小区1和小区2之间新增的一个小区，因此将小区6填充至小区1和小区2之间。
值得注意的是，服务器200在建立小区关联信息库的过程中，还会根据各个终端设备上报的其连续接入的多个小区的信息来统计各个小区的驻留时间以及前一小区和后移小区的转移概率。
具体的，服务器200在接收各个终端设备上报的其连续接入的多个小区的信息的同时，该小区的信息还会携带接入时间、驻留时间，或者还携带断开时间、表征网络覆盖状态相关信息、通过全球定位系统(global positioning system，GPS)模块获得的位置信息等等。服务器200可以根据接入时间、驻留时间，或者开时间来统计终端设备在每个小区的驻留时间，例如用正态分布函数来表征驻留时间。以及，服务器200还可以根据表征网络覆盖状态相关信息确定卡顿小区的信息，或者服务器200还可以根据通过位置信息确定终端设备所处的地铁、高铁、汽车的行驶路线等。此外，当多个终端上报的连续接入的多个小区的信息中，前一个小区连接的后一个小区有多个的情况下，服务器200还可以统计前一个小区转移至连接到不同小区的概率。
可以理解的是，图5所示的建立小区关联信息库的原理仅以两条线路上的骨架数据为例进行介绍，在本申请另一些示例中，骨架数据还可以包括更多，每条路线上的骨架数据所包含的小区数量可能更多或者更少，以及每个小区之间的切换关系也可以为其他，本申请实施例对此不作限制。
参考图6，图6示例性示出小区关联信息库存储模型示意图。
如图6所示，图6中的小区关联信息库仅仅以博物馆开往机场方向的1号线以及城市A开往城市B的高铁这两个路线对应的小区关联信息为例示出，以及每个小区的驻留时间，和前一小区转移到后移小区的概率。除此之外，小区关联信息还可能包含更多的路线所对应的小区关联信息，以及每条路线上的小区之间的切换关系也可以为其他，本申请实施例对此不作限制。
卡顿小区信息库包括：一个或多个卡顿小区的信息，如小区标识、小区的驻留时间等，或者，还可以包括小区的卡顿时间段等。其中，小区标识包括但不限于：小区的名称、位置、型号等。小区的驻留时间包含终端接入该小区到断开与该小区的连接之间的时间。小区的卡顿时间段是指，小区业务质量不满足预设条件所对应的时间。造成小区卡顿的原因包括但不限于建设不周/数据配置不当，或者接入设备超负载等。其中建设不周/数据配置的原因可能会导致小区持续卡顿(不分时间段)，而接入设备超负载通常具备潮汐效应，即小区仅在高峰时间段内接入设备超负载，进而导致小区仅在高峰时间段内卡顿。
卡顿小区信息库可以是通过以下三种方式中的任意方式生成的，或者小区关联信息库的生成方法还可以采用其他方式，本申请对此不作限制：
(1)开发人员通过现场测试，或者通过采集群众反馈的信息确定卡顿小区的信息后输入至服务器200中；
(2)服务器200通过获取网络侧设备上报的小区信息而生成的，其中小区信息包括指示终端设备接入的小区的通话业务和数据业务质量的信息，或者还包括接入时间、驻留时间等的信息；
(3)服务器200通过获取终端设备上报的小区信息而生成的，其中小区信息包括指示终端设备接入的小区的通话业务和数据业务质量的信息，或者还包括接入时间、驻留时间等的信息。
在本申请实施例中，服务器200生成卡顿小区信息库时采集到的终端设备上报的小区信息还可以被称为第三小区信息。
在采用方式(2)或方式(3)生成卡顿小区信息库时，具体的，服务器200可以根据接入小区的质量将质量低于阈值的小区作为卡顿小区，或者还可以通过分析不同时间段内小区卡顿与否，来具体分析卡顿小区的具体卡顿时间，当某个小区卡顿只在特定时间段内卡顿且具备周期性卡顿时，则确认该小区具备潮汐效应，相应的，在后续服务器200对终端设备进行网络预测时，则不会将非卡顿时间内的卡顿小区作为卡顿小区进行预测，从而避免网络预测误判的问题。其中潮汐效应是指在高峰时间段内地铁、高铁、汽车等行驶路线上的终端设备是比非高峰时间端多的，因此会出现业务卡顿的现象。
网络预测算法可以是开发人员预置的，也可以是基于开发人员预置的初始算法通过学习迭代实时训练更新的算法。在本申请实施例中，网络预测算法可以实现：
(1)根据终端设备上报的N个连续接入的小区的信息，从小区关联信息库中匹配到符合终端设备之后的移动路线中可能存在的小区切换关系；
(2)获取匹配到的小区切换关系中存在的卡顿小区的信息；
(3)计算终端设备当前接入的小区到卡顿小区预计的时间和该时间对应的概率，以及计算在卡顿小区的滞留时间和对应的概率。
关于网络预测算法的具体计算方法，可以参考后文S404的描述，在此暂不赘述。
阶段2(S402-S403)：终端设备100向服务器200上报其接入的小区的信息。
S402，终端设备100检测到符合网络预测的场景。
具体的，终端设备100可以通过加速度传感器检测到的终端设备的移动加速度来确定终端设备是否处于符合网络预测的场景；或者，还可以通过获取终端设备100利用NFC、电子乘车码进行乘车的信息，来确定终端设备是否处于符合网络预测的场景。或者，还可以通过定位，网上订票的方式来确定终端设备是否处于符合网络预测的场景。
其中，符合网络预测的场景包括但不限于终端设备在地铁、高铁、汽车等行驶路线上移动的场景，由于在这些场景中，终端设备因为快速移动位置会频繁的切换小区，很有可能切换到卡顿小区，给用户带来上网卡顿等的体验，因此将这类场景作为重点对象进行网络预测。但在其他一些实施例中，符合网络预测的场景还可以包括其他，本申请实施例对此不作限制。
在本申请实施例中，S402为可选步骤，也就是说，无论终端设备处于任何场景，都可以向服务器200上报其接入的小区的信息，由服务器200端对这些小区的信息进行进一步的筛选或者网络预测等。
S403，终端设备100向服务器200发送连续接入的多个小区的信息。
具体的，终端设备100在检测到符合网络预测场景后，则会向服务器200上报其连续接入的N个小区的信息。该N个小区的信息可以是分N次按照接入顺序上报的，也可以是按照接入顺序打包后一次性上报的。其中，终端设备100向服务器200上报其连续接入的多个/N个小区的信息还可以被称为第一小区信息。
其中，小区的信息包括但不限于：小区的标识，接入到该小区的时间、在该小区的驻留时间等等。
阶段3(S404)：服务器200对终端设备100即将到达的环境进行网络预测。
S404，服务器200根据终端设备100接入的小区的信息进行网络预测。
具体的，服务器200中已经存储有网络预测算法、小区关联信息库和卡顿小区，在接收到N个小区的信息后，服务器200中的网络预测算法可以根据N个连续接入的小区的信息，从小区关联信息库中匹配到符合终端设备之后的移动路线中可能存在的小区切换关系，以及获取匹配到的小区切换关系中存在的卡顿小区的信息，最后计算得到网络预测结果。该网络预测结果包括：终端设备当前接入的小区到卡顿小区预计的时间和该时间对应的概率，以及计算在卡顿小区的驻留时间和对应的概率。
可选的，当一些卡顿小区具备潮汐效应时，则对于非潮汐时间端内接收到终端设备上报的连续接入的小区的信息时，在对其进行网络预测时，认为具备潮汐效应的卡顿小区不是卡顿小区，即不讲这类小区纳入网络预测范围内。其中潮汐效应是指，一些小区仅在早晚高峰时间段内会出现业务卡顿的情况，而在其他时间段内小区业务正常。
接下来以一个具体的示例来介绍网络预测结果的具体计算过程：
当服务器200接收到的N个小区依次为：小区A、小区B和小区C时，则可以从前文图6所示的小区关联信息库中匹配到城市A开往城市B的高铁的行驶路线上的小区切换关系，该小区切换关系具体包括以下3条小区切换路线，该34条切换路线都是终端设备100 在接下的行驶路线中会存在的切换行为：
切换路线1的切换顺序依次为：小区A、小区B、小区C、小区D、小区F；
切换路线2的切换顺序依次为：小区A、小区B、小区C、小区D、小区G和小区H；
切换路线3的切换顺序依次为：小区A、小区B、小区C、小区E、小区G和小区H。
其中，小区G为卡顿小区。在本申请实施例中，小区G还可以被称为第一卡顿小区。
此外，小区关联信息库中还会记载，前一个小区切换到后一个小区的概率。例如小区C切换至小区D的概率为70％，小区D切换至小区G的概率为60％，小区C切换至小区E的概率为30％，小区E切换至小区G的概率为100％。
此外，小区关联信息库中还会记载每个小区驻留时间。该驻留时间可以是服务器根据统计数据直接获取的均值，也可以是在一定概率范围内的一段时间。其中统计数据可以是驻留时间的正态分布函数。例如，小区C的概率分布的均值为20秒，标准差为2秒，方差为4秒，则小区C的驻留时间在(20-4,20+4)秒内的概率为95％；小区D的概率分布的均值为30秒，标准差为2秒，方差为4秒，则小区D的驻留时间在(30-4,30+4)秒内的概率为95％；小区E的概率分布的均值为20秒，标准差为4秒，方差为16秒，则小区D的驻留时间在(20-16,20+16)秒内的概率为68％。
最后，计算终端设备到达卡顿小区的时间的方法包括以下任一种：
(1)计算法则1(仅采用均值)：
走切换路线2进入卡顿小区G的概率为70％*60％＝42％，所需时间为20+30＝50秒；
走切换路线3进入卡顿小区G的概率为30％*100％＝30％，所需时间为20+20＝40秒；
总计，终端设备将在42％+30％＝72％的可能下，在40-50秒后接入到卡顿小区G。
(2)计算法则2(采用概率转移+均值)：
走切换路线2或切换路线3进入卡顿小区G的概率为：70％*60％+30％*100％＝72％，所需时间为：42％/72％(20+30)+30％/72％(20+20)＝29.2+16.7＝45.9；
总计，终端设备将在72％的可能下，在45.9秒后接入到卡顿小区G。
(3)计算法则3(采用概率转移+方差)：
走切换路线2进入卡顿小区G的概率为95％*70％*95％*60％＝37.905％，所需时间为20-4+30-4＝42秒到20+4+30+4＝58秒之间；
走切换路线3进入卡顿小区G的概率为95％*30％*68％*100％＝19.38％，所需时间为20-4+20-16＝12秒到20+4+20+16＝60秒之间；
总计：走切换路线2或3进入卡顿小区G的概率为37.905％+19.38％＝57.285％，所需时间为12秒到60秒之间。
上述三种计算方式得到的预测结果中，进入卡顿小区G的概率可以称为第一概率，且在第一概率下进入卡顿小区G所需时间还可以称为第一时长，在卡顿小区G驻留的概率为第二概率，在第二概率下驻留在小区G的时长还可以称为第二概率。
可以理解的是，前文所述的网络预测结果的计算方法仅为示例，在本申请另一些示例中当N个小区的信息为其他，匹配到的小区切换关系可能为其他，或者卡顿小区的信息可能为其他，因此计算得到的网络预测结果可能不相同，但计算原理相同，仍然可以参考上 文示例的方法进行计算。以及，根据每个小区的驻留时间的概率分布来对小区驻留时间进行取值时，除了采取均值，以及采取均值到方差范围内的时间段外，还可用于取值均值到标准差范围内的时间段，或者取其他时间段来进行计算，其区别仅在于去不同时间段对应的驻留概率不同，但计算原理相同，此处不再展开赘述。
阶段4(S405-S406)：服务器200向终端设备100推送网络预测结果。
S405，服务器200向终端设备100发送网络预测结果。
具体的。网络预测结果包括但不限于：卡顿小区的信息，到达卡顿小区所需时间及对应的概率，和在卡顿小区的驻留时间及对应的概率。其中，关于到达卡顿小区所需时间的计算法则可以是S404中示例的任一种，卡顿小区的驻留时间，可以采用均值，或者可以采用方差范围的时间，本申请实施例对此不作限制。
S406，终端设备100输出网络预测结果，和/或根据网络预测结果调整上网措施。
其中，提示信息的内容例如可以是到达卡顿小区所需时间及对应的概率，和在卡顿小区的驻留时间及对应的概率，提示方式包括但不限于通过短信、通知、卡片、语音播报等的方式。这样可以，提示用户根据网络预测结果提前做好相关措施，例如提前缓存网络内容或降低观看网络内容的清晰度，避免用户在进入卡顿小区后无法出现上网卡顿的现象。
其中，控制终端设备100调整上网措施例如包括提前缓存网络内容和/或降低观看网络内容的清晰度。该措施可以是和用户上网行为相关，例如提前缓存的网络内容和/或降低观看网络内容是用户正在使用的APP提供的内容，或者是用户经常使用的APP提供的内容，该APP可以是系统APP也可以是第三方APP。这样，可以在用户无感知的情况下，提前帮用户采取相关上网措施，使得用户在进入卡顿小区后仍然可以畅通无阻的观看网络内容。
例如不接打电话，提前缓存或者下载网上的内容或者降低网络视频的清晰度等等。和/或，终端设备100还可以控制其安装的APP自动做好相关上网措施，例如提前缓存或者下载网上的内容，或者降低网络视频的清晰度等等。
最后，结合图7所示的网络预测架构图来详细介绍本申请提供的网络预测方法。
如图7所示，该网络预测主要包括四个部分：小区信息上报、小区关联信息库建立、网络预测和网络预测结果推送这四部分。其中，小区信息上报、网络预测结果推送由终端设备100端执行，小区关联信息库建立和网络预测由服务器200端执行，详细执行过程如下：
1、小区信息上报。
终端设备100中的场景识别模块识在别到符合网络预测的场景(例如乘坐地铁、高铁、汽车等场景)，则会通知小区信息上报模块将其连续接入的N个小区的信息的上报至服务器200的小区信息模块或网络预测算法模块。其中，上报至小区信息模块的N个小区的信息是用于服务器200建立小区关联信息库，上报至网络预测算法模块的N个小区的信息则是用于服务器200生成网络预测结果的。前者，是在服务器200建立小区关联信息库或者更新小区关联信息库的过程中执行的，后者是在服务器200已经成功建立小区关联信息库后执行的。
2、小区关联信息库建立。
服务器200中的小区信息模块可以接收人工输入的小区的信息(即前文所述的骨架数据)，以及接收多个终端设备上报的小区的信息，然后将这些小区的信息经过数据处理后建立、更新得到小区关联信息库。
其中，数据处理过程包括但不限于数据清洗、路线方向识别、小区切换关系聚合以及时间相关性分析等步骤。其中，数据清洗为可选的处理过程，其是指将从终端设备中接收到少于N个的连续接入的小区的信息删除掉。关于小区切换关系聚合以及时间相关性分析的具体介绍可以参考前文方法流程中S401的描述，在此暂不赘述。
3、网络预测。
服务器200中的网络预测算法模块在每次接收到终端设备100上报的N个连续接入的小区的信息后，会根据该N个连续接入的小区的信息从小区关联信息库中进行匹配，在匹配到终端设备100行驶路线上可能存在的小区切换关系时，则会结合该小区切换关系中存在的卡顿小区，然后计算终端设备即将到达该卡顿小区的时间，以及在该卡顿小区驻留的时间，或者还会计算：达到卡顿小区的时间所对应的概率，以及在该卡顿小区的驻留时间所对应的概率等，最终将计算得到的预测结果输出至网络预测信息库中。
4、网络预测结果推送。
终端设备100中的网络预测推送模块在接收到服务器200的网络预测信息库发送的网络预测结果后，则可以控制终端设备100的显示屏194、音频模块170等输出网络预测结果，用于提示用户接下来做好相关措施，例如不接打电话，提前缓存或者下载网上的内容或者降低网络视频的清晰度等等。和/或，网络预测推送模块还可以控制终端设备中安装的视频类APP、游戏类APP自动做好相关上网措施，例如提前缓存或者下载网上的内容，或者降低网络视频的清晰度等等。或者，上网策略还可以由第三方APP的提供者、开发者根据网络预测结果自己制定相应的策略，本申请实施例对此不作限制。
综上所述，实施本申请后，可用于对终端设备即将所处环境以及该环境对应的网络质量进行预测，用于提示用户预先采取相关上网措施，或者用于控制终端设备自动采取相关上网措施，避免在终端设备接入卡顿小区过程中给用户带来上网卡顿等的问题。
此外，网络预测结果包括但不限于：预计终端设备到达卡顿小区的时间，在该卡顿小区的驻留时间，预计到达卡顿小区的时间所对应的概率，以及在该卡顿小区的驻留时间所对应的概率等。这样，可以提示用户预先采取相关上网措施，或者用于控制终端设备自动采取相关上网措施，避免在终端设备接入卡顿小区过程中给用户带来上网卡顿等的问题。这样，能够使得用户能够根据网络结果和该结果发生的概率决定是否调整相关上网策略以及如何调整策略等。或者使得终端中安装的APP根据网络结果和该结果发生的概率来划分上网调整策略，例如当，进入卡顿小区的概率越大，或者进入卡顿小区所述时间越短，或者在卡顿小区驻留时间越长时，则控制相应的上网策略越严苛，例如观看网络内容的清晰度越低，或者预先下载/缓存的网络内容越多等等。
应理解，本申请提供的上述方法实施例中的各步骤可以通过处理器中的硬件的集成逻 辑电路或者软件形式的指令完成。结合本申请实施例所公开的方法步骤可以直接体现为硬件处理器执行完成，或者用处理器中的硬件及软件模块组合执行完成。
本申请还提供一种终端设备，该终端设备可以包括：存储器和处理器。其中，存储器可用于存储计算机程序；处理器可用于调用所述存储器中的计算机程序，以使得该终端设备执行上述任意一个实施例中的方法。
本申请还提供了一种芯片系统，所述芯片系统包括至少一个处理器，用于实现上述任意一个实施例中终端设备执行的方法中所涉及的功能。
在一种可能的设计中，所述芯片系统还包括存储器，所述存储器用于保存程序指令和数据，存储器位于处理器之内或处理器之外。
该芯片系统可以由芯片构成，也可以包含芯片和其他分立器件。
可选地，该芯片系统中的处理器可以为一个或多个。该处理器可以通过硬件实现也可以通过软件实现。当通过硬件实现时，该处理器可以是逻辑电路、集成电路等。当通过软件实现时，该处理器可以是一个通用处理器，通过读取存储器中存储的软件代码来实现。
可选地，该芯片系统中的存储器也可以为一个或多个。该存储器可以与处理器集成在一起，也可以和处理器分离设置，本申请实施例并不限定。示例性地，存储器可以是非瞬时性处理器，例如只读存储器ROM，其可以与处理器集成在同一块芯片上，也可以分别设置在不同的芯片上，本申请实施例对存储器的类型，以及存储器与处理器的设置方式不作具体限定。
示例性地，该芯片系统可以是现场可编程门阵列(field programmable gate array，FPGA)，可以是专用集成芯片(application specific integrated circuit，ASIC)，还可以是系统芯片(system on chip，SoC)，还可以是中央处理器(central processor unit，CPU)，还可以是网络处理器(network processor，NP)，还可以是数字信号处理电路(digital signal processor，DSP)，还可以是微控制器(micro controller unit，MCU)，还可以是可编程控制器(programmable logic device，PLD)或其他集成芯片。
本申请还提供一种计算机程序产品，所述计算机程序产品包括：计算机程序(也可以称为代码，或指令)，当所述计算机程序被运行时，使得计算机执行上述任一个实施例中终端设备执行的方法。
本申请还提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序(也可以称为代码，或指令)。当所述计算机程序被运行时，使得计算机执行上述任一个实施例中终端设备执行的方法。
本申请的各实施方式可以任意进行组合，以实现不同的技术效果。
在上述实施例中，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时，可以全部或部分地以计算机程序产品的形式实现。所述计算机程序产品包括一个或多个计算机指令。在计算机上加载和执行所述计算机程序指令时，全部或部分地产生按照本申请所述的流程或功能。所述计算机可以是通用计算机、专用计算机、计算机网络、或者其他可编程装置。所述计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一个计算机可读存储介质传输，例如，所述计算机指令 可以从一个网站站点、计算机、服务器或数据中心通过有线(例如同轴电缆、光纤、数字用户线)或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。所述计算机可读存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。所述可用介质可以是磁性介质，(例如，软盘、硬盘、磁带)、光介质(例如，DVD)、或者半导体介质(例如固态硬盘Solid State Disk)等。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，该流程可以由计算机程序来指令相关的硬件完成，该程序可存储于计算机可读取存储介质中，该程序在执行时，可包括如上述各方法实施例的流程。而前述的存储介质包括：ROM或随机存储记忆体RAM、磁碟或者光盘等各种可存储程序代码的介质。
总之，以上所述仅为本发明技术方案的实施例而已，并非用于限定本发明的保护范围。凡根据本发明的揭露，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。

Claims (21)

  1. 一种网络预测方法，其特征在于，所述方法应用于服务器，所述方法包括：
    所述服务器接收第一设备发送的第一小区信息，所述第一小区信息包括所述第一设备连续接入的多个小区的信息；
    所述服务器基于所述第一小区信息生成网络预测结果，所述网络预测结果表征所述第一设备即将接入至卡顿小区；
    所述服务器向所述第一设备发送所述网络预测结果；
    所述网络预测结果用于指示所述第一设备输出提示信息，和/或，调整上网策略。
  2. 根据权利要求1所述的方法，其特征在于，所述网络预测结果用于指示所述第一设备调整上网策略具体包括：指示所述第一设备缓存网络内容，和/或，降低观看网络内容的清晰度。
  3. 根据权利要求1或2所述的方法，其特征在于，所述网络预测结果包括第一卡顿小区的信息，所述第一卡顿小区的信息包括以下任一项或多项：
    所述第一设备接入至第一卡顿小区所需的第一时长，所述第一设备在所述第一时长内接入至所述第一卡顿小区的第一概率，在所述第一卡顿小区驻留的第二时长，所述第一卡顿小区驻留的第二时长的第二概率。
  4. 根据权利要求3所述的方法，其特征在于，所述第一时长和所述第一概率为所述服务器根获取计到的多个设备在相应小区驻留时间的概率分布而确定的；
    所述第二时长和所述第二概率为所述服务器根据获取到的多个设备在所述第一卡顿小区驻留时间的概率分布而确定的。
  5. 根据权利要求3或4所述的方法，其特征在于，所述第一卡顿小区包括：
    所述终端设备即将依次接入的多个小区中属于卡顿小区的小区；
    所述终端设备即将依次接入的多个小区包括：小区关联信息库中与所述第一小区信息匹配的小区；
    其中，所述小区关联信息库包含多路小区切换关系，每路小区切换关系包括：多个小区依次切换的顺序。
  6. 根据权利要求5所述的方法，其特征在于，所述第一卡顿小区包括：
    所述终端设备即将依次接入的多个小区中在当前时刻或当前时段属于卡顿小区的小区。
  7. 根据权利要求5或6所述的方法，其特征在于，在所述服务器基于所述第一小区信息生成网络预测结果之前，所述方法还包括：
    所述服务器接收第二设备发送的第二小区信息，所述第二小区信息为所述第二设备连续接入的多个小区的信息；
    所述服务器将所述第二小区信息填充至骨架数据，以更新得到所述小区关联信息库；
    所述骨架数据包括多个路线上布局的小区的切换关系。
  8. 根据权利要求7所述的方法，其特征在于，所述第二设备连续接入的多个小区的信息具体包括：每个小区的标识、每个小区的接入时间和驻留时间。
  9. 根据权利要求5-7中任一项所述的方法，其特征在于，在所述服务器基于所述第一小区信息生成网络预测结果之前，所述方法还包括：
    所述第二设备向所述服务器发送第三小区信息，所述第三小区信息指示所述第二设备接入的小区的业务质量；
    所述服务器根据所述业务质量确定所述卡顿小区。
  10. 一种网络预测方法，其特征在于，所述方法应用于第一设备，所述方法包括：
    所述第一设备向服务器发送第一小区信息，所述第一小区信息包括所述第一设备连续接入的多个小区的信息；
    所述第一小区信息用于所述服务器生成网络预测结果，所述网络预测结果表征所述第一设备即将接入至卡顿小区；
    第一设备接收所述服务器发送的所述网络预测结果；
    所述第一设备根据所述网络预测结果输出提示信息，和/或，调整上网策略。
  11. 根据权利要求10所述的方法，其特征在于，所述第一设备根据所述网络预测结果调整上网策略具体包括：所述第一设备缓存网络内容，和/或，降低观看网络内容的清晰度。
  12. 根据权利要求10或11所述的方法，其特征在于，所述网络预测结果包括第一卡顿小区的信息，所述第一卡顿小区的信息包括以下任一项或多项：
    所述第一设备接入至第一卡顿小区所需的第一时长，所述第一设备在所述第一时长内接入至所述第一卡顿小区的第一概率，在所述第一卡顿小区驻留的第二时长，所述第一卡顿小区驻留的第二时长的第二概率。
  13. 根据权利要求12所述的方法，其特征在于，所述第一时长和所述第一概率为所述服务器根获取计到的多个设备在相应小区驻留时间的概率分布而确定的；
    所述第二时长和所述第二概率为所述服务器根据获取到的多个设备在所述第一卡顿小区驻留时间的概率分布而确定的。
  14. 根据权利要求12或13所述的方法，其特征在于，所述第一卡顿小区包括：
    所述终端设备即将依次接入的多个小区中属于卡顿小区的小区；
    所述终端设备即将依次接入的多个小区包括：小区关联信息库中与所述第一小区信息匹配的小区；
    其中，所述小区关联信息库包含多路小区切换关系，每路小区切换关系包括：多个小区依次切换的顺序。
  15. 根据权利要求14所述的方法，其特征在于，所述第一卡顿小区包括：
    所述终端设备即将依次接入的多个小区中在当前时刻或当前时段属于卡顿小区的小区。
  16. 根据权利要求10-15中任一项所述的方法，其特征在于，在所述第一设备向所述服务器发送第一小区信息之前，所述方法还包括：
    所述第一设备识别到处于地铁、高铁或汽车行驶的场景。
  17. 一种网络预测方法，其特征在于，所述方法应用于包含第一设备和服务器的通信系统，所述方法包括：
    所述第一设备向所述服务器发送第一小区信息，所述第一小区信息包括所述第一设备连续接入的多个小区的信息；
    所述服务器基于所述第一小区信息生成网络预测结果，所述网络预测结果表征所述第一设备即将接入至卡顿小区；
    所述服务器向所述第一设备发送所述网络预测结果；
    所述第一设备根据所述网络预测结果输出提示信息，和/或，调整上网策略。
  18. 一种服务器，其特征在于，所述服务器包括存储器、一个或多个处理器；所述存储器与所述一个或多个处理器耦合，所述存储器用于存储计算机程序代码，所述计算机程序代码包括计算机指令，所述一个或多个处理器调用所述计算机指令以使得所述服务器执行如权利要求1-9中任一项所述的方法。
  19. 一种终端设备，其特征在于，所述终端设备包括存储器、一个或多个处理器；所述存储器与所述一个或多个处理器耦合，所述存储器用于存储计算机程序代码，所述计算机程序代码包括计算机指令，所述一个或多个处理器调用所述计算机指令以使得所述终端设备执行如权利要求10-16中任一项所述的方法。
  20. 一种芯片，所述芯片应用于电子设备，其特征在于，所述芯片包括一个或多个处理器，所述处理器用于调用计算机指令以使得所述电子设备执行如权利要求1-16中任一项所述的方法。
  21. 一种计算机可读存储介质，包括指令，其特征在于，当所述指令在电子设备上运行时，使得所述电子设备执行如权利要求1-16中任一项所述的方法。
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