Network Quality Determination Method, Apparatus, Network Device, and Computer Storage Medium

Abstract

An embodiment of the present invention provides a network quality determination method, which obtains monitoring results by monitoring the call service data of each terminal, and determines the current network quality based on the monitoring results of each terminal; an embodiment of the present invention also provides a network quality determination device, network equipment and computer storage medium. By implementing the above scheme, in certain implementation processes, attention is paid to the call service data of each terminal, and the current network quality is determined with the help of the call service data of each terminal. Firstly, the experience of a single terminal is taken into account, and secondly, the call service data of the control plane is used, the amount of data collected is small, and thus the computing and storage overhead is also small, and the speed is faster; in short, on the basis of ensuring that the experience of a single terminal is taken into account, the computing and storage overhead is greatly reduced, the network quality is well determined, and deployment and implementation are facilitated.

Description

Technical Field

[0001] The embodiments of the present invention relate to, but are not limited to, the field of mobile communications. Specifically, they relate to, but are not limited to, a method and apparatus for determining network quality, a network device, and a computer storage medium. Background Art

[0002] With the rapid development of communication technology and the rapid growth of data services, users' requirements for network quality are becoming increasingly higher. To ensure network quality, timely detection of network quality issues is becoming increasingly important. There are two main methods for detecting network quality issues.

[0003] The first approach uses network element statistics to identify suboptimal service quality provided by certain network elements using various key performance indicators (KPIs), such as call drop rate, handover success rate, and coverage. These KPIs are calculated by the network elements based on pre-defined rules, identifying abnormal and normal call flows and counting their occurrences. This method reduces overhead and is highly efficient in identifying network quality issues. However, since these statistics are generated from network element statistics and do not include specific user information, they tend to be macro-level. They are not very sensitive to subtle changes in the network, making them less conducive to continuous improvement of network quality.

[0004] The second approach involves deploying probes in the network to analyze data packets generated during user browsing to obtain metrics such as TCP retransmission rate, TCP establishment delay, and transmission rate. These basic metrics, combined with user-focused metrics, generate user perception assessments, generally known as Key Quality Indicators (KQIs). For example, by analyzing data packet interactions during online video streaming, basic metrics such as transmission rate, response delay, and video file quality can be obtained. This data can then be used to identify user-focused experiences such as slow response times and video freezes. These experiences are then scored to generate quantifiable KQIs. Per-user KQI metrics are statistically analyzed to identify poor-quality network elements. This approach requires large amounts of data to analyze, requiring significant computational effort for data collection and analysis. Furthermore, it is significantly affected by factors such as terminal and website load, and website location, which can affect the accuracy of user perception assessments. Furthermore, there can be bias in the mapping of user service data to specific network elements, resulting in a low accuracy rate for poor-quality network elements.

[0005] It can be seen that the network quality is not well determined in the related art, which greatly affects the improvement of network service quality. Summary of the Invention

[0006] The embodiments of the present invention provide a network quality determination method, apparatus, network equipment, and computer storage medium, which mainly solve the technical problem that the related technologies do not determine the network quality well, which greatly affects the improvement of network service quality.

[0007] To solve the above technical problems, an embodiment of the present invention provides a method for determining network quality, including:

[0008] Monitor the call service data of each terminal and obtain monitoring results;

[0009] The current network quality is determined based on the monitoring results of each terminal.

[0010] An embodiment of the present invention further provides a network quality determination device, the network quality determination device comprising: a monitoring module and a determination module;

[0011] The monitoring module is used to monitor the call service data of each terminal and obtain monitoring results;

[0012] The determining module is used to determine the current network quality according to the monitoring results of each terminal.

[0013] An embodiment of the present invention further provides a network device, comprising: a processor, a memory, and a communication bus;

[0014] The communication bus is used to realize the connection and communication between the processor and the memory;

[0015] The processor is configured to execute one or more computer programs stored in the memory to implement the steps of the network quality determination method described above.

[0016] An embodiment of the present invention further provides a computer storage medium storing one or more programs. The one or more programs can be executed by one or more processors to implement the steps of the network quality determination method described above.

[0017] The network quality determination method, apparatus, network device, and computer storage medium provided by the embodiments of the present invention monitor the call service data of each terminal, obtain monitoring results, and determine the current network quality based on the monitoring results of each terminal. This solves the problem that the network quality is not well determined in related technologies, which greatly affects the improvement of network service quality. In other words, the network quality determination method, apparatus, network device, and computer storage medium provided by the embodiments of the present invention focus on the call service data of each terminal and use the call service data of each terminal to determine the current network quality. Firstly, it takes into account the experience of a single terminal. Secondly, it uses the call service data of the control plane, collects less data, and thus has less computing and storage overhead and a faster rate. In short, while ensuring that the experience of a single terminal is taken into account, the computing and storage overhead is greatly reduced, that is, the network quality is well determined, which is conducive to deployment and implementation.

[0018] Other features and corresponding beneficial effects of the present invention are described in the latter part of the specification, and it should be understood that at least some of the beneficial effects become obvious from the description in the specification of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A basic flow chart of the network quality determination method provided in the first embodiment of the present invention;

[0020] Figure 2 A basic flow chart for monitoring call service data of each terminal and obtaining monitoring results provided in the first embodiment of the present invention;

[0021] Figure 3 A basic flow chart for determining the current network quality based on the monitoring results of each terminal provided in the first embodiment of the present invention;

[0022] Figure 4 A basic flow chart for determining whether a problem exists in a terminal itself, provided in the first embodiment of the present invention;

[0023] Figure 5 A basic flow chart of the network quality determination method provided in the second embodiment of the present invention;

[0024] Figure 6 A schematic diagram of the structure of a network quality determination device provided in Embodiment 3 of the present invention;

[0025] Figure 7 This is a schematic diagram of the structure of a terminal provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0026] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the following is a further detailed description of the embodiments of the present invention through specific implementation methods in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0027] Example 1:

[0028] In order to solve the problem that the network quality is not well determined in the related art, which greatly affects the improvement of network service quality, the embodiment of the present invention provides a network quality determination method, which monitors the call service data of each terminal, obtains the monitoring results, and determines the current network quality based on the monitoring results of each terminal; see Figure 1 shown.

[0029] S101: Monitor call service data of each terminal and obtain monitoring results.

[0030] S102: Determine the current network quality based on the monitoring results of each terminal.

[0031] It should be noted that the call service data in the embodiment of the present invention includes call service data that affects the user experience, among which it may only include call service data that has a greater impact on the user experience, or it may only include call service data that has a smaller impact on the user experience, or it may include call service data that has both a greater and a smaller impact on the user experience; in actual applications, the degree of impact of the call service data on the user experience can be judged first, and then the call service data that needs to be monitored can be determined, and further, the determined call service data can be monitored.

[0032] The call service data in the embodiments of the present invention includes call service data that impacts user experience. Furthermore, this call service data may be call service data that occurs infrequently under normal circumstances. Optionally, the call service data in the embodiments of the present invention includes, but is not limited to, call service data related to IP address acquisition and inter-system handover. It is worth noting that in actual applications, call service data can be flexibly adjusted based on specific application scenarios and is not limited to the two types of call service data listed in the embodiments of the present invention, namely, IP address acquisition and inter-system handover. It should be understood that call service data related to IP address acquisition generally occurs after the terminal is powered on, using the corresponding process to acquire an IP address. This IP address is then used for communication until the terminal is powered off. The terminal will only re-initiate the call service process related to IP address acquisition if it encounters a serious problem, such as a prolonged period of inactivity with the core network or severe packet loss. Therefore, based on this analysis, call service data related to IP address acquisition occurs infrequently under normal circumstances.

[0033] For a better understanding, here we take the example of call service data including call service data related to obtaining IP addresses. It should be understood that in different systems, the call service data related to IP addresses is obtained differently. In the Long Term Evolution (LTE) system, the call service data related to IP addresses includes ATTACH service data, that is, in the LTE system, the terminal obtains the IP address through the ATTACH process; in the 5G New Radio (NR) system, the call service data related to IP addresses includes REGISTER service data, that is, in the 5G NR terminal, the IP address is obtained through the REGISTER process. At the same time, for the LTE system, the control plane between the base station and the core network (MME) uses the S1MME interface, and the relevant records of the ATTACH process can be obtained from the signaling monitoring system of the S1MME interface; for the 5G NR system, the control plane between the base station and the core network (AMF) uses the Ng interface, and the relevant records of the REGISTER process are obtained from the signaling monitoring system of the Ng interface.

[0034] Among them, in the embodiment of the present invention, the terminal identifier can be determined from the correlation between the interfaces to determine which terminal's call service data belongs to, such as determining the terminal identifier through the S1MME interface, etc. for the LTE system, and determining the terminal identifier through the Ng interface, etc. for the 5G NR system; it should be understood that the terminal identifier is used to identify the terminal, and IMSI (International Mobile Subscriber Identity), MSISDN (Mobile Subscriber International ISDN number), or IMEI (International Mobile Equipment Identity), etc. It is worth noting that in actual applications, determining the terminal identifier to determine which terminal's call service data belongs to needs to be flexibly adjusted according to the specific application scenario.

[0035] In this way, compared with the KPI method in related technologies, the experience of a single terminal can be taken into account, and network quality problems can be discovered even when there is no obvious deterioration in network indicators, so that network quality problems can be solved to optimize network quality; compared with the KQI method in related technologies, due to the use of call service data on the control plane, the amount of collected data is relatively small, the computing and storage overhead is low, and the speed is fast.

[0036] Optionally, in the embodiment of the present invention, monitoring the call service data of each terminal and obtaining the monitoring results include at least the following steps, see Figure 2 As shown:

[0037] S201: Monitor call service data of each terminal within a preset time period.

[0038] S202: Obtain the number of times the call service process corresponding to the call service data is successful within a preset time period.

[0039] For a better understanding, an example is used here to illustrate; for example, the call service data of terminals A, B, C, D, and E within 15 minutes are monitored. Assuming that the number of successful call service processes corresponding to terminals A, B, C, D, and E within 15 minutes are 5, 8, 2, 4, and 6 respectively, then the number of successful call service processes of terminal A within 15 minutes is 5, the number of successful call service processes of terminal B within 15 minutes is 8, the number of successful call service processes of terminal C within 15 minutes is 2, the number of successful call service processes of terminal D within 15 minutes is 4, and the number of successful call service processes of terminal E within 15 minutes is 6.

[0040] It is worth noting that in actual applications, the preset time period can be flexibly set, such as 15 minutes, 30 minutes, etc.

[0041] Optionally, in the embodiment of the present invention, determining the current network quality according to the monitoring results of each terminal includes at least the following steps, see Figure 3 As shown:

[0042] S301: When the number of times is greater than a first preset threshold, it is determined that the terminal corresponding to the call service data is a suspected poor quality terminal.

[0043] S302: Classify each suspected poor-quality terminal according to the base station or cell to which it belongs, and obtain a classification result.

[0044] S303: Determine the current network quality based on the classification result.

[0045] For a better understanding, an example is used here to illustrate; for example, following the above example, assuming that the first preset threshold is 3 times, the number of successful call service processes of terminals A, B, D, and E is greater than 3 times, and terminals A, B, D, and E are determined to be suspected poor quality terminals; further, the base stations or cells to which terminals A, B, D, and E belong are obtained from the call service processes corresponding to the terminals respectively, and the terminals A, B, D, and E are classified according to the base stations or cells to which the terminals A, B, D, and E belong. For example, terminals belonging to the same base station are divided into one category, and terminals A, B, and D belong to base station or cell a1, and terminal E belongs to base station or cell a2. At this time, the terminals are divided into two categories, terminals A, B, and D are in one category, and terminal E is in another category; further, the current network quality is determined based on the classification results.

[0046] It is worth noting that in actual applications, the first preset threshold can be flexibly set, such as 5 times, 8 times, etc., and the classification can also be flexibly adjusted, as long as the current network quality can be determined according to the classification result after classification.

[0047] Optionally, in an embodiment of the present invention, each suspected poor-quality terminal is classified according to the base station or cell to which it belongs, and a classification result is obtained, including at least the following steps:

[0048] Each suspected poor-quality terminal is classified according to the base station or cell to which it belongs, and the number of suspected poor-quality terminals contained in each base station or cell is calculated.

[0049] For better understanding, an example is used here to illustrate; for example, continuing the above example, the classification result is that the base station or cell a1 contains terminals A, B, and D, and the base station or cell a2 contains terminal E, then the number of suspected poor quality terminals corresponding to the base station or cell a1 is 3, and the number of suspected poor quality terminals corresponding to the base station or cell a2 is 1.

[0050] Optionally, in an embodiment of the present invention, determining the current network quality according to the classification result includes:

[0051] The base stations or cells are sorted from most to least according to the number of suspected poor quality terminals they contain, wherein the base station or cell containing the largest number of suspected poor quality terminals is determined to have the worst network quality, and the base station or cell containing the least number of suspected poor quality terminals is determined to have good network quality.

[0052] For better understanding, an example is given here to illustrate; for example, following the above example, it can be determined that if base station or cell a1 contains the largest number of suspected poor quality terminals, then the network quality of base station or cell a1 is the worst, and if base station or cell a2 contains the least number of suspected poor quality terminals, then the network quality of base station or cell a1 is relatively good.

[0053] It is worth noting that in the examples listed above, the number of terminals and their base stations involved is relatively small for the sake of convenience. In actual applications, the number of terminals and their base stations needs to be flexibly adjusted according to specific application scenarios.

[0054] Optionally, in the embodiment of the present invention, before determining that the terminal corresponding to the call service data is a suspected poor quality terminal when the number of times is greater than the first preset threshold, at least the following steps are included. Figure 4 As shown:

[0055] S401: Obtain the total number of call service processes corresponding to call service data within a preset time period.

[0056] S402: Calculate the ratio of the number of successful call service processes to the total number of successful call service processes.

[0057] S403: When the ratio is lower than a second preset threshold, it is determined that there is a problem with the terminal itself.

[0058] It should be understood that after obtaining the number of successful call service processes corresponding to the call service data within a preset time period, the total number of call service processes corresponding to the call service data within the preset time period can also be obtained. In this case, the ratio of the number of successful calls to the total number of calls is calculated. When the ratio is lower than a second preset threshold, it is determined that the terminal itself has a problem, rather than being determined as a suspected poor quality terminal. In this way, the phenomenon of low accuracy in determining suspected poor quality terminals due to problems with the terminal itself can be avoided, and the accuracy of determining whether a terminal is a suspected poor quality terminal can be improved to a certain extent, thereby improving the accuracy of determining whether a terminal is a suspected poor quality terminal, and thus improving the accuracy of determining the current network quality.

[0059] The network quality determination method provided in an embodiment of the present invention monitors the call service data of each terminal, obtains monitoring results, and determines the current network quality based on the monitoring results of each terminal. This solves the problem that related technologies do not effectively determine network quality, which significantly affects the improvement of network service quality. Specifically, the network quality determination method provided in an embodiment of the present invention focuses on the call service data of each terminal and uses this data to determine the current network quality. This not only takes into account the experience of a single terminal, but also uses call service data from the control plane, which collects less data and thus reduces computing and storage overhead, resulting in a faster rate. In short, while ensuring that the experience of a single terminal is taken into account, computing and storage overhead are greatly reduced, and network quality can be effectively determined.

[0060] Furthermore, the network quality determination method provided in an embodiment of the present invention uses call service data on the control plane that affects user experience and occurs infrequently under normal circumstances. In this way, network quality problems can be discovered even when network indicators do not deteriorate significantly, thereby resolving network quality problems to optimize network quality.

[0061] Furthermore, the network quality determination method provided in the embodiment of the present invention can determine whether there is a problem with the terminal itself by obtaining the ratio of the number of successful call service processes corresponding to the call service data within a preset time period to the total number of successful times. In this way, the accuracy of determining whether it is a suspected poor quality terminal is improved, and the accuracy of determining the current network quality is thereby improved.

[0062] Furthermore, the network quality determination method provided by the embodiment of the present invention has a simple process, is easy to implement, and is conducive to deployment.

[0063] Example 2:

[0064] The embodiment of the present invention is based on the embodiment 1, and takes a specific network quality determination method as an example to further illustrate the present invention. Figure 5 As shown:

[0065] S501: Monitor call service data of each terminal within a preset time period.

[0066] S502: Obtain the number of times and the total number of times the call service process corresponding to the call service data is successful within a preset time period.

[0067] S503: Calculate the ratio of the number of successful call service processes to the total number of times.

[0068] S504: Determine whether the ratio is lower than a second preset threshold;

[0069] If not, execute S505; if so, execute S506.

[0070] S505: Determine if there is a problem with the terminal itself.

[0071] S506: Determine whether the number of successes is greater than a first preset threshold;

[0072] If yes, execute S507; if no, end the process.

[0073] S507: Determine that the terminal is a suspected poor-quality terminal.

[0074] S508: Classify each suspected poor quality terminal according to the base station or cell to which it belongs, and calculate the number of suspected poor quality terminals contained in each base station or cell.

[0075] S509: Sort the base stations or cells according to the number of suspected poor quality terminals from most to least, wherein the base station or cell containing the largest number of suspected poor quality terminals is determined to have the worst network quality, and the base station or cell containing the least number of suspected poor quality terminals is determined to have good network quality.

[0076] The network quality determination method provided in the embodiment of the present invention takes into account the experience of a single terminal. When the network indicators do not deteriorate significantly, network quality problems of base stations or cells can be discovered, so that network quality problems can be solved to optimize network quality. At the same time, due to the use of call service data of the control plane, the amount of collected data is relatively small. On the one hand, the computing and storage overhead is small and the speed is fast. On the other hand, the corresponding base station or cell is directly included in the call service data, and the accuracy of the determined network quality of the base station or cell is higher.

[0077] Example 3:

[0078] The embodiment of the present invention provides a network quality determination device, see Figure 6 As shown, the network quality determination device provided by the embodiment of the present invention includes: a monitoring module 601 and a determination module 602, wherein:

[0079] Monitoring module 601, used to monitor call service data of each terminal and obtain monitoring results;

[0080] The determination module 602 is configured to determine the current network quality according to the monitoring results of each terminal.

[0081] Optionally, in the embodiment of the present invention, the monitoring module 601 is configured to monitor call service data of each terminal within a preset time period; and obtain the number of times the call service process corresponding to the call service data is successful within the preset time period.

[0082] Optionally, in an embodiment of the present invention, the determination module 602 is used to determine that the terminal corresponding to the call service data is a suspected poor quality terminal when the number of times is greater than a first preset threshold; classify each suspected poor quality terminal according to the base station or cell to which it belongs to obtain a classification result; and determine the current network quality based on the classification result.

[0083] Optionally, in the embodiment of the present invention, the determining module 602 is configured to classify each suspected poor quality terminal according to the base station or cell to which it belongs, and calculate the number of suspected poor quality terminals contained in each base station or cell.

[0084] Optionally, in an embodiment of the present invention, the determination module 602 is used to sort the base stations or cells from most to least according to the number of suspected poor quality terminals contained therein, wherein the base station or cell containing the largest number of suspected poor quality terminals is determined to have the worst network quality, and the base station or cell containing the least number of suspected poor quality terminals is determined to have better network quality.

[0085] Optionally, in an embodiment of the present invention, the determination module 602 is also used to obtain the total number of call service processes corresponding to the call service data within a preset time period; calculate the proportion of the number of successful call service processes to the total number of times; when the proportion is lower than a second preset threshold, it is determined that there is a problem with the terminal itself.

[0086] Optionally, in the embodiment of the present invention, the determining module 602 is further configured to determine call service data, where the call service data includes call service data that affects user experience.

[0087] Optionally, in the embodiment of the present invention, the call service data includes at least one of the following: call service data related to obtaining an IP address, and call service data related to inter-system switching.

[0088] Optionally, in an embodiment of the present invention, in an LTE system, obtaining call service data related to an IP address includes: ATTACH service data; in a 5G NR system, obtaining call service data related to an IP address includes: REGISTER service data.

[0089] It is worth noting that in order to avoid redundant description, not all examples in Embodiments 1 to 2 are fully described in the embodiments of the present invention. It should be clear that all examples in Embodiments 1 to 2 are applicable to the embodiments of the present invention.

[0090] The network quality determination device provided in the embodiment of the present invention monitors the call service data of each terminal, obtains monitoring results, and determines the current network quality based on the monitoring results of each terminal. This solves the problem that the network quality is not well determined in the related art, which greatly affects the improvement of network service quality. Therefore, compared with the network quality determination device in the related art, the network quality determination device provided in the embodiment of the present invention focuses on the call service data of each terminal and uses the call service data of each terminal to determine the current network quality. Firstly, it takes into account the experience of a single terminal. Secondly, it uses the call service data of the control plane, collects a small amount of data, and thus has less computing and storage overhead and a faster rate. In short, on the basis of ensuring that the experience of a single terminal is taken into account, the computing and storage overhead is greatly reduced, and the network quality can be well determined.

[0091] Example 4:

[0092] The embodiment of the present invention provides a network device, see Figure 7 As shown, the network device provided by the embodiment of the present invention includes a processor 701 , a memory 702 , and a communication bus 703 .

[0093] The communication bus 703 in the embodiment of the present invention is used to realize the connection and communication between the processor 701 and the memory 702, and the processor 701 is used to execute one or more programs stored in the memory 702 to implement the following steps:

[0094] Monitor call service data of each network device and obtain monitoring results;

[0095] Determine the current network quality based on the monitoring results of each network device.

[0096] It is worth noting that in order to avoid redundant description, not all examples in Embodiments 1 to 2 are fully described in the embodiments of the present invention. It should be clear that all examples in Embodiments 1 to 2 are applicable to the embodiments of the present invention.

[0097] An embodiment of the present invention further provides a computer storage medium storing one or more programs. The one or more programs can be executed by one or more processors to implement the steps of the network quality determination method in embodiments one to two.

[0098] The computer storage media includes volatile or nonvolatile, removable or non-removable media implemented in any method or technology for storage of information (such as computer-readable instructions, data structures, computer program modules or other data). Computer storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable read-only memory), flash memory or other memory technology, CD-ROM (Compact Disc Read-Only Memory), digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer.

[0099] It can be seen that those skilled in the art should understand that all or some of the steps, systems, and functional modules / units in the methods disclosed above can be implemented as software (which can be implemented using computer program code executable by a computing device), firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component can have multiple functions, or a function or step can be performed by several physical components in cooperation. Some or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit.

[0100] In addition, it is well known to those skilled in the art that communication media generally contain computer-readable instructions, data structures, computer program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media. Therefore, the present invention is not limited to any specific hardware and software combination.

[0101] The above content is a further detailed description of the embodiments of the present invention in conjunction with specific implementation methods, and the specific implementation of the present invention cannot be considered to be limited to these descriptions. For those skilled in the art of the present invention, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should be considered to fall within the scope of protection of the present invention.

Claims

1. A method for determining network quality, comprising: Monitoring call service data of each terminal within a preset time period, the call service data including non-voice signaling data of the control plane that affects the user experience and normally occurs with low frequency, where the low frequency is a discontinuous triggering characteristic of the control plane signaling; Obtaining the number of successful call service processes corresponding to the call service data within the preset time period; When the number of times is greater than a first preset threshold, determining that the terminal corresponding to the call service data is a suspected poor-quality terminal; Classifying each of the suspected poor-quality terminals according to the base station or cell to which it belongs, and obtaining a classification result; The current network quality is determined according to the classification result.

2. The network quality determination method according to claim 1, wherein: Classifying each of the suspected poor-quality terminals according to the base station or cell to which it belongs and obtaining a classification result includes: Classifying each of the suspected poor-quality terminals according to the base station or cell to which it belongs, and calculating the number of suspected poor-quality terminals contained in each base station or cell; Determining the current network quality according to the classification result includes: The base stations or cells are sorted from most to least according to the number of suspected poor quality terminals they contain, wherein the base station or cell containing the largest number of suspected poor quality terminals is determined to have the worst network quality, and the base station or cell containing the least number of suspected poor quality terminals is determined to have good network quality.

3. The network quality determination method according to claim 1, wherein: Before determining that the terminal corresponding to the call service data is a suspected poor-quality terminal when the number of times is greater than a first preset threshold, the method further includes: Obtaining the total number of call service processes corresponding to the call service data within the preset time period; Calculate the ratio of the number of times the call service process is successful to the total number of times; When the ratio is lower than a second preset threshold, it is determined that there is a problem with the terminal itself.

4. The network quality determination method according to any one of claims 1 to 3, wherein: The monitoring of the call service data of each terminal and obtaining the monitoring results further includes: Call service data is determined, where the call service data includes call service data that affects user experience.

5. The network quality determination method according to claim 4, wherein: The call service data includes at least one of the following: call service data related to obtaining an IP address, and call service data related to switching between different systems.

6. The network quality determination method according to claim 5, wherein: In the LTE system, the acquiring of the call service data related to the IP address includes: ATTACH service data; In the 5G NR system, the acquisition of call service data related to the IP address includes: REGISTER service data.

7. A network quality determination device, characterized in that: The network quality determination device includes: a monitoring module and a determination module; The monitoring module is configured to monitor call service data of each terminal within a preset time period, the call service data including non-voice signaling data of the control plane that affects user experience and normally occurs with a low frequency, the low frequency being a discontinuous triggering characteristic of control plane signaling; and obtain the number of successful call service processes corresponding to the call service data within the preset time period; The determination module is used to determine that the terminal corresponding to the call service data is a suspected poor quality terminal when the number of times is greater than a first preset threshold; classify each suspected poor quality terminal according to the base station or cell to which it belongs to obtain a classification result; and determine the current network quality based on the classification result.

8. A network device, characterized in that: The network device includes: a processor, a memory and a communication bus; The communication bus is used to realize the connection and communication between the processor and the memory; The processor is configured to execute one or more computer programs stored in the memory to implement the steps of the network quality determination method according to any one of claims 1 to 6.

9. A computer storage medium, characterized in that The computer storage medium One or more computer programs are stored, and the one or more computer programs can be executed by one or more processors to implement the steps of the network quality determination method according to any one of claims 1 to 6.

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