Diagnosis method and device for mobile network 5G voice service complaint

Abstract

The invention discloses a diagnosis method and device for a mobile network 5G voice service complaint. The method comprises the following steps: obtaining a complaint problem of a mobile network 5G voice service complaint and a telephone number corresponding to a complaint user; according to the complaint question and the telephone number, inquiring contract signing and registration information of the complaint user in a core network to obtain user contract signing and registration information; and inputting the complaint problem and the user signing registration information into an expert database model to obtain a diagnosis result and a diagnosis suggestion so as to complete the diagnosis of the mobile network 5G voice service complaint, wherein the expert database model is an intelligent diagnosis tool which is pre-constructed on the basis of logic rules set by expert experience in combination with the influence of complaint scenes, network element priorities and contract signing functions on the 5G voice service of the mobile network. According to the method, the 5G voice service complaint in the mobile network can be automatically diagnosed, manual intervention is not needed, the processing efficiency is remarkably improved, and the requirements of a user can be rapidly met.

Description

Technical Field

[0001] The present invention belongs to the field of communication technologies, and particularly relates to a method and device for diagnosing complaints about 5G voice services in a mobile network. Background Art

[0002] Currently, the core network side mainly relies on traditional manual methods to handle complaints about 5G user voice services, facing the following two prominent problems:

[0003] (1) Network complexity: The 5G voice VoNR network structure is complex, involving multiple network elements and complex service logics. When handling user complaints, technicians need to log in to multiple core network elements to query and locate problems one by one. This process not only increases the workload and complexity of manual operations, but also results in high labor costs and resource consumption, seriously affecting the operation and maintenance efficiency.

[0004] (2) Lack of automation: The current complaint handling highly relies on manual operations and lacks automated and intelligent means. This leads to a significant extension of the problem-solving time and makes it difficult to achieve rapid response. The manual handling method not only delays the timely solution of problems, but also seriously affects user satisfaction and service experience, making it particularly difficult to solve problems efficiently. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to propose a method and device for diagnosing complaints about 5G voice services in a mobile network in view of the above deficiencies of the prior art. This method can automatically diagnose complaints about 5G voice services in a mobile network without manual intervention, significantly improving the processing efficiency and being able to quickly meet the needs of users.

[0006] In the first aspect, the present invention provides a method for diagnosing complaints about 5G voice services in a mobile network, and the method includes the following steps:

[0007] Obtain the complaint problem of the 5G voice service complaint in the mobile network and the telephone number corresponding to the complaining user;

[0008] According to the complaint problem and the telephone number, query the subscription and registration information of the complaining user in the core network to obtain the user subscription and registration information;

[0009] Input the complaint problem and the user subscription and registration information into the expert database model to obtain a diagnosis result and a diagnosis suggestion, so as to complete the diagnosis of the 5G voice service complaint in the mobile network;

[0010] Wherein, the expert database model is an intelligent diagnosis tool pre-constructed based on logical rules set according to expert experience, combined with the impact of complaint scenarios, network element priorities, and subscription functions on 5G voice services in the mobile network.

[0011] Further, the steps of obtaining the complaint problems of the 5G voice service of the mobile network and the telephone numbers corresponding to the complaining users specifically include the following steps:

[0012] Automatically obtain the complaint work orders of the 5G voice service from the customer service system or the online service platform;

[0013] Extract the complaint problems and the telephone numbers corresponding to the complaining users from the complaint work orders respectively, so as to obtain the complaint problems of the 5G voice service of the mobile network and the telephone numbers corresponding to the complaining users.

[0014] Further, the steps of querying the subscription and registration information of the complaining user in the core network according to the complaint problems and the telephone numbers specifically include the following steps:

[0015] Define the query target according to the complaint problems;

[0016] Wherein, the query target is the voice calling state, and / or, the voice called state, and / or, the roaming permission, and / or, the call forwarding state, and / or, the power-off or power-on state, and / or, the registration state;

[0017] According to the query target, query the subscription and registration information of the complaining user in the core network from the network elements, and mark the abnormal subscription and registration information with color brightness;

[0018] Wherein, the network elements are the User Data Management Center UDM, and / or, the VoLTE Application Server VoLTE AS, and / or, the Session Control Function S-CSCF, and / or, the ENUM Domain Name System ENUMDNS, and / or, the Virtual Circuit Switch vCS; when there are multiple network elements, synchronously obtain the subscription and registration information of the complaining user in the core network from multiple network elements for query.

[0019] Further, the steps of obtaining the subscription and registration information of the complaining user in the core network from the network elements specifically include:

[0020] Obtain the voice calling state from the VoLTE Application Server VoLTE AS, the Session Control Function S-CSCF, the ENUM Domain Name System ENUMDNS, and the Virtual Circuit Switch vCS service; and,

[0021] Obtain the voice called state from the VoLTE Application Server VoLTE AS, the Session Control Function S-CSCF, the ENUM Domain Name System ENUMDNS, and the Virtual Circuit Switch vCS service; and,

[0022] Obtain the roaming permission from the User Data Management Center UDM service; and,

[0023] Obtain the call forwarding status from the User Data Management Center (UDM) and the Session Control Function (S-CSCF) service; and,

[0024] Obtain the power-off or power-on status from the UDM service; and,

[0025] Obtain the registration status from the UDM and the S-CSCF service;

[0026] The VoLTE Application Server (VoLTE AS) service is obtained by connecting to the VoLTE AS through the SSH protocol;

[0027] The S-CSCF service is obtained by connecting to the S-CSCF using the Telnet protocol;

[0028] The UDM service is obtained by constructing a SOAP request and using the SOAP protocol;

[0029] The ENUM Domain Name System (ENUMDNS) service is obtained by querying the registration status of the user's telephone number through an HTTP GET request;

[0030] The virtual circuit switching (vCS) service is obtained by querying through an API or a command-line tool.

[0031] Further, before inputting the complaint problem and the user's subscribed registration information into the expert library model, the method further includes: constructing an expert library model;

[0032] The construction of the expert library model specifically includes the following steps:

[0033] Based on the experience and knowledge of experts in handling 5G voice service complaints in the mobile network, preset complaint scenarios;

[0034] Based on the preset complaint scenarios and in accordance with the instruction parameter specifications and parameter values in the standard knowledge base, set diagnostic logic rules; and, according to the 5G service functions, set the network element priorities for 5G voice service complaints in the mobile network;

[0035] Among them, the diagnostic logic rules include complaint type classification, diagnostic priorities for different complaint types, and the impact of user subscription and registration information on the quality of 5G voice services;

[0036] Based on the diagnostic logic rules and the network element priorities, clarify the specific reasons for different complaint problems;

[0037] Based on the experience and knowledge of experts in handling 5G voice service complaints in the mobile network, determine the specific solutions corresponding to the specific reasons;

[0038] Summarize the complaint problems, the diagnostic logic rules, the network element priorities, the specific reasons, and the specific solutions to obtain an expert library model.

[0039] Further, before setting the diagnostic logic rules based on the preset complaint scenarios and according to the instruction parameter specifications and parameter values in the standard knowledge base, the method further includes: constructing a standard knowledge base;

[0040] The construction of the standard knowledge base specifically includes the following steps:

[0041] Collect relevant query instructions and parameter specifications from the network elements of the core network;

[0042] Determine the influencing parameters affecting 5G voice services from the query instructions and the parameter specifications;

[0043] Set a normal value range or status for each of the influencing parameters to obtain influencing parameter specifications;

[0044] Organize the query instructions, the parameter specifications, and the influencing parameter specifications to form a set of knowledge bases for extracting user data affecting 5G voice services from network elements, thereby obtaining a standard knowledge base.

[0045] Further, setting the network element priorities for 5G voice service complaints in the mobile network specifically includes the following steps:

[0046] Identify 5G service functions; the 5G service functions include basic voice functions, roaming permissions, call forwarding, and outage status;

[0047] Determine the network elements affecting 5G service functions;

[0048] Set the network element priorities for 5G voice service complaints in the mobile network;

[0049] Among them, setting the network element priorities for 5G voice service complaints in the mobile network specifically includes: setting the network elements affecting basic voice functions as the first priority; and setting the network elements affecting roaming permissions as the second priority; and setting the network elements affecting call forwarding as the third priority; and setting the network elements affecting outage status as the fourth priority.

[0050] In a second aspect, the present invention provides a diagnostic device for 5G voice service complaints in a mobile network, and the device includes:

[0051] An acquisition unit, configured to acquire the complaint problems of 5G voice service complaints in the mobile network and the telephone number corresponding to the complaining user;

[0052] A query unit, connected to the acquisition unit, for querying the subscription and registration information of the complaining user in the core network according to the complaint problem and the telephone number, so as to obtain the user subscription and registration information;

[0053] An input unit, connected to the query unit, for inputting the complaint problem and the user subscription and registration information into the expert library model to obtain a diagnosis result and a diagnosis suggestion, so as to complete the diagnosis of the 5G voice service complaint of the mobile network;

[0054] Wherein, the expert library model is an intelligent diagnosis tool pre-constructed based on the logical rules set by expert experience, combined with the influence of the complaint scenario, network element priority, and subscription function on the 5G voice service of the mobile network.

[0055] Further, the query unit includes:

[0056] A definition module, for defining a query target according to the complaint problem;

[0057] Wherein, the query target is the voice calling state, and / or, the voice called state, and / or, the roaming permission, and / or, the call forwarding state, and / or, the shutdown or startup state, and / or, the registration state;

[0058] A query module, connected to the definition module, for querying the subscription and registration information of the complaining user in the core network from the network elements according to the query target, and performing color brightness marking on the abnormal subscription and registration information;

[0059] Wherein, the network elements are the User Data Management Center (UDM), and / or, the VoLTE Application Server (VoLTE AS), and / or, the Session Control Function (S-CSCF), and / or, the ENUM Domain Name System (ENUMDNS), and / or, the virtual circuit switching (vCS); when there are multiple network elements, the subscription and registration information of the complaining user in the core network is synchronously obtained from multiple network elements for query.

[0060] Further, the device further includes a construction unit, the construction unit is connected to the input unit, and is used for constructing an expert library model, so that the input unit inputs the complaint problem and the user subscription and registration information into the expert library model;

[0061] The construction unit includes:

[0062] A preset module, for presetting complaint scenarios based on the experience and knowledge of experts in handling 5G voice service complaints of the mobile network;

[0063] A setting module, connected to the preset module, is used to set diagnostic logic rules based on preset complaint scenarios and in accordance with the instruction parameters and parameter values in the standard knowledge base; and, set the network element priority for 5G voice service complaints in the mobile network according to the 5G service function.

[0064] Among them, the diagnostic logic rules include complaint type classification, diagnostic priorities for different complaint types, and the impact of user subscription and registration information on the quality of 5G voice services.

[0065] A first processing module, connected to the setting module, is used to clarify the specific reasons for different complaint problems based on the diagnostic logic rules and the network element priority.

[0066] A second processing module, connected to the first processing module, is used to determine the specific solutions corresponding to the specific reasons based on the experience and knowledge of experts in handling 5G voice service complaints in the mobile network.

[0067] A summary module, respectively connected to the setting module, the first processing module, and the second processing module, is used to summarize the complaint problems, the diagnostic logic rules, the network element priority, the specific reasons, and the specific solutions to obtain an expert database model.

[0068] Through the expert database model, the present invention can automatically diagnose 5G voice service complaints in the mobile network without manual intervention, can achieve one-key diagnosis, significantly improves the processing efficiency, and can quickly meet the needs of users. The specific beneficial effects are as follows:

[0069] 1. High degree of automation, reducing the risk of human intervention: With the help of the expert database model, automatic diagnosis of user complaints is realized, without the need for manual analysis and judgment of each complaint problem one by one, greatly reducing the manual operation links. This not only reduces the high dependence on humans but also avoids the risk of mistakes caused by human negligence, fatigue, and other factors, ensuring the accuracy and stability of the diagnostic results.

[0070] 2. Efficient processing, quickly responding to user needs: By quickly obtaining and deeply analyzing relevant information of users, this method can significantly shorten the complaint handling time, achieve rapid response and resolution of complaints. After the user submits a complaint, the system can quickly give a diagnostic result and handling suggestions, timely meet the user's needs, and effectively improve the user's satisfaction with the service.

[0071] 3. Provide decision-making support to assist in making reasonable operation and maintenance decisions: The expert library model has accumulated rich experience and professional knowledge, and can provide diagnosis suggestions based on experience for operation and maintenance personnel. These valuable suggestions help operation and maintenance personnel understand complex problems more comprehensively and deeply, so as to make more scientific and reasonable decisions when handling complaints, and improve the efficiency and quality of problem-solving.

[0072] 4. Save costs and optimize the allocation of human resources: Since the diagnosis process is highly automated, a large amount of manual intervention is reduced, thereby reducing the investment in human costs during operation and maintenance. At the same time, human resources are liberated from tedious repetitive work and can be invested in more valuable and innovative work, effectively improving the utilization rate of human resources.

[0073] 5. Continuously optimize and promote the improvement of service quality: By continuously accumulating and analyzing the data and experience generated during each complaint handling process, the expert library model can continuously optimize its own performance and continuously improve the accuracy of diagnosis and service quality. At the same time, based on in-depth analysis of complaint data, operators can also identify improvement points in services, and conduct targeted business optimization and improvement to promote the continuous improvement of services.

[0074] 6. Intelligent identification and rapid focus on the root cause of problems: Using a variety of intelligent algorithms, such as the synchronization algorithm of network element priority and subscription function priority, the instant termination mechanism, and the abnormal high-light marking algorithm, etc., can quickly locate the root cause of problems and focus on the core key information. For example, when a user fails to activate a key voice function, the instant termination mechanism will immediately stop unnecessary analysis and save resources; the abnormal high-light marking algorithm can visually present abnormal problems, helping operation and maintenance personnel quickly identify and handle them, and improving the efficiency of problem-solving. At the same time, automated data processing and knowledge base-driven intelligent diagnosis algorithms further ensure the accurate, standardized and efficient use of information. Brief Description of the Drawings

[0075] Figure 1 It is a schematic diagram of the diagnosis method for 5G voice service complaints in the embodiment of the present invention;

[0076] Figure 2 It is a diagnostic framework diagram for 5G voice service complaints in the embodiment of the present invention;

[0077] Figure 3 It is a diagnostic flow chart for 5G voice service complaints in the embodiment of the present invention;

[0078] Figure 4 It is a diagnostic logic flow chart for the international roaming permission of users in the embodiment of the present invention;

[0079] Figure 5It is the integrated logic flowchart for diagnosing user roaming permissions in the embodiments of the present invention;

[0080] Figure 6 It is the schematic diagram of the diagnosing device for 5G voice service complaints in the mobile network in the embodiments of the present invention.

[0081] Reference numerals: 10, acquisition unit; 20, query unit; 30, input unit. Specific embodiments

[0082] To enable those skilled in the art to better understand the technical solutions of the present invention, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0083] It can be understood that the specific embodiments and the accompanying drawings described herein are only for explaining the present invention, rather than limiting the present invention.

[0084] It can be understood that, without conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

[0085] It can be understood that, for the convenience of description, only the parts related to the present invention are shown in the accompanying drawings of the present invention, and the parts unrelated to the present invention are not shown in the accompanying drawings.

[0086] It can be understood that each unit and module involved in the embodiments of the present invention may correspond to only one entity structure, or may be composed of multiple entity structures, or multiple units and modules may also be integrated into one entity structure.

[0087] It can be understood that, without conflict, the functions and steps marked in the flowcharts and block diagrams of the present invention may occur in an order different from that marked in the accompanying drawings.

[0088] It can be understood that in the flowcharts and block diagrams of the present invention, the possible architectures, functions, and operations of the systems, devices, equipment, and methods according to the embodiments of the present invention are shown. Among them, each block in the flowchart or block diagram may represent a unit, module, program segment, or code, which contains executable instructions for implementing the specified function. Moreover, each block or combination of blocks in the block diagram and flowchart can be implemented by a hardware-based system for implementing the specified function, or can be implemented by a combination of hardware and computer instructions.

[0089] It can be understood that the units and modules involved in the embodiments of the present invention can be implemented in software or in hardware. For example, the units and modules can be located in the processor.

[0090] Embodiment 1:

[0091] This embodiment provides a diagnostic method for 5G voice service complaints in a mobile network. This method can be applied to the customer service center and the technical support department. Through an intelligent expert library model, it can automatically analyze and judge various complaint problems encountered by users during the use of 5G voice services. This method can quickly obtain the complaint problems of users and relevant registration information, so as to efficiently provide accurate diagnostic results and solution suggestions. It is applicable to various scenarios such as user troubleshooting, voice quality problems, service interruptions, etc., and can significantly improve the customer service response speed and overall service quality, enhancing the user experience.

[0092] As Figure 1 shown, the diagnostic method for 5G voice service complaints in this embodiment specifically includes the following steps:

[0093] Step K1: Obtain the complaint problem of the 5G voice service complaint in the mobile network and the telephone number corresponding to the complaining user.

[0094] As a specific implementation manner, the obtaining of the complaint problem of the 5G voice service complaint in the mobile network and the telephone number corresponding to the complaining user specifically includes the following steps:

[0095] Automatically obtain the complaint work order of the 5G voice service from the customer service system or the online service platform;

[0096] Respectively extract the complaint problem and the telephone number corresponding to the complaining user from the complaint work order, so as to obtain the complaint problem of the 5G voice service complaint in the mobile network and the telephone number corresponding to the complaining user.

[0097] The specific steps of obtaining the complaint problem of the 5G voice service complaint in the mobile network and the telephone number corresponding to the complaining user can be divided into several stages. First, the system seamlessly docks with the customer service system or the online service platform through an interface, and automatically retrieves the complaint work orders related to the 5G voice service. This process not only improves work efficiency but also reduces the error of manual operation. Subsequently, the system deeply analyzes each complaint work order to extract the key information therein, including the specific complaint problems reflected by the user, such as poor call quality, unstable connection, or insufficient signal coverage. At the same time, the telephone number submitted by the user will also be extracted. This series of automated processing steps ensures that the complaint information and user contact information related to the 5G voice service in the mobile network can be accurately and comprehensively obtained, laying a solid foundation for subsequent scientific diagnosis and effective handling, and ultimately improving the user satisfaction and service quality.

[0098] Step K2: According to the complaint problem and the telephone number, query the subscription and registration information of the complaining user in the core network to obtain the user subscription registration information.

[0099] Query the subscription and registration information of the complaining user in the core network according to the complaint problem and the telephone number, and the specific steps are as follows:

[0100] Define a query target according to the complaint problem;

[0101] Among them, the query target is the voice calling status, and / or the voice called status, and / or the roaming permission, and / or the call forwarding status, and / or the shutdown or startup status, and / or the registration status;

[0102] According to the query target, query the subscription and registration information of the complaining user in the core network from the network elements, and perform color brightness marking on the abnormal subscription and registration information;

[0103] Among them, the network elements are the User Data Management Center (UDM), and / or the VoLTE Application Server (VoLTE AS), and / or the Session Control Function (S-CSCF), and / or the ENUM Domain Name System (ENUMDNS), and / or the virtual circuit switching (vCS); when there are multiple network elements, synchronously obtain the subscription and registration information of the complaining user in the core network from multiple network elements for query.

[0104] The obtaining of the subscription and registration information of the complaining user in the core network from the network elements specifically includes:

[0105] Obtain the voice calling status from the VoLTE Application Server (VoLTE AS), Session Control Function (S-CSCF), ENUM Domain Name System (ENUMDNS), and virtual circuit switching (vCS) services; and,

[0106] Obtain the voice called status from the VoLTE Application Server (VoLTE AS), Session Control Function (S-CSCF), ENUM Domain Name System (ENUMDNS), and virtual circuit switching (vCS) services; and,

[0107] Obtain the roaming permission from the User Data Management Center (UDM) service; and,

[0108] Obtain the call forwarding status from the User Data Management Center (UDM) and Session Control Function (S-CSCF) services; and,

[0109] Obtain the shutdown or startup status from the User Data Management Center (UDM) service; and,

[0110] Obtain the registration status from the User Data Management Center (UDM) and Session Control Function (S-CSCF) services;

[0111] The VoLTE Application Server (VoLTE AS) service is obtained by connecting to the VoLTE AS through the SSH protocol;

[0112] The Session Control Function S-CSCF service is obtained by connecting to the S-CSCF using the Telnet protocol;

[0113] The User Data Management Center UDM service is obtained by constructing a SOAP request and using the SOAP protocol;

[0114] The ENUM Domain Name System ENUMDNS service is obtained by querying the telephone number registration status of the user through an HTTP GET request;

[0115] The Virtual Circuit Switching vCS service is obtained by querying through an API or a command-line tool.

[0116] Step K3: Input the complaint problem and the user subscription and registration information into the expert library model to obtain a diagnosis result and a diagnosis suggestion, so as to complete the diagnosis of the 5G voice service complaint in the mobile network; the expert library model is an intelligent diagnosis tool pre-constructed based on the logical rules set by expert experience, combined with the impact of the complaint scenario, network element priority, and subscription function on the 5G voice service in the mobile network.

[0117] Before specifically implementing this step, an expert library model needs to be constructed first;

[0118] The construction of the expert library model specifically includes the following steps:

[0119] Based on the experience and knowledge of experts in handling 5G voice service complaints in the mobile network, preset the complaint scenario;

[0120] Based on the preset complaint scenario and according to the instruction parameter specifications and parameter values in the standard knowledge base, set the diagnostic logic rules; and, according to the 5G service function, set the network element priority of the 5G voice service complaint in the mobile network.

[0121] Among them, the diagnostic logic rules include complaint type classification, diagnostic priorities for different complaint types, and the impact of user subscription and registration information on the quality of the 5G voice service;

[0122] Based on the diagnostic logic rules and the network element priority, clarify the specific reasons for different complaint problems;

[0123] Based on the experience and knowledge of experts in handling 5G voice service complaints in the mobile network, determine the specific solutions corresponding to the specific reasons;

[0124] Summarize the complaint problems, the diagnostic logic rules, the network element priority, the specific reasons, and the specific solutions to obtain the expert library model.

[0125] As a more specific implementation, before setting the diagnostic logic rules based on the preset complaint scenarios and in accordance with the instruction parameters and parameter values in the standard knowledge base, the method further includes: constructing a standard knowledge base;

[0126] The construction of the standard knowledge base specifically includes the following steps:

[0127] Collect relevant query instructions and parameter specifications from the network elements of the core network;

[0128] Determine the influencing parameters affecting the 5G voice service from the query instructions and the parameter specifications;

[0129] Set a normal value range or status for each of the influencing parameters to obtain the influencing parameter specifications;

[0130] Organize the query instructions, the parameter specifications, and the influencing parameter specifications to form a knowledge base for extracting user data affecting the 5G voice service from the network elements, thereby obtaining the standard knowledge base.

[0131] As a specific implementation, setting the network element priority for complaints about the 5G voice service of the mobile network specifically includes the following steps:

[0132] Identify the 5G service functions; the 5G service functions include basic voice functions, roaming permissions, call forwarding, and outage status;

[0133] Determine the network elements affecting the 5G service functions;

[0134] Set the network element priority for complaints about the 5G voice service of the mobile network;

[0135] Among them, setting the network element priority for complaints about the 5G voice service of the mobile network specifically includes: setting the network elements affecting the basic voice function as the first priority; and setting the network elements affecting the roaming permissions as the second priority; and setting the network elements affecting the call forwarding as the third priority; and setting the network elements affecting the outage status as the fourth priority.

[0136] In this embodiment, through the expert library model, the automatic diagnosis of complaints about the 5G voice service in the mobile network is realized, which completely does not require manual intervention, and the user only needs to click a button to complete the diagnosis. As Figure 2 shown, the specific steps of this method include five steps: data collection, service logic judgment, data query, data analysis, and result presentation.

[0137] The first step is data collection: For key network elements in the core network, including User Data Management (UDM), VoLTE Application Server (VoLTE AS), Call Session Control Function (CSCF), ENUM Domain Name System (ENUM DNS), and virtual Circuit Switching (vCS), specific instructions for querying 5G voice user subscription functions and registration information will be collected. Subsequently, the execution results of normal service-state users will be analyzed, with a focus on extracting the key parameter specifications that affect voice functions. These key parameters include, but are not limited to, the access network type, the activation status of basic voice services (such as basic calls, emergency calls, etc.), the settings of roaming permissions (domestic roaming, international roaming, etc.), the real-time information of the power-on / off status, the configuration of the call forwarding function, the identification of the registered network element, and the confirmation of the registration status, etc.

[0138] For each key parameter, its normal parameter value range or status will be clarified. For example, the access network type should support multiple networks such as 5G, 4G, 3G, and 2G, the basic voice services need to be in an activated state, the roaming permissions are configured according to user needs, the power-on / off status should be powered on, the call forwarding function should be configured according to user settings, the registered network element should be the network element where the user is currently located, and the registration status should be registered, etc.

[0139] Finally, all query instructions, key parameter specifications, and their normal parameter values will be sorted and summarized into a standard knowledge base. This knowledge base will serve as an important basis for subsequent service logic judgment, helping to quickly and accurately locate and solve problems encountered by 5G voice users during use.

[0140] The second step is service logic judgment: Specifically, as Figure 3 shown, first, based on the experience of experts, manual logical analysis is carried out, complaint scenarios are preset, the involved network elements, the content to be queried, and specific query instructions are clarified. At the same time, priority sorting is set, the key fields and their correct parameter values are determined. In this process, each key point is deduced one by one to confirm each query conclusion, and based on this, the diagnostic results and corresponding suggestions for each key point are provided. On the basis of this process, an expert library for 5G voice service complaint logic judgment analysis is constructed.

[0141] Next, using digital and intelligent means, according to various complaint scenarios recorded in the logic judgment analysis expert library, parallel logical judgments are carried out in the order of network element priorities and the priorities of the impact of subscription functions on user voice services. Specifically, as Figure 4As shown, if it is found during the preliminary logical analysis stage that a basic voice function with a higher priority (such as the TS11 function) is not enabled in the User Data Management (UDM), the system will immediately abort the subsequent detailed analysis, directly present the summary of the query results based on the constructed expert library for logical judgment analysis, intuitively give the diagnostic result, and provide targeted optimization and solution suggestions.

[0142] In addition, the one - key diagnosis device for 5G voice service complaints uses deep learning technology to deeply understand each subscribed function of the user on the core network - related network elements, checkpoints of the registration status, query instructions, main parameters, and judgment logic, so as to accurately locate the root cause of the problem.

[0143] As Figure 5 shown, in the diagnostic logic of 5G voice service roaming permissions, it is first necessary to understand two main areas it covers: Circuit Switched (CS) and IP Multimedia Subsystem (IMS). The roaming permissions of the CS voice function can be divided into three cases: domestic, international, and unknown, involving network elements such as the Home Subscriber Server (HSS) and Unified Data Management (UDM); while the IMS voice roaming permissions also include domestic, international, and unknown. The data related to EPC can be obtained from the UDM, mainly involving network elements such as the VoLTE Application Server (VoLTE AS). The diagnostic function of the voice service roaming permissions is divided into four sub - items, which respectively perform accuracy diagnosis on international roaming permissions, 2 / 3G service roaming permissions, 4G service roaming permissions, and 5G service roaming permissions. Finally, after summarizing the four results, a comprehensive analysis is carried out to obtain the final diagnostic result. Taking the user's international roaming permissions as an example, the diagnosis will check whether the user has enabled international roaming permissions, query through the SOAP interface instruction "LST_ODBDAT" of a certain company, and the return example of the main parameters is presented in XML format, including the user's IMSI, ISDN, and relevant roaming permission status information. For example, when "ResultCode" is 0, it indicates success.

[0144] The specific instructions are as follows:

[0145]

[0146]

[0147] In the code, "NOBAR" means allowing the user to roam internationally, while "BAR" means not allowing the user to roam internationally.

[0148] In the third - step data query, the basic information of the user will be mainly checked, such as whether the functions of voice calling, voice called, roaming permission, call forwarding, power - on / off status, and registration status are normal. This process involves multiple network elements such as UDM, VoLTE AS, S - CSCF, ENUMDNS, and vCS. According to the communication protocols used by each network element (including SOAP - based WebService, SSH, Telnet, and vendor - defined protocols), synchronous data query will be performed and user data will be extracted. Specifically, first, a request is constructed through the SOAP protocol and the remote WebService is called to obtain the user service subscription and registration information of the UDM network element in XML format; then, SSH or Telnet is used to execute commands to obtain the user subscription and registration data of the S - CSCF, VoLTE AS, and vCS network elements. Finally, according to the phone number and problems of the complaining user, a query is made, key parameters are filtered out, and the valid data is organized into a normalized format and stored in the database for subsequent data analysis.

[0149] In the fourth - step data analysis, the user data queried will be comprehensively and deeply analyzed according to the judgment conditions of the 5G voice service complaint - handling logic (which has been organized into an expert library in the second step), and the results will be summarized to output the diagnostic results and suggestions. This analysis process mainly uses SAX (Simple API for XML) parsing technology. Through a custom ContentHandler, accurate identification and information extraction, data conversion, and validity verification of key elements in the XML - formatted data are realized, thus providing solid data support for the output of the diagnostic results. In the ContentHandler, the parsing logic for the complaint scenarios and judgment conditions will be written, specifically including identifying specific tags (such as UserBasicInfo, CommunicationStatus, SubscriptionInfo, and RegistrationStatus) to locate the key data parts, extracting key fields (such as subscription functions, roaming permissions, power - on / off status, and registration status) and accurately extracting them according to the XML structure, and at the same time performing data conversion and verification, converting the extracted data into the format used inside the program and ensuring that it conforms to the business logic and expected values.

[0150] In the result presentation of the fifth step, the front-end data display of the 5G voice one-key diagnosis device uses the React framework combined with the Ant Design (AntD) framework. Through the component-based development mode of React, an efficient and reusable user interface is constructed, and the high-quality UI component library provided by AntD is used to achieve beautiful and professional data display effects. The device clearly and orderly displays key information such as the user number, detailed complaint information, instant query results, accurate diagnosis conclusions, targeted diagnosis suggestions, convenient expand details buttons, and detailed results of various network element queries. For any detected abnormal problems, red highlighting is used to effectively help operation and maintenance personnel quickly identify the core problems of user complaints in a prominent way, thus significantly improving the efficiency and quality of problem handling.

[0151] This embodiment deeply integrates various network element communication protocols of the 5G network and the IMS network, realizing real-time seamless interaction with key network elements of the 5G core network and the IMS network. Through automation and intelligent technologies, it can efficiently capture the subscription and registration data of users, greatly reducing manual operations, thus significantly improving the operation efficiency. At the same time, with the help of deep learning technology, the device can pre-insight the normal subscription and registration status of users in relevant network elements of the mobile core network. Based on key conditions such as the user's telephone number and complaint matters, in-depth and comprehensive analysis of user data is carried out to intelligently identify problems with the subscription function and registration status that affect 5G voice services, including abnormal function subscriptions, arrears outages, abnormal registered network status, and call forwarding activation status. Finally, based on the priority judgment of the impact on user service usage, the device can output accurate diagnosis results and improvement suggestions, greatly improving the efficiency and accuracy of diagnosing user complaint problems.

[0152] Embodiment 2:

[0153] As Figure 6 shown, this embodiment provides a diagnosis device for complaints about 5G voice services in a mobile network. The device includes:

[0154] An acquisition unit 10, configured to acquire a complaint problem of a 5G voice service complaint in a mobile network and the telephone number corresponding to the complaining user;

[0155] A query unit 20, connected to the acquisition unit 10, configured to query the subscription and registration information of the complaining user in the core network according to the complaint problem and the telephone number to obtain user subscription registration information;

[0156] An input unit 30, connected to the query unit 20, configured to input the complaint problem and the user subscription registration information into an expert library model to obtain a diagnosis result and a diagnosis suggestion, so as to complete the diagnosis of a 5G voice service complaint in a mobile network;

[0157] Among them, the expert database model is an intelligent diagnostic tool pre-constructed based on the logical rules set according to expert experience, combined with the impact of the complaint scenario, network element priority, and subscription function on the 5G voice service of the mobile network.

[0158] As a specific implementation manner, the query unit 20 includes:

[0159] A definition module, configured to define a query target according to the complaint problem;

[0160] Among them, the query target is the voice calling state, and / or the voice called state, and / or the roaming permission, and / or the call forwarding state, and / or the shutdown or startup state, and / or the registration state;

[0161] A query module, connected to the definition module, configured to query the subscription and registration information of the complaint user in the core network from the network elements according to the query target, and perform color brightness marking on the abnormal subscription and registration information;

[0162] Among them, the network elements are the User Data Management Center (UDM), and / or the VoLTE Application Server (VoLTE AS), and / or the Session Control Function (S-CSCF), and / or the ENUM Domain Name System (ENUMDNS), and / or the virtual circuit switching (vCS); when the network elements are multiple network elements, the subscription and registration information of the complaint user in the core network is synchronously obtained from multiple network elements for query.

[0163] As a specific implementation manner, the device further includes a construction unit, and the construction unit is connected to the input unit, configured to construct an expert database model, so that the input unit inputs the complaint problem and the user subscription and registration information into the expert database model;

[0164] The construction unit includes:

[0165] A preset module, configured to preset a complaint scenario based on the experience and knowledge of experts in handling complaints about 5G voice services of the mobile network;

[0166] A setting module, connected to the preset module, configured to set diagnostic logic rules based on the preset complaint scenario and according to the instruction parameter specifications and parameter values in the standard knowledge base; and set the network element priority of complaints about 5G voice services of the mobile network according to the 5G service function;

[0167] Among them, the diagnostic logic rules include complaint type classification, diagnostic priorities of different complaint types, and the impact of user subscription and registration information on the quality of 5G voice services;

[0168] The first processing module, connected to the setting module, is configured to clarify the specific reasons for different complaint problems based on the diagnostic logic rules and the network element priorities;

[0169] The second processing module, connected to the first processing module, is configured to determine the specific solutions corresponding to the specific reasons based on the experience and knowledge of experts in handling 5G voice service complaints in the mobile network;

[0170] The summarization module, respectively connected to the setting module, the first processing module, and the second processing module, is configured to summarize the complaint problems, the diagnostic logic rules, the network element priorities, the specific reasons, and the specific solutions to obtain an expert library model.

[0171] The device in this embodiment can execute the method in Embodiment 1.

[0172] It can be understood that the above embodiments are merely exemplary embodiments adopted to illustrate the principle of the present invention, but the present invention is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also regarded as the protection scope of the present invention.

Claims

1. A diagnostic method for complaints about 5G voice services in a mobile network, characterized in that, The method includes the following steps: Obtain the complaint problem of the 5G voice service of the mobile network and the telephone number corresponding to the complaining user; According to the complaint problem and the telephone number, query the subscription and registration information of the complaining user in the core network to obtain the user subscription and registration information; Input the complaint problem and the user subscription and registration information into the expert library model to obtain a diagnosis result and a diagnosis suggestion, so as to complete the diagnosis of the 5G voice service complaint of the mobile network; Among them, the expert library model is an intelligent diagnosis tool pre-constructed based on the logical rules set by expert experience, combined with the impact of the complaint scenario, network element priority, and subscription function on the 5G voice service of the mobile network.

2. The diagnosis method of the 5G voice service complaint of the mobile network according to claim 1, characterized in that The obtaining of the complaint problem of the 5G voice service complaint of the mobile network and the telephone number corresponding to the complaining user specifically includes the following steps: Automatically obtain the complaint work order of the 5G voice service from the customer service system or the online service platform; Respectively extract the complaint problem and the telephone number corresponding to the complaining user from the complaint work order, so as to obtain the complaint problem of the 5G voice service complaint of the mobile network and the telephone number corresponding to the complaining user.

3. The diagnosis method of the 5G voice service complaint of the mobile network according to claim 1, characterized in that The querying of the subscription and registration information of the complaining user in the core network according to the complaint problem and the telephone number specifically includes the following steps: Define the query target according to the complaint problem; Among them, the query target is the voice calling status, and / or, the voice called status, and / or, the roaming permission, and / or, the call forwarding status, and / or, the shutdown or startup status, and / or, the registration status; According to the query target and the telephone number, query the subscription and registration information of the complaining user in the core network from the network elements, and perform color brightness marking on the abnormal subscription and registration information; Among them, the network elements are the User Data Management Center (UDM), and / or, the VoLTE Application Server (VoLTE AS), and / or, the Session Control Function (S-CSCF), and / or, the ENUM Domain Name System (ENUMDNS), and / or, the Virtual Circuit Switching (vCS); when there are multiple network elements, simultaneously obtain the subscription and registration information of the complaining user in the core network from multiple network elements for query.

4. The diagnosis method of the 5G voice service complaint of the mobile network according to claim 3, characterized in that The obtaining of the subscription and registration information of the complaining user in the core network from the network elements specifically includes: Obtain the voice calling status from the VoLTE Application Server (VoLTE AS), the Session Control Function (S-CSCF), the ENUM Domain Name System (ENUMDNS), and the Virtual Circuit Switching (vCS) service; and, Obtain the voice called status from the VoLTE Application Server (VoLTE AS), the Session Control Function (S-CSCF), the ENUM Domain Name System (ENUMDNS), and the Virtual Circuit Switching (vCS) service; and, Obtain the roaming permission from the User Data Management Center (UDM) service; and, Obtain the call forwarding status from the User Data Management Center (UDM) and the Session Control Function (S-CSCF) service; and, Obtain the power-off or power-on status from the UDM service; and, Obtain the registration status from the UDM and the S-CSCF service; The VoLTE Application Server (VoLTE AS) service is obtained by connecting to the VoLTE AS through the SSH protocol; The S-CSCF service is obtained by connecting to the S-CSCF using the Telnet protocol; The UDM service is obtained by constructing a SOAP request and using the SOAP protocol; The ENUM Domain Name System (ENUMDNS) service is obtained by querying the registration status of the user's telephone number through an HTTP GET request; The virtual circuit switching (vCS) service is obtained by querying through an API or a command-line tool.

5. The diagnostic method for complaints about 5G voice services in a mobile network according to any one of claims 1 to 4, characterized in that, Before inputting the complaint problem and the user's subscribed registration information into the expert library model, the method further includes: constructing an expert library model; The construction of the expert library model specifically includes the following steps: Based on the experience and knowledge of experts in handling complaints about 5G voice services in a mobile network, preset complaint scenarios; Based on the preset complaint scenarios and in accordance with the instruction parameter specifications and parameter values in the standard knowledge base, set diagnostic logic rules; and, according to the 5G service functions, set the network element priorities for complaints about 5G voice services in a mobile network; Among them, the diagnostic logic rules include complaint type classification, diagnostic priorities for different complaint types, and the impact of user subscription and registration information on the quality of 5G voice services; Based on the diagnostic logic rules and the network element priorities, clarify the specific reasons for different complaint problems; Based on the experience and knowledge of experts in handling complaints about 5G voice services in a mobile network, determine the specific solutions corresponding to the specific reasons; Summarize the complaint problems, the diagnostic logic rules, the network element priorities, the specific reasons, and the specific solutions to obtain an expert library model.

6. The diagnostic method for complaints about 5G voice services in a mobile network according to claim 5, characterized in that, Before setting the diagnostic logic rules based on the preset complaint scenarios and in accordance with the instruction parameter specifications and parameter values in the standard knowledge base, the method further includes: constructing a standard knowledge base; The construction of the standard knowledge base specifically includes the following steps: Collect relevant query instructions and parameter specifications from the network elements of the core network; Determine the impact parameters affecting 5G voice services from the query instructions and the parameter specifications; Set a normal value range or status for each of the impact parameters to obtain impact parameter specifications; Sort out the query instructions, the parameter specifications, and the impact parameter specifications to form a knowledge base for extracting user data affecting 5G voice services from network elements, thereby obtaining a standard knowledge base.

7. The diagnostic method for complaints about 5G voice services in a mobile network according to claim 5, characterized in that setting the network element priority for complaints about 5G voice services in a mobile network according to 5G service functions, which specifically includes the following steps: identifying 5G service functions; the 5G service functions include basic voice functions, roaming permissions, call forwarding, and outage status; determining the network elements that affect 5G service functions; setting the network element priority for complaints about 5G voice services in a mobile network; wherein, setting the network element priority for complaints about 5G voice services in a mobile network specifically includes: setting the network elements that affect basic voice functions as the first priority; and setting the network elements that affect roaming permissions as the second priority; and setting the network elements that affect call forwarding as the third priority; and setting the network elements that affect outage status as the fourth priority.

8. A diagnostic device for complaints about 5G voice services in a mobile network, characterized in that, including: an acquisition unit, configured to acquire the complaint problem of the complaint about 5G voice services in a mobile network and the telephone number corresponding to the complaining user; a query unit, connected to the acquisition unit, configured to query the subscription and registration information of the complaining user in the core network according to the complaint problem and the telephone number to obtain user subscription and registration information; an input unit, connected to the query unit, configured to input the complaint problem and the user subscription and registration information into an expert database model to obtain a diagnostic result and a diagnostic suggestion, so as to complete the diagnosis of the complaint about 5G voice services in a mobile network; wherein, the expert database model is an intelligent diagnostic tool pre-constructed based on the logical rules set according to expert experience, combined with the influence of the complaint scenario, network element priority, and subscription function on 5G voice services in a mobile network.

9. The diagnostic device for complaints about 5G voice services in a mobile network according to claim 8, characterized in that the query unit includes: a definition module, configured to define a query target according to the complaint problem; wherein, the query target is the voice calling status, and / or the voice called status, and / or the roaming permission, and / or the call forwarding status, and / or the outage or power-on status, and / or the registration status; a query module, connected to the definition module, configured to query the subscription and registration information of the complaining user in the core network from network elements according to the query target, and perform color brightness marking on abnormal subscription and registration information; wherein, the network elements are a User Data Management Center (UDM), and / or a VoLTE Application Server (VoLTE AS), and / or a Session Control Function (S-CSCF), and / or an ENUM Domain Name System (ENUMDNS), and / or a virtual circuit switch (vCS); when there are multiple network elements, the subscription and registration information of the complaining user in the core network is synchronously obtained from multiple network elements for query.

10. The diagnostic device for 5G voice service complaints in a mobile network according to claim 8 or 9, characterized in that, The device further includes a construction unit, the construction unit is connected to the input unit, and is configured to construct an expert database model, so that the input unit inputs the complaint problem and the user subscription and registration information into the expert database model; the construction unit includes: a preset module, configured to preset a complaint scenario based on the experience and knowledge of experts in handling complaints about 5G voice services in a mobile network A setting module, connected to the preset module, is used to set diagnostic logic rules based on preset complaint scenarios and in accordance with the instruction parameter specifications and parameter values in the standard knowledge base; and, to set the network element priorities for 5G voice service complaints in the mobile network according to the 5G service functions. Among them, the diagnostic logic rules include complaint type classification, diagnostic priorities for different complaint types, and the impact of user subscription and registration information on the quality of 5G voice services. A first processing module, connected to the setting module, is used to clarify the specific causes of different complaint problems based on the diagnostic logic rules and the network element priorities. A second processing module, connected to the first processing module, is used to determine the specific solutions corresponding to the specific causes based on the experience and knowledge of experts in handling 5G voice service complaints in the mobile network. A summary module, respectively connected to the setting module, the first processing module, and the second processing module, is used to summarize the complaint problems, the diagnostic logic rules, the network element priorities, the specific causes, and the specific solutions to obtain an expert library model.

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