Method for intelligently adapting 4g and 5g base station parameters and storage medium

Abstract

The application discloses a method for intelligently adapting 4G and 5G base station parameters and a storage medium, wherein system initialization is performed, a basic parameter model library is loaded, and a connection with a base station is established; an information acquisition request is sent to the base station to acquire base station information; information matching is performed on the basic parameter model library according to the base station information, parameter value initialization is performed on the base station according to a matching result, and a corresponding relationship between the parameter value and a data model obtained through matching is established; parameter states of each base station are monitored in real time, and matching is performed with parameter configuration of the data model; a base station that fails in the matching is corrected or alarmed; through the basic parameter model library, different types and versions of base stations are matched, and then parameter configuration is performed on the base stations, so that the adaptation of 4G and 5G base stations is simultaneously realized, the parameter states of each base station are monitored in real time, abnormal parameters are corrected or alarmed, and effective management of each base station is realized.

Description

Technical Field

[0001] This invention relates to the field of mobile communication technology, and in particular to a method and storage medium for intelligently adapting 4G and 5G base station parameters. Background Technology

[0002] A small cell is a relatively small base station device used to provide wireless communication services within a limited range. They typically cover a small area, such as indoor locations, streets, residential areas, industrial zones, or other localized areas. Small cells consume less power and are relatively flexible in deployment; they can be installed on buildings or other infrastructure to fill gaps in coverage areas or high-density user areas not covered by macrocells. Small cells typically use low-power transmission to provide more stable signal coverage and enhanced data transmission capabilities.

[0003] 4G and 5G small base stations come in various types. Based on coverage and functional characteristics, they can be categorized as enterprise-grade and home-grade; based on module combination, they can be classified as extended, integrated, and split-type, etc. Different types of base station equipment may support different parameters, and base stations manufactured by different companies may also differ.

[0004] Current base station parameter management systems are typically designed and developed for specific types of base stations, making it impossible to simultaneously adapt to and manage 4G and 5G base stations. Furthermore, existing parameter management methods primarily rely on hard coding or manual configuration, leading to difficulties in interface expansion, a lack of effective management tools for multiple instance nodes, and the need to redevelop the interface or manually configure it when adding parameters to a device, resulting in wasted cost and time. This invention aims to provide a system and method for intelligently adapting to and managing 4G and 5G base station parameters. By uniformly retrieving relevant basic configuration information from a database and processing and matching information obtained from base station equipment, a dynamic interface is generated, achieving interface flexibility and scalability, and reducing the workload and cost of interface development.

[0005] Existing technologies cannot simultaneously adapt to and manage 4G and 5G base stations, resulting in the need to use different systems for management, which increases the complexity of operation and maintenance, and also makes it impossible to efficiently manage multiple instance nodes. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a method and storage medium for intelligently adapting 4G and 5G base station parameters, so as to realize the simultaneous adaptation and management of 4G and 5G base station parameters.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0008] A method for intelligently adapting 4G and 5G base station parameters includes the following steps:

[0009] S1. System initialization, loading the basic parameter model library, and establishing a connection with the base station;

[0010] S2. Send an information acquisition request to the base station to obtain base station information;

[0011] S3. Match the base station information with the basic parameter model library, initialize the base station parameter values ​​according to the matching results, and establish the correspondence between the parameter values ​​and the matched data model.

[0012] S4. Monitor the parameter status of each base station in real time and match it with the parameter configuration of the data model. Correct or alarm for base stations that fail to match.

[0013] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows:

[0014] A storage medium having a computer program stored thereon, wherein the computer program, when executed, performs the following steps:

[0015] S1. System initialization, loading the basic parameter model library, and establishing a connection with the base station;

[0016] S2. Send an information acquisition request to the base station to obtain base station information;

[0017] S3. Match the base station information with the basic parameter model library, initialize the base station parameter values ​​according to the matching results, and establish the correspondence between the parameter values ​​and the matched data model.

[0018] S4. Monitor the parameter status of each base station in real time and match it with the parameter configuration of the data model. Correct or alarm for base stations that fail to match.

[0019] The beneficial effects of the present invention are as follows: The present invention provides a method and storage medium for intelligently adapting 4G and 5G base station parameters. By setting up a basic parameter model library, it is used to match different types and versions of base stations, and then configure their parameters to achieve simultaneous adaptation of 4G and 5G base stations. At the same time, it monitors the parameter status of each base station in real time, corrects or alarms for abnormal parameters, and achieves effective management of each base station. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating a method for intelligently adapting 4G and 5G base station parameters according to an embodiment of the present invention;

[0021] Figure 2 This is a schematic diagram illustrating the specific process of a method for intelligently adapting 4G and 5G base station parameters according to an embodiment of the present invention.

[0022] Figure 3 This is an example diagram of the table architecture of the basic parameter model library for a method of intelligently adapting 4G and 5G base station parameters according to an embodiment of the present invention. Detailed Implementation

[0023] To explain in detail the technical content, objectives, and effects of the present invention, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0024] Please refer to Figures 1 to 3 A method for intelligently adapting 4G and 5G base station parameters, comprising the following steps:

[0025] S1. System initialization, loading the basic parameter model library, and establishing a connection with the base station;

[0026] S2. Send an information acquisition request to the base station to obtain base station information;

[0027] S3. Match the base station information with the basic parameter model library, initialize the base station parameter values ​​according to the matching results, and establish the correspondence between the parameter values ​​and the matched data model.

[0028] S4. Monitor the parameter status of each base station in real time and match it with the parameter configuration of the data model. Correct or alarm for base stations that fail to match.

[0029] As can be seen from the above description, the beneficial effects of the present invention are as follows: The present invention provides a method and storage medium for intelligently adapting 4G and 5G base station parameters. By setting up a basic parameter model library, it is used to match base stations of different types and versions, and then configure their parameters to achieve simultaneous adaptation of 4G and 5G base stations. At the same time, it monitors the parameter status of each base station in real time, corrects or alarms for abnormal parameters, and achieves effective management of each base station.

[0030] Furthermore, step S3 includes the following steps:

[0031] S31. Match the base station information with the basic parameter model library. If the match is successful, initialize the base station parameter values ​​according to the matched data model and establish the correspondence between the parameter values ​​and the data model.

[0032] S32. If there are parameters that fail to match, then according to the preset rules and algorithms, match the parameter type and parameter value range, add new parameter configurations, initialize the parameter values ​​according to the new parameter configurations, and configure the parameter values ​​for the base station.

[0033] As described above, by obtaining base station information and matching it with the parameter model library, the data model corresponding to the base station in the parameter model library is determined, and then the parameters of the base station are initialized. At the same time, based on preset rules and algorithms, it can support the intelligent matching and updating of configuration information when a new base station type or version is released, so as to support the new base station.

[0034] Furthermore, it also includes the following steps:

[0035] Receive a user's data update request and update the basic parameter model library according to the data update request.

[0036] As described above, when a new base station type or version is released, users can also update and upgrade the parameters to adapt to the ever-changing base station environment and requirements.

[0037] Furthermore, the feature is that it further includes the step of:

[0038] Receive a user's task set creation request, obtain the configuration information of each parameter contained or specified in the request, and create a task set;

[0039] Accept user batch configuration requests, and configure parameters for at least one user-specified base station according to the parameter configuration information in the task set specified in the batch configuration request.

[0040] As described above, users can create task sets of commonly used parameter configurations for quick base station configuration or batch configuration operations.

[0041] Furthermore, it also includes the following steps:

[0042] Based on the parameter configuration information in the basic parameter model library, a parameter node display interface is generated.

[0043] As described above, a parameter node display interface can be generated based on the parameter configuration information in the basic parameter model library, enabling users to more intuitively understand the parameter configurations used by each base station.

[0044] A storage medium having a computer program stored thereon, wherein the computer program, when executed, performs the following steps:

[0045] S1. System initialization, loading the basic parameter model library, and establishing a connection with the base station;

[0046] S2. Send an information acquisition request to the base station to obtain base station information;

[0047] S3. Match the base station information with the basic parameter model library, initialize the base station parameter values ​​according to the matching results, and establish the correspondence between the parameter values ​​and the matched data model.

[0048] S4. Monitor the parameter status of each base station in real time and match it with the parameter configuration of the data model. Correct or alarm for base stations that fail to match.

[0049] As can be seen from the above description, the beneficial effects of the present invention are as follows: The present invention provides a method and storage medium for intelligently adapting 4G and 5G base station parameters. By setting up a basic parameter model library, it is used to match base stations of different types and versions, and then configure their parameters to achieve simultaneous adaptation of 4G and 5G base stations. At the same time, it monitors the parameter status of each base station in real time, corrects or alarms for abnormal parameters, and achieves effective management of each base station.

[0050] Furthermore, step S3 includes the following steps:

[0051] S31. Match the base station information with the basic parameter model library. If the match is successful, initialize the base station parameter values ​​according to the matched data model and establish the correspondence between the parameter values ​​and the data model.

[0052] S32. If there are parameters that fail to match, then according to the preset rules and algorithms, match the parameter type and parameter value range, add new parameter configurations, initialize the parameter values ​​according to the new parameter configurations, and configure the parameter values ​​for the base station.

[0053] As described above, by obtaining base station information and matching it with the parameter model library, the data model corresponding to the base station in the parameter model library is determined, and then the parameters of the base station are initialized. At the same time, based on preset rules and algorithms, it can support the intelligent matching and updating of configuration information when a new base station type or version is released, so as to support the new base station.

[0054] Furthermore, it also includes the following steps:

[0055] Receive a user's data update request and update the basic parameter model library according to the data update request.

[0056] As described above, when a new base station type or version is released, users can also update and upgrade the parameters to adapt to the ever-changing base station environment and requirements.

[0057] Furthermore, the feature is that it further includes the step of:

[0058] Receive a user's task set creation request, obtain the configuration information of each parameter contained or specified in the request, and create a task set;

[0059] Accept user batch configuration requests, and configure parameters for at least one user-specified base station according to the parameter configuration information in the task set specified in the batch configuration request.

[0060] As described above, users can create task sets of commonly used parameter configurations for quick base station configuration or batch configuration operations.

[0061] Furthermore, it also includes the following steps:

[0062] Based on the parameter configuration information in the basic parameter model library, a parameter node display interface is generated.

[0063] As described above, a parameter node display interface can be generated based on the parameter configuration information in the basic parameter model library, enabling users to more intuitively understand the parameter configurations used by each base station.

[0064] The present invention provides a method and storage medium for intelligently adapting 4G and 5G base station parameters, applicable to base station network management in the field of mobile communications, for adapting and managing the parameters of 4G and 5G base stations.

[0065] Please refer to Figure 1 Embodiment 1 of the present invention is as follows:

[0066] A method for intelligently adapting 4G and 5G base station parameters includes the following steps:

[0067] S1. System initialization: Load the basic parameter model library and establish a connection with the base station.

[0068] In this embodiment, the system initializes upon startup, loading configuration information for the base station type and version, and establishing a connection with the base station via the TR069 protocol. Specifically, the system pre-loads and loads a basic parameter model library, which stores base station parameter configuration information, including basic base station information, parameter node information, and corresponding parameter configuration values. This database design enables centralized management and storage of parameters, facilitating subsequent automated management and intelligent display. The interface display type, default values, value ranges, and relationships are implemented using an extended field storing JSON-formatted data; using JSON allows for more flexible expansion.

[0069] S2. Send an information acquisition request to the base station to obtain base station information.

[0070] In this embodiment, when the system begins base station identification and adaptation, it proactively sends an information acquisition request to the base station to obtain base station information such as its type and version. Based on the received base station information, the system determines whether the base station is a 5G or 4G base station. Through an adapter, it adapts to the different processing methods preset for 4G and 5G nodes, using the 4G process for 4G and the 5G process for 5G, enabling a single server to support simultaneous access by both 4G and 5G devices.

[0071] Specifically:

[0072] 1. Identify base station type and version: Obtain basic information such as the base station type and version by sending an information acquisition request to the base station.

[0073] 2. Base Station Type Determination: Key parameter paths are filtered out using the acquired configuration information. The configuration information is filtered based on specific parameter paths; for example, paths containing LTE indicate a 4G base station, and paths containing NR indicate a 5G base station. By examining these key parameter paths, the base station type is determined and stored in memory for later use.

[0074] 3.4G Base Station Adaptation Processing: If the base station type is 4G, the system will perform adaptation processing based on the preset 4G nodes. This may include steps such as loading the 4G base station parameter configuration file and setting the 4G base station parameter values.

[0075] 4.5G Base Station Adaptation Processing: If the base station type is 5G, the system will perform adaptation processing based on the preset 5G nodes. This may include steps such as loading the 5G base station parameter configuration file and setting the 5G base station parameter values.

[0076] The system will then proactively send information acquisition requests to the base station to obtain more base station information, including all parameter information supported by the base station.

[0077] S3. Match the base station information with the basic parameter model library, initialize the base station parameter values ​​according to the matching results, and establish the correspondence between the parameter values ​​and the matched data model.

[0078] Step S3 includes the following steps:

[0079] S31. Match the base station information with the basic parameter model library. If the match is successful, initialize the base station parameter values ​​according to the matched data model and establish the correspondence between the parameter values ​​and the data model.

[0080] In this embodiment, the system compares and adapts the base station's type and version with all supported parameter information against the parameters in the basic parameter model library. For matches, parameter values ​​are initialized to establish a correspondence between parameter values ​​and the data model, and the rules in the basic parameter model library can be used for interface pre-rendering subsequently.

[0081] Specifically:

[0082] Parameter configuration and association establishment: Based on the base station type and version, the system configures the base station's parameters according to the configuration information in the basic parameter model library. The system initializes the base station's parameter values ​​based on the matching results and establishes a correspondence between the parameter values ​​and the matched data model. This ensures that the base station's parameter configuration remains consistent with the data model.

[0083] S32. If there are parameters that fail to match, then according to the preset rules and algorithms, match the parameter type and parameter value range, add new parameter configurations, initialize the parameter values ​​according to the new parameter configurations, and configure the parameter values ​​for the base station.

[0084] In this embodiment, parameters not found in the basic parameter model library can be automatically matched with appropriate parameter types, display methods, and value ranges to intelligently add new parameter nodes according to the system's preset rules and algorithms. The parameter values ​​are then initialized, and pre-configured values ​​can be directly sent to the device based on preset rules. This intelligent adaptation function ensures the accuracy and consistency of parameter configuration, improves operational convenience and efficiency, and reduces manual operation.

[0085] Specifically, the preset rules and algorithms can include the following aspects:

[0086] Parameter type matching rules: Based on the parameter types of the base station and the parameter types in the basic parameter model library, the system can use various rules and algorithms to determine the degree of matching between them. For example, if the base station parameter is of integer type, while the parameter in the basic parameter model library is of floating-point type, rules such as rounding or integer rounding can be used to match them.

[0087] Parameter value range matching rules: Base station parameters may have certain value range requirements, while parameters in the basic parameter model library also have their allowed value ranges. The system can use rules and algorithms to determine whether the base station parameters are within the allowed range based on these requirements. For example, if the base station parameter value range is 0-100, while the parameter value range in the basic parameter model library is 0-50, rules such as linear mapping or proportional adjustment can be used to map the base station parameter value to the value range in the basic parameter model library.

[0088] New parameter configuration rules: When the base station's parameters cannot match any parameters in the basic parameter model library, the system can generate new parameter configurations based on preset rules and algorithms. This may involve deriving rules and generating new parameter configurations based on the specific needs of the base station and the parameter characteristics of the basic parameter model library.

[0089] Here is an example to illustrate:

[0090] Assume the base station's parameter is "bandwidth," and the parameter in the basic parameter model library is "bandwidth." The base station requires a bandwidth range of 10MHz to 100MHz. However, the allowed range for the "bandwidth" parameter in the basic parameter model library is 5MHz to 50MHz.

[0091] Based on preset rules and algorithms, linear mapping can be used to map base station parameters to the range of a basic parameter model library. For example, for a base station requiring a bandwidth of 50MHz, the following calculation can be used to map it to the range of the basic parameter model library:

[0092] Mapped bandwidth = (Base station required bandwidth - Base station bandwidth lower limit) / (Base station bandwidth upper limit - Base station bandwidth lower limit) * (Basic parameter model library bandwidth upper limit - Basic parameter model library bandwidth lower limit) + Basic parameter model library bandwidth lower limit

[0093] Using the above algorithm, the 50MHz bandwidth required by the base station is mapped to the range of the basic parameter model library, and the calculation is as follows:

[0094] Mapped bandwidth = (50-10) / (100-10)*(50-5)+5 = 40MHz

[0095] Therefore, the bandwidth parameters of the base station can be mapped to the range of the basic parameter model library through preset rules and algorithms, and the corresponding parameter values ​​can be initialized and configured.

[0096] In addition, the matching and initialization of parameters also include the following steps:

[0097] PM file processing: Based on the base station type determination, different parsing methods can be used to process PM files for different types of base stations. For 4G base stations, the system will use the corresponding parsing method to parse the PM files; for 5G base stations, the system will use the corresponding parsing method to parse the PM files.

[0098] Real-time monitoring and processing: The system monitors the parameter status of each base station in real time and matches it with the parameter configuration of the data model. If there are base stations with failed matches or abnormal parameters, the system will correct them or issue an alarm to achieve effective management of each base station.

[0099] S4. Monitor the parameter status of each base station in real time and match it with the parameter configuration of the data model. Correct or alarm for base stations that fail to match.

[0100] In this embodiment, after completing parameter configuration, the system begins parameter management and monitoring. The system monitors the base station's parameter status in real time and compares it with the configuration information in the basic parameter model library. If any abnormal or inconsistent parameter configuration occurs, the system can automatically repair the issue or issue an alarm.

[0101] Please refer to Figure 1 and Figure 2 Embodiment two of the present invention is as follows:

[0102] A method for intelligently adapting 4G and 5G base station parameters, which differs from Embodiment 1 in that it further includes the following steps:

[0103] Based on the parameter configuration information in the basic parameter model library, a parameter node display interface is generated.

[0104] In this embodiment, the system provides a parameter display interface, which can generate a display interface for parameter nodes based on parameter configuration information in the basic parameter model library and the intelligently adapted parameter information therein. The interface generator can automatically adapt according to the data type of the parameter attributes to generate appropriate input controls, such as text boxes, drop-down lists, and sliders. Users can adjust the parameter values ​​as needed and view the parameter display effect in real time.

[0105] The system can dynamically display changes in parameters based on user actions.

[0106] The system can also provide parameter analysis functions based on the characteristics and relationships of parameter attributes. For example, the system can analyze the value range of a parameter and provide reasonable suggested values ​​or warning messages. The system can also display the influence and dependencies between parameters based on their relationships. Users can add new parameter node types and interface styles through configuration and integrate them with existing systems.

[0107] This embodiment also includes the following steps:

[0108] Receive a user's data update request and update the basic parameter model library according to the data update request.

[0109] In this embodiment, when a new base station type or version is released, the system can automatically match and update the configuration information in the database through intelligent adaptation to support the new base station. Users can also update and upgrade parameters through the system interface to adapt to the constantly changing base station environment and requirements.

[0110] This embodiment also includes the following steps:

[0111] Receive a user's task set creation request, obtain the configuration information of each parameter contained or specified in the request, and create a task set;

[0112] Accept user batch configuration requests, and configure parameters for at least one user-specified base station according to the parameter configuration information in the task set specified in the batch configuration request.

[0113] In this embodiment, users can create task sets of frequently used parameter configurations for quick base station configuration or batch configuration operations. In the parameter configuration interface, users can select a created task set and apply the parameter configurations from the task set to the current base station or a group of base stations. The system will automatically configure the base station parameters based on the parameter configuration information in the task set and display the configuration results. Users can adjust and confirm as needed.

[0114] For reference Figure 3 Embodiment 3 of the present invention is as follows:

[0115] A method for intelligently adapting 4G and 5G base station parameters, which differs from Embodiment 1 or 2 in that the design of the basic parameter model library is explained in this embodiment.

[0116] In this embodiment, the system administrator or operator accesses the parameter configuration interface through the system interface.

[0117] The parameter configuration interface allows users to set base station parameter attributes, such as parameter name, default parameter value, display method, value range, parameter type, and parameter node hierarchy, and store these attributes in the database. These attribute settings will be used for subsequent parameter display and management. Operators can configure parameter nodes as needed and store the parameter configuration information in the database to form a basic model library. The system pre-configures parameter rules for currently known devices.

[0118] The table structure of the basic parameter model library can be found by referring to Figure 3 In this case, the PATH field in the ITEM table uses placeholders, for example:

[0119] In Device.Services.FAPService.{x}.FAPControl.NR.XnIpAddrMapInfo.{y}.SubnetMask, {x} and {y} represent placeholders for the first and second multiple instances, respectively.

[0120] The VALUE table stores [2,3] in INSTANCE, representing that the first placeholder has a value of 2 and the second placeholder has a value of 3, respectively. The PATH field in the VALUE table stores the actual path, which is:

[0121] Device.Services.FAPService.2.FAPControl.NR.XnIpAddrMapInfo.3.SubnetMas k.

[0122] This approach enables support for multi-instance parameter management, and the ITEM table no longer needs to store all multi-instance PATH information, reducing storage requirements and speeding up processing, thus achieving efficient management of multi-instance nodes.

[0123] The basic parameter model library is designed to support efficient management of multiple instance nodes. Below is an explanation of the meaning, function, and table structure design of each table:

[0124] MODEL table: This table stores the names of the models and is used to categorize them. It contains the following fields:

[0125] PKID: Primary key, uniqueness, and relationship between tables.

[0126] NAME: Name, used to identify the model

[0127] REMARK: Note

[0128] CLASS table: This table categorizes parameter paths for easier hierarchical relationships. It contains the following fields:

[0129] PKID: Primary key, uniqueness, and table joins.

[0130] PATH: The parameter path, indicating the current path to the specified location.

[0131] NAME: Name, used to identify the parameter type

[0132] PARENT_ID: Parent CLASS_ID

[0133] SORT: Sort

[0134] MODEL_ID: The ID of the model to which it belongs

[0135] REMARK: Note

[0136] DEVICE table: Device table. It contains the following fields:

[0137] PKID: Primary key ID, unique, used for relationships between tables.

[0138] NAME: Device name, used to identify the device.

[0139] SN: Serial Number

[0140] MODEL_ID: Model table ID

[0141] The ITEM table stores parameter node information from the basic parameter model library. It contains the following fields:

[0142] PKID: Primary key, uniqueness, and relationship between tables.

[0143] EXT_JSON: JSON extension used to specify the display format, value range, default value, data type, etc. of parameters on the interface.

[0144] PATH: The hierarchical path of the parameter node, using placeholders to represent multiple instance nodes.

[0145] The PATH field in the ITEM table defines the path to multi-instance nodes by using placeholders such as {x} and {y}, and these placeholders are replaced with their corresponding values ​​during actual instantiation. For example, {x} and {y} in the path represent placeholders for the first and second multi-instance nodes, respectively.

[0146] The VALUE table stores the instantiation value information of parameter nodes in the basic parameter model library. It contains the following fields:

[0147] PKID: Primary Key ID

[0148] PATH: The actual path of the parameter node, that is, replacing the placeholder with the specific instance value.

[0149] INSTANCE: The specific instance value corresponding to the placeholder.

[0150] ITEM_BASE_ID: The ID corresponding to the ITEM table.

[0151] DEVICE_ID: Device ID

[0152] UPDATE_TIME: Update time

[0153] The INSTANCE field in the VALUE table stores the values ​​of the corresponding placeholders. For example, [2,3] means that the first placeholder has a value of 2 and the second placeholder has a value of 3. The PATH field stores the actual path of the parameter node, that is, replacing the placeholders with the specific instance values.

[0154] This design enables efficient management of multiple instance nodes. The specific explanation is as follows:

[0155] Reduced storage requirements: Since multiple instance nodes have the same structure, using placeholders avoids storing independent path information for each instance. Instead, only the placeholder and the corresponding instance value need to be stored, significantly reducing storage requirements.

[0156] Faster processing speed: When querying and accessing multiple instance nodes, the actual parameter path can be quickly generated by combining placeholders with instance values. This avoids performing a full path calculation for each operation, thus improving processing speed.

[0157] By designing a basic parameter model library and using a combination of placeholders and arrays, multiple instance nodes can be managed efficiently, reducing storage requirements and improving processing speed. This design makes the adaptation and management of base station parameters more flexible and efficient.

[0158] That is, by using placeholders and arrays to combine and input data, efficient management of multiple instance nodes can be achieved.

[0159] Embodiment four of the present invention is as follows:

[0160] A storage medium storing a computer program thereon, which, when executed, implements the steps of a method for intelligently adapting 4G and 5G base station parameters as described in any one of embodiments one to three.

[0161] In summary, the present invention provides a method and storage medium for intelligently adapting 4G and 5G base station parameters. By setting up a basic parameter model library, it is used to match different types and versions of base stations, and then configure their parameters to achieve simultaneous adaptation to 4G and 5G base stations. At the same time, it monitors the parameter status of each base station in real time, corrects or alarms for abnormal parameters, and achieves effective management of each base station.

[0162] This invention features intelligent adaptation capabilities, automatically configuring and managing parameters based on base station type and version, thus improving operational convenience and efficiency. In the design of the basic parameter model library, efficient management of multiple instance nodes is achieved through the use of placeholders and array combinations. Simultaneously, by storing parameter configuration information in the basic parameter model library and combining it with intelligent algorithms and interface display technology, automated parameter management and intelligent display are realized. Adding new device types or parameters not only eliminates the need for hard-coding development but also reduces the workload of manual configuration and maintenance, while improving management accuracy and efficiency.

[0163] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for intelligently adapting 4G and 5G base station parameters, characterized in that, Including the following steps: S1. System initialization, loading the basic parameter model library, and establishing a connection with the base station; S2. Send an information acquisition request to the base station to obtain base station information; S3. Match the base station information with the basic parameter model library, initialize the base station parameter values ​​based on the matching results, and establish the correspondence between the parameter values ​​and the matched data model, including: S31. Match the base station information with the basic parameter model library. If the match is successful, initialize the base station parameter values ​​according to the matched data model and establish the correspondence between the parameter values ​​and the data model. S32. If there are parameters that fail to match, then according to the preset rules and algorithms, match the parameter type and parameter value range, add new parameter configurations, initialize the parameter values ​​according to the new parameter configurations, and configure the parameter values ​​for the base station. S4. Monitor the parameter status of each base station in real time and match it with the parameter configuration of the data model. Correct or alarm for base stations that fail to match. It also includes the following steps: Based on the parameter configuration information in the basic parameter model library, a parameter node display interface is generated.

2. The method for intelligently adapting 4G and 5G base station parameters according to claim 1, characterized in that, It also includes the following steps: Receive a user's data update request and update the basic parameter model library according to the data update request.

3. The method for intelligently adapting 4G and 5G base station parameters according to claim 1, characterized in that, It also includes the following steps: Receive a user's task set creation request, obtain the configuration information of each parameter contained or specified in the request, and create a task set; Accept user batch configuration requests, and configure parameters for at least one user-specified base station according to the parameter configuration information in the task set specified in the batch configuration request.

4. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it performs the following steps: S1. System initialization, loading the basic parameter model library, and establishing a connection with the base station; S2. Send an information acquisition request to the base station to obtain base station information; S3. Match the base station information with the basic parameter model library, initialize the base station parameter values ​​based on the matching results, and establish the correspondence between the parameter values ​​and the matched data model, including: S31. Match the base station information with the basic parameter model library. If the match is successful, initialize the base station parameter values ​​according to the matched data model and establish the correspondence between the parameter values ​​and the data model. S32. If there are parameters that fail to match, then according to the preset rules and algorithms, match the parameter type and parameter value range, add new parameter configurations, initialize the parameter values ​​according to the new parameter configurations, and configure the parameter values ​​for the base station. S4. Monitor the parameter status of each base station in real time and match it with the parameter configuration of the data model. Correct or alarm for base stations that fail to match. It also includes the following steps: Based on the parameter configuration information in the basic parameter model library, a parameter node display interface is generated.

5. A storage medium according to claim 4, characterized in that, It also includes the following steps: Receive a user's data update request and update the basic parameter model library according to the data update request.

6. A storage medium according to claim 4, characterized in that, It also includes the following steps: Receive a user's task set creation request, obtain the configuration information of each parameter contained or specified in the request, and create a task set; Accept user batch configuration requests, and configure parameters for at least one user-specified base station according to the parameter configuration information in the task set specified in the batch configuration request.

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