Base station parameter calibration method and electronic device

Abstract

This application provides a base station parameter calibration method and electronic device. The method includes: acquiring base station parameters of a base station; sending a request to a real-time dynamic carrier phase differential (RTK) proxy server to perform differential measurement of the base station parameters, and acquiring differential correction values ​​of the base station parameters from the RTK proxy server; and sending the differential correction values ​​to the base station to perform base station parameter calibration. Therefore, this application can solve the problem in related technologies where collecting, calculating, and processing base station parameters at the base station side increases the security risks of data leakage and tampering, thereby improving the security and accuracy of base station parameter calibration.

Description

Technical Field

[0001] This application relates to the field of communication technology, and more specifically, to a base station parameter calibration method and electronic device. Background Technology

[0002] With the continuous development and popularization of mobile communication networks, the number of base stations is constantly increasing and the network coverage is constantly expanding. Base station parameter calibration is becoming increasingly important. Traditional base station parameter calibration methods have problems such as large workload and low calibration security and accuracy. In the current stage of large-scale network deployment, it is necessary to calibrate the engineering parameters of thousands of base stations. Relying solely on traditional calibration methods is becoming increasingly difficult. Therefore, how to achieve convenient and efficient base station parameter calibration in a large-scale network environment has become an urgent problem to be solved. Summary of the Invention

[0003] This application provides a base station parameter calibration method and electronic device to at least solve the problem in related technologies that the collection, calculation and processing of base station parameters on the base station side leads to increased security risks of data leakage and tampering, thereby achieving the effect of improving the security and accuracy of base station parameter calibration.

[0004] According to one embodiment of this application, a base station parameter calibration method is provided, applied to a network management system. The method includes: acquiring base station parameters of a base station; sending a request to a real-time dynamic carrier phase differential (RTK) proxy server to perform differential measurement of the base station parameters, and acquiring differential correction values ​​of the base station parameters from the RTK proxy server; and sending the differential correction values ​​to the base station to perform base station parameter calibration through the base station.

[0005] According to another embodiment of this application, a base station parameter calibration method is provided, applied to a base station. The method includes: receiving differential correction values ​​of base station parameters from a network management system, wherein the differential correction values ​​of the base station parameters are obtained by an RTK proxy server performing differential measurements based on the base station parameters and sending them to the network management system; and calibrating the base station parameters based on the differential correction values.

[0006] According to yet another embodiment of this application, a computer-readable storage medium is also provided, wherein a computer program is stored therein, and the computer program is configured to perform the steps in any of the above method embodiments when it is run.

[0007] According to yet another embodiment of this application, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in the above method embodiments.

[0008] According to yet another embodiment of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0009] The above embodiments of this application provide a base station parameter calibration method applied to a network management system. By acquiring the base station parameters, a request is sent to an RTK proxy server to perform differential measurements on the base station parameters. The RTK proxy server performs the differential measurements, avoiding the security risks of data leakage and tampering that may arise from data processing at the base station side. After the RTK proxy server obtains the differential correction value, the network management system retrieves the differential correction value of the base station parameters from the RTK proxy server and sends it to the base station for base station parameter calibration. In the calibration process, the base station does not need to directly expose an external interface to interact with the RTK proxy server; instead, communication occurs through the network management system. Furthermore, multi-layered protection measures, including a security server, firewall, and certificates, are employed to ensure the security and reliability of data transmission. Therefore, this method solves the problem in related technologies where collecting, calculating, and processing base station parameters at the base station side increases the security risks of data leakage and tampering, thereby improving the security and accuracy of base station parameter calibration. Attached Figure Description

[0010] Figure 1 This is a hardware structure block diagram of a computer terminal for a base station parameter calibration method according to an embodiment of this application;

[0011] Figure 2 This is a schematic diagram of the network structure operating according to the base station parameter calibration method in the embodiments of this application;

[0012] Figure 3 This is a flowchart of a base station parameter calibration method applied to a network management system according to an embodiment of this application;

[0013] Figure 4 This is a flowchart of a base station parameter calibration method applied to a base station according to an embodiment of this application;

[0014] Figure 5 This is a network architecture diagram for base station parameter calibration according to an embodiment of this application. Detailed Implementation

[0015] The embodiments of this application will be described in detail below with reference to the accompanying drawings and examples.

[0016] It should be noted that the terms "first," "second," etc., in the specification, claims, and drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0017] The methods and embodiments provided in this application can be executed on a mobile terminal, a computer terminal, or a similar computing device. Taking running on a computer terminal as an example, Figure 1 This is a hardware structure block diagram of a computer terminal for a base station parameter calibration method according to an embodiment of this application. Figure 1 As shown, a computer terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The computer terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the computer terminal described above. For example, the computer terminal may also include components that are more complex than those described above. Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0018] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the base station parameter calibration method in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thus implementing the above-described method. The memory 104 may include high-speed random access memory and non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to a computer terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0019] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider for the computer terminal. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0020] Currently, traditional base station parameter calibration methods mostly employ the following approaches:

[0021] (1) Manual measurement: The base station parameters (i.e., engineering parameters, such as base station azimuth, base station downtilt angle, base station latitude and longitude) are obtained by manual on-site measurement using testing instruments. This method is time-consuming and labor-intensive, not only easily affected by external environment and human factors, but also requires a high level of experience from the surveyors, and cannot be verified in batches, resulting in a large workload.

[0022] (2) Base Station Calibration: This involves calibrating base station parameters by collecting, calculating, and processing data at the base station. This includes installing sensors such as accelerometers, magnetoresistive sensors, and antenna installation angle monitors; collecting Measurement Report (MR) data and Minimization Drive Test (MDT) data, combined with various algorithms to estimate and process engineering parameters; and collecting data using satellite positioning technology. However, these methods still require manual intervention and operation. With a large number of base stations, maintenance becomes difficult and costly. Furthermore, a significant amount of calibration data is not uploaded to the network management system, hindering the analysis of base station parameters and failing to efficiently support daily network optimization projects. More importantly, directly processing sensitive data at the base station level may increase the security risks of data leakage and tampering, and may also interfere with the normal operation of the base station.

[0023] It is evident that traditional base station parameter calibration methods suffer from problems such as low efficiency, high cost, large workload, poor usability, and low security. During the large-scale deployment of 5G networks, the parameters of thousands of base stations need to be calibrated, making it increasingly difficult to rely solely on traditional calibration methods.

[0024] This application addresses the problems of low efficiency, high cost, large workload, poor usability, and low security of traditional base station parameter calibration methods in large-scale 5G network environments, and proposes a method for achieving high-precision calibration of base station parameters.

[0025] Figure 2 This is a schematic diagram of the network structure operating according to the base station parameter calibration method of the embodiments of this application, such as... Figure 2As shown, the network architecture may include the following network devices: base stations (also referred to as network elements or cells in other scenarios), a network management system (NMS), and a Real-Time Kinematic (RTK) proxy server. Through data interaction and processing among the network devices in the network architecture, high-precision calibration of base station parameters can be achieved. It should be noted that the term "base station" in this embodiment can refer to all types of base stations, such as inductive base stations and other base stations in the conventional sense. The network management system obtains the base station parameters of the base station to be calibrated. This acquisition can be done in various ways. For example, the network management system can initiate a base station parameter calibration task to the base station, and the base station responds by uploading the base station parameter file to the network management system. Alternatively, the base station parameters of the base station to be calibrated can be manually imported into the network management system. Then, the network management system interacts with the RTK proxy server, sending the base station parameters of the base station to be calibrated to the RTK proxy server. The RTK proxy server performs differential measurements on the base station parameters of the base station to be calibrated to generate differential correction values ​​for the base station parameters. The RTK proxy server then sends the differential correction values ​​to the network management system, which in turn sends the differential correction values ​​to the base station. After receiving the differential correction values, the base station automatically parses and calibrates the configuration of its internal base station parameters, thereby achieving high-precision base station parameter calibration.

[0026] Furthermore, the network management system can also display the execution results of base station parameter calibration, including success and failure results. In the case of failure, the reason for the failure is displayed so that maintenance personnel can monitor and analyze it in a timely manner. Figure 3 This is a flowchart of a base station parameter calibration method according to an embodiment of this application. This embodiment uses a sensing base station as an example for illustration. Figure 3 As shown, the method may specifically include the following steps:

[0027] Step S302: The network management system obtains the base station parameters of the sensing base station.

[0028] Specifically, for example, the network management system sends a request for base station parameters to the sensing base station. The sensing base station responds to this request, and when the request is approved by the sensing base station, the network management system obtains the base station parameters from the sensing base station. These base station parameters may include one or more of the following: base station latitude and longitude, base station downtilt angle, and base station azimuth angle.

[0029] In this step, the network management system can obtain a base station parameter file containing base station parameters from the antenna information sensor unit (AISU) of the sensing base station. Communication between the network management system and the sensing base station can be achieved through Action messages. In other embodiments, the network management system and the sensing base station can also communicate through command / response mechanisms, Simple Network Management Protocol (SNMP), etc.

[0030] In this embodiment, data transmission between the network management system and the sensing base station can be performed using an SFTP server. In other embodiments, data transmission between the network management system and the sensing base station can also be performed using Hypertext Transfer Protocol Secure (HTTPS), Secure Copy Protocol (SCP), or similar protocols.

[0031] In some embodiments, the request information may carry one or more of the following: base station identifier, antenna base station antenna element identifier, Uniform Resource Locator (URL) of the base station parameter file containing base station parameters, and SFTP server password.

[0032] Base station identifiers are codes or names used to identify and distinguish individual base stations in a large-scale 5G network environment. For example, a base station ID is used by the network management system to establish communication with the target base station whose parameters need to be calibrated, ensuring that the request information can be accurately sent to the target base station.

[0033] Antenna unit identifiers, such as Active Antenna Unit (AAU) device IDs, are used to identify target antenna units within a base station. For multi-antenna base stations, this ensures that the network management system can accurately locate the target antenna unit within the base station by using request information containing the AAU device ID, thereby obtaining the base station parameter file.

[0034] A Uniform Resource Locator (URL) for a base station parameter file, which contains base station parameters, is a standard address used to locate and access network resources. In this embodiment, the URL is used to determine the address of the Secure File Transfer Protocol (SFTP) server storing the base station parameter file, ensuring that the base station parameter file can be uploaded or downloaded.

[0035] The SFTP server password is a key used to encrypt and verify the security of data transmission between the SFTP server and the network management system. In this embodiment, the SFTP server serves as a secure protocol for transmitting base station parameter files between the base station and the network management system. Passwords are used to enhance communication security, and this password is employed during both the uploading and differential correction data distribution phases to ensure data integrity and security. In some embodiments, before calibrating the base station parameters, the user can select the sensing base station to be calibrated and initiate a base station parameter calibration task on the network management system side. This calibration task can be controlled and executed by the network management system, thus improving the automation of the base station parameter calibration accuracy process. After the base station parameter calibration task is initiated, the network management system sends a request for base station parameters to the sensing base station through the steps described above in this embodiment. Based on the request information, the network management system obtains the base station parameter file containing the base station parameters from the wireless parameter sensing module of the sensing base station.

[0036] In some embodiments, the triggering mode of the base station parameter calibration task can be flexible and diverse. For example, the base station parameter calibration task can be triggered manually once or at a set time to meet the base station parameter calibration needs in different scenarios. When a set time is required, the user can fill in a timed task execution plan to create a timed base station parameter calibration task. The timed triggering mode can realize the execution of the base station parameter calibration task at a fixed period, making the operation simple for users and enhancing the usability of the network management system.

[0037] Step S304: The network management system sends a request to the real-time dynamic carrier phase differential RTK proxy server to perform differential measurement of the base station parameters, and obtains the differential correction number of the base station parameters from the RTK proxy server.

[0038] Specifically, for example, the network management system first sends a base station parameter file containing base station parameters to the RTK proxy server and receives the path to the base station parameter file corresponding to the base station parameter file. Then, based on the base station parameter file path, it sends a differential measurement request to the RTK proxy server. The RTK proxy server performs differential measurements on the base station parameters in the base station parameter file. For example, the RTK proxy server compares the base station parameters in the base station parameter file with the base station reference parameters stored in the RTK proxy server to obtain the differential correction values ​​for the base station parameters. The network management system then retrieves the differential correction values ​​for the base station parameters from the RTK proxy server.

[0039] In this embodiment, the interaction between the network management system and the RTK proxy server can be achieved by accessing the API interface provided by the RTK proxy server. After the network management system confirms that the link between it and the RTK proxy server is normally connected, the network management system initiates a differential measurement request to the RTK proxy server and uploads a base station parameter file containing base station parameters in GPGGA format to the RTK proxy server. At this time, the RTK server returns the path and file name of the corresponding stored base station parameter file to the network management system. Based on the path and file name of the base station parameter file, the network management system adds a differential generation task (a task generated according to the differential measurement request) to the RTK proxy server. The parameters uploaded in the differential generation task include the path and file name of the base station parameter file stored by the RTK proxy server, the base station parameter file type, the coordinate system type in the base station parameter file, etc. The RTK proxy server returns the corresponding differential generation task ID to the network management system.

[0040] In some embodiments, the RTK proxy server can perform differential measurement according to the differential generation task, compare the base station parameters in the base station parameter file with the target parameters, and obtain the differential correction number of the base station parameters, wherein the target parameters are the base station reference parameters stored in the RTK proxy server.

[0041] In some embodiments, after sending a request to the RTK proxy server to perform differential measurement on the base station parameters in the base station parameter file, the network management system may also receive the task status of the differential generation task in the RTK proxy server, wherein the differential generation task is a task generated according to the differential measurement request, and the task status may be task progress, task details, or task alarm, etc.

[0042] In some embodiments, the network management system can also query the RTK server for the current differential generation task status based on the differential generation task ID described above. When the task progress reaches 100%, the differential correction file corresponding to the differential generation task ID is downloaded, so that the network management system can obtain the base station's differential correction file from the RTK server.

[0043] In some embodiments, the parameter information required for the network management system to interact with the RTK proxy server is not limited to the base station parameter file path and base station parameter file name mentioned above. For example, it also includes network bandwidth, network latency, etc. The network management system can interact with different RTK proxy servers, and different parameter information is required for interaction with different RTK proxy servers. As long as the information rules for interaction with the corresponding RTK proxy server are met, it is acceptable.

[0044] Step S306: The network management system sends the differential correction data to the sensing base station to perform base station parameter calibration through the sensing base station.

[0045] Specifically, for example, after the network management system obtains the differential correction data file from the RTK proxy server, it distributes the differential correction data file to the sensing base station. Specifically, the network management system first uploads the differential correction data file transmitted from the RTK proxy server to a specified Uniform Resource Locator URL on the SFTP server, then sends an Action message to the sensing base station to establish communication, and distributes the differential correction data file to the sensing base station.

[0046] After the network management system sends the differential correction data file to the sensing base station, the remote radio unit (RRU) of the sensing base station parses the differential correction data file and generates high-precision base station parameter configuration information. The base band unit (BBU) of the sensing base station stores the generated high-precision engineering parameter configuration information into the configuration model, automatically modifies the base station parameter configuration on the sensing base station, and the network management system visualizes the changes in base station parameters.

[0047] Therefore, through the automated base station parameter calibration process provided in this embodiment, users only need to select the base station to be calibrated in the network management system interface, and the entire process from task initiation and data acquisition to engineering parameter calibration can be completed automatically, reducing manual intervention and human error, and greatly reducing labor costs.

[0048] In some embodiments, users can visually observe changes in base station parameters on the network management system side, and can export the interaction result file to view the execution results by downloading attachments. The interaction result file contains basic information of each sensing base station and the execution result of each sensing base station (including success and failure results). In addition, in the case of interaction failure, the interaction result file can display the specific reason for the failure.

[0049] In some embodiments, the initiation, management, and result presentation of base station parameter calibration tasks are all performed in the network management system, which is beneficial for the management and analysis of base station parameters and enables batch calibration of base station parameters for multiple sensing base stations simultaneously, thereby improving the efficiency of base station parameter calibration.

[0050] According to another embodiment of this application, a base station parameter calibration method is also provided. The base station involved in this embodiment is a non-inductive base station, such as a common macro base station or a distributed base station. The steps of the base station parameter calibration method in this embodiment are basically the same as those of the inductive base station parameter calibration method in the previous embodiment; therefore, the similarities will not be repeated here. The only difference between the base station parameter calibration method in this embodiment and the inductive base station parameter calibration method in the previous embodiment is that the network management system obtains the base station parameters of the non-inductive base station in a different way. Non-inductive base stations do not have a wireless parameter sensing module and cannot automatically obtain base station parameters; they need to collect base station parameters using manual measurement, drone measurement, or other external means. Therefore, non-inductive base stations cannot send base station parameters to the network management system. After collecting base station parameters through manual measurement, drone measurement, or other external means, the base station parameter file containing the base station parameters can be imported into or sent to the network management system. All other steps in the inductive base station parameter calibration method in the previous embodiment are applicable to this embodiment.

[0051] According to another embodiment of this application, a base station parameter calibration method is also provided. The base station involved in this embodiment can be either a sensing base station or a non-sensing base station. The steps of the base station parameter calibration method in this embodiment are basically the same as those of the sensing or non-sensing base station parameter calibration methods in the previous embodiments; therefore, the similarities will not be repeated here. The only difference between this embodiment and the sensing or non-sensing base station parameter calibration methods in the previous embodiments is that, in this embodiment, a base station parameter file containing base station parameters can be imported or sent to the network management system. Other steps in the sensing or non-sensing base station parameter calibration methods in the previous embodiments are applicable to this embodiment.

[0052] Figure 4 This is a flowchart of a base station parameter calibration method applied to a base station according to an embodiment of this application, such as... Figure 4 As shown, the specific steps include:

[0053] Step S402: Receive differential correction values ​​for base station parameters from the network management system, wherein the differential correction values ​​for base station parameters are obtained by the RTK proxy server through differential measurement based on the base station parameters and sent to the network management system.

[0054] In some embodiments, base station parameters are sent to the network management system before receiving differential correction values ​​for base station parameters from the network management system.

[0055] In some embodiments, before sending base station parameters to the network management system, the method further includes: receiving request information requesting a base station parameter file, the request information including at least one of the following: base station identifier, antenna base station antenna element identifier, Uniform Resource Locator (URL) of the base station parameter file containing the base station parameters, and Secure Transfer Protocol (SFTP) server password.

[0056] Step S404: Perform base station parameter calibration based on the differential correction value.

[0057] In step S404 of this embodiment, calibrating the base station parameters according to the differential correction number includes: generating base station parameter calibration information according to the differential correction number; inputting the base station parameter calibration information into the parameter calibration model, so as to output the corrected base station parameters through the parameter calibration model to calibrate the base station parameters.

[0058] In this embodiment, a sensing base station is used as an example. After the network management system sends the differential correction data file containing differential correction data to the sensing base station, the RRU unit of the sensing base station parses the differential correction data file and generates high-precision engineering parameter configuration information (i.e., base station parameter calibration information). The BBU unit of the sensing base station stores the generated high-precision engineering parameter configuration information into the configuration model (i.e., parameter calibration model), automatically modifies the base station parameter configuration on the sensing base station, and the result generation submodule updates the final result information and visualizes the engineering parameter changes on the network management system.

[0059] This application embodiment improves the operational efficiency and user experience of communication networks through automated processes, enhanced security deployment, and large-scale calibration capabilities. It achieves high-precision parameter calibration of base stations, effectively solving the problems of time-consuming, labor-intensive, unusable, and insecure traditional base station parameter calibration methods. This application embodiment is not only convenient and efficient, but also ensures the security and flexibility of the network management system, providing users with more accurate, secure, and convenient engineering parameter calibration services.

[0060] In the embodiments of this application, the features and functions of the two or more modules described above can be specified in one module; conversely, the features and functions of one module described above can be further divided into multiple modules for specification.

[0061] The above embodiments of this application provide a base station parameter calibration method applied to a network management system. By obtaining the base station parameter file of the base station, a request is sent to an RTK proxy server to perform differential measurements on the base station parameters in the file. The RTK proxy server performs the differential measurements, avoiding the security risks of data leakage and tampering that may arise from data processing at the base station side. After the RTK proxy server obtains the differential correction value, the network management system obtains the differential correction value of the base station parameters from the RTK proxy server and sends it to the base station for base station parameter calibration. In the calibration process, the base station does not need to directly expose an external interface to interact with the RTK proxy server; instead, it communicates with the RTK proxy server through the network management system. Simultaneously, multi-layered protection measures, including a security server, firewall, and certificates, are adopted to ensure the security and reliability of data transmission. Therefore, this method solves the problem in related technologies where collecting, calculating, and processing base station parameters at the base station side increases the security risks of data leakage and tampering, thereby improving the security and accuracy of base station parameter calibration.

[0062] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0063] This application also provides a network architecture diagram for base station parameter calibration. Figure 5 This is a network architecture diagram for base station parameter calibration according to an embodiment of this application, such as... Figure 5 As shown, the network architecture diagram for base station parameter calibration includes: RTK proxy server, network management system, and base station.

[0064] The network management system can be composed of four parts: a parameter acquisition module, an RTK interaction module, a data distribution module, and a management and scheduling center. The functions of each component are as follows:

[0065] The parameter acquisition module collects base station parameter files containing base station parameters from the base station side and uploads these files to the RTK interaction module. The inputs to this module are basic base station information such as base station ID, base station IP, and AAU device ID, as well as base station interaction information such as the base station parameter file URL and SFTP server password. The outputs of this module are the base station parameter file collected from the base station side and the results of the interaction with the base station (whether the base station parameter file acquisition was successful).

[0066] In some embodiments, the data information acquired by the parameter acquisition module is not limited to the basic base station information and base station interaction information mentioned above, but may also include equipment status, signal transmission quality, etc., as long as it can contain the basic base station information and base station interaction information of the base station.

[0067] In some embodiments, the base station can be a sensing base station. The base station parameter file is a GPGGA format base station parameter file generated by the AISU of the sensing base station. The base station parameter file stores base station parameter information (i.e., engineering parameter information, such as base station location information: base station azimuth, base station downtilt angle, base station latitude and longitude, base station altitude, etc., time information: base station parameter acquisition time, time format, etc., and accuracy information: horizontal dilution of precision (HDOP), etc.).

[0068] In some embodiments, the parameter acquisition module consists of a parameter query submodule, a data transmission submodule, and a result generation submodule.

[0069] The parameter query submodule is used to query the approximate location information of the base station.

[0070] The data transmission submodule is used for data exchange between the base station and the network management system.

[0071] The results generation submodule is used to integrate the results of interaction with the base station into a result file, which is then transmitted between modules as a file stream.

[0072] In this embodiment, the parameter query submodule in the parameter acquisition module can communicate with the base station using the Action method, and an SFTP server that supports the secure file transfer protocol can be used during the communication process to achieve data exchange through the data transmission submodule.

[0073] Specifically, the parameter query submodule first sends an Action message to the base station to query the base station parameter file containing base station parameters. This Action message may include the base station ID, base station IP, AAU device ID, base station parameter file URL, SFTP server password, etc. The base station receives the Action message, uploads the base station parameter file to the SFTP server, and retrieves the base station parameter file from the SFTP server through the data transmission submodule. Then, the result generation submodule integrates the base station parameter file and the results of the interaction with the base station into a result file, which is transmitted to the RTK interaction module as a file stream.

[0074] RTK Interaction Module: Performs data interaction between the network management system and the RTK proxy server. The input to this module is the base station parameter file, and the output is the differential correction values ​​of the base station parameters obtained from the RTK proxy server. These differential correction values ​​include base station location information after differential measurement: base station azimuth, base station downtilt angle, base station latitude and longitude, base station altitude, etc., and differential time information: differential date, differential time, etc.

[0075] The RTK interaction module consists of a differential measurement submodule and a security submodule.

[0076] The differential measurement submodule is used to initiate differential measurement requests to the RTK proxy server to perform differential measurements of base station parameters and transmit differential correction values ​​to the data delivery module.

[0077] The security submodule is used to ensure normal network link communication and secure data transmission.

[0078] In some embodiments, every interaction between the network management system and the RTK proxy server is protected by multiple layers of security measures, including firewalls, certificate access mechanisms, and security servers, within the security submodule of the RTK interaction module. The base station does not need to directly expose external interfaces to interact with the RTK proxy server. Instead, it communicates with the RTK proxy server through the network management system, avoiding the risks of data leakage and tampering that may arise from directly processing data on the base station side, thus ensuring the security and reliability of data transmission.

[0079] Data delivery module: Delivers the differential correction data obtained from the RTK interaction module to the base station.

[0080] The data distribution module consists of an update differential data submodule, a data transmission submodule, and a result generation submodule.

[0081] The Update Differential Data submodule is used to update the base station parameters of the base station.

[0082] The data transmission submodule is used for data exchange between the base station and the network management system.

[0083] The results generation submodule is used to integrate the base station parameter calibration results (whether the base station parameter calibration was successful, the reasons for failure, etc.) and generate the final result file.

[0084] In some embodiments, the differential data update submodule and the base station can communicate via an Action method. During communication, data exchange is achieved through the data transmission submodule, using the SFTP secure file transfer protocol. The differential data update submodule first uploads the differential correction data transmitted by the RTK proxy server to the specified Uniform Resource Locator (URL) of the SFTP server through the data transmission submodule. Then, it sends an Action message to the base station to update the base station parameters. This Action message includes the base station ID, base station IP, AAU device ID, base station parameter file URL, and SFTP server password.

[0085] Management and Scheduling Center: Primarily responsible for task management, task scheduling, and resource allocation, ensuring concurrent execution across multiple base stations. The Management and Scheduling Center breaks down tasks at the base station level. Each task then utilizes the resources provided by the service to complete the entire business process at the base station level. It is responsible for scheduling the task list in the session, coordinating and optimizing resource allocation, ensuring that each base station task is executed concurrently, and is isolated from each other through context.

[0086] Through the aforementioned parameter acquisition module, RTK interaction module, and data delivery module, the management and scheduling center, via the parameter acquisition module in the network management system, first obtains the base station parameter file. Then, through the RTK interaction module in the network management system, it establishes a link with the RTK proxy server, transmitting the base station parameter file to the RTK proxy server for differential measurement and obtaining the differential correction values. Finally, through the data delivery module in the network management system, the differential correction values ​​are transmitted to the base station. During this process, the management and scheduling center is responsible for task initiation, management, scheduling, and multi-concurrent execution. Upon receiving the differential correction values, the base station parses them and automatically adjusts its internal base station parameter configuration, correcting the base station parameters to achieve base station parameter calibration.

[0087] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0088] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above method embodiments when run.

[0089] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0090] Embodiments of this application also provide an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0091] In one exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0092] According to yet another embodiment of this disclosure, a computer program product is also provided, including a computer program that, when executed by a processor, implements the steps of the methods described in various embodiments of this disclosure.

[0093] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0094] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0095] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A base station parameter calibration method, applied to a network management system, characterized in that, include: Obtain the base station parameters; Send a request to the real-time dynamic carrier phase differential RTK proxy server to perform differential measurement of the base station parameters, and obtain the differential correction number of the base station parameters from the RTK proxy server; The differential correction is sent to the base station for base station parameter calibration.

2. The method according to claim 1, characterized in that, Before obtaining the base station parameters, the method further includes: Send a request message to the base station requesting base station parameters. The request message includes at least one of the following: base station identifier, antenna unit identifier of the antenna base station, Uniform Resource Locator of the base station parameter file containing the base station parameters, and SFTP server password.

3. The method according to claim 1, characterized in that, The acquisition of base station parameters includes: The base station parameters are obtained from the wireless parameter sensing module of the base station.

4. The method according to claim 1, characterized in that, The step of sending a request to the RTK proxy server to perform differential measurement of the base station parameters and obtaining the differential correction values ​​of the base station parameters from the RTK proxy server includes: Send a base station parameter file containing the base station parameters to the RTK proxy server, and receive the base station parameter file path corresponding to the base station parameter file; According to the path of the base station parameter file, a differential measurement request is sent to the RTK proxy server so that the RTK proxy server can perform differential measurement on the base station parameters in the base station parameter file and obtain the differential correction number of the base station parameters. Obtain the differential correction values ​​of the base station parameters from the RTK proxy server.

5. The method according to claim 1, characterized in that, After sending a request to the RTK proxy server to perform differential measurements of the base station parameters, the method further includes: Receive the task status of the differential generation task in the RTK proxy server, wherein the differential generation task is a task generated according to the differential measurement request, and the task status includes at least one of the following: task progress, task details, and task alarm.

6. The method according to claim 1, characterized in that, Sending a request to the RTK proxy server to perform differential measurements of the base station parameters includes: A request is sent to the RTK proxy server to perform differential measurement of the base station parameters, so that the RTK proxy server can compare the differences between the base station parameters and the target parameters to obtain the differential correction number of the base station parameters, wherein the target parameters are the base station reference parameters stored in the RTK proxy server.

7. The method according to claim 1, characterized in that, The base station parameters include at least one of the following: base station latitude and longitude, base station downtilt angle, and base station azimuth angle.

8. A base station parameter calibration method, applied to a base station, characterized in that, include: The differential correction values ​​of base station parameters are received from the network management system, wherein the differential correction values ​​of the base station parameters are obtained by the RTK proxy server through differential measurement based on the base station parameters and sent to the network management system. Base station parameters are calibrated based on the differential correction values.

9. The method according to claim 8, characterized in that, Before receiving the differential correction value of the base station parameters from the network management system, the method further includes: Send base station parameters to the network management system.

10. The method according to claim 9, characterized in that, Before sending base station parameters to the network management system, the method further includes: The system receives a request for base station parameters, the request information including at least one of the following: base station identifier, antenna unit identifier of the base station, Uniform Resource Locator (URL) of the base station parameter file containing the base station parameters, and SFTP server password.

11. The method according to claim 8, characterized in that, The calibration of base station parameters based on the differential correction includes: Based on the differential correction, base station parameter calibration information is generated; The base station parameter calibration information is input into the parameter calibration model, and the corrected base station parameters are output through the parameter calibration model to perform base station parameter calibration.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of the method described in any one of claims 1-7 or 8-11.

13. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method described in any one of claims 1-7 or 8-11.

14. A computer program product, comprising a computer program and instructions, characterized in that, When the computer program or instructions are executed by the processor, they implement the steps of the method described in any one of claims 1-7 or 8-11.

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