Base station scoring methods, devices, and related equipment

Abstract

This application provides a base station scoring method, apparatus, and related equipment, relating to the field of communication technology. The method includes: acquiring multiple first data corresponding to a target base station; generating multiple second data based on location information determined by the multiple first data and the multiple first data; determining a target scoring rule; and scoring the multiple second data according to the target scoring rule to obtain a score value for the target base station. This application collects multiple first data with different feature dimensions within the target base station, thereby associating the multiple first data with location information determined by the multiple first data to generate multiple second data corresponding to site information. Furthermore, it scores the multiple second data using a target scoring rule that matches the geographical location of the target base station. This approach considers multiple dimensions of data and site information when scoring the base station, improving the accuracy of base station scoring.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and specifically to a scoring method, apparatus, and related equipment for a base station. Background Technology

[0002] Current base station scoring methods primarily rely on input data related to the base station's geographical location, such as traffic, signal quality (e.g., RSRP), number of users, and user complaints. Because existing scoring methods depend mainly on single-site dimension data directly related to the base station's geographical location, they neglect data errors caused by differences in data across multiple site dimensions when scoring base stations. This leads to the problem of poor accuracy in current base station scoring methods. Summary of the Invention

[0003] This invention provides a base station scoring method, apparatus, and related equipment, which solves the problem of poor accuracy in base station scoring in the prior art.

[0004] To solve the above problems, the present invention is implemented as follows:

[0005] In a first aspect, embodiments of this application provide a base station scoring method, the method comprising:

[0006] Acquire multiple first data corresponding to the target base station, wherein the multiple first data are communication data of multiple dimensions corresponding to the target base station, and the feature dimensions corresponding to different first data are different;

[0007] Based on the location information determined by the plurality of first data and the plurality of first data, a plurality of second data are generated. The location information includes the station information associated with each of the plurality of first data. The plurality of second data corresponds one-to-one with the plurality of first data. The second data is the data obtained by associating and marking the corresponding first data with the corresponding station information.

[0008] A target scoring rule is determined, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station;

[0009] The target base station is scored by scoring the plurality of second data according to the target scoring rules.

[0010] Optionally, the plurality of first data includes: a plurality of base station data, a plurality of site data, and a plurality of user data, wherein the base station data, the site data, and the user data are different first data;

[0011] The multiple base station data includes basic information data of the target base station, the multiple site data includes network quality data of multiple sites within the communication range of the target base station, and the multiple user data includes user perception data corresponding to multiple sites within the communication range of the target base station.

[0012] Optionally, generating multiple sets of second data based on the location information determined by the multiple sets of first data and the multiple sets of first data includes:

[0013] The location information is determined based on the multiple site data and the multiple user data;

[0014] Based on the location information and the preset grid size, the multiple user data are divided into grid regions to obtain multiple first division data, and the multiple first division data correspond one-to-one with the multiple user data.

[0015] Based on the location information and the preset grid size, the multiple station data are divided into grid regions to obtain multiple second division data, and the multiple second division data correspond one-to-one with the multiple station data.

[0016] Based on the location information, the data from the multiple base stations are corrected to obtain multiple corrected data, and the multiple corrected data correspond one-to-one with the data from the multiple base stations.

[0017] The plurality of second data includes the plurality of first partition data, the plurality of second partition data, and the plurality of correction data, wherein the first partition data, the second partition data, and the correction data are different second data.

[0018] Optionally, based on the location information and a preset grid size, the multiple user data are divided into grid regions to obtain multiple first partition data, including:

[0019] Based on the multiple user data and the location information, the multiple user data are associated with the corresponding physical stations to obtain multiple first associated data;

[0020] Based on the multiple user data and the location information, the multiple user data are associated with the corresponding logical stations to obtain multiple second associated data;

[0021] Based on the location information and the preset grid size, the plurality of first associated data and the plurality of second associated data are divided into grid regions to obtain the plurality of first partitioned data.

[0022] Optionally, based on the location information, the data from the plurality of base stations is corrected to obtain a plurality of corrected data, including:

[0023] Based on the location information, determine the latitude and longitude information corresponding to the data from the multiple base stations;

[0024] Based on the latitude and longitude information and the data mapping relationship table, the communication node data corresponding to the latitude and longitude information is determined. The communication node data includes physical station data and / or logical station data. The data mapping relationship table includes multiple mapping data entries, wherein the mapping data includes a set of corresponding latitude and longitude information, physical station data, and logical station data.

[0025] The multiple base station data are corrected based on the communication node data to obtain the multiple corrected data.

[0026] Optionally, the step of scoring the plurality of second data according to the target scoring rule to obtain the score value of the target base station includes:

[0027] The target base station is scored by scoring the plurality of first partition data, the plurality of second partition data, and the plurality of corrected data according to the target scoring rules, thereby obtaining the score value of the target base station.

[0028] Optionally, the determination of the target scoring rule includes:

[0029] Multiple scoring rules are obtained, and different scoring rules correspond to different geographical locations;

[0030] Determine the geographical location of the target base station;

[0031] Based on the geographical location of the target base station, the target scoring rule is determined by matching among the multiple scoring rules.

[0032] The second invention, according to an embodiment of this application, provides a base station scoring device, the device comprising:

[0033] The acquisition module is used to acquire multiple first data corresponding to the target base station. The multiple first data are communication data of multiple dimensions corresponding to the target base station. Among the multiple first data, different feature dimensions correspond to different first data.

[0034] The generation module is used to generate multiple second data based on the location information determined by the multiple first data and the multiple first data. The location information includes the station information associated with each of the multiple first data. The multiple second data correspond one-to-one with the multiple first data. The second data is the data obtained by associating and marking the corresponding first data with the corresponding station information.

[0035] A determination module is used to determine the target scoring rule, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station;

[0036] The scoring module is used to score the plurality of second data according to the target scoring rules to obtain the score value of the target base station.

[0037] Thirdly, this application also provides an electronic device, including a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method described in the first aspect above.

[0038] Fourthly, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.

[0039] Fifthly, this application also provides a computer program product, including computer instructions that, when executed by a processor, implement the steps of the method described in the first aspect above.

[0040] This application provides a base station scoring method, apparatus, and related equipment, relating to the field of communication technology. The method includes: acquiring multiple first data corresponding to a target base station, wherein the multiple first data are communication data of multiple dimensions corresponding to the target base station, and different feature dimensions correspond to different first data; generating multiple second data based on location information determined by the multiple first data and the multiple first data, wherein the location information includes site information associated with each of the multiple first data, and the multiple second data correspond one-to-one with the multiple first data, and the second data is data obtained by associating and marking the corresponding first data with the corresponding site information; determining a target scoring rule, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station; and scoring the multiple second data according to the target scoring rule to obtain a score value for the target base station. This application collects first data with multiple different feature dimensions within the target base station, and then associates the location information determined by the multiple first data with the multiple first data to generate multiple second data corresponding to the site information. The multiple second data are then scored using a target scoring rule that matches the geographical location of the target base station. This approach considers multiple dimensions of data and site information when scoring the base station, thereby improving the accuracy of the base station scoring. Attached Figure Description

[0041] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description of the present invention will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 A schematic flowchart illustrating a base station scoring method provided in an embodiment of this application;

[0043] Figure 2 The overall system logic diagram provided for the embodiments of this application;

[0044] Figure 3 A flowchart illustrating the multi-dimensional business data transformation, calculation, and scoring process provided in this application embodiment;

[0045] Figure 4 A schematic diagram of the structure of a base station scoring device provided in an embodiment of this application;

[0046] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0047] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0048] The terms "first," "second," etc., used in the embodiments of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices. Additionally, the use of "and / or" in this application indicates at least one of the connected objects, such as A and / or B and / or C, representing seven possibilities: including A alone, B alone, C alone, and the presence of both A and B, both B and C, both A and C, and the presence of A, B, and C.

[0049] See Figure 1 , Figure 1 This is a flowchart illustrating the base station scoring method provided in an embodiment of this application. Figure 1As shown, the base station scoring method may include the following steps:

[0050] Step 101: Obtain multiple first data corresponding to the target base station. The multiple first data are communication data of multiple dimensions corresponding to the target base station. Among the multiple first data, different first data correspond to different feature dimensions.

[0051] In this embodiment, before scoring the target base station, it is necessary to obtain multiple sets of first data corresponding to the target base station. These multiple sets of first data are data of different dimensions corresponding to the target base station. Specifically, each set of first data corresponds to a different feature dimension. For example, the feature dimensions corresponding to the first data may include basic information of the base station itself, network quality information of the site, user perception information, etc., such as base station bandwidth data, latitude and longitude data, site traffic, site signal quality, service support data, etc.

[0052] Step 102: Generate multiple second data based on the location information determined by the multiple first data and the multiple first data. The location information includes the station information associated with each of the multiple first data. The multiple second data correspond one-to-one with the multiple first data. The second data is the data obtained by associating and marking the corresponding first data with the corresponding station information.

[0053] In this embodiment, the location information of multiple first data is determined based on the acquired multiple first data. The location information includes the site information associated with each of the multiple first data. Specifically, the site information is the relevant information of at least one site covered within the communication range of the base station, such as the site's traffic, signal quality, number of users, etc.

[0054] Data association is performed based on location information and multiple sets of primary data. This involves associating and tagging the site information associated with each set of primary data with its corresponding primary data, thereby generating secondary data for each set of primary data, ultimately resulting in multiple sets of secondary data. Compared to primary data, secondary data incorporates the site information associated with the primary data, making the primary data more accurate and sourced from a wider range of sources. Therefore, the evaluation of target base stations is more comprehensive.

[0055] Step 103: Determine the target scoring rule, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station.

[0056] In this embodiment, the geographical location corresponding to the target base station is determined based on the target base station. For example, due to significant differences in economic development and geographical location among provinces, the sensitivity of different provinces to service data also varies. Therefore, it is necessary to determine the target scoring rules matching the target base station based on its geographical location. For example, the target scoring rules include full score rules (T), zero score rules (Y), weight (Q), full score threshold (M), zero score threshold (O), service data value (R), etc., which are not specifically limited in this embodiment.

[0057] Step 104: Score the plurality of second data according to the target scoring rules to obtain the score value of the target base station.

[0058] In this embodiment, multiple second data points are scored according to the matching target scoring rules to obtain the target base station's score value. This score value is an overall evaluation of the target base station across multiple dimensions. For example, after obtaining the target scoring rules, if T is satisfied, a value of Q*100 (P) is returned.

[0059] If Y is satisfied, return 0 (P);

[0060] If T and T do not meet the requirements, return (RO) / (MO)*Q*100 and the value is (P);

[0061] For a given second data point, there can be multiple different types of rating calculations, so a single second data point will contain multiple types of ratings P1 P2 P3....

[0062] Therefore, the total score of the second data is P_total = P1 + P2 + P3 + ... . Thus, compared with existing technical solutions, this application has significant technical advantages in supporting business data of different site dimensions, adapting to the development status of different provinces, and calculating site business data more accurately, and can better meet the needs of specific application scenarios.

[0063] This application collects first data with multiple different feature dimensions within the target base station, and then associates the location information determined by the multiple first data with the multiple first data to generate multiple second data corresponding to the site information. The multiple second data are then scored using a target scoring rule that matches the geographical location of the target base station. This approach considers multiple dimensions of data and site information when scoring the base station, thereby improving the accuracy of the base station scoring.

[0064] In some feasible implementations, optionally, the plurality of first data includes: a plurality of base station data, a plurality of site data, and a plurality of user data, wherein the base station data, the site data, and the user data are different first data;

[0065] The multiple base station data includes basic information data of the target base station, the multiple site data includes network quality data of multiple sites within the communication range of the target base station, and the multiple user data includes user perception data corresponding to multiple sites within the communication range of the target base station.

[0066] In this embodiment, the multiple first data consists of multiple base station data, multiple site data, and multiple user data, wherein the multiple base station data, multiple site data, and multiple user data are different first data.

[0067] Specifically, the data from multiple base stations includes basic information data of the target base station, which includes latitude and longitude, bandwidth, frequency band, equipment type, province, etc. Among these, latitude and longitude refer to the longitude and latitude coordinates of the target base station. Bandwidth and frequency band refer to the bandwidth and frequency band that the target base station can cover. Equipment type refers to the type of communication equipment used by the target base station. Province indicates the current status of the target base station.

[0068] The multiple site data includes network quality data for multiple sites within the communication range of the target base station. This network quality data includes site-to-traffic, site-to-signal quality, site-to-user count, and site-to-complaint data. Specifically, site-to-traffic refers to the traffic data corresponding to the site; site-to-signal quality refers to the signal quality data corresponding to the site; site-to-user count refers to the number of users corresponding to the site; and site-to-complaints refers to user complaint data corresponding to the site.

[0069] Multiple user data include user-perceived data corresponding to multiple sites within the communication range of the target base station. User-perceived data includes logical station data, physical station data, and coverage area data. It should be noted that a physical station refers to a specific physical device or node, such as a computer, server, router, or switch. Physical stations are characterized by being physically tangible and visible, and are typically hardware facilities. Physical station data refers to data transmitted or generated by the physical station. A logical station refers to a virtual node defined in a network protocol or system. These logical stations do not necessarily correspond to specific physical devices and may be an abstract representation. Logical stations are typically used for data transmission and control in the network, involving logical addresses or identifiers at the protocol level, such as IP addresses and MAC addresses. Logical station data refers to data transmitted or generated by the logical station. Coverage area data refers to data transmitted or generated within the communication coverage area of ​​the target base station.

[0070] In this embodiment, the fusion application of multi-dimensional business data is realized through base station data, site data and user data, thereby enabling the target base station to be measured from multiple dimensions.

[0071] Optionally, generating multiple sets of second data based on the location information determined by the multiple sets of first data and the multiple sets of first data includes:

[0072] The location information is determined based on the multiple site data and the multiple user data;

[0073] Based on the location information and the preset grid size, the multiple user data are divided into grid regions to obtain multiple first division data, and the multiple first division data correspond one-to-one with the multiple user data.

[0074] Based on the location information and the preset grid size, the multiple station data are divided into grid regions to obtain multiple second division data, and the multiple second division data correspond one-to-one with the multiple station data.

[0075] Based on the location information, the data from the multiple base stations are corrected to obtain multiple corrected data, and the multiple corrected data correspond one-to-one with the data from the multiple base stations.

[0076] The plurality of second data includes the plurality of first partition data, the plurality of second partition data, and the plurality of correction data, wherein the first partition data, the second partition data, and the correction data are different second data.

[0077] In this embodiment, as Figure 2 As shown, Figure 2 The above is the overall system logic diagram in this embodiment. The audit data storage unit stores data from multiple base stations, the site-dimensional data storage unit stores data from multiple sites, and the other-dimensional data storage units store data from multiple users. Specifically, the audit data storage unit interacts with the calculation module and serves as a data input to the module, storing data to be audited, including latitude and longitude, bandwidth, frequency band, device type, and province. The site-dimensional data manager interacts with the calculation module and serves as a data input to the module, storing service support data already associated with a site, such as site-traffic, site-signal quality, site-user count, and site-complaints. The other-dimensional data storage units interact with the calculation module and serve as a data input to the module, storing service support data not yet associated with a site, such as logical site data, physical site data, and coverage area data.

[0078] In this embodiment, multiple base station data, multiple site data, and multiple user data are input into the calculation module for processing to obtain multiple second data, which are then scored according to the scorer. Specifically, the calculation module interacts with the site dimension data storage, other dimension data storage, and review data storage, reads data from the data storage area, interacts with the output module, performs dimensional transformation, spatial correlation, scoring, and other calculations on the input data, and then sends it to the reviewer for review.

[0079] The dimensional data transformation section of the calculation module is responsible for converting business data from other dimensions into site-dimensional business data. The site data and base station association section of the calculation module is responsible for associating site data with raster areas. The provincial scoring rule library in the calculation module provides different scoring rules for different provinces, including full score rules, zero score rules, weights, and full / zero score thresholds. The scorer in the calculation module finds the corresponding multi-dimensional spatial data (in raster units) based on the base station data and scores it according to the provincial scoring rules. The reviewer in the output module interacts with the calculation module to receive the raster scoring results output by the calculation module. The reviewer reviews the results according to review rules and stores the results.

[0080] Specifically, the location information is determined based on multiple site data and multiple user data, wherein the location information includes site information associated with each of the multiple first data. The preset grid size can be set according to actual conditions. In this embodiment, based on the latitude and longitude information of the cell, it can be divided into a 50M*50M grid. Specifically, the division process involves processing multiple user data, i.e., data at the cell dimension, specifically including: dividing the data into a 50M*50M grid based on the latitude and longitude information of the cell; aggregating the service data (such as traffic, signal quality, number of users, etc.) of each cell by grid to obtain the service data (V) of each grid; calculating the center latitude and longitude of each grid, converting it to Mercator coordinates, and generating a unique id50 identifier; fuzzifying the latitude and longitude to obtain a long-type K value; establishing a mapping relationship between the K value and multiple id50 values, recording the service data and center latitude and longitude corresponding to each id50, forming a Map set for subsequent use in finding the nearest physical station.

[0081] Therefore, based on location information and preset grid sizes, multiple user data and multiple site data are divided into grid regions to obtain multiple first-division data and multiple second-division data. Additionally, multiple base station data are corrected to obtain multiple corrected data. Thus, the multiple second data include multiple first-division data, multiple second-division data, and multiple corrected data, wherein the first-division data, second-division data, and the positive data are different types of second data.

[0082] In this embodiment, for service data of different dimensions, site data and user data of different dimensions such as logical stations, physical stations, and coverage areas can be processed in a unified manner and accurately associated with base station data.

[0083] Optionally, based on the location information and a preset grid size, the multiple user data are divided into grid regions to obtain multiple first partition data, including:

[0084] Based on the multiple user data and the location information, the multiple user data are associated with the corresponding physical stations to obtain multiple first associated data;

[0085] Based on the multiple user data and the location information, the multiple user data are associated with the corresponding logical stations to obtain multiple second associated data;

[0086] Based on the location information and the preset grid size, the plurality of first associated data and the plurality of second associated data are divided into grid regions to obtain the plurality of first partitioned data.

[0087] In this embodiment, multiple user data and location information are associated to obtain multiple first association data that associate multiple user data with corresponding physical stations. For example, such as... Figure 3 As shown, Figure 3 This is a flowchart illustrating the multi-dimensional business data transformation and scoring process. Based on multiple user data points and location information, the process associates these user data points with corresponding physical stations to obtain multiple primary associated data sets. Specifically, one physical station contains multiple cells. The process of converting a physical station into cell-level data is as follows: Merging the cell information corresponding to a physical station; calculating the center latitude and longitude of the physical station and performing id50 latitude and longitude fuzzification processing to obtain a long-type K value; generating multiple cell-level data sets.

[0088] Based on multiple user data and location information, the user data is associated with corresponding logical stations to obtain multiple second-level associated data. Specifically, a logical station may have multiple physical stations, and a physical station may also include multiple cells under different logical stations. Therefore, further processing of the data at the logical station level is required, including: merging all cell stations under a logical station; calculating the service data of each cell = logical station service data / number of cells under the logical station; and generating multiple cell-level data.

[0089] Therefore, based on location information and a preset grid size, multiple first-related data and multiple second-related data are divided into grid regions to obtain multiple first-division data. Specifically, the coverage area and engineering parameter information are merged to obtain all cell data within the coverage area. These cell data are rasterized, and the physical station ID50 of multiple grids within the coverage area is obtained through a hash algorithm. The number of physical stations (N) in the current coverage area is determined: if N is less than or equal to 2, all service data of these physical stations are set as service data for the coverage area. If N is greater than 2, the service data of each physical station is calculated according to the following formula: Current physical station service data = (Number of cells to which the current physical station belongs / Total number of cells) * Coverage area service data. Thus, physical station data corresponding to one or more coverage areas is finally generated. For service data of the station dimension that already contains spatial information such as latitude and longitude, such as complaint data, the latitude and longitude information is divided into 50M*50M grids and then the service data is aggregated to obtain multiple first-division data.

[0090] Optionally, based on the location information, the data from the plurality of base stations is corrected to obtain a plurality of corrected data, including:

[0091] Based on the location information, determine the latitude and longitude information corresponding to the data from the multiple base stations;

[0092] Based on the latitude and longitude information and the data mapping relationship table, the communication node data corresponding to the latitude and longitude information is determined. The communication node data includes physical station data and / or logical station data. The data mapping relationship table includes multiple mapping data entries, wherein the mapping data includes a set of corresponding latitude and longitude information, physical station data, and logical station data.

[0093] The multiple base station data are corrected based on the communication node data to obtain the multiple corrected data.

[0094] In this embodiment, multiple base station data are corrected based on latitude and longitude information and a data mapping table to obtain the corrected data. First, the latitude and longitude information corresponding to the multiple base station data is obtained. A fuzzy K value is calculated based on the latitude and longitude information. Multiple K values ​​within a 1000-meter range are calculated using GIS technology. From the data mapping sets for each service type established in steps A1-A4, the physical station data corresponding to these K values ​​is searched. Based on the latitude and longitude distance between the physical station and the base station data, the physical station closest to the base station data is found. Various service data (traffic, signal quality, number of users, etc.) of the found nearest physical station are assigned to the corresponding dimensions of the base station data. Through this process, the nearest physical station can be quickly found based on the fuzzy latitude and longitude of the base station data, and its service data can be associated with the base station data. This ensures that the base station data accurately represents the actual situation at the current location, providing accurate input data for subsequent scoring calculations.

[0095] By fuzzing the latitude and longitude information of base station data and establishing a mapping set, the physical site closest to the base station data can be quickly found, improving the accuracy of data matching.

[0096] Optionally, the step of scoring the plurality of second data according to the target scoring rule to obtain the score value of the target base station includes:

[0097] The target base station is scored by scoring the plurality of first partition data, the plurality of second partition data, and the plurality of corrected data according to the target scoring rules, thereby obtaining the score value of the target base station.

[0098] In this embodiment, multiple first partition data, multiple second partition data, and multiple correction data are scored according to the determined target scoring rules to obtain the score value of the target base station. The multiple second data are determined as multiple first partition data, multiple second partition data, and multiple correction data, realizing a scoring system that integrates multiple data sources such as site dimension, logical site dimension, physical site dimension, and coverage area dimension, which can more comprehensively reflect the actual situation of the base station.

[0099] Optionally, the determination of the target scoring rule includes:

[0100] Multiple scoring rules are obtained, and different scoring rules correspond to different geographical locations;

[0101] Determine the geographical location of the target base station;

[0102] Based on the geographical location of the target base station, the target scoring rule is determined by matching among the multiple scoring rules.

[0103] In this embodiment, different provinces are used as examples to illustrate different geographical locations. Different scoring rules are set for multiple different identities. When it is necessary to score a target base station, the province where the target base station is located is determined, and the target scoring rule can be determined based on the province. Therefore, by supporting flexible configuration of scoring rules, weights, and thresholds for different provinces, targeted scoring can be performed based on the differences in economic development levels and geographical conditions in different regions. This adaptability greatly improves the system's applicability in different provinces and has broad application potential.

[0104] This application collects first data with multiple different feature dimensions within the target base station, and then associates the location information determined by the multiple first data with the multiple first data to generate multiple second data corresponding to the site information. The multiple second data are then scored using a target scoring rule that matches the geographical location of the target base station. This approach considers multiple dimensions of data and site information when scoring the base station, thereby improving the accuracy of the base station scoring.

[0105] See Figure 4 , Figure 4 This is a structural diagram of the base station scoring device provided in an embodiment of this application. Figure 4 As shown, the base station scoring device 400 includes:

[0106] The acquisition module 410 is used to acquire multiple first data corresponding to the target base station. The multiple first data are communication data of multiple dimensions corresponding to the target base station. Among the multiple first data, different feature dimensions correspond to different first data.

[0107] The generation module 420 is used to generate multiple second data based on the location information determined by the multiple first data and the multiple first data. The location information includes the station information associated with each of the multiple first data. The multiple second data correspond one-to-one with the multiple first data. The second data is the data obtained by associating and marking the corresponding first data with the corresponding station information.

[0108] The determination module 430 is used to determine the target scoring rule, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station;

[0109] The scoring module 440 is used to score the plurality of second data according to the target scoring rules to obtain the score value of the target base station.

[0110] Optionally, the plurality of first data includes: a plurality of base station data, a plurality of site data, and a plurality of user data, wherein the base station data, the site data, and the user data are different first data;

[0111] The multiple base station data includes basic information data of the target base station, the multiple site data includes network quality data of multiple sites within the communication range of the target base station, and the multiple user data includes user perception data corresponding to multiple sites within the communication range of the target base station.

[0112] Optionally, the generation module 420 includes:

[0113] The first determining submodule is used to determine the location information based on the multiple site data and the multiple user data;

[0114] The first partitioning submodule is used to partition the multiple user data into grid regions based on the location information and the preset grid size to obtain multiple first partition data, and the multiple first partition data correspond one-to-one with the multiple user data.

[0115] The second partitioning submodule is used to partition the multiple station data into grid regions based on the location information and the preset grid size to obtain multiple second partitioning data, and the multiple second partitioning data correspond one-to-one with the multiple station data;

[0116] The correction submodule is used to correct the multiple base station data based on the location information to obtain multiple corrected data, and the multiple corrected data correspond one-to-one with the multiple base station data;

[0117] The plurality of second data includes the plurality of first partition data, the plurality of second partition data, and the plurality of correction data, wherein the first partition data, the second partition data, and the correction data are different second data.

[0118] Optionally, the first partitioning submodule includes:

[0119] The first association unit is used to associate the multiple user data with the corresponding physical station based on the multiple user data and the location information to obtain multiple first association data;

[0120] The second association unit is used to associate the multiple user data with the corresponding logical station based on the multiple user data and the location information to obtain multiple second association data;

[0121] A partitioning unit is used to partition the plurality of first associated data and the plurality of second associated data into grid regions based on the location information and the preset grid size, so as to obtain the plurality of first partitioned data.

[0122] Optional, the correction submodule includes:

[0123] The first determining unit is configured to determine the latitude and longitude information corresponding to the multiple base station data based on the location information;

[0124] The second determining unit is used to determine the communication node data corresponding to the latitude and longitude information according to the latitude and longitude information and the data mapping relationship table. The communication node data includes physical station data and / or logical station data. The data mapping relationship table includes multiple mapping data, wherein the mapping data includes a set of corresponding latitude and longitude information, physical station data and logical station data.

[0125] The correction unit is used to correct the multiple base station data based on the communication node data to obtain the multiple corrected data.

[0126] Optionally, the scoring module 440 includes:

[0127] The scoring submodule is used to score the plurality of first partition data, the plurality of second partition data and the plurality of corrected data according to the target scoring rules, so as to obtain the score value of the target base station.

[0128] Optionally, the determining module 430 includes:

[0129] The acquisition submodule is used to acquire multiple scoring rules, wherein different scoring rules correspond to different geographical locations;

[0130] The second determining submodule is used to determine the geographical location of the target base station;

[0131] The third determining submodule is used to match the multiple scoring rules based on the geographical location of the target base station to determine the target scoring rule.

[0132] This application collects first data with multiple different feature dimensions within the target base station, and then associates the location information determined by the multiple first data with the multiple first data to generate multiple second data corresponding to the site information. The multiple second data are then scored using a target scoring rule that matches the geographical location of the target base station. This approach considers multiple dimensions of data and site information when scoring the base station, thereby improving the accuracy of the base station scoring.

[0133] This application also provides an electronic device. Please refer to [link to relevant documentation]. Figure 5 The electronic device may include a processor 501, a memory 502, and a program 5021 stored in the memory 502 and capable of running on the processor 501.

[0134] When program 5021 is executed by processor 501, it can achieve the following: Figure 1 Any step in the corresponding method embodiment:

[0135] Acquire multiple first data corresponding to the target base station, wherein the multiple first data are communication data of multiple dimensions corresponding to the target base station, and the feature dimensions corresponding to different first data are different;

[0136] Based on the location information determined by the plurality of first data and the plurality of first data, a plurality of second data are generated. The location information includes the station information associated with each of the plurality of first data. The plurality of second data corresponds one-to-one with the plurality of first data. The second data is the data obtained by associating and marking the corresponding first data with the corresponding station information.

[0137] A target scoring rule is determined, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station;

[0138] The target base station is scored by scoring the plurality of second data according to the target scoring rules.

[0139] Optionally, the plurality of first data includes: a plurality of base station data, a plurality of site data, and a plurality of user data, wherein the base station data, the site data, and the user data are different first data;

[0140] The multiple base station data includes basic information data of the target base station, the multiple site data includes network quality data of multiple sites within the communication range of the target base station, and the multiple user data includes user perception data corresponding to multiple sites within the communication range of the target base station.

[0141] Optionally, generating multiple sets of second data based on the location information determined by the multiple sets of first data and the multiple sets of first data includes:

[0142] The location information is determined based on the multiple site data and the multiple user data;

[0143] Based on the location information and the preset grid size, the multiple user data are divided into grid regions to obtain multiple first division data, and the multiple first division data correspond one-to-one with the multiple user data.

[0144] Based on the location information and the preset grid size, the multiple station data are divided into grid regions to obtain multiple second division data, and the multiple second division data correspond one-to-one with the multiple station data.

[0145] Based on the location information, the data from the multiple base stations are corrected to obtain multiple corrected data, and the multiple corrected data correspond one-to-one with the data from the multiple base stations.

[0146] The plurality of second data includes the plurality of first partition data, the plurality of second partition data, and the plurality of correction data, wherein the first partition data, the second partition data, and the correction data are different second data.

[0147] Optionally, based on the location information and a preset grid size, the multiple user data are divided into grid regions to obtain multiple first partition data, including:

[0148] Based on the multiple user data and the location information, the multiple user data are associated with the corresponding physical stations to obtain multiple first associated data;

[0149] Based on the multiple user data and the location information, the multiple user data are associated with the corresponding logical stations to obtain multiple second associated data;

[0150] Based on the location information and the preset grid size, the plurality of first associated data and the plurality of second associated data are divided into grid regions to obtain the plurality of first partitioned data.

[0151] Optionally, based on the location information, the data from the plurality of base stations is corrected to obtain a plurality of corrected data, including:

[0152] Based on the location information, determine the latitude and longitude information corresponding to the data from the multiple base stations;

[0153] Based on the latitude and longitude information and the data mapping relationship table, the communication node data corresponding to the latitude and longitude information is determined. The communication node data includes physical station data and / or logical station data. The data mapping relationship table includes multiple mapping data entries, wherein the mapping data includes a set of corresponding latitude and longitude information, physical station data, and logical station data.

[0154] The multiple base station data are corrected based on the communication node data to obtain the multiple corrected data.

[0155] Optionally, the step of scoring the plurality of second data according to the target scoring rule to obtain the score value of the target base station includes:

[0156] The target base station is scored by scoring the plurality of first partition data, the plurality of second partition data, and the plurality of corrected data according to the target scoring rules, thereby obtaining the score value of the target base station.

[0157] Optionally, the determination of the target scoring rule includes:

[0158] Multiple scoring rules are obtained, and different scoring rules correspond to different geographical locations;

[0159] Determine the geographical location of the target base station;

[0160] Based on the geographical location of the target base station, the target scoring rule is determined by matching among the multiple scoring rules.

[0161] This application collects first data with multiple different feature dimensions within the target base station, and then associates the location information determined by the multiple first data with the multiple first data to generate multiple second data corresponding to the site information. The multiple second data are then scored using a target scoring rule that matches the geographical location of the target base station. This approach considers multiple dimensions of data and site information when scoring the base station, thereby improving the accuracy of the base station scoring.

[0162] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, this computer program implements the various processes of the scoring method embodiment of the base station described above, and achieves the same technical effect. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0163] This application also provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the various processes of the above-described base station scoring method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0164] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0165] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of 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 (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0166] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method for scoring base stations, characterized in that, The method includes: Multiple first data corresponding to a target base station are acquired. The multiple first data are communication data of multiple dimensions corresponding to the target base station. Different first data correspond to different feature dimensions. The multiple first data include: multiple base station data, multiple site data, and multiple user data. The base station data, the site data, and the user data are different first data. Among them, the multiple base station data includes basic information data of the target base station, the multiple site data includes network quality data of multiple sites included within the communication range of the target base station, and the multiple user data includes user perception data corresponding to multiple sites included within the communication range of the target base station. Based on the location information determined by the plurality of first data and the plurality of first data, a plurality of second data are generated. The location information includes station information associated with each of the plurality of first data. The plurality of second data corresponds one-to-one with the plurality of first data. The second data is data obtained by associating and marking the corresponding first data with the corresponding station information. The step of generating a plurality of second data based on the location information determined by the plurality of first data and the plurality of first data includes: determining the location information based on the plurality of station data and the plurality of user data; and dividing the plurality of user data into grid regions based on the location information and a preset grid size to obtain a plurality of second data. The system firstly divides the data, with each first division corresponding to a specific set of user data. Based on the location information and the preset grid size, it further divides the site data into grid regions to obtain multiple second division data, each corresponding to a specific set of site data. Then, based on the location information, it corrects the base station data to obtain multiple corrected data, each corresponding to a specific set of base station data. The multiple second data include the first division data, the second division data, and the corrected data, wherein the first division data, the second division data, and the corrected data are different types of second data. A target scoring rule is determined, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station; The target base station is scored by scoring the plurality of second data according to the target scoring rules.

2. The method according to claim 1, characterized in that, Based on the location information and a preset grid size, the multiple user data are divided into grid regions to obtain multiple first partition data, including: Based on the multiple user data and the location information, the multiple user data are associated with the corresponding physical stations to obtain multiple first associated data; Based on the multiple user data and the location information, the multiple user data are associated with the corresponding logical stations to obtain multiple second associated data; Based on the location information and the preset grid size, the plurality of first associated data and the plurality of second associated data are divided into grid regions to obtain the plurality of first partitioned data.

3. The method according to claim 1, characterized in that, Based on the location information, the data from the multiple base stations is corrected to obtain multiple corrected data, including: Based on the location information, determine the latitude and longitude information corresponding to the data from the multiple base stations; Based on the latitude and longitude information and the data mapping relationship table, the communication node data corresponding to the latitude and longitude information is determined. The communication node data includes physical station data and / or logical station data. The data mapping relationship table includes multiple mapping data entries, wherein the mapping data includes a set of corresponding latitude and longitude information, physical station data, and logical station data. The multiple base station data are corrected based on the communication node data to obtain the multiple corrected data.

4. The method according to claim 1, characterized in that, The step of scoring the plurality of second data according to the target scoring rule to obtain the score value of the target base station includes: The target base station is scored by scoring the plurality of first partition data, the plurality of second partition data, and the plurality of corrected data according to the target scoring rules, thereby obtaining the score value of the target base station.

5. The method according to any one of claims 1-4, characterized in that, The rules for determining the target scoring include: Multiple scoring rules are obtained, and different scoring rules correspond to different geographical locations; Determine the geographical location of the target base station; Based on the geographical location of the target base station, the target scoring rule is determined by matching among the multiple scoring rules.

6. A scoring device for a base station, characterized in that, The device includes: The acquisition module is used to acquire multiple first data corresponding to a target base station. The multiple first data are communication data of multiple dimensions corresponding to the target base station. Different first data correspond to different feature dimensions. The multiple first data include: multiple base station data, multiple site data, and multiple user data. The base station data, the site data, and the user data are different first data. Among them, the multiple base station data includes basic information data of the target base station, the multiple site data includes network quality data of multiple sites included within the communication range of the target base station, and the multiple user data includes user perception data corresponding to multiple sites included within the communication range of the target base station. A generation module is configured to generate multiple second data based on location information determined from the multiple first data and the multiple first data. The location information includes station information associated with each of the multiple first data. The multiple second data correspond one-to-one with the multiple first data. The second data is data obtained by associating and marking the corresponding first data with the corresponding station information. The generation module includes: a first determination submodule, configured to determine the location information based on the multiple station data and the multiple user data; and a first division submodule, configured to divide the multiple user data into grid regions based on the location information and a preset grid size to obtain multiple first division data. A first partitioning data module corresponds one-to-one with the multiple user data modules; a second partitioning submodule is used to partition the multiple site data modules into grid regions based on the location information and the preset grid size to obtain multiple second partitioning data modules, each corresponding one-to-one with the multiple site data modules; a correction submodule is used to correct the multiple base station data modules based on the location information to obtain multiple corrected data modules, each corresponding one-to-one with the multiple base station data modules; wherein, the multiple second data modules include the multiple first partitioning data modules, the multiple second partitioning data modules, and the multiple corrected data modules, wherein the first partitioning data modules, the second partitioning data modules, and the corrected data modules are different second data modules; A determination module is used to determine the target scoring rule, wherein the geographical location corresponding to the target scoring rule matches the geographical location of the target base station; The scoring module is used to score the plurality of second data according to the target scoring rules to obtain the score value of the target base station.

7. An electronic device, characterized in that, include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein the program, when executed by the processor, implements the steps of the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method as described in any one of claims 1 to 5.

9. A computer program product, characterized in that, Includes computer instructions that, when executed by a processor, implement the steps of the method as described in any one of claims 1 to 5.

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