Method and device for determining working parameter position, electronic device, storage medium and product

Abstract

The present disclosure provides a method and device for determining the position of an industrial parameter, an electronic device, a storage medium and a product. The present disclosure uses the sampling data of each 4G sampling point in the 4G fingerprint library to backfill the position of the measurement report data of the 5G sampling point, and obtains the sampling data of the 5G sampling point. Afterwards, based on the grid identifier carried in each sampling data, the 4G sampling point and the 5G sampling point are associated and processed to obtain the sampling point set corresponding to each grid. Thus, based on the sampling point set of each grid, the 5G cell and the 4G cell are co-located and analyzed. Then, for any of the 5G cells, when there is no co-located 4G cell in the 5G cell, the sampling data of the 5G sampling point is used to determine the industrial parameter position of the 5G cell. The technical solution provided by the present disclosure can determine the industrial parameter position of the cell, thereby improving the accuracy and efficiency of the audit results of the industrial parameter position of the cell to a certain extent.

Description

Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a method and device for determining an industrial parameter position, an electronic device, a storage medium, and a product. Background Art

[0002] Accurate working parameter information is very important for the network optimization process of the communication system. In the working parameter audit scenario, the working parameter location of the cell needs to be audited and confirmed.

[0003] Traditionally, measurement report of original (MRO) data is used to verify industrial parameters. However, in 5G communication scenarios, MROs do not include the location information of sampling points, requiring a collection solution to obtain the sampling point locations, such as using drones to collect the location information. However, traditional industrial parameter location auditing solutions have issues such as an inability to guarantee the accuracy of the data source and a single data basis. Therefore, auditing industrial parameters based on this approach can lead to significant deviations, affecting the accuracy of the audit results. Summary of the Invention

[0004] The present disclosure provides a method and device for determining the location of industrial parameters, an electronic device, a storage medium and a product, which are used to determine the location of industrial parameters in a cell, thereby improving the accuracy and efficiency of audit results.

[0005] In a first aspect, the present disclosure provides a method for determining an operation parameter position, comprising:

[0006] Using the sampling data of each 4G sampling point in the 4G fingerprint library, the measurement report data of the 5G sampling point is backfilled to obtain the sampling data of the 5G sampling point;

[0007] Based on the grid identifier carried in each sampling data, the 4G sampling point and the 5G sampling point are associated to obtain a sampling point set corresponding to each grid;

[0008] Performing co-location analysis on the 5G cell and the 4G cell based on the sampling point set of each grid;

[0009] For any of the 5G cells, when there is no co-located 4G cell in the 5G cell, the sampling data of the 5G sampling point is used to determine the working parameter position of the 5G cell.

[0010] In a second aspect, the present disclosure provides a device for determining a working parameter position, comprising:

[0011] A backfill unit is configured to backfill the measurement report data of the 5G sampling point using the sampling data of each 4G sampling point in the 4G fingerprint library to obtain the sampling data of the 5G sampling point;

[0012] an associating unit, configured to associate the 4G sampling point with the 5G sampling point based on the grid identifier carried in each sampling data, to obtain a sampling point set corresponding to each grid;

[0013] an analysis unit, configured to perform co-location analysis on 5G cells and 4G cells based on the sampling point sets of each grid;

[0014] A determination unit is used to determine, for any one of the 5G cells, the working parameter position of the 5G cell using the sampling data of the 5G sampling point when the 5G cell does not have a co-located 4G cell.

[0015] In a third aspect, the present disclosure provides an electronic device, comprising: a memory for storing computer-readable instructions; and a processor for executing the computer-readable instructions so that the electronic device executes the method as described in any embodiment of the first aspect.

[0016] In a fourth aspect, the present disclosure provides a non-transitory computer-readable storage medium for storing computer-readable instructions, which, when executed by a processor, causes the processor to execute the method described in any embodiment of the first aspect.

[0017] In a fifth aspect, the present disclosure provides a computer program product, comprising a computer program, which, when executed by a processor, implements the method described in any embodiment of the first aspect.

[0018] The present disclosure provides a method and device for determining the position of an industrial parameter, an electronic device, a storage medium and a product. The present disclosure combines a 4G fingerprint library with 5G measurement report data (MRO), and uses a 4G fingerprint library with a certain degree of accuracy to supplement the 5G MRO data. On the one hand, the 4G fingerprint library is used to backfill the position of the 5G MRO data, so that the 5G sampling data obtained after backfilling contains both MRO data and position information; on the other hand, the 4G sampling points in the 4G fingerprint library and the 5G sampling points are co-located and analyzed to determine whether there is a 4G cell that has a co-location relationship with the 5G cell (hereinafter referred to as a co-located 4G cell); the so-called co-location relationship means that the industrial parameter address of the 4G cell is consistent with the industrial parameter address of the 5G cell. Thus, when there is a co-located 4G cell in the 5G cell, the working parameter address of the co-located 4G cell can be directly determined as the working parameter address of the corresponding 5G cell; at this time, there is no need to perform complex analysis and processing on the 5G sampling data, and the working parameter address of the 5G cell can be directly determined based on the 4G fingerprint library with high accuracy (the working parameter data of the 4G cell, the sampling data of each 4G sampling point, etc., all come from the 4G fingerprint library), with high accuracy and efficiency. In addition, when there is no co-located 4G cell in the 5G cell, the sampling data of the 5G sampling point is used to determine the working parameter position of the 5G cell; at this time, it is only necessary to process the sampling data of the 5G sampling points that do not have a co-located 4G cell to determine the sampling data of these 5G sampling points. Compared with the existing scheme, in the present disclosure, it is only necessary to process the sampling data of some 5G sampling points that do not have a co-located 4G cell, and there is no need to perform complex data processing on all of them, which greatly reduces the data processing volume and processing efficiency. In summary, the technical solution provided by the present disclosure can determine the location of the cell's work parameters, thereby improving the accuracy and efficiency of the audit results of the cell's work parameters location to a certain extent.

[0019] It is to be understood that both the foregoing general description and the following detailed description are exemplary, and are intended to provide further explanation of the technology as claimed. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The above and other purposes, features, and advantages of the present disclosure will become more apparent through a more detailed description of the embodiments of the present disclosure in conjunction with the accompanying drawings. The accompanying drawings are intended to provide a further understanding of the embodiments of the present disclosure and constitute a part of the specification. Together with the embodiments of the present disclosure, they are used to explain the present disclosure and are not intended to limit the present disclosure. In the drawings, the same reference numerals generally represent the same components or steps.

[0021] Figure 1 A flow chart of a method for determining a working parameter position provided in an embodiment of the present disclosure;

[0022] Figure 2A schematic diagram of an implementation method for determining the working parameter position of a 5G cell based on sampling data of a 5G sampling point provided by the present disclosure;

[0023] Figure 3 A schematic flow chart of another method for determining the position of an industrial parameter provided in an embodiment of the present disclosure;

[0024] Figure 4 A schematic diagram of a location backfill process provided by the present disclosure;

[0025] Figure 5 A structural block diagram of a device for determining a working parameter position provided by an embodiment of the present disclosure;

[0026] Figure 6 A hardware block diagram of an electronic device provided in an embodiment of the present disclosure;

[0027] Figure 7 A schematic diagram of a computer-readable storage medium provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solutions and advantages of the present disclosure more apparent, the following will describe in detail exemplary embodiments of the present disclosure with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments of the present disclosure, and it should be understood that the present disclosure is not limited to the exemplary embodiments described herein.

[0029] In the industrial parameter audit scenario, it is necessary to audit the location of the cell industrial parameter. Specifically, the location of each sampling point must be determined, that is, the sample point positioning is performed. The cell industrial parameter position is then determined based on the positioned sample point position. Then, the determined cell industrial parameter position is used to audit the cell industrial parameter table.

[0030] However, as described in the background technology, in the 5G communication scenario, MRO does not have sampling point location information. If other collection schemes are used to collect sampling point location information, there will be problems such as the accuracy of the data source cannot be guaranteed and the data basis is single. Conducting work parameter audits based on this may lead to large deviations and affect the accuracy of the audit results.

[0031] Based on this, the present disclosure provides a new technical concept: using a 4G fingerprint library with high accuracy, the position of the 5G sampling points is backfilled, and the 4G sampling points and the 5G sampling points are co-located to determine whether each 5G cell has a co-located 4G cell. Thus, when a co-located 4G cell exists, a more accurate cell working parameter position can be directly obtained; for the case where there is no co-located 4G cell, the working parameter position of the 5G cell is determined based on the sampling data of the 5G sampling points after the position is backfilled. Thus, with the assistance of the known accurate information in the 4G fingerprint library, the working parameter position of each 5G cell can be quickly determined, thereby improving processing efficiency and ensuring data accuracy, which is conducive to obtaining accurate working parameter audit results. The following is a detailed explanation.

[0032] First, the present disclosure provides a method for determining the position of an industrial parameter. Figure 1 , Figure 1 This is a flow chart of a method for determining the position of a working parameter provided by an embodiment of the present disclosure. Figure 1 As shown, the method includes:

[0033] S102 , using the sampling data of each 4G sampling point in the 4G fingerprint library, backfill the measurement report data of the 5G sampling point to obtain the sampling data of the 5G sampling point.

[0034] In the present disclosure, the 4G fingerprint library can be constructed in advance by other means, or the present solution can be implemented based on the already constructed 4G fingerprint library. The present disclosure has no special restrictions on the source and acquisition method of the 4G fingerprint library. Exemplarily, the 4G fingerprint library can be constructed based on the MRO data and MDT (Minimization Drive Test) data of the 4G base station. In the present disclosure, the 4G fingerprint library contains the sampling data (or measurement data, for the convenience of subsequent explanations) of the 4G sampling points of each cell, and the sampling data of the 4G sampling points at least includes: location information. Exemplarily, the location information can be represented in the form of a grid identifier (i.e., a grid ID); and / or, the location information can be represented by latitude and longitude information. In addition, the sampling data of the 4G sampling points may also include other information. Exemplarily, in a possible embodiment, the sampling data of the 4G sampling point may include at least one of the following: a grid ID, a cell identifier (which may be recorded as Cellid), a field strength value (Reference Signal Receiving Power, RSRP), a time advance (TA), an angle of arrival (AOA), longitude, latitude, and a coding identifier (for example, Geohashid), without exhausting them all.

[0035] As previously mentioned, the measurement report data (MRO) of a 5G sampling point does not include location information. Therefore, this disclosure uses the 4G fingerprint library to perform location rebound on the test data of the 5G sampling point. This backfilled sampling data of the 5G sampling point includes the MRO and location information of the 5G sampling point. The location information is obtained by backfilling the location using the 4G fingerprint library.

[0036] Thus, in one possible embodiment, after the position of the 4G fingerprint library is backfilled, the sampling data of the 5G sampling point includes the following information: grid ID, cell ID (Cellid), field strength value (RSRP), timing advance (Ta), horizontal angle of arrival (Haoa), vertical angle of arrival (Vaoa). In addition, it may also include longitude and latitude, coding identifier, etc., which are not exhaustive. In one possible embodiment, a 5G fingerprint library can also be constructed based on this.

[0037] S104: Based on the grid identifiers carried in each sampling data, the 4G sampling points and the 5G sampling points are associated to obtain a sampling point set corresponding to each grid.

[0038] Based on the above processing, considering that the sampling data of the 4G sampling point carries the grid ID, the sampling data of the 4G sampling point also carries the grid ID, and the grid division method of the two is consistent in the same scene, the 4G sampling point and the 5G sampling point can be associated based on the grid ID, that is, the 4G sampling point and the 5G sampling point corresponding to each grid ID are determined.

[0039] Moreover, in actual implementation scenarios, the division methods of 4G cells and 5G cells may not be the same, and it is impossible to simply determine whether the two are co-located based on their Cellids. However, the correspondence between 4G cells and grid IDs is fixed, and the correspondence between 5G cells and grid IDs is also fixed. Therefore, using the grid ID as a medium, it is possible to determine the 4G cells and 5G cells corresponding to each grid ID. In actual scenarios, a cell often corresponds to multiple grids, that is, a 4G (or 5G) cell corresponds to at least one grid.

[0040] For example, 4G cell 1 corresponds to grids 1, 2, and 3; 4G cell 2 corresponds to grids 4, 5, and 6; and 5G cell 1 corresponds to grids 2, 3, and 4. Thus, taking grid 3 as an example, the cells corresponding to grid 3 can be determined to be 4G cell 1 and 5G cell 1; and for another example, the cells corresponding to grid 4 can be determined to be 4G cell 2 and 5G cell 1.

[0041] For example, reference may be made to Table 1, which is a schematic diagram of the data structure obtained by performing sampling point association matching based on grid IDs in the disclosure.

[0042] Table 1

[0043]

[0044] Based on this, when conducting subsequent co-location analysis, we can conduct specific analysis on the 4G sampling points and 5G sampling points corresponding to each grid ID based on the grid ID corresponding to each cell, so as to determine whether the 5G cell is co-located with a 4G cell.

[0045] S106: Perform co-location analysis on the 5G cell and the 4G cell based on the sampling point set of each grid.

[0046] As previously mentioned, this step is used to determine whether each 5G cell is co-located with a 4G cell. In this disclosure, a co-located 4G cell means that the 4G cell and the 5G cell are co-located, that is, they have a common cell parameter location. In other words, for any 4G cell and 5G cell, if the two have a co-location relationship, it means that the parameter address of the 4G cell is consistent with the parameter address of the 5G cell.

[0047] In this step, the grid range covered by each cell may be limited to perform co-location analysis on the sampling point set corresponding to each grid ID (including 4G sampling points and 5G sampling points).

[0048] When implementing this step specifically, it can be obtained by performing feature comparison analysis on the sampling data (also called fingerprint data) of each 4G sampling point and each 5G sampling point in the sampling point set. For any 5G cell, when there is a 4G cell, the sampling data of the 4G cell is highly correlated with the sampling data of the 5G cell (in actual scenarios, certain correlation conditions are met), then the 4G cell is considered to be a co-located 4G cell of the 5G cell, and the 5G cell and the 4G cell have a co-location relationship. This is only an exemplary explanation, and the specific implementation method will be explained later and will not be repeated here.

[0049] S108A: For any 5G cell, when there is no co-located 4G cell in the 5G cell, use the sampling data of the 5G sampling point to determine the working parameter position of the 5G cell.

[0050] In the present disclosure, for some 5G cells that do not have co-located 4G cells, the working parameter locations of the 5G cells can be determined by analyzing the sampling data of each 5G cell (as mentioned above, including location information).

[0051] S108B: For any 5G cell, when the 5G cell is co-located with a 4G cell, the working parameter position of the co-located 4G cell is determined as the working parameter position of the 5G cell.

[0052] As mentioned above, when a 5G cell co-locates with a 4G cell, no other processing is required. The working parameter address of the co-located 4G cell can be directly determined as the working parameter address of the 5G cell, which has high accuracy and processing efficiency.

[0053] In summary, the present disclosure combines the 4G fingerprint library with the 5G measurement report data (MRO), and uses the 4G fingerprint library with a certain degree of accuracy to supplement the 5G MRO data. On the one hand, the 4G fingerprint library is used to backfill the position of the 5G MRO data, so that the 5G sampling data obtained after backfilling contains both MRO data and location information; on the other hand, the 4G sampling points in the 4G fingerprint library and the 5G sampling points are co-located for analysis to determine whether there is a 4G cell co-located with the 5G cell (hereinafter referred to as the co-located 4G cell); the so-called co-location relationship means that the working parameter address of the 4G cell is consistent with the working parameter address of the 5G cell. Thus, when there is a co-located 4G cell in the 5G cell, the working parameter address of the co-located 4G cell can be directly determined as the working parameter address of the corresponding 5G cell; at this time, there is no need to perform complex analysis and processing on the 5G sampling data, and the working parameter address of the 5G cell can be directly determined based on the 4G fingerprint library with high accuracy (the working parameter data of the 4G cell, the sampling data of each 4G sampling point, etc., all come from the 4G fingerprint library), with high accuracy and efficiency. In addition, when there is no co-located 4G cell in the 5G cell, the sampling data of the 5G sampling point is used to determine the working parameter position of the 5G cell; at this time, it is only necessary to process the sampling data of the 5G sampling points that do not have a co-located 4G cell to determine the sampling data of these 5G sampling points. Compared with the existing scheme, in the present disclosure, it is only necessary to process the sampling data of some 5G sampling points that do not have a co-located 4G cell, and there is no need to perform complex data processing on all of them, which greatly reduces the data processing volume and processing efficiency. In summary, the technical solution provided by the present disclosure can determine the location of the cell's work parameters, thereby improving the accuracy and efficiency of the audit results of the cell's work parameters location to a certain extent.

[0054] The following describes the implementation method of the co-location analysis (S106) provided by the present disclosure in combination with multiple embodiments.

[0055] First, it should be noted that in this disclosure, when performing co-location analysis, the sampled data can be all the sampled data in the target grid, or it can be part of the sampled data. Then, when performing co-location analysis, there are the following implementation methods:

[0056] The evaluation data can be matched and analyzed to determine whether each 5G cell is co-located with each 4G cell.

[0057] The evaluation data is all or part of the sampled data, and the evaluation data includes at least one of the following: timing advance (TA) and field strength value (RSRP).

[0058] For example, all the sampling data in Table 1 may be subjected to co-location analysis (specifically, the matching analysis or correlation coefficient acquisition described later) to determine the overall result based on the analysis results of each type of sampling data.

[0059] For another example, only TA and RSRP can be used as evaluation data for subsequent analysis and calculation, and the co-location relationship between 4G cells and 5G cells can be determined accordingly.

[0060] For ease of explanation, the following description will still be in the form of sampled data. It should be understood that in the specific analysis steps, the evaluation data described here can be used in the calculation. The following description will be combined with specific examples.

[0061] In the present disclosure, when performing co-location analysis, it can be implemented as follows: First, based on the sampling point set of each grid, the 4G cell and 5G cell corresponding to each grid are determined; thereby, the sampling data in the target grid is matched and analyzed to determine whether each 5G cell and each 4G cell has a co-location relationship. Therefore, the co-location analysis has two possible results: when any of the 5G cells has a co-located 4G cell, the working parameter position of the co-located 4G cell is determined as the working parameter position of the 5G cell (S108B above). Conversely, when any of the 5G cells does not have a co-located 4G cell, the steps shown in S108A above are executed.

[0062] As mentioned above, after determining the sampling point set corresponding to each grid, it is also necessary to determine the 5G cell and 4G cell corresponding to each grid. For details, please refer to the above and will not be repeated here.

[0063] Based on this, when conducting co-location analysis for each cell, it is also necessary to consider that the coverage of each 5G cell may not be exactly the same as the coverage of each 4G cell. Therefore, when implementing co-location analysis, there are also multiple possible implementation methods for the target grid.

[0064] Thus, when performing co-location analysis, in a preferred embodiment, the target grid includes: the portion of the grid where the coverage of the 5G cell overlaps with the coverage of the 4G cell (i.e., the overlapping grid); in this case, the determination of whether the 5G cell and the 4G cell are co-located can be based on the sampled data in the overlapping grid. Alternatively, in some other possible embodiments, the target grid includes: the full amount of data in the coverage of the 5G cell and the coverage of the 4G cell, that is, the co-location analysis can also be performed based on the full amount of data of the 5G cell and the 4G cell.

[0065] In addition, in actual implementation scenarios, the co-location relationship between each 5G cell and each 4G cell can be traversally analyzed; alternatively, the method described above can be adopted to treat 4G cells with grid overlapping relationships as related cells. For each 5G cell, there is no need to traverse irrelevant 4G cells, but only to determine the co-location relationship between each 5G cell and its corresponding related 4G cell.

[0066] Exemplarily, the present disclosure provides a specific implementation method for determining whether each 5G cell and each 4G cell has a co-location relationship, including the following steps:

[0067] S2: For any one of the 5G cells, determine the related 4G cells that have a grid overlapping relationship with the 5G cell, and determine the overlapping grid.

[0068] In the present disclosure, overlapping grids refer to grid coverage overlaps between 5G cells and 4G cells. In this case, the 4G cell is a related 4G cell of the 5G cell, and grids with overlapping coverage are overlapping grids.

[0069] Using the previous example, let's assume that 4G cell 1 corresponds to grids 1, 2, and 3; 4G cell 2 corresponds to grids 4, 5, and 6; and 5G cell 1 corresponds to grids 2, 3, and 4. In this case, if the overlapping grids of 5G cell 1 and 4G cell 1 are grids 2 and 3, then the sampling data in grids 2 and 3 can be used to determine whether 5G cell 1 is co-located with 4G cell 1 (as a related 4G cell). Furthermore, if the overlapping grid of 5G cell 1 and 4G cell 2 is grid 4, then the sampling data in grid 4 can also be used to determine whether 5G cell 1 is co-located with 4G cell 2 (as another related 4G cell).

[0070] As described above, in one possible embodiment, step S2 can be omitted, and the entire data can be directly filtered or filtered in other ways to obtain the target grid, and the co-location analysis can be performed in the subsequent manner (i.e., the overlapping grids in the subsequent embodiments can be replaced with the target grid). In addition, when implementing the co-location analysis in a traversal manner, for 4G cells and 5G cells without overlapping grids, all grids of the two can be used as target grids to implement subsequent analysis.

[0071] S4, performing matching analysis on the sampling data of each 5G sampling point and each 4G sampling point in each overlapping grid to determine the local relationship corresponding to each overlapping grid.

[0072] In this embodiment, the grid is used as the smallest unit, and the sampling data in each overlapping grid (or target grid) is first matched and analyzed, and then combined with the overall situation to determine whether the 5G cell and the related 4G cell are co-located.

[0073] In the present disclosure, the local relationship corresponding to any grid is used to characterize whether the 4G cell and the 5G cell to which the grid belongs have a co-location relationship.

[0074] S6. Determine whether the 5G cell and the related 4G cell have a co-location relationship based on the local relationship corresponding to each overlapping grid.

[0075] In this step, based on the local relationship of each overlapping grid, a comprehensive judgment is made as to whether the 5G cell is co-located with the related 4G cell. At this point, different decision-making methods can be used.

[0076] For example, when there is a local relationship of any overlapping grid that is "the 5G cell and the related 4G cell have a co-location relationship", it is determined that the 5G cell and the related 4G cell have a co-location relationship.

[0077] or,

[0078] For example, when the number of overlapping grids whose local relationship is "the 5G cell and the related 4G cell have a co-location relationship" is large or accounts for a large proportion, it is determined that the 5G cell and the related 4G cell have a co-location relationship. In a possible embodiment, a second number can be obtained, so that when the second number is greater than or equal to the preset third threshold, or the second ratio is greater than or equal to the preset fourth threshold, it is determined that the 5G cell and the related 4G cell have a co-location relationship. The second number is the overlapping grids whose local relationship is that the 5G cell and the related 4G cell have a co-location relationship; the second ratio is the proportion of the second number in the total number of overlapping grids. It should be understood that the third threshold and the fourth threshold can be customized in actual scenarios and will not be elaborated on.

[0079] For example, if the number of overlapping grids between the 5G cell and the related 4G cell is 10, and the number of overlapping grids whose local relationship is "the 5G cell and the related 4G cell have a co-location relationship" (i.e., the second number) is 9, at this time, the second number is greater than or equal to the preset third threshold (for example, 8), or the proportion of the second number (i.e., the second ratio) exceeds 80% (i.e., the fourth threshold), at this time, it is determined that the 5G cell and the related 4G cell have a co-location relationship.

[0080] There are also multiple ways to determine the local relationship in step S4.

[0081] In an exemplary embodiment, for any overlapping grid, the difference between the sampled data of each 5G sampling point and each 4G sampling point is obtained, and then a first number of sampling point pairs for which the difference satisfies a preset first condition is obtained. Thus, when the first number is greater than or equal to a preset first threshold, or a first ratio is greater than or equal to a preset second threshold, the local relationship corresponding to the overlapping grid is determined to be: the 5G cell and the related 4G cell are co-located. The first ratio is the ratio of the first number to the total number of 5G sampling points in the overlapping grid. In other words, when the proportion or number of sampling points in the overlapping grid that are relatively close to the 5G sampling points is relatively large, the local relationship of the overlapping grid is determined to be: the 5G cell and the related 4G cell are co-located. Conversely, when the above condition is not met, the local relationship of the overlapping grid is determined to be: the 5G cell and the related 4G cell are not co-located.

[0082] As described above, when this step is implemented, the difference between the evaluation data (TA and RSRP) of each 5G sampling point and each 4G sampling point can be obtained, thereby counting the number of sampling points whose differences between the two each meet the preset first condition, and then determining the local relationship of the overlapping grid.

[0083] In this disclosure, the first condition is used to limit the data range within which the 4G sampling point and the 5G sampling point are similar. This condition can specifically be a preset threshold or preset interval of the sampled data (or evaluation data). Exemplarily, the first condition is: the TA difference is 0 and the RSRP difference is within 3dB.

[0084] Give an example.

[0085] For example, in one possible embodiment, for a 5G cell and any 4G cell (or related 4G cell), in the overlapping grids of the two, if the difference in TA between each 4G sampling point and the 5G sampling point in a certain overlapping grid is 0 and the number of sampling points whose RSRP difference is within 3dB (i.e., the first ratio mentioned above) exceeds 80% (i.e., the second threshold), then the local relationship between the 5G cell and the 4G cell in the overlapping grid is determined to be: the two have a co-location relationship. Further, at this time, if at least one local relationship is a co-location relationship, then it can be determined that the 5G cell and the 4G cell have a co-location relationship. Conversely, if the first ratio in all overlapping grids is less than the second threshold, that is, there is no overlapping grid that meets the first condition, then it can be determined that the 5G cell and the 4G cell do not have a co-location relationship.

[0086] For another example, in another embodiment, for a 5G cell and any 4G cell (or related 4G cell), in the overlapping grids of the two, if the number of sampling points in the overlapping grid where the difference in TA between the 4G sampling point and the 5G sampling point is 0 and the difference in RSRP is within 3dB accounts for more than 80% (i.e., the first ratio mentioned above), then the local relationship between the 5G cell and the 4G cell in the overlapping grid is determined to be: the two have a co-location relationship. Further, the number of overlapping grids with a co-location relationship is counted (i.e., the second ratio). When the second ratio exceeds 70 (i.e., the fourth threshold), it is determined that the 5G cell and the 4G cell have a co-location relationship. Conversely, if the second ratio is less than the fourth threshold, that is, there are overlapping grids that meet the first condition, but the number of overlapping grids is small. In this case, it is determined that the 5G cell and the 4G cell do not have a co-location relationship.

[0087] In another exemplary embodiment, the local relationship of the overlapping grids may be determined based on the Pearson correlation coefficient. Alternatively, in another possible embodiment, whether each 5G cell and each 4G cell has a co-location relationship may be determined directly based on the Pearson correlation coefficient (described below).

[0088] Specifically, when determining the local relationship of overlapping grids based on the Pearson correlation coefficient, for any overlapping grid, the Pearson correlation coefficient between the sampling data (or evaluation data) of each 4G sampling point and the sampling data (or evaluation data) of the 5G sampling point can be calculated, and the local relationship of the overlapping grid is determined based on its statistics.

[0089] In actual implementation scenarios, when it is necessary to calculate the Pearson correlation coefficient of multiple sampling data (or evaluation data), the multiple sampling data (or evaluation data) can be used as a group of vectors to participate in the calculation. Thus, the Pearson correlation coefficient between the vector corresponding to each 4G sampling point and the vector corresponding to each 5G sampling point can be calculated. Alternatively, the Pearson correlation coefficient of each type of sampling data (or evaluation data) can be calculated separately, and then weighted processing (or other preset processing, not limited here) can be performed to obtain the Pearson correlation coefficient between each 4G sampling point and each 5G sampling point.

[0090] Thus, for any overlapping grid, the number of sampling points (recorded as the third number) or the proportion of the number (recorded as the third ratio) whose Pearson correlation coefficient satisfies the preset third condition (which has the same meaning as the second condition below, and the specific content can be the same or different, and can be customized) can be obtained. Thus, when the third number is greater than or equal to the preset fifth threshold, or the third ratio is greater than or equal to the preset sixth threshold, it is determined that the local relationship corresponding to the overlapping grid is: the 5G cell and the related 4G cell have a co-location relationship. Conversely, if the corresponding number or proportion condition is not met (i.e., less than the corresponding threshold), the local relationship corresponding to the overlapping grid is determined to be: there is no co-location relationship.

[0091] Afterwards, the above-mentioned solution can be combined to determine whether the 5G cell and the related 4G cell have a co-location relationship based on the local relationship of each overlapping grid, without repeating it.

[0092] In addition, as mentioned above, the Pearson correlation coefficient can also be directly used to determine whether the 5G cell and the 4G cell have a co-location relationship.

[0093] In an exemplary embodiment, matching analysis is performed on the sampling data to determine whether each 5G cell and each 4G cell has a co-location relationship, which may include the following steps: obtaining the Pearson correlation coefficient between the sampling data of each 5G cell and the sampling data of each 4G cell; thereby, when the Pearson correlation coefficient meets the preset second condition, it is determined that the 5G cell corresponding to the Pearson correlation coefficient has a co-location relationship with the 4G cell.

[0094] In specific implementation, there is no need to process them separately according to the grid. The 5G sampling points and 4G sampling points of each cell can be directly analyzed. That is, the Pearson correlation coefficient between the 5G sampling points in each 5G cell and the 4G sampling points in each 4G cell can be calculated separately.

[0095] In addition, when the Pearson correlation coefficient of multiple sampling data (or evaluation data) needs to be calculated, it can be calculated as a whole vector, or it can be calculated separately and then weighted or aggregated in other ways. Please refer to the previous article and will not repeat it here.

[0096] In the present disclosure, the second condition is used to indicate the data volume threshold (in the form of: proportion threshold or number threshold) of the Pearson correlation coefficient within a preset numerical interval. That is, when the number of sampling points (recorded as the third number) or the proportion of the number (recorded as the third ratio) of the Pearson correlation coefficient within the numerical interval indicated by the second condition, thus, when the third number is greater than or equal to the preset fifth threshold, or the third ratio is greater than or equal to the preset sixth threshold, it is determined that the 5G cell corresponding to the Pearson correlation coefficient and the 4G cell have a co-location relationship. On the contrary, if the second condition is not met, it is determined that the 5G cell corresponding to the Pearson correlation coefficient and the 4G cell do not have a co-location relationship.

[0097] Specifically, when obtaining the Pearson correlation coefficient of the 4G sampling point and the 5G sampling point, the frequency factor needs to be considered, and the Pearson correlation coefficient of the sampling points with the same frequency should be analyzed.

[0098] For example, the Pearson correlation coefficient ρ of two continuous variables (X, Y) is X,Y Equal to the covariance between them cov(X,Y) divided by the product of their respective standard deviations σ X σ Y The relationship between continuous variables X, Y and Pearson correlation coefficient satisfies the following formula:

[0099]

[0100]

[0101]

[0102] Among them, ρ X,Y represents the Pearson correlation coefficient between variables X and Y, cov(X,Y) represents the covariance between variables X and Y, σ X represents the standard deviation of variable X, σ Y represents the standard deviation of variable Y. E(XY) represents the mathematical expectation of XY, E(X) represents the mathematical expectation of variable X, and E(Y) represents the mathematical expectation of variable Y. In terms of data relationships, cov(X,Y) = E(XY) - E(X)E(Y). Covariance is used in probability theory and statistics to measure the overall error between two variables, while variance can be considered the covariance when the two variables are identical.

[0103] In a specific implementation of the present disclosure, it is only necessary to use the sampling data of the 4G sampling point and the sampling data of the 5G sampling point as variables X and Y respectively to obtain the Pearson correlation coefficient of the 4G sampling point and the 5G sampling point.

[0104] Specifically, the Pearson correlation coefficient always ranges from -1 to 1. Variables close to 0 are considered uncorrelated, while those close to 1 or -1 are considered strongly correlated. In other words, the larger the absolute value of the correlation coefficient, the stronger the correlation; conversely, the closer the absolute value of the correlation coefficient is to 0, the weaker the correlation.

[0105] Thus, when implementing this solution, the numerical interval indicated by the second condition can be expressed as: the minimum threshold of the absolute value. At this time, when the absolute value of the Pearson correlation coefficient is greater than or equal to the minimum threshold, the relevant sampling point satisfies the numerical interval indicated by the second condition, and the amount of data of this part of the data is subsequently used to determine whether the data amount threshold indicated by the second condition is met. Alternatively, in another embodiment, the numerical interval indicated by the second condition can be expressed as: two specific intervals, for example, including: [-1, i] and [j, 1], wherein the values ​​of i and j are any values ​​other than 0 in the range of (-1, 1), and the values ​​of i and j can be the same or different. Thus, when the Pearson correlation coefficient falls within these two specific intervals, the relevant sampling point satisfies the numerical interval indicated by the second condition, and the amount of data of this part of the data is subsequently used to determine whether the data amount threshold indicated by the second condition is met.

[0106] In summary, the present disclosure can determine the co-location relationship between the 4G cell and the 5G cell by performing statistical analysis on the data difference of the sampled data of the 4G cell and the 5G cell, and / or performing Pearson correlation coefficient processing analysis on the sampled data of the 4G cell and the 5G cell. The sampled data taken may be full data, such as the data listed in Table 1, or may be part of the data therein (i.e., the evaluation data described above), such as TA, RSRP values, etc. When performing specific processing, the co-location analysis can be performed only on the partially related 4G cells that have a grid overlap relationship with the 5G cell through the divided grids, or the co-location analysis can be performed on each 5G cell and each 4G cell in a traversal manner. Furthermore, when performing the co-location analysis based on the related 4G cells, the co-location analysis can be performed based on the data in the overlapping grids, or the co-location analysis can be performed based on the data in all grids of the 4G cell and the 5G cell.

[0107] Based on the above co-location analysis, there may be a situation where the 5G cell does not have a co-located 4G cell. In this case, it is necessary to analyze the sampled data in the 5G cell to determine the working parameter location of the 5G cell. That is, it is necessary to perform the following Figure 1 The present disclosure provides a possible implementation method, please refer to Figure 2 , Figure 2 This is a schematic diagram of an implementation method for determining the working parameter position of a 5G cell based on the sampling data of a 5G sampling point provided by the present disclosure. Figure 2As shown, the following steps may be included:

[0108] Step A1: Obtain the 5G sampling point set corresponding to the target base station.

[0109] The target base station may be any base station involved in the process of determining the location of the cell working parameter in the present disclosure. When implementing this step, the MDT data and working parameter data may be directly read.

[0110] In a preferred embodiment, after the full set of sampling points of the base station is read, outlier filtering can be performed based on the TA value (and / or RSRP). That is, the full set of 5G sampling points corresponding to the target base station can be first obtained, and then the 5G sampling points whose sampling data does not meet the preset third condition can be filtered to obtain the 5G sampling point set.

[0111] Exemplarily, sampling points in the full set of sampling points whose TA values ​​are less than or equal to a seventh threshold (customizable, not particularly limited, for example, 16) can be filtered as outliers to obtain a 5G sampling point set corresponding to the target base station.

[0112] Exemplarily, sampling points in the full sampling point set whose RSRP values ​​are greater than or equal to an eighth threshold (customizable, no special restrictions, for example, -80) can be filtered as outliers to obtain a 5G sampling point set corresponding to the target base station.

[0113] In a possible implementation scenario, Figure 2 As shown, outlier filtering can be performed based on the TA value first. When the TA value does not exist, outlier filtering can be performed based on the RSRP value.

[0114] Step A2: Based on the sampling data of each 5G sampling point, obtain the average distance between the 5G sampling point set and the target base station.

[0115] In a specific implementation, the 5G sampling point set can be grouped according to the Cell Global Identifier (CGI). The length of each group is less than a preset threshold (for example, 100), and the groups are sorted according to longitude and latitude. All the obtained longitude and latitude values ​​are taken as a set and the median is taken to obtain the average distance between the 5G sampling point set and the target base station, which can be recorded as L0.

[0116] Step A3: Select a collection point set from the 5G sampling points of the target base station, and obtain a first distance between each collection point and the target base station.

[0117] In this step, the collection point set includes multiple 5G collection points. These are 5G sampling points that are far from the target base station (illustratively, exceeding a preset distance threshold). The distance from each 5G collection point to the target base station can be calculated using a ray propagation model. For example, the distances L1, L2, and L3 from each collection point to the base station are obtained.

[0118] Step A4: obtaining the difference between each first distance in the collection point set and the average distance, and obtaining the sum of each difference to obtain a second distance.

[0119] That is, the differences between L1, L2, L3 and L0 are obtained respectively to obtain d1, d2, and d3, and the second distance can be expressed as: d1+d2+d3.

[0120] Step A5: With the second distance minimized as the goal, the sampling data in the 5G sampling point set is processed using the gradient descent principle to obtain the working parameter position of the 5G cell corresponding to the 5G sampling point set.

[0121] In the specific implementation, with min(d1+d2+d3) as the goal, the gradient descent method is used to estimate the longitude and latitude for iterative calculation; in each round of calculation, the longitude and latitude are re-estimated, and based on the longitude and latitude estimated by the gradient descent method and the longitude and latitude recorded in the working parameter table, the CGI, original longitude and latitude, median longitude and latitude, distance, method type, indoor macro station type, number of valid sample points, Ta value and other calculation parameters are updated, and the longitude and latitude values ​​are re-estimated. When the preset iterative termination condition is reached, the estimation process of the gradient descent algorithm is terminated, and the currently estimated longitude and latitude are determined as the cell working parameter position. Among them, the iterative termination condition can be customized; exemplarily, it can be the number of iterative cycles, such as 100 rounds; exemplarily, it can be set to the calculation duration.

[0122] In summary, the present disclosure uses accurate data from the 4G fingerprint library as a basis, performs co-location analysis on 4G and 5G cells, and thereby determines the working parameter location of the co-located 4G cell as the working parameter location of the corresponding 5G cell. Furthermore, for some 5G cells that do not have co-located 4G cells, the working parameter location of the 5G cell is estimated based on the 5G sampling data containing location information after position backfilling, thereby clarifying the working parameter location of each 5G cell. This process has a small amount of data processing and high processing efficiency. Furthermore, based on the data in the 4G fingerprint library, the data source is more stable and reliable, and the data accuracy is also higher.

[0123] In addition, before executing the aforementioned co-location analysis method in the aforementioned embodiments, or before associating the 4G sampling points with the 5G sampling points based on the grid identifiers, abnormal data may be filtered using a straight path filtering method.

[0124] In other words, before S104 in any of the aforementioned embodiments, the method further includes:

[0125] S103A: Perform a straight line analysis on the sampling data of the 4G sampling points, and perform filtering processing on the 4G sampling points based on the straight line analysis results.

[0126] and / or,

[0127] S103B: Perform a straight line analysis on the sampling data of the 5G sampling point, and filter the 5G sampling point based on the straight line analysis result.

[0128] In actual implementation scenarios, S103A and S103B can be executed simultaneously, that is, direct path filtering is performed on both 4G sampling points and 5G sampling points. The processing methods for both can be the same. The following uses the implementation of direct path filtering (i.e., S103A) on 4G sampling points as an example to illustrate the implementation of direct path filtering.

[0129] Exemplarily, the specific implementation of S103A may include the following steps:

[0130] For any of the 4G sampling points, based on the first direct path data carried in the sampling data of the 4G sampling point, an estimated value of the second direct path data between the 4G sampling point and its base station is obtained, so that when a target error is greater than or equal to a preset error threshold, the 4G sampling point is deleted; wherein the target error is the error between the estimated value and the second direct path data carried in the sampling data.

[0131] Specifically, the first straight path data and the second straight path data are TA and distance respectively. At this time, there are two possible implementations:

[0132] In the first embodiment, when the first direct path data is a timing advance, the second direct path data is a distance between the 4G sampling point and its base station.

[0133] In this embodiment, the TA value carried in the 4G sampling data can be obtained. Then, based on the relationship between the TA value and distance in the 4G scenario (D = sampling point Ta * 78 + 39), an estimated distance value is determined, recorded as D; and the distance value carried in the 4G sampling data is recorded as d. In this way, when the error between D and d (i.e., the target error) is greater than or equal to an error threshold (e.g., 20%), it indicates that the 4G sampling point is relatively abnormal, and the abnormal data is deleted. Conversely, when the error between D and d is less than the error threshold (i.e., within the error threshold range), the 4G sampling point is retained.

[0134] Similarly, a similar approach can be adopted for 5G sampling points. Specifically, the TA value carried in the 5G sampling data can be obtained, and then, based on the relationship between the TA value and the distance in the 5G scenario (D = sampling point Ta*78+19.5), the estimated value of the distance is determined, recorded as D; and the distance value carried in the 5G sampling data is recorded as d. In this way, when the error between D and d (i.e., the target error) is greater than or equal to the error threshold (e.g., 20% or 25%, custom setting), it means that the 5G sampling point is relatively abnormal, and the abnormal data (i.e., the sampling data of the 5G sampling point) is deleted. Conversely, when the error between D and d is less than the error threshold (i.e., within the range of the error threshold), the 5G sampling point is retained.

[0135] Alternatively, in the second embodiment, when the first direct path data is the distance between the 4G sampling point and its base station, the second direct path data is the time advance.

[0136] In this embodiment, the distance value (denoted as d) carried in the 4G sampling data can be obtained. Then, based on the relationship between the TA value and distance in the 4G scenario (Ta = d / 78), an estimated TA value is determined, denoted as TA1; and the TA value carried in the 4G sampling data is denoted as TA2. In this way, when the error between TA1 and TA2 (i.e., the target error) is greater than or equal to an error threshold (e.g., 20%), it indicates that the 4G sampling point is relatively abnormal and the abnormal data is deleted. Conversely, when the error between TA1 and TA2 is less than the error threshold (i.e., within the error threshold range), the 4G sampling point is retained.

[0137] Similarly, a similar approach can be adopted for 5G sampling points. Specifically, the distance value (denoted as d) carried in the 5G sampling data can be obtained, and then, based on the relationship between the TA value and the distance in the 5G scenario (Ta=d / 39), the estimated value of TA is determined, denoted as TA1; and the TA value carried in the 5G sampling data is denoted as TA2. In this way, when the error between TA1 and TA2 (ie, the target error) is greater than or equal to the error threshold (for example, 20%), it indicates that the 5G sampling point is relatively abnormal, and the abnormal data is deleted. Conversely, when the error between TA1 and TA2 is less than the error threshold (ie, within the range of the error threshold), the 5G sampling point is retained.

[0138] At this point, for example, the present disclosure also provides a possible embodiment, please refer to Figure 3 , Figure 3 This is a flow chart of another method for determining the position of a working parameter provided by an embodiment of the present disclosure. Figure 3 As shown, the method includes:

[0139] S302: Use the 4G fingerprint library to backfill the positions of the 5G sampling points and build a 5G fingerprint library.

[0140] S304: Filter the 4G sampling data and the 5G sampling data using a straight path filtering method.

[0141] S306 , associating the 4G sampling point with the 5G sampling point based on the grid identifier.

[0142] S308, determine whether the 5G cell is co-located with a 4G cell; if not, use the gradient descent method to determine the working parameter position of the 5G cell.

[0143] Furthermore, based on determining the location of the cell working parameters, the method may further include the following steps:

[0144] Based on the working parameter location of the 5G cell, the working parameter table is audited.

[0145] Through the above processing, after the working parameter position of the 5G cell is determined, it can be checked and calibrated with the cell working parameter position in the working parameter table. When the two are inconsistent or the gap is large, a reminder message is output to remind the management personnel to handle it.

[0146] The following, combined Figure 4 , briefly describe the position backfilling method provided by the present disclosure (i.e., S102 in the aforementioned implementation). Figure 4 A schematic diagram of a position backfill process provided by the present disclosure, such as Figure 4 As shown, the position backfilling method includes the following processes:

[0147] First, input the 4G MRO file, and parse the 5G MRO file accordingly, and obtain the 5G main neighbor information and the 4G neighbor information of the heterofrequency measurement. After that, the 4G sampling point and the 5G sampling point are positioned and matched (that is, matched based on the MRO data of the two). After that, it is necessary to combine the 4G main neighbor information to determine the main neighbor relationship of the 5G sampling point. When this step is implemented, it can be sorted from high to low based on RSRP, and the one with the largest RSRP in the 4G neighbor area is used as the main area of ​​the 5G sampling point, and the others are used as neighbor areas. After that, it is also necessary to obtain the working parameter information according to the 4G and 5G neighbor relationship tables. At this time, if the 4G neighbor working parameters can be directly found in the neighbor relationship table, they are directly read and the parameters that meet the preset conditions (such as Figure 4 Frequency band requirements, etc., which can be customized without special restrictions). If the information cannot be found, it is necessary to obtain the 4G neighboring area working parameters closest to the 5G main area working parameters as the 4G neighboring area working parameters, and continue to look up the table until the 4G main neighboring area working parameters are obtained, or it is determined that they cannot be found. After that, the 4G fingerprint library can be called to calculate the positioning error. If it meets the preset error requirements, the position backfill process can be completed to obtain the sampling data of the 5G sampling point. At this time, these sampling data can also be encapsulated into a 5G fingerprint library, stored and maintained.

[0148] The present disclosure also provides a device for determining the position of an industrial parameter. Figure 5 This is a structural block diagram of a device for determining a working parameter position provided by an embodiment of the present disclosure, such as Figure 5 As shown, the working parameter position determination device 500 includes:

[0149] A backfill unit 510 is configured to backfill the measurement report data of the 5G sampling point using the sampling data of each 4G sampling point in the 4G fingerprint library to obtain the sampling data of the 5G sampling point;

[0150] An associating unit 520 is configured to associate the 4G sampling point with the 5G sampling point based on the grid identifier carried in each sampling data to obtain a sampling point set corresponding to each grid;

[0151] An analyzing unit 530 is configured to perform co-location analysis on 5G cells and 4G cells based on the sampling point sets of each grid;

[0152] The determination unit 540 is configured to determine, for any one of the 5G cells, the working parameter position of the 5G cell using the sampling data of the 5G sampling point when the 5G cell does not have a co-located 4G cell.

[0153] In an exemplary embodiment, the analysis unit 530 is specifically configured to:

[0154] Based on the sampling point set of each grid, the 4G cell and the 5G cell corresponding to each grid are determined,

[0155] Perform matching analysis on the sampled data in the target grid to determine whether each 5G cell is co-located with each 4G cell.

[0156] When any one of the 5G cells is co-located with a 4G cell, the working parameter position of the co-located 4G cell is determined as the working parameter position of the 5G cell.

[0157] In an exemplary embodiment, the analysis unit 530 is specifically configured to:

[0158] For any of the 5G cells, determining related 4G cells that have a grid overlap relationship with the 5G cell, and determining the overlapping grid;

[0159] Matching analysis is performed on the sampling data of each 5G sampling point and each 4G sampling point in each overlapping grid to determine the local relationship corresponding to each overlapping grid;

[0160] Based on the local relationship corresponding to each overlapping grid, determine whether the 5G cell and the related 4G cell have a co-location relationship.

[0161] In an exemplary embodiment, the analysis unit 530 is specifically configured to:

[0162] For any of the overlapping grids, obtaining the difference between the sampling data of each 5G sampling point and each 4G sampling point;

[0163] Obtaining a first number of sampling point pairs whose difference satisfies a preset first condition;

[0164] When the first number is greater than or equal to a preset first threshold, or the first ratio is greater than or equal to a preset second threshold, determining that the local relationship corresponding to the overlapping grid is: the 5G cell and the related 4G cell have a co-location relationship;

[0165] The first ratio is the proportion of the first number to the total number of 5G sampling points in the overlapping grid.

[0166] In an exemplary embodiment, the analysis unit 530 is specifically configured to:

[0167] Obtaining a second number; the second number is an overlapping grid in which the local relationship is that the 5G cell and the related 4G cell have a co-location relationship;

[0168] When the second number is greater than or equal to a preset third threshold, or the second ratio is greater than or equal to a preset fourth threshold, it is determined that the 5G cell and the related 4G cell have a co-location relationship;

[0169] The second ratio is the proportion of the second number to the total number of overlapping grids.

[0170] In an exemplary embodiment, the analysis unit 530 is specifically configured to:

[0171] Obtain the Pearson correlation coefficient between the sampled data of each 5G cell and the sampled data of each 4G cell;

[0172] When the Pearson correlation coefficient satisfies a preset second condition, determining that the 5G cell and the 4G cell corresponding to the Pearson correlation coefficient have a co-location relationship;

[0173] The second condition is used to indicate the amount of data of the Pearson correlation coefficient within a preset numerical range.

[0174] In an exemplary embodiment, the analysis unit 530 is specifically configured to:

[0175] Perform matching analysis on the evaluation data to determine whether each 5G cell is co-located with each 4G cell;

[0176] The evaluation data is all or part of the sampled data, and the evaluation data includes at least one of the following: a time advance value and a field strength value.

[0177] In an exemplary embodiment, the determining unit 540 is specifically configured to:

[0178] Get the 5G sampling point set corresponding to the target base station;

[0179] Based on the sampling data of each 5G sampling point, obtaining an average distance between the set of 5G sampling points and the target base station;

[0180] Selecting a collection point set from the 5G sampling points of the target base station, and obtaining a first distance between each collection point and the target base station;

[0181] Obtaining the difference between each first distance in the collection point set and the average distance, and obtaining the sum of each difference to obtain a second distance;

[0182] With the goal of minimizing the second distance, the sampling data in the 5G sampling point set is processed using the gradient descent principle to obtain the working parameter position of the 5G cell corresponding to the 5G sampling point set.

[0183] In an exemplary embodiment, the determining unit 540 is specifically configured to:

[0184] Obtain all 5G sampling points corresponding to the target base station;

[0185] Filter the 5G sampling points whose sampling data do not meet a preset third condition to obtain the 5G sampling point set.

[0186] In an exemplary embodiment, the device may further include a filtering unit 550 ( Figure 5 (not shown), the filtering unit 550 is specifically used for:

[0187] Before associating the 4G sampling point with the 5G sampling point based on the grid identifier carried in each sampling data, performing a straight path analysis on the sampling data of the 4G sampling point, and filtering the 4G sampling point based on the straight path analysis result; and / or,

[0188] Before associating the 4G sampling point with the 5G sampling point based on the grid identifier carried in each sampling data, a straight path analysis is performed on the sampling data of the 5G sampling point, and the 5G sampling point is filtered based on the straight path analysis result.

[0189] In an exemplary embodiment, the filtering unit 550 is specifically configured to:

[0190] For any of the 4G sampling points, based on the first direct path data carried in the sampling data of the 4G sampling point, obtaining an estimated value of the second direct path data between the 4G sampling point and its base station;

[0191] When the target error is greater than or equal to a preset error threshold, the 4G sampling point is deleted; wherein the target error is the error between the estimated value and the second straight path data carried in the sampling data;

[0192] Among them, when the first direct path data is the time advance, the second direct path data is the distance between the 4G sampling point and the base station to which it belongs; or, when the first direct path data is the distance between the 4G sampling point and the base station to which it belongs, the second direct path data is the time advance.

[0193] In an exemplary embodiment, the device may further include an audit unit 560 ( Figure 5 (not shown), the filtering unit 560 is specifically used for:

[0194] Based on the working parameter location of the 5G cell, the working parameter table is audited.

[0195] Figure 6 This is a hardware block diagram of an electronic device provided in an embodiment of the present disclosure. The electronic device 600 according to an embodiment of the present disclosure includes at least a processor and a memory for storing computer-readable instructions. When the computer-readable instructions are loaded and executed by the processor, the processor executes the method for determining the position of the working parameters described in any of the preceding embodiments of the present disclosure.

[0196] Figure 6 The electronic device 600 shown specifically includes: a central processing unit (CPU) 601, a graphics processing unit (GPU) 602, and a memory 603. These units are interconnected via a bus 604. The central processing unit (CPU) 601 and / or the graphics processing unit (GPU) 602 can be used as the above-mentioned processor, and the memory 603 can be used as the above-mentioned memory for storing computer-readable instructions. In addition, the electronic device 600 may also include a communication unit 605, a storage unit 606, an output unit 607, an input unit 608, and an external device 609, which are also connected to the bus 604.

[0197] Figure 7 A schematic diagram of a computer-readable storage medium provided in an embodiment of the present disclosure. Figure 7As shown, a computer-readable storage medium 700 according to an embodiment of the present disclosure has computer-readable instructions 701 stored thereon. When the computer-readable instructions 701 are executed by a processor, the method for determining the position of the working parameter according to any of the above embodiments of the present disclosure described with reference to the above figures is executed. The computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0198] The present disclosure further provides a computer program product, including a computer program, which, when executed by a processor, implements the method for determining the position of working parameters described in any of the foregoing embodiments of the present disclosure.

[0199] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0200] The basic principles of the present disclosure have been described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in this disclosure are merely illustrative and not restrictive, and should not be construed as necessarily possessed by each embodiment of the present disclosure. Furthermore, the specific details disclosed above are provided for illustrative purposes and to facilitate understanding, rather than as limitations. These details do not limit the present disclosure to necessarily being implemented using these specific details.

[0201] The block diagrams of the devices, devices, equipment, and systems involved in this disclosure are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As will be appreciated by those skilled in the art, these devices, devices, equipment, and systems can be connected, arranged, or configured in any manner. Words such as "include," "comprise," "have," and the like are open-ended words, meaning "including but not limited to," and can be used interchangeably therewith. The words "or" and "and" used herein refer to the words "and / or" and can be used interchangeably therewith, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to," and can be used interchangeably therewith.

[0202] Additionally, as used herein, "or" used in a list of items beginning with "at least one" indicates a separate list, so that, for example, a list of "at least one of A, B, or C" means A or B or C, or AB or AC or BC, or ABC (i.e., A and B and C). Furthermore, the word "exemplary" does not mean that the example described is preferred or better than other examples.

[0203] It should also be noted that in the system and method of the present disclosure, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present disclosure.

[0204] Various changes, substitutions, and modifications may be made to the technology described herein without departing from the teachings defined by the appended claims. Moreover, the scope of the claims of this disclosure is not limited to the specific aspects of the processes, machines, manufactures, compositions of things, means, methods, and actions described above. Currently existing or later developed processes, machines, manufactures, compositions of things, means, methods, or actions that perform substantially the same function or achieve substantially the same results as the corresponding aspects described herein may be utilized. Accordingly, the appended claims include within their scope such processes, machines, manufactures, compositions of things, means, methods, or actions.

[0205] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0206] The above description has been provided for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for determining the position of an industrial parameter, characterized in that: The method comprises: Using the sampling data of each 4G sampling point in the 4G fingerprint library, the measurement report data of the 5G sampling point is backfilled to obtain the sampling data of the 5G sampling point; Based on the grid identifier carried in each sampling data, the 4G sampling point and the 5G sampling point are associated to obtain a sampling point set corresponding to each grid; Performing co-location analysis on the 5G cell and the 4G cell based on the sampling point set of each grid; For any of the 5G cells, when there is no co-located 4G cell in the 5G cell, the sampling data of the 5G sampling point is used to determine the working parameter position of the 5G cell.

2. The method according to claim 1, characterized in that The performing co-location analysis on the 5G cell and the 4G cell based on the sampling point set of each grid includes: Determine, based on the sampling point set of each grid, the 4G cell and the 5G cell corresponding to each grid; Perform matching analysis on the sampled data in the target grid to determine whether each 5G cell is co-located with each 4G cell. When any one of the 5G cells is co-located with a 4G cell, the working parameter position of the co-located 4G cell is determined as the working parameter position of the 5G cell.

3. The method according to claim 2, characterized in that The matching analysis of the sampled data to determine whether each 5G cell and each 4G cell has a co-location relationship includes: For any of the 5G cells, determining related 4G cells that have a grid overlap relationship with the 5G cell, and determining the overlapping grid; Matching analysis is performed on the sampling data of each 5G sampling point and each 4G sampling point in each overlapping grid to determine the local relationship corresponding to each overlapping grid; Based on the local relationship corresponding to each overlapping grid, determine whether the 5G cell and the related 4G cell have a co-location relationship.

4. The method according to claim 3, characterized in that The matching analysis of the sampling data of each 5G sampling point and each 4G sampling point in each overlapping grid to determine the local relationship corresponding to each overlapping grid includes: For any of the overlapping grids, obtaining the difference between the sampling data of each 5G sampling point and each 4G sampling point; Obtaining a first number of sampling point pairs whose difference satisfies a preset first condition; When the first number is greater than or equal to a preset first threshold, or the first ratio is greater than or equal to a preset second threshold, determining that the local relationship corresponding to the overlapping grid is: the 5G cell and the related 4G cell have a co-location relationship; The first ratio is the proportion of the first number to the total number of 5G sampling points in the overlapping grid.

5. The method according to claim 3, characterized in that The determining, based on the local relationship between the overlapping grids, whether the 5G cell and the related 4G cell have a co-location relationship includes: Obtaining a second number; the second number is an overlapping grid in which the local relationship is that the 5G cell and the related 4G cell have a co-location relationship; When the second number is greater than or equal to a preset third threshold, or the second ratio is greater than or equal to a preset fourth threshold, it is determined that the 5G cell and the related 4G cell have a co-location relationship; The second ratio is the proportion of the second number in the total number of overlapping grids.

6. The method according to claim 2 or 3, characterized in that The matching analysis of the sampled data to determine whether each 5G cell and each 4G cell has a co-location relationship includes: Obtain the Pearson correlation coefficient between the sampled data of each 5G cell and the sampled data of each 4G cell; When the Pearson correlation coefficient satisfies a preset second condition, determining that the 5G cell and the 4G cell corresponding to the Pearson correlation coefficient have a co-location relationship; The second condition is used to indicate the amount of data of the Pearson correlation coefficient within a preset numerical range.

7. The method according to any one of claims 2 to 6, characterized in that: The matching analysis of the sampled data to determine whether each 5G cell and each 4G cell has a co-location relationship includes: Perform matching analysis on the evaluation data to determine whether each 5G cell is co-located with each 4G cell; The evaluation data is all or part of the sampled data, and the evaluation data includes at least one of the following: a time advance value and a field strength value.

8. The method according to claim 1, characterized in that The determining the working parameter position of the 5G cell by using the sampling data of the 5G sampling point includes: Get the 5G sampling point set corresponding to the target base station; Based on the sampling data of each 5G sampling point, obtaining an average distance between the set of 5G sampling points and the target base station; Selecting a collection point set from the 5G sampling points of the target base station, and obtaining a first distance between each collection point and the target base station; Obtaining the difference between each first distance in the collection point set and the average distance, and obtaining the sum of each difference to obtain a second distance; With the goal of minimizing the second distance, the sampling data in the 5G sampling point set is processed using the gradient descent principle to obtain the working parameter position of the 5G cell corresponding to the 5G sampling point set.

9. The method according to claim 8, characterized in that The obtaining of the 5G sampling point set corresponding to the target base station includes: Obtain all 5G sampling points corresponding to the target base station; Filter the 5G sampling points whose sampling data do not meet a preset third condition to obtain the 5G sampling point set.

10. The method according to any one of claims 1 to 9, characterized in that Before associating the 4G sampling point with the 5G sampling point based on the grid identifier carried in each sampling data, the method further includes: Performing a straight line analysis on the sampling data of the 4G sampling points, and filtering the 4G sampling points based on the straight line analysis results; and / or, Performing a straight line analysis on the sampling data of the 5G sampling points, and performing filtering processing on the 5G sampling points based on the straight line analysis results.

11. The method according to claim 10, characterized in that The performing a straight path analysis on the sampling data of the 4G sampling points, and filtering the 4G sampling points based on the straight path analysis results, includes: For any of the 4G sampling points, based on the first direct path data carried in the sampling data of the 4G sampling point, obtaining an estimated value of the second direct path data between the 4G sampling point and its base station; When the target error is greater than or equal to a preset error threshold, the 4G sampling point is deleted; wherein the target error is the error between the estimated value and the second straight path data carried in the sampling data; Among them, when the first direct path data is the time advance, the second direct path data is the distance between the 4G sampling point and the base station to which it belongs; or, when the first direct path data is the distance between the 4G sampling point and the base station to which it belongs, the second direct path data is the time advance.

12. The method according to any one of claims 1 to 11, characterized in that The method further comprises: Based on the working parameter location of the 5G cell, the working parameter table is audited.

13. A device for determining the position of an industrial parameter, characterized in that: The device comprises: A backfill unit is configured to backfill the measurement report data of the 5G sampling point using the sampling data of each 4G sampling point in the 4G fingerprint library to obtain the sampling data of the 5G sampling point; an associating unit, configured to associate the 4G sampling point with the 5G sampling point based on the grid identifier carried in each sampling data, to obtain a sampling point set corresponding to each grid; an analysis unit, configured to perform co-location analysis on 5G cells and 4G cells based on the sampling point sets of each grid; A determination unit is used to determine, for any one of the 5G cells, the working parameter position of the 5G cell using the sampling data of the 5G sampling point when the 5G cell does not have a co-located 4G cell.

14. An electronic device, characterized in that: include: a memory for storing computer-readable instructions; as well as A processor is configured to execute the computer-readable instructions so that the electronic device performs the method according to any one of claims 1 to 12.

15. A non-transitory computer-readable storage medium for storing computer-readable instructions, characterized in that: When the computer-readable instructions are executed by a processor, the processor is caused to perform the method according to any one of claims 1 to 12.

16. A computer program product, characterized in that The method comprises a computer program, which implements the method according to any one of claims 1 to 12 when the computer program is executed by a processor.

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