CN109936851B - LTE network index processing method and device - Google Patents
LTE network index processing method and device Download PDFInfo
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Abstract
The embodiment of the invention provides a method and a device for processing LTE network indexes, which are provided by the embodiment of the invention, by acquiring monitoring values of network indexes of LTE cells and RSRP values acquired by MR acquisition points in the cells, grouping the MR acquisition points in each cell according to an RSRP threshold value, acquiring the positions of the MR acquisition points in each cell, rasterizing the MR acquisition points according to the positions of the MR acquisition points in each cell, acquiring the numerical value of each grid by adopting an index formula according to the monitoring values, the total number and the number of target cells, and dividing the grid based on a numerical range, so that the indexes in each grid are more consistent with a real service level, and the problem grid is more accurately positioned.
Description
Technical Field
The embodiment of the invention relates to the technical field of network optimization, in particular to a method and a device for processing LTE (Long term evolution) network indexes.
Background
In 4G network optimization, LTE (Long term evolution) cell-level indexes can quickly and effectively reflect the problems existing in the whole cell, and a corresponding solution can be formulated according to the reasons of the problems. However, in practical application, the coverage area of a single cell is generally a sector area of 500-2000 m, the position of a problem area cannot be determined through cell-level indexes, a large amount of labor is still consumed, a detailed traversal test is performed on the coverage area of the cell to perform problem location, and then a relevant solution is made based on the problem location, so that the problem solution efficiency is low and the cost investment is high. At present, on one hand, the grid accuracy based on MR positioning can reach 50m x 50m or even higher, and the cell-level indexes are rasterized by a reasonable and efficient means, so that the cell-level indexes can be converted into grid-level indexes with geographical position information; on the other hand, the grid MR indexes are not enough to represent the grid problem, and if the multi-dimensional grid-level cell indexes can be introduced, the problem area can be quickly and accurately positioned, and meanwhile, the problem root is dug deeply.
In the conventional cell index rasterization technical scheme, a geographic area is first subjected to rasterization processing, the whole network is divided into grids of N x N, and each grid is numbered; thirdly, rasterizing the LTE cells to obtain grids covered by each cell; thirdly, according to the cell rasterization processing result, uniformly distributing the LTE network index to each grid covered by the corresponding cell; finally, the LTE network indexes of all cells in each grid are overlapped to obtain the LTE network indexes after each grid is overlapped, and rasterization of the LTE network indexes is achieved.
In the prior art, the LTE network index is uniformly distributed to each grid covered by a corresponding cell, but each grid index covered by the cell is the same, and the problem of an actual grid cannot be reflected.
Disclosure of Invention
The embodiment of the invention provides a method and a device for processing LTE network indexes, which are used for solving the problem that an actual grid cannot be reflected in the prior art.
In a first aspect, an embodiment of the present invention provides an LTE network index processing method, including:
acquiring monitoring values of network indexes of each LTE cell and acquiring RSRP values acquired by MR acquisition points in each cell;
grouping the MR acquisition points in each cell according to the RSRP value acquired by the MR acquisition points in each cell and a preset RSRP threshold value to obtain the total number of the MR acquisition points in each group;
acquiring the positions of the MR acquisition points in each cell, and rasterizing the MR acquisition points according to the positions of the MR acquisition points in each cell to determine a grid to which each MR acquisition point belongs;
determining a target cell contained in each grid, and acquiring the number of the target cells to which the MR acquisition points belong in each grid under each group;
obtaining the numerical value of each grid by adopting an index formula according to the monitoring value, the total number and the number of the target cell;
and dividing the grid according to the corresponding relation between the numerical value and a preset numerical value range and the division identification, and displaying the division result.
In a second aspect, an embodiment of the present invention provides an LTE network index processing apparatus, including:
the acquisition module is used for acquiring monitoring values of network indexes of each LTE cell and acquiring RSRP values acquired by MR acquisition points in each cell;
the dividing module is used for grouping the MR acquisition points in each cell according to the RSRP value acquired by the MR acquisition points in each cell and a preset RSRP threshold value to obtain the total number of the MR acquisition points in each group;
the rasterization processing module is used for acquiring the positions of the MR acquisition points in each cell, and rasterizing the MR acquisition points according to the positions of the MR acquisition points in each cell to determine grids to which the MR acquisition points belong;
the statistical module is used for determining the target cell contained in each grid and acquiring the number of the target cells to which the MR acquisition points belong in each grid under each group;
the calculation module is used for obtaining the numerical value of each grid by adopting an index formula according to the monitoring value of the target cell, the total number and the number;
and the display module is used for dividing the grids according to the corresponding relation between the numerical value and the preset numerical value range and the division identification and displaying the division result.
In a third aspect, an embodiment of the present invention provides an electronic device, including: a processor, a memory, a bus, and a computer program stored on the memory and executable on the processor;
the processor and the memory complete mutual communication through the bus;
the processor, when executing the computer program, implements the method as described above.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores thereon a computer program, and when executed by a processor, the computer program implements the method as described above.
According to the technical scheme, the monitoring values of the network indexes of each cell of the LTE and the RSRP values acquired by the MR acquisition points in each cell are acquired, the MR acquisition points in each cell are grouped according to the RSRP threshold, the positions of the MR acquisition points in each cell are acquired, the MR acquisition points are rasterized according to the positions of the MR acquisition points in each cell, finally, the numerical value of each grid is acquired by using an index formula according to the monitoring values, the total number and the number of the target cell, and the grid is divided based on the numerical value range, so that the indexes in each grid conform to the real service level, and the problem grid can be positioned more accurately.
Drawings
Fig. 1 is a schematic flowchart of an LTE network index processing method according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating an LTE network index processing method according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating indicators after rasterizing the success rate of the ESRVCC handover according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an LTE network indicator processing apparatus according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
Fig. 1 shows an LTE network index processing method according to an embodiment of the present invention, which includes:
s11, acquiring monitoring values of network indexes of each LTE cell, and acquiring RSRP values acquired by MR acquisition points in each cell.
In this step, it should be noted that, in the embodiment of the present invention, the LTE has multiple service network indicators, such as a call drop rate, a handover success rate, an eSRVCC handover percentage, and the like.
In this embodiment, the independent system for analyzing and processing the LTE network index first needs to obtain the monitoring value of the network index of each cell, and the monitoring can be obtained by monitoring through the base station. The RSRP value (i.e., the reference signal received power) acquired by the MR acquisition point in each cell is also acquired. The MR acquisition point can be terminal equipment, fixed communication equipment and the like.
S12, grouping the MR acquisition points in each cell according to the RSRP value acquired by the MR acquisition points in each cell and a preset RSRP threshold value, and obtaining the total number of the MR acquisition points in each group.
In this step, it should be noted that, in the embodiment of the present invention, the RSRP value acquired by the MR acquisition point in each cell and the preset RSRP threshold are grouped into the MR acquisition points in each cell.
In the embodiment of the invention, the RSRP threshold value can be calculated in advance through a logistic regression function based on experimental data to be used in the method. The specific calculation process is as follows:
for the indexes such as handover success rate and ESRVCC handover percentage, a triggering threshold RSRP is often set in a cell as an event triggering condition, but triggering is not achieved when the threshold RSRP is reached, actually triggered RSRP often fluctuates, and RSRP values triggered by a call drop event also fluctuate. And (3) obtaining a probability scatter diagram of triggering the occurrence of an index S event when different RSRP values are obtained through laboratory and actual network test data, and making a corresponding probability curve model by using a Logistic regression function.
Logistic regression is a probability type nonlinear regression model, and is used for researching two classification observation results y and some influence factors x ═ x0，x1，x2，…xn) The multivariate analysis method of the relationship between the trigger indexes can generally study whether a certain result occurs under certain factor conditions, and is mainly used for predicting corresponding RSRP values of the trigger indexes S under different probabilities so as to judge a proper RSRP threshold value.
Consider a vector with N independent variables (x ═ x)0，x1，x2，…xn) Let P (y 1| X) be the probability of occurrence of an event X based on the observed quantity. Then the Logistic regression model can be expressed as:
are referred to herein as
Is a Logistic regression function.
Wherein g (x) w0+w1x1+…+wnxnObtained by the LR classifier. In the classification case, the learned LR classifier is a set of weights (w)0,w1,w2,…wn) When the data of the test sample is input, the set of weights and the test data are linearly added to obtain g (x).
Then the probability that y does not occur under x conditions is:
the ratio of the probability of an event occurring to that not occurring is:
this ratio is called the occurrence ratio of events (the odds of experiential an event), abbreviated as odds.
Logarithmically to odds yields:
for considering only one variable RSRP, it can be simplified to g (x) w0+w1X; this nonlinear regression equation can then be converted into a simple linear regression equation. The corresponding w can be obtained by the least square method0，w1The value of (c).
Wherein p isiWhen the RSRP takes the value of XiThe probability of the time index S triggering,
are averages.
According to the Logistic regression function:
the probability of triggering any MR sampling point index S can be estimated as piTime corresponding to RSRP of Xi。
In practice, p may be takeniWhen the RSRP is 95%, the RSRP value is calculated to be RSRP0As RSRP decision threshold.
S13, acquiring the positions of the MR acquisition points in each cell, and performing rasterization processing on the MR acquisition points according to the positions of the MR acquisition points in each cell to determine the grids to which the MR acquisition points belong.
In this step, it should be noted that, in the embodiment of the present invention, an MR positioning technique based on a fingerprint library first acquires the positions of MR acquisition points in each cell, performs rasterization processing on the MR acquisition points according to the positions of the MR acquisition points in each cell, positions the MR acquisition points in a grid of 50 × 50 meters, and determines which MR acquisition points belong to which grid. Through the rasterization processing, the network index differentiation of the cell i can be presented in the cell grid, and the cell problem grid position can be more accurately positioned.
S14, determining the target cell contained in each grid, and acquiring the number of the target cells under each group to which the MR acquisition points belong in each grid.
In this step, it should be noted that in the embodiment of the present invention, a plurality of cells may be involved in one grid, and therefore, MR acquisition points of a plurality of cells are included in one grid. Therefore, the system can determine the cells contained in each grid as target cells through the cell identifiers, and simultaneously acquire the number of the target cells under each group to which the MR acquisition points belong in each grid. I.e. how many acquisition points are in the grid for all MR acquisition points under a group of one target cell.
And S15, obtaining the numerical value of each grid by adopting an index formula according to the monitoring value of the target cell, the total number and the number.
In this step, it should be noted that, in the embodiment of the present invention, since a plurality of target cells are hunted in each grid, the monitored values of the target cells need to be obtained. The total number of all MR acquisition points of the target cell and the number of the target cells under each group to which the MR acquisition points belong in each grid.
And after the parameters are obtained, obtaining the numerical value of each grid according to a preset index formula.
The index formula is as follows:
wherein, TjIs the value of the network index of the grid j, i is the identifier of the network index, k is the number of target cells in the grid, A1ij、A2ij…AnijThe number N of target cells under each group to which the MR acquisition points belong in each grid1i、N2i…NniIs the total number of MR acquisition points, K, in each group of target cell i1、K2…KnInfluence factor, S, corresponding to each group of target cell iiIs the monitored value of the network index of the target cell i.
And S16, dividing the grid according to the corresponding relation between the numerical value and the preset numerical value range and the division identification.
In this step, it should be noted that, in the embodiment of the present invention, different corresponding relationships between the value range and the partition identifier may be configured for different network indicators. In this way, a raster map with different partitioning results can be obtained for different networks.
According to the LTE network index processing method provided by the embodiment of the invention, monitoring values of network indexes of each cell of LTE and RSRP values acquired by MR acquisition points in each cell are acquired, the MR acquisition points in each cell are grouped according to an RSRP threshold value, positions of the MR acquisition points in each cell are acquired at the same time, the MR acquisition points are subjected to rasterization according to the positions of the MR acquisition points in each cell, finally, numerical values of each grid are acquired by adopting an index formula according to the monitoring values, the total number and the number of a target cell, the grids are divided based on a numerical range, and division results are displayed, so that indexes in each grid are more consistent with a real service level, and more accurate positioning of problem grids is facilitated.
Fig. 2 shows an LTE network index processing method according to an embodiment of the present invention, which includes:
s21, acquiring monitoring values of network indexes of each LTE cell and acquiring RSRP values acquired by MR acquisition points in each cell;
s22, grouping the MR acquisition points in each cell according to the RSRP value acquired by the MR acquisition points in each cell and a preset RSRP threshold value to obtain the total number of the MR acquisition points in each group;
s23, acquiring the positions of the MR acquisition points in each cell, and rasterizing the MR acquisition points according to the positions of the MR acquisition points in each cell to determine the grids to which the MR acquisition points belong;
s24, determining a target cell contained in each grid, and acquiring the number of the target cells of the MR acquisition points in each grid under each group;
s25, obtaining the numerical value of each grid by adopting an index formula according to the monitoring value of the target cell, the total number and the number;
s26, obtaining a division identifier corresponding to the numerical value according to the numerical value and the corresponding relation between the preset numerical value range and the division identifier;
s27, setting the division identifications in the grid.
Regarding the above steps S21-S25, it should be noted that the principles of these steps are the same as those of the above embodiments from step S11 to step S15, and are not repeated herein. It is only necessary to state that:
for step S22, in the embodiment of the present invention, the sets of MR acquisition points of the cell center region and the sets of MR acquisition points of the cell edge region are grouped.
And dividing the RSRP value larger than the RSRP threshold value into a group, namely a cell center region MR acquisition point set, and dividing the RSRP value smaller than or equal to the RSRP threshold value into a group, namely a cell edge region MR acquisition point set.
The method specifically comprises the following steps:
wherein, RSRP0Is a threshold value, K1And K2Is an index influence factor.
And counting the total number of MR acquisition points in each group. In cell i, the total number of MR acquisition points in the central region of the cell is N1iThe total number of MR acquisition points in the edge area of the cell is N2i。
For step S25, in the embodiment of the present invention, taking the set of MR acquisition points in the cell center region and the set of MR acquisition points in the cell edge region as an example, the index formula may be changed as follows:
with respect to steps S26 to S27, it should be noted that the system may obtain the division identifier corresponding to the numerical value according to the corresponding relationship between the numerical value and the preset numerical range and the division identifier, where the division identifier may be different patterns, different colors, different numbers, and the like. And setting the division identification in the grid and displaying the division identification as a division result.
Fig. 3 is a schematic diagram illustrating the isvcc handover success rate after rasterization. As can be seen from FIG. 3, the colors within the ranges of, for example, 0-5, 5-10, 10-15, and 15-40 are all different, so that the rasterization index can more accurately reflect the actual situation.
According to the LTE network index processing method provided by the embodiment of the invention, monitoring values of network indexes of each cell of LTE and RSRP values acquired by MR acquisition points in each cell are acquired, the MR acquisition points in each cell are grouped according to an RSRP threshold value, positions of the MR acquisition points in each cell are acquired at the same time, the MR acquisition points are subjected to rasterization according to the positions of the MR acquisition points in each cell, finally, numerical values of each grid are acquired by adopting an index formula according to the monitoring values, the total number and the number of a target cell, the grids are divided based on a numerical range, and division results are displayed, so that indexes in each grid are more consistent with a real service level, and more accurate positioning of problem grids is facilitated.
Fig. 4 shows an LTE network index processing apparatus provided in an embodiment of the present invention, which includes an obtaining module 21, a grouping module 22, a rasterization processing module 23, a statistics module 24, a calculation module 25, and a display module 26, where:
the acquisition module 21 is configured to acquire a monitoring value of a network index of each LTE cell and acquire an RSRP value acquired by an MR acquisition point in each cell;
the grouping module 22 is configured to group the MR acquisition points in each cell according to the RSRP value acquired by the MR acquisition points in each cell and a preset RSRP threshold value, so as to obtain the total number of the MR acquisition points in each group;
the rasterization processing module 23 is configured to acquire positions of the MR acquisition points in each cell, perform rasterization processing on the MR acquisition points according to the positions of the MR acquisition points in each cell, and determine a grid to which each MR acquisition point belongs;
the statistical module 24 is configured to determine a target cell included in each grid, and obtain the number of target cells under each group to which the MR acquisition point belongs in each grid;
a calculating module 25, configured to obtain a numerical value of each grid by using an index formula according to the monitoring value of the target cell, the total number, and the number;
and the dividing module 26 is configured to divide the grid according to the corresponding relationship between the numerical value and the preset numerical value range and the division identifier, and display a division result.
In the processing process, the obtaining module 21 obtains the monitoring values of the network indexes of each LTE cell, obtains RSRP values collected by MR collection points in each cell, sends the monitoring values to the calculating module, and sends the RSRP values to the grouping module. The grouping module 22 groups the MR acquisition points in each cell according to the RSRP value acquired by the MR acquisition points in each cell and a preset RSRP threshold value, obtains the total number of the MR acquisition points in each group, and sends the total number of the MR acquisition points in each group to the calculation module.
The rasterization processing module 23 acquires the positions of the MR acquisition points in each cell, and performs rasterization processing on the MR acquisition points according to the positions of the MR acquisition points in each cell to determine the grids to which the MR acquisition points belong. The counting module 24 determines the target cell included in each grid, obtains the number of the target cells to which the MR acquisition points belong in each group in each grid, and sends the number of the target cells to which the MR acquisition points belong in each grid in each group to the calculating module.
The calculating module 25 obtains the value of each grid by using an index formula according to the monitoring value, the total number and the number of the target cell, and sends the value to the dividing module. The dividing module 26 divides the grid according to the corresponding relationship between the numerical value and the preset numerical value range and the division identifier.
Since the principle of the apparatus according to the embodiment of the present invention is the same as that of the method according to the above embodiment, further details are not described herein for further explanation.
It should be noted that, in the embodiment of the present invention, the relevant functional module may be implemented by a hardware processor (hardware processor).
According to the LTE network index processing device provided by the embodiment of the invention, the monitoring values of the network indexes of each cell of LTE and the RSRP values acquired by the MR acquisition points in each cell are acquired, the MR acquisition points in each cell are grouped according to the RSRP threshold value, the positions of the MR acquisition points in each cell are acquired at the same time, the MR acquisition points are subjected to rasterization processing according to the positions of the MR acquisition points in each cell, finally, the numerical value of each grid is acquired by adopting an index formula according to the monitoring values, the total number and the number of the target cell, the grids are divided based on the numerical range, and the division result is displayed, so that the indexes in each grid are more consistent with the real service level, and the problem grid can be positioned more accurately.
Fig. 5 shows an electronic device provided in an embodiment of the present invention, including: a processor 301, a memory 302, and a bus 303, wherein,
the processor and the memory complete mutual communication through the bus;
the memory stores program instructions executable by the processor to perform the methods provided by the method embodiments described above, including, for example: acquiring monitoring values of network indexes of each LTE cell and acquiring RSRP values acquired by MR acquisition points in each cell; grouping the MR acquisition points in each cell according to the RSRP value acquired by the MR acquisition points in each cell and a preset RSRP threshold value to obtain the total number of the MR acquisition points in each group; acquiring the positions of the MR acquisition points in each cell, and rasterizing the MR acquisition points according to the positions of the MR acquisition points in each cell to determine a grid to which each MR acquisition point belongs; determining a target cell contained in each grid, and acquiring the number of the target cells to which the MR acquisition points belong in each grid under each group; obtaining the numerical value of each grid by adopting an index formula according to the monitoring value, the total number and the number of the target cell; and dividing the grid according to the corresponding relation between the numerical value and a preset numerical value range and the division identification.
An embodiment of the present invention provides a non-transitory computer-readable storage medium storing computer instructions, which cause the computer to execute the method provided by the above method embodiments, for example, including: acquiring monitoring values of network indexes of each LTE cell and acquiring RSRP values acquired by MR acquisition points in each cell; grouping the MR acquisition points in each cell according to the RSRP value acquired by the MR acquisition points in each cell and a preset RSRP threshold value to obtain the total number of the MR acquisition points in each group; acquiring the positions of the MR acquisition points in each cell, and rasterizing the MR acquisition points according to the positions of the MR acquisition points in each cell to determine a grid to which each MR acquisition point belongs; determining a target cell contained in each grid, and acquiring the number of the target cells to which the MR acquisition points belong in each grid under each group; obtaining the numerical value of each grid by adopting an index formula according to the monitoring value, the total number and the number of the target cell; and dividing the grid according to the corresponding relation between the numerical value and a preset numerical value range and the division identification.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Those of ordinary skill in the art will understand that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit of the corresponding technical solutions and scope of the present invention as defined in the appended claims.
Claims (10)
1. An LTE network index processing method is characterized by comprising the following steps:
acquiring monitoring values of network indexes of each LTE cell and acquiring RSRP values acquired by MR acquisition points in each cell;
grouping the MR acquisition points in each cell according to the RSRP value acquired by the MR acquisition points in each cell and a preset RSRP threshold value to obtain the total number of the MR acquisition points in each group;
acquiring the positions of the MR acquisition points in each cell, and rasterizing the MR acquisition points according to the positions of the MR acquisition points in each cell to determine a grid to which each MR acquisition point belongs;
determining a target cell contained in each grid, and acquiring the number of the target cells to which the MR acquisition points belong in each grid under each group;
obtaining the numerical value of each grid by adopting an index formula according to the monitoring value, the total number and the number of the target cell;
and dividing the grid according to the corresponding relation between the numerical value and a preset numerical value range and the division identification.
2. The method of claim 1, wherein the index formula is:
wherein, TjIs the value of the network index of the grid j, i is the identifier of the network index, k is the number of target cells in the grid, A1ij、A2ij…AnijThe number N of target cells under each group to which the MR acquisition points belong in each grid1i、N2i…NniIs the total number of MR acquisition points, K, in each group of target cell i1、K2…KnInfluence factor, S, corresponding to each group of target cell iiIs the monitored value of the network index of the target cell i.
3. The method of claim 1, wherein the grouping comprises a set of cell center region MR acquisition points and a set of cell edge region MR acquisition points.
4. The method according to claim 1, wherein the dividing the grid according to the corresponding relationship between the numerical value and the preset numerical value range and the division identifier and displaying the division result comprises:
obtaining a division identifier corresponding to the numerical value according to the corresponding relation between the numerical value and a preset numerical value range and the division identifier;
setting the division identification in the grid.
5. An LTE network index processing apparatus, comprising:
the acquisition module is used for acquiring monitoring values of network indexes of each LTE cell and acquiring RSRP values acquired by MR acquisition points in each cell;
the grouping module is used for grouping the MR acquisition points in each cell according to the RSRP value acquired by the MR acquisition points in each cell and a preset RSRP threshold value to obtain the total number of the MR acquisition points in each group;
the rasterization processing module is used for acquiring the positions of the MR acquisition points in each cell, and rasterizing the MR acquisition points according to the positions of the MR acquisition points in each cell to determine grids to which the MR acquisition points belong;
the statistical module is used for determining the target cell contained in each grid and acquiring the number of the target cells to which the MR acquisition points belong in each grid under each group;
the calculation module is used for obtaining the numerical value of each grid by adopting an index formula according to the monitoring value of the target cell, the total number and the number;
and the dividing module is used for dividing the grids according to the corresponding relation between the numerical value and the preset numerical value range and the dividing identification.
6. The apparatus of claim 5, wherein the index formula is:
wherein, TjIs the value of the network index of the grid j, i is the identifier of the network index, k is the number of target cells in the grid, A1ij、A2ij…AnijThe number N of target cells under each group to which the MR acquisition points belong in each grid1i、N2i…NniIs the total number of MR acquisition points, K, in each group of target cell i1、K2…KnInfluence factor, S, corresponding to each group of target cell iiIs the monitored value of the network index of the target cell i.
7. The apparatus of claim 5, wherein the grouping comprises a set of cell center region MR acquisition points and a set of cell edge region MR acquisition points.
8. The apparatus of claim 5, wherein the partitioning module is specifically configured to:
obtaining a division identifier corresponding to the numerical value according to the corresponding relation between the numerical value and a preset numerical value range and the division identifier;
setting the division identification in the grid.
9. An electronic device, comprising: a processor, a memory, a bus, and a computer program stored on the memory and executable on the processor;
the processor and the memory complete mutual communication through the bus;
the processor, when executing the computer program, implements the method of any of claims 1-4.
10. A non-transitory computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, implements the method of any one of claims 1-4.
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