CN115086970A - Measurement data analysis method, measurement data analysis device, measurement data analysis medium, and electronic device - Google Patents
Measurement data analysis method, measurement data analysis device, measurement data analysis medium, and electronic device Download PDFInfo
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Abstract
The application provides a method, a device, a medium and an electronic device for analyzing measurement data, which relate to the technical field of wireless network communication and comprise the following steps: determining sampling points corresponding to the measurement data in the measurement data set to obtain a sampling point set; positioning a grid to which each sampling point in the sampling point set belongs in a rasterized preset region; and generating a cell coverage result of each grid in the preset area according to the cell corresponding to each sampling point in the sampling point set. Therefore, the coverage analysis can be performed by the rasterization result of the region with a finer granularity analysis dimension, so that the accuracy of the coverage analysis result can be improved, the accurate positioning of the grid region with coverage problems by related personnel is facilitated, and the adjustment of the coverage region of the cell network is facilitated.
Description
Technical Field
The present disclosure relates to the field of wireless network communication technologies, and in particular, to a measurement data analysis method, a measurement data analysis device, a computer-readable storage medium, and an electronic device.
Background
The placement of cellular network stations in an area is often an important means of achieving wireless network coverage. Generally, the arrangement of the cellular network station is manually set, and the manually set cellular network station inevitably has unreasonable network coverage problems, such as weak coverage, over coverage, overlapping coverage, and the like. For the above problems, the conventional network management system generally uses a cell as an analysis dimension, and analyzes whether a coverage problem exists between a main cell and a co-frequency neighboring cell through measurement data, and a coverage analysis result obtained in this way has a problem of low accuracy.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present application and therefore may include information that does not constitute prior art known to a person of ordinary skill in the art.
Disclosure of Invention
An object of the present application is to provide a measurement data analysis method, a measurement data analysis device, a computer-readable storage medium, and an electronic device, which can perform coverage analysis with a finer granularity of analysis dimension by rasterizing a result of an area, thereby improving accuracy of a coverage analysis result, facilitating accurate positioning of a grid area with coverage problems by related personnel, and facilitating adjustment of a cell network coverage area.
Other features and advantages of the present application will be apparent from the following detailed description, or may be learned by practice of the application.
According to an aspect of the present application, there is provided a measurement data analysis method including:
determining sampling points corresponding to the measurement data in the measurement data set to obtain a sampling point set;
positioning a grid to which each sampling point in the sampling point set belongs in a rasterized preset region;
and generating a cell coverage result of each grid in the preset area according to the cell corresponding to each sampling point in the sampling point set.
In an exemplary embodiment of the present application, locating a grid to which each sample point in a set of sample points belongs in a pre-set region of rasterization includes:
positioning the grid to which each sampling point in the sampling point set belongs according to the grid numbering rule and the rasterization parameter; wherein, the rasterization parameters at least comprise grid size and grid degree.
In an exemplary embodiment of the present application, generating a cell coverage result of each grid in a preset area according to a cell corresponding to each sampling point in a sampling point set includes:
determining to screen target grids from all grids according to screening rules corresponding to preset frequency bands;
determining the number of sampling points corresponding to different cells in a target grid and the total number of sampling points in the target grid;
generating a cell coverage result of the target grid according to the ratio of the number of sampling points corresponding to different cells to the total number of sampling points;
the cell coverage result comprises non-overlapping coverage or overlapping coverage with preset strength, and the preset strength is used for representing the overlapping coverage degree.
In an exemplary embodiment of the present application, after positioning the grid to which each sample point in the set of sample points belongs in the rasterized preset region, the method further includes:
screening target grids from the grids according to a preset screening rule;
clustering the target grid and removing a noise point grid in the target grid according to a clustering result to obtain a plurality of clusters of grids to be processed;
determining the coordinates of a base station according to the grid number and the grid center coordinates in each cluster of grids to be processed;
comparing the base station coordinate with the engineering coordinate, and determining an azimuth center point according to a comparison result;
and analyzing and calculating the azimuth angle of the cell according to the center point of the azimuth angle and outputting the azimuth angle.
In an exemplary embodiment of the present application, determining the azimuth center point according to the comparison result includes:
if the comparison result shows that the distance between the base station coordinate and the engineering coordinate is greater than the preset distance, determining the base station coordinate as an azimuth center point;
and if the comparison result shows that the distance is less than or equal to the preset distance, determining the engineering coordinate as the azimuth center point.
In an exemplary embodiment of the present application, after positioning the grid to which each sample point in the set of sample points belongs in the rasterized preset region, the method further includes:
determining the capacity corresponding to different cells according to the wireless resource utilization rate in each measurement data in the measurement data set; the capacity is used for representing the busy degree of a cell in one day;
and carrying out differentiated marking on the cells in the preset area according to the corresponding capacities of different cells.
In an exemplary embodiment of the present application, after positioning the grid to which each sample point in the set of sample points belongs in the rasterized preset region, the method further includes:
determining the current busy duration of each cell in a preset area;
and calculating the current busy duration of each grid in the preset area according to the sampling point of each grid in the preset area, the cell corresponding to each sampling point in the sampling point set and the current busy duration of each cell in the preset area.
According to an aspect of the present application, there is provided a measurement data analysis apparatus including: sampling point acquisition unit, sampling point positioning unit and district cover result determine unit, wherein:
the sampling point acquisition unit is used for determining sampling points corresponding to the measurement data in the measurement data set to obtain a sampling point set;
the sampling point positioning unit is used for positioning the grids to which the sampling points in the sampling point set belong in the rasterized preset region;
and the cell coverage result determining unit is used for generating a cell coverage result of each grid in the preset area according to the cell corresponding to each sampling point in the sampling point set.
In an exemplary embodiment of the present application, the sampling point positioning unit positions, in a rasterized preset region, a grid to which each sampling point in the set of sampling points belongs, including:
positioning the grid to which each sampling point in the sampling point set belongs according to the grid numbering rule and the rasterization parameter; wherein, the rasterization parameters at least comprise grid size and grid degree.
In an exemplary embodiment of the present application, the generating, by the cell coverage result determining unit, the cell coverage result of each grid in the preset area according to the cell corresponding to each sampling point in the sampling point set includes:
determining to screen a target grid from all grids according to a screening rule corresponding to a preset frequency band;
determining the number of sampling points corresponding to different cells in a target grid and the total number of sampling points in the target grid;
generating a cell coverage result of the target grid according to the ratio of the number of sampling points corresponding to different cells to the total number of sampling points;
the cell coverage result comprises non-overlapping coverage or overlapping coverage with preset strength, and the preset strength is used for representing the overlapping coverage degree.
In an exemplary embodiment of the present application, the apparatus further includes:
the grid screening unit is used for screening target grids from all the grids according to a preset screening rule after the sampling point positioning unit positions the grids to which all the sampling points belong in the sampling point set in the rasterized preset region;
the clustering unit is used for clustering the target grid and removing the noise point grid in the target grid according to the clustering result to obtain a multi-cluster grid to be processed;
the coordinate calculation unit is used for determining the coordinates of the base station according to the grid number and the grid center coordinates in each cluster of grids to be processed;
the position determining unit is used for comparing the base station coordinates with the engineering coordinates and determining an azimuth center point according to a comparison result;
and the azimuth angle analysis unit is used for analyzing and calculating the azimuth angle of the cell according to the center point of the azimuth angle and outputting the azimuth angle.
In an exemplary embodiment of the present application, the determining the azimuth center point according to the comparison result by the position determining unit includes:
if the comparison result shows that the distance between the base station coordinate and the engineering coordinate is greater than the preset distance, determining the base station coordinate as an azimuth center point;
and if the comparison result shows that the distance is less than or equal to the preset distance, determining the engineering coordinate as the azimuth center point.
In an exemplary embodiment of the present application, the apparatus further includes:
the capacity calculation unit is used for determining the capacity corresponding to different cells according to the utilization rate of wireless resources in each measurement data in the measurement data set after the sampling point positioning unit positions the grids to which each sampling point in the sampling point set belongs in the rasterized preset region; the capacity is used for representing the busy degree of a cell in one day;
and the cell marking unit is used for distinguishing and marking the cells in the preset area according to the corresponding capacities of different cells.
In an exemplary embodiment of the present application, the apparatus further includes:
the busy duration calculation unit is used for determining the current busy duration of each cell in the preset area after the sampling point positioning unit positions the grid to which each sampling point in the sampling point set belongs in the rasterized preset area; and calculating the current busy duration of each grid in the preset area according to the sampling point of each grid in the preset area, the cell corresponding to each sampling point in the sampling point set and the current busy duration of each cell in the preset area.
According to an aspect of the present application, there is provided an electronic device including: a processor; and a memory for storing executable instructions for the processor; wherein the processor is configured to perform the method of any of the above via execution of the executable instructions.
According to an aspect of the application, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of any one of the above.
According to an aspect of the application, a computer program product or computer program is provided, comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method provided in the various alternative implementations described above.
The exemplary embodiments of the present application may have some or all of the following advantages:
in the measurement data analysis method provided by an exemplary embodiment of the present application, a sampling point corresponding to each measurement data in a measurement data set may be determined to obtain a sampling point set; positioning a grid to which each sampling point in the sampling point set belongs in a rasterized preset region; and generating a cell coverage result of each grid in the preset area according to the cell corresponding to each sampling point in the sampling point set. According to the technical description, on one hand, coverage analysis can be performed by using a finer-grained analysis dimension according to the rasterization result of the area, so that the accuracy of the coverage analysis result can be improved, the accurate positioning of the grid area with coverage problems by related personnel is facilitated, and the adjustment of the coverage area of the cell network is facilitated. In another aspect of the present application, the accuracy of the analysis of the network coverage problem can be further improved by rasterizing the regions and positioning the sampling points.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort.
Fig. 1 is a schematic diagram illustrating an exemplary system architecture to which a measurement data analysis method and a measurement data analysis apparatus according to an embodiment of the present application may be applied;
FIG. 2 illustrates a schematic structural diagram of a computer system suitable for use in implementing an electronic device of an embodiment of the present application;
FIG. 3 schematically shows a flow diagram of a measurement data analysis method according to an embodiment of the present application;
FIG. 4 schematically shows a clustering result diagram according to an embodiment of the present application;
FIG. 5 schematically illustrates a multi-cell base station cell diagram according to an embodiment of the present application;
FIG. 6 schematically illustrates a single-cell base station cell diagram according to an embodiment of the present application;
fig. 7 schematically shows a multi-cell clustering diagram according to an embodiment of the present application;
fig. 8 schematically shows a single cell clustering diagram according to an embodiment of the present application;
figure 9 schematically shows a cell coverage result according to an embodiment of the application;
figure 10 schematically shows a cell capacity diagram according to an embodiment of the application;
FIG. 11 schematically illustrates a parameter presentation interface diagram according to an embodiment of the present application;
FIG. 12 schematically illustrates a parameter presentation interface diagram according to another embodiment of the present application;
FIG. 13 schematically illustrates an overlay result presentation interface diagram according to an embodiment of the present application;
fig. 14 schematically shows a block diagram of a measurement data analysis apparatus in an embodiment according to the present application.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the subject matter of the present application can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present application.
Furthermore, the drawings are merely schematic illustrations of the present application and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
Fig. 1 is a schematic diagram illustrating a system architecture of an exemplary application environment to which a measured data analysis method and a measured data analysis apparatus according to an embodiment of the present application may be applied.
As shown in fig. 1, the system architecture 100 may include one or more of terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few. The terminal devices 101, 102, 103 may be various electronic devices having a display screen, including but not limited to desktop computers, portable computers, smart phones, tablet computers, and the like. It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. For example, server 105 may be a server cluster comprised of multiple servers, or the like.
The measurement data analysis method provided by the embodiment of the present application is generally executed by the server 105, and accordingly, the measurement data analysis apparatus is generally disposed in the server 105. However, it is easily understood by those skilled in the art that the measurement data analysis method provided in the embodiment of the present application may also be executed by the terminal device 101, 102, or 103, and accordingly, the measurement data analysis apparatus may also be disposed in the terminal device 101, 102, or 103, which is not particularly limited in this exemplary embodiment. For example, in an exemplary embodiment, the server 105 may determine a sampling point corresponding to each measurement data in the measurement data set, to obtain a sampling point set; positioning a grid to which each sampling point in the sampling point set belongs in a rasterized preset region; and generating a cell coverage result of each grid in the preset area according to the cell corresponding to each sampling point in the sampling point set.
FIG. 2 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.
It should be noted that the computer system 200 of the electronic device shown in fig. 2 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 2, the computer system 200 includes a Central Processing Unit (CPU)201 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)202 or a program loaded from a storage section 208 into a Random Access Memory (RAM) 203. In the RAM 203, various programs and data necessary for system operation are also stored. The CPU 201, ROM 202, and RAM 203 are connected to each other via a bus 204. An input/output (I/O) interface 205 is also connected to bus 204.
The following components are connected to the I/O interface 205: an input portion 206 including a keyboard, a mouse, and the like; an output section 207 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 208 including a hard disk and the like; and a communication section 209 including a network interface card such as a LAN card, a modem, or the like. The communication section 209 performs communication processing via a network such as the internet. A drive 210 is also connected to the I/O interface 205 as needed. A removable medium 211, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like, is mounted on the drive 210 as necessary, so that a computer program read out therefrom is installed into the storage section 208 as necessary.
In particular, according to embodiments of the present application, the processes described below with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 209 and/or installed from the removable medium 211. The computer program, when executed by a Central Processing Unit (CPU)201, performs various functions defined in the methods and apparatus of the present application.
The present example embodiment provides a measurement data analysis method. The measurement data analysis method may be applied to the server 105, and may also be applied to one or more of the terminal devices 101, 102, and 103, which is not particularly limited in this exemplary embodiment. Referring to fig. 3, the measurement data analysis method may include the following steps S310 to S330.
Step S310: and determining sampling points corresponding to the measurement data in the measurement data set to obtain a sampling point set.
Step S320: and positioning the grids to which the sampling points in the sampling point set belong in the preset rasterization area.
Step S330: and generating a cell coverage result of each grid in the preset area according to the cell corresponding to each sampling point in the sampling point set.
By implementing the method shown in fig. 3, coverage analysis can be performed with a finer-grained analysis dimension by using the rasterization result of the area, so that the accuracy of the coverage analysis result can be improved, and it is beneficial for related personnel to accurately position the grid area with coverage problems, thereby facilitating adjustment of the coverage area of the cell network. In addition, the analysis accuracy of the network coverage problem can be further improved by rasterizing the region and positioning the grid of the sampling points.
The above steps of the present exemplary embodiment will be described in more detail below.
In step S310, a sampling point corresponding to each measured data in the measured data set is determined, and a sampling point set is obtained.
Specifically, each Measurement data in the Measurement data set may be data of a Measurement Report (MR), and the MR generally includes multiple items of important index information such as a Reference Signal Receiving Power (RSRP), a Reference Signal Receiving Quality (RSRQ), and the like of a base station number, a cell number, a PCI, a serving cell, and a neighboring cell. Wherein RSRP is one of the key parameters that can represent radio signal strength in LTE networks and the physical layer measurement requirement, and is the average of the received signal power over all REs (resource elements) that carry reference signals within a certain symbol. In addition, the MR includes measurement data reported by a mobile terminal connected to the network to an Evolved NodeB (eNodeB) in a preset time and length, specifically including information of a serving cell and information of a strongest target cell, and the information of the base station database is combined to locate a sampling point in the MR. In addition, each measurement data in the measurement data set may be a time-of-week-granularity sample data.
In addition, the MR data may reflect the real distribution of the users in the preset area, and before step S310, the method may further include: logging in the network management center to configure the parameters of the measurement report function so as to realize measurement data acquisition. Generally, all mobile terminals in a preset area report measurement data, so that the richness of sample data can be ensured.
In step S320, a grid to which each sample point in the set of sample points belongs is located in the rasterized preset region.
Specifically, positioning the grid to which each sample point in the set of sample points belongs in the preset rasterized region includes: analyzing each sampling point file (MRO file) in the sampling point set, and extracting the position data (AGPS data) of the sampling point containing longitude and latitude in the analysis result. Further, the method may further include: the method comprises the steps that a downloading program which is deployed on an interface machine in advance is connected with a data acquisition machine, and the data at the sampling point position is downloaded and loaded into a data warehouse tool (hive) through a distributed file system (HDFS), so that the data at the sampling point position can be called in time conveniently.
As an alternative embodiment, locating the grid to which each sample point in the set of sample points belongs in the preset region of rasterization includes: positioning the grid to which each sampling point in the sampling point set belongs according to the grid numbering rule and the rasterization parameter; wherein, the rasterization parameters at least comprise grid size and grid degree.
Specifically, the grid size may be represented by L ═ 20.0 (meters), from which the divided grid size may be 20 meters by 20 meters; the grid degree may be expressed as D ═ L × 0.00001; the GRID numbering rule may be used to define a numbering manner for the divided GRIDs, and a format of the GRID number (GRID _ ID) obtained according to the GRID numbering rule may specifically be expressed as a longitude number + "|" + latitude number; the rasterization parameters are used for performing raster division on the preset area. In addition, it should be noted that the rasterization process is to perform regular version layout on the region where the sampling points are reported on the platform by using horizontal lines and vertical lines.
In addition, positioning the grid to which each sampling point in the sampling point set belongs according to the grid numbering rule and the rasterization parameter comprises the following steps: carrying out grid division on a preset area; projecting each sampling point in the sampling point set to a preset area after rasterization processing; carrying out rounding-down and rounding-down processing according to the longitude (Lon) and the latitude (Lat) of each sampling point to obtain the longitude Lon1 and the latitude Lat1 of the grid to which the sampling point belongs; wherein, longitude Lon1 ═ math.floor (Lon × 100000/L), latitude Lat1 ═ math.floor (Lat × 100000/L) +1, Lon1 and Lat1 are integers; then, the longitude Lon2 and the latitude Lat2 are calculated from Lon2 ═ Lon1 ═ L and Lat2 ═ Lat1 ═ L, and the GRID number (GRID _ ID) Lon2| Lat2 is obtained; furthermore, longitude Lon3 of the upper left corner of the grid to which the sampling point belongs and latitude Lat3 of the upper left corner of the grid can be calculated according to Lon3 ═ Lon2 ═ 0.00001 and Lat3 ═ Lat2 ═ 0.00001; furthermore, the longitude lon4 of the center point of the grid to which the sampling point belongs and the latitude lat4 of the center point of the grid can be calculated according to lon4 (lon 3+ D/2) and lat4 (lat 3-D/2), so that the grid number, the longitude and latitude coordinates of the center point of the grid and the longitude and latitude coordinates of the upper left corner of the grid to which each sampling point belongs in the sampling point set can be determined.
Therefore, by implementing the optional embodiment, the fine analysis of the measurement data can be realized through rasterization of the preset area, so that the content richness of the analysis result of the measurement data can be improved.
As an alternative embodiment, after positioning the grid to which each sample point in the set of sample points belongs in the rasterized preset region, the method further includes: screening target grids from the grids according to a preset screening rule; clustering the target grid and removing a noise point grid in the target grid according to a clustering result to obtain a plurality of clusters of grids to be processed; determining the coordinates of a base station according to the grid number and the grid center coordinates in each cluster of grids to be processed; comparing the base station coordinates with the engineering coordinates, and determining an azimuth center point according to a comparison result; and analyzing and calculating the azimuth angle of the cell according to the azimuth center point and outputting the azimuth angle.
Specifically, a cell (also referred to as a cell) refers to an area covered by one base station or a part (sector antenna) of the base station in a cellular mobile communication system, in which mobile stations in the area can communicate with the base station through a radio channel, and one base station corresponds to a plurality of cells, and the base station includes a macro base station and a cell base station. In addition, the cell coordinates include a cell longitude and a cell latitude, and a preset screening rule is used for limiting the brushing condition of the target grid.
In one aspect, for a room division base station:
the preset screening rules may include that RSRP is greater than a preset power (e.g., -100dBm) and the number of grids is greater than a preset number (e.g., 50), and the target grid is screened from the respective grids according to the preset screening rules, including: and screening grids with RSRP < -100dBm and the grid number larger than 50 from each grid as target grids.
Based on this, clustering the target grid includes: and clustering the target grids according to a DBSCAN clustering algorithm. The DBSCAN clustering algorithm is a density-based spatial clustering algorithm, which can divide a target grid with sufficient density into clusters, find clusters of any shape in a noisy spatial database, and define the clusters as a maximum set of density-connected points, and is influenced by two parameters, namely, a distance threshold (Eps) and a minimum direct reachable point (MinPts). Referring to fig. 4, fig. 4 schematically shows a clustering result diagram according to an embodiment of the present application. As shown in fig. 4, the grids indicated as black dots are clustered according to the DBSCAN clustering algorithm, and the clustering range of each grid is a circle having a center coordinate of the grid as a center and a preset radius. According to fig. 4, the clustering range of the grids belonging to one class in the clustering result is represented as a solid line 410, the clustering range of the grids belonging to the clustering edge in the clustering result is represented as a dotted line 420, and the grids represented by the dotted line 430 are far from other grids and are not classified as one class with other grids under the DBSCAN clustering algorithm. Therefore, the clustering range is represented as no connecting line between the grid of the dotted line 430 and other grids, and there is a connecting line between adjacent grids belonging to one class for representing being classified as one class.
Based on this, removing the noisy point grid in the target grid according to the clustering result comprises: and removing the noise point grids in the target grid according to the radius Eps-50 and the preset number minPts-5. Further, determining the coordinates of the base station according to the grid number and the grid center coordinates in each cluster of grids to be processed, comprising: determining a specific grid corresponding to a preset RSRP (such as an RSRP mean value in a cluster of grids) in each cluster of grids to be processed, and if the number of the specific grids is 1, determining the longitude and latitude coordinates of the center point of the specific grid as base station coordinates (namely virtual site coordinates of a cell); if the number of the specific grids is 2, determining the middle point of the longitude and latitude coordinates of the central points of the two specific grids as the coordinates of the base station; if the number of the specific grids is more than 2, extracting the clustering centers of the longitude and latitude coordinates of the central points of the specific grids, and determining the longitude and latitude coordinates of the clustering centers as the coordinates of the base station.
Based on the method, the cell azimuth is analyzed and calculated according to the azimuth center point and output, and the method comprises the following steps: and determining the azimuth center point as 360 degrees by taking the azimuth center point as a circle center and outputting the azimuth center point for the user to refer.
On the other hand, for a macro base station:
for example, the frequency band of a cell a corresponding to the macro base station is 800M/1800M/2100M, the frequency band of a cell B corresponding to the macro base station is 800M/1800M, the frequency band of a cell C corresponding to the macro base station is 800/2100M, and the frequency band of a cell D corresponding to the macro base station is 1800/2100M. Referring to fig. 5, fig. 5 schematically illustrates a multi-cell base station cell diagram according to an embodiment of the present application. As shown in fig. 5, one base station may correspond to a plurality of cells, each of which may be represented by a sector, and overlapping sectors represent a plurality of frequency bands of one cell. Referring to fig. 6, fig. 6 schematically illustrates a single-cell base station cell diagram according to an embodiment of the present application. As shown in fig. 6, a base station may correspond to a cell including multiple frequency bands, which may be represented as multiple overlapping sectors in the illustration.
Based on this, the preset screening rule includes the same-frequency-band screening and the limitation that the RSRP is greater than the preset power (such as-100 dBm), and the target grid is screened from each grid according to the preset screening rule, including: if the cell frequency band comprises 1800M, screening a grid with the frequency band of 1800M and the RSRP larger than preset power (such as-100 dBm) as a target grid; if the cell frequency band comprises 2100M but not 1800M, screening a grid with the frequency band of 2100M and the RSRP larger than preset power (such as-100 dBm) as a target grid; if the cell band includes a grid including only 800M, a grid with a frequency band of 800M and an RSRP greater than a predetermined power (e.g., -100dBm) is selected as a target grid.
Based on this, removing the noisy point grid in the target grid according to the clustering result comprises: and removing the noise point grids in the target grid according to the radius Eps-50 and the preset number minPts-5.
Based on this, the base station coordinate is determined according to the grid number and the grid center coordinate in each cluster of grids to be processed, and the method comprises the following steps: determining a specific grid corresponding to a preset RSRP (such as the maximum RSRP in a cluster of grids) in each cluster of grids to be processed, and if the number of the specific grids is 1, determining the longitude and latitude coordinates of the center point of the specific grid as base station coordinates (namely virtual site coordinates of a cell); if the number of the specific grids is 2, determining the midpoint of the longitude and latitude coordinates of the central points of the two specific grids as the coordinates of the base station; if the number of the specific grids is more than 2, extracting the clustering centers of the longitude and latitude coordinates of the central points of the specific grids, and determining the longitude and latitude coordinates of the clustering centers as the coordinates of the base station.
For example, referring to fig. 7 for multiple cells, fig. 7 schematically illustrates a diagram of multi-cell clustering according to an embodiment of the present application. As shown in fig. 7, different cells correspond to different clustering centers according to different grid clustering results, the clustering centers corresponding to the three cells are connected in pairs to obtain a triangle, and the midpoint (point a) of the triangle can be determined as the coordinates of the base station. Referring to fig. 8, fig. 8 schematically illustrates a single-cell clustering diagram according to an embodiment of the present application. As shown in fig. 8, the origin of the coordinate system is the base station location and is obtained by grid clustering of a single cell.
Based on this, for the spotlight class macro station cell, according to azimuth central point analysis calculation cell azimuth and output, including: and setting the azimuth angle of the cell to be 0 degree by taking the azimuth angle central point as a circle center and outputting. For the non-spotlight macro station cell, the cell azimuth is analyzed and calculated according to the azimuth center point and output, and the method comprises the following steps: if the base station coordinate is the azimuth center point, a coordinate system comprising an X axis and a Y axis is constructed by taking the base station coordinate as the center, and a Y ═ ax linear function taking an axis sampling point as scattered point information according to the coordinate system is determined; determining an included angle between the linear function and a preset direction (such as a due north direction in a map, and a preset area belonging to a certain area in the map) as a cell direction angle; wherein a is a constant. If the engineering coordinate is the azimuth center point, a coordinate system comprising an X axis and a Y axis is constructed by taking the engineering coordinate as the center, and a Y ═ ax linear function taking an axis sampling point as scattered point information according to the coordinate system is determined; and determining the included angle of the linear function and the due north direction in the map as the direction angle of the cell.
Therefore, by implementing the optional embodiment, the correct cell azimuth can be determined, so that relevant personnel can conveniently adjust the network coverage.
As an optional implementation manner, determining the azimuth center point according to the comparison result includes: if the comparison result shows that the distance between the base station coordinate and the engineering coordinate is greater than the preset distance, determining the base station coordinate as an azimuth center point; and if the comparison result shows that the distance is less than or equal to the preset distance, determining the engineering coordinate as the azimuth center point.
Specifically, engineering coordinates for representing the position of the base station may be acquired, and the distance between the engineering coordinates and the base station coordinates may be calculated. Furthermore, the method may further include: and calculating and outputting cell lobes so that related personnel can jointly judge whether the cell has cell reverse connection and cell handover conditions according to the cell lobes and the cell direction angles. The method specifically comprises the following steps: calculating 3db lobes on a cell according to a 3db lobe calculation formula TAN ((90-downtilt angle + vertical half-power angle/2) × pi/180) × station height on the cell; calculating the main lobe of the cell according to a main lobe calculation formula TAN ((90-lower dip angle) pi/180) station height of the cell; and calculating the lower 3db lobe of the cell according to a lower 3db lobe calculation formula TAN ((90-downtilt angle-vertical half-power angle/2) × pi/180) × station height.
Therefore, by implementing the optional embodiment, the correct cell coordinate can be determined through the engineering parameters, so that the cell azimuth angle can be determined according to the correct cell coordinate, the cell reverse connection and the handover judgment can be performed, and the rationality of the cell network coverage can be improved.
In step S330, a cell coverage result of each grid in the preset area is generated according to the cell corresponding to each sampling point in the sampling point set.
After step S330, the method may further include: and identifying each grid in the preset area according to the cell coverage result of each grid in the preset area so as to enable the grid identifications corresponding to the same cell coverage result to be the same, and further outputting the identified preset area for the user to perform reference analysis. Referring to fig. 9, fig. 9 schematically shows a cell coverage result according to an embodiment of the present application. As shown in fig. 9, in the preset area, different grids correspond to the same or different cell coverage results, and for different cell coverage results, the grids may be identified by different grid fillers, and the grids of the same grid filler may correspond to the same cell coverage result. The grid filler may be an icon, a color, a line, and the like, and in the embodiment of the present application, different lines are taken as examples and are not limited.
The grids of different cell coverage results can be identified in different ways
As an optional embodiment, generating a cell coverage result of each grid in a preset area according to a cell corresponding to each sampling point in the sampling point set includes: determining to screen a target grid from all grids according to a screening rule corresponding to a preset frequency band; determining the number of sampling points corresponding to different cells in a target grid and the total number of sampling points in the target grid; generating a cell coverage result of the target grid according to the ratio of the number of sampling points corresponding to different cells to the total number of sampling points; the cell coverage result comprises non-overlapping coverage or overlapping coverage with preset strength, and the preset strength is used for representing the overlapping coverage degree.
Specifically, different predetermined frequency bands (e.g., 800M, 1800M, 2100M, etc.) may correspond to different filtering rules that define the number of samples within a grid, the average RSRP, and the ratio of the number of samples to the total number of samples. In addition, generating a cell coverage result of the target grid according to a ratio of the number of sampling points corresponding to different cells to the total number of sampling points includes: calculating the ratio of the number of sampling points corresponding to different cells to the total number of sampling points; determining a cell corresponding to the number of the sampling points with the largest proportion as a main coverage cell; if the maximum occupation ratio is in a first preset range (for example, 50% -100%), judging that the cell coverage result of the grid is non-overlapping coverage; if the maximum occupation ratio is in a second preset range (e.g. 40% -50%), judging that the cell coverage result of the grid is light overlapping coverage; if the maximum occupation ratio is in a third preset range (for example, 20% -40%), judging that the cell coverage result of the grid is moderate overlapping coverage; and if the maximum ratio is in a fourth preset range (e.g., 0% -20%), determining that the cell coverage result of the grid is heavy overlapping coverage.
Therefore, by implementing the optional embodiment, compared with a coverage problem analysis mode which generally cannot form an overlapping coverage problem area and takes a cell as an analysis dimension, the grid dimension cell coverage analysis can be realized, and the fineness of a coverage analysis result is improved.
As an alternative embodiment, after positioning the grid to which each sample point in the set of sample points belongs in the rasterized preset region, the method further includes: determining the capacity corresponding to different cells according to the wireless resource utilization rate in each measurement data in the measurement data set; the capacity is used for representing the busy degree of a cell in one day; and carrying out differentiated marking on the cells in the preset area according to the corresponding capacities of different cells.
Specifically, determining the capacity corresponding to different cells according to the radio resource utilization rate in each measurement data in the measurement data set includes: acquiring the utilization rate of wireless resources in each measurement data in the measurement data set, and calculating the average utilization rate of the wireless resources (PDSCH PRBs) of each cell in a preset region in a resource scheduling period (TTI) according to the utilization rate of the wireless resources; calculating the number of times that the average value of the utilization rates of the radio resources (PDSCH PRBs) is greater than a preset threshold (e.g., 50%) according to a preset time granularity (e.g., hour, minute, second, day, etc.), and determining the number as the number of times of the cell overload hours, for example, the average value of the utilization rates of the radio resources (PDSCH PRBs) greater than 50% may be calculated; further, the number of cell overload hours may be determined as the capacity of the corresponding cell. Based on this, the above method may further include: and if the capacity is within the range of the preset threshold value, determining the cell corresponding to the capacity as a super-busy cell.
In addition, after the cells in the preset area are differentially marked according to the capacities corresponding to the different cells, the method may further include: and outputting the preset area marked with the differentiation for the reference of the user. Referring to fig. 10, fig. 10 schematically shows a cell capacity diagram according to an embodiment of the present application. As shown in fig. 10, for three cells of one base station in a preset region, the number of times that the average value of the utilization rate of the radio resource (PDSCH PRB) is greater than a preset threshold may be calculated according to a preset time granularity. According to the threshold value range of the corresponding times of different cells, distinguishing marks can be carried out on the cells so as to visually represent the busy and idle degrees of different cells in the preset region, and related personnel can be facilitated to carry out capacity expansion on the super-busy cells according to the distinguishing marks. In addition, the way of distinguishing the marks may be: the distinguishing marks are made by icons, colors, lines and/or the like, and the embodiments of the present application take different lines as examples but are not limited.
Therefore, by implementing the optional embodiment, relevant personnel can be helped to know the busy and idle degree of the cell more quickly and intuitively through the analyzed cell capacity, so that the capacity expansion of the super-busy cell by the relevant personnel is facilitated in time, and the network use experience of a user is improved.
As an alternative embodiment, after positioning the grid to which each sample point in the set of sample points belongs in the rasterized preset region, the method further includes: determining the current busy duration of each cell in a preset area; and calculating the current busy duration of each grid in the preset area according to the sampling point of each grid in the preset area, the cell corresponding to each sampling point in the sampling point set and the current busy duration of each cell in the preset area.
Specifically, determining the current busy duration of each cell in the preset area includes: and determining the current busy duration of each cell in the unit period according to the cell capacity. Based on this, according to the sampling point of each grid in the preset area, the cell corresponding to each sampling point in the sampling point set and the current busy duration of each cell in the preset area, calculating the current busy duration of each grid in the preset area, including: calculating a sampling point ratio (s/c) × (RSRP of cell n in one grid/RSRP of grid) corresponding to cell n according to the sampling points of each grid in the preset area and the cells corresponding to the sampling points in the sampling point set, wherein s and c may be self-defined constant weight values, for example, 1/1; further, calculating the current busy duration T of each grid according to an expression T ═ the number of sampling points of cell 1 + the number of sampling points of cell 2 + the number of busy times of cell 2 + … … + the number of sampling points of cell n + the number of busy times of cell n; wherein n is a positive integer.
Therefore, by implementing the optional embodiment, the busy duration of each grid can be analyzed, so that the busy duration of the cell can be further helped to be known by related personnel more quickly and intuitively, and the capacity of the super-busy cell can be expanded in time by the related personnel.
Referring to fig. 11, fig. 11 schematically illustrates a parameter presentation interface according to an embodiment of the present application. As shown in fig. 11, in the parameter presentation interface, when the user selects a target location in a preset area, longitude (108.036325) and latitude (22.575056) of a base station may be calculated from measurement data of a grid in which the target location is located, and presented in the parameter presentation interface. The user can realize the operations of copying, positioning and closing the longitude and latitude (108.036325) and the latitude (22.575056) by clicking the controls of copying, positioning or closing, and the like. Referring to fig. 12, fig. 12 schematically illustrates a parameter presentation interface according to another embodiment of the present application. As shown in fig. 12, the parameter detail can be displayed for the position in the preset area selected by the user in the parameter display interface. Referring to fig. 13, fig. 13 schematically illustrates an overlay result presentation interface according to an embodiment of the present application. As shown in fig. 13, the overlapping result presentation interface may be used to present grids under different cell coverage results through different grid marks, and the user may select a polygonal closed-loop area in the overlapping result presentation interface in a frame mode, so that the system further presents the overlapping result analysis for the polygonal closed-loop area, where the overlapping result analysis may include specific presentation and/or improvement suggestion for the cell coverage result.
Further, in the present exemplary embodiment, a measurement data analysis device is also provided. Referring to fig. 14, the measurement data analysis apparatus 1400 may include: a sample point acquisition unit 1401, a sample point positioning unit 1402, and a cell coverage result determination unit 1403, wherein:
a sampling point acquisition unit 1401, configured to determine sampling points corresponding to each measurement data in the measurement data set, and obtain a sampling point set;
a sampling point positioning unit 1402, configured to position, in a rasterized preset region, a grid to which each sampling point in the sampling point set belongs;
a cell coverage result determining unit 1403, configured to generate a cell coverage result of each grid in the preset area according to the cell corresponding to each sampling point in the sampling point set.
It can be seen that, by implementing the apparatus shown in fig. 14, coverage analysis can be performed with a finer-grained analysis dimension by using the rasterization result of the region, so that the accuracy of the coverage analysis result can be improved, and it is beneficial for related personnel to accurately locate the grid region with coverage problems, thereby facilitating adjustment of the coverage area of the cell network. In addition, the analysis accuracy of the network coverage problem can be further improved by rasterizing the region and positioning the grid of the sampling points.
In an exemplary embodiment of the present application, the sampling point positioning unit 1402 positions a grid to which each sampling point in the set of sampling points belongs in a rasterized preset region, including:
positioning the grid to which each sampling point in the sampling point set belongs according to the grid numbering rule and the rasterization parameter; wherein, the rasterization parameters at least comprise grid size and grid degree.
Therefore, by implementing the optional embodiment, the fine analysis of the measurement data can be realized through rasterization of the preset area, so that the content richness of the analysis result of the measurement data can be improved.
In an exemplary embodiment of the present application, the cell coverage result determining unit 1403 generates a cell coverage result of each grid in the preset area according to a cell corresponding to each sampling point in the sampling point set, including:
determining to screen a target grid from all grids according to a screening rule corresponding to a preset frequency band;
determining the number of sampling points corresponding to different cells in a target grid and the total number of sampling points in the target grid;
generating a cell coverage result of the target grid according to the ratio of the number of sampling points corresponding to different cells to the total number of sampling points;
the cell coverage result comprises non-overlapping coverage or overlapping coverage with preset strength, and the preset strength is used for representing the overlapping coverage degree.
Therefore, by implementing the optional embodiment, compared with a coverage problem analysis mode which generally cannot form an overlapping coverage problem area and takes a cell as an analysis dimension, the grid dimension cell coverage analysis can be realized, and the fineness of a coverage analysis result is improved.
In an exemplary embodiment of the present application, the apparatus further includes:
a grid screening unit (not shown) for screening a target grid from each grid according to a preset screening rule after the sampling point positioning unit positions the grid to which each sampling point in the sampling point set belongs in the rasterized preset region;
a clustering unit (not shown) for clustering the target grid and removing the noise point grid in the target grid according to the clustering result to obtain a multi-cluster grid to be processed;
a coordinate calculation unit (not shown) for determining coordinates of the base station according to the number of grids in each cluster of grids to be processed and grid center coordinates;
a position determining unit (not shown) for comparing the coordinates of the base station with the engineering coordinates and determining an azimuth center point according to the comparison result;
and an azimuth analysis unit (not shown) for analyzing and calculating the cell azimuth according to the azimuth center point and outputting the cell azimuth.
Therefore, by implementing the optional embodiment, the correct cell azimuth can be determined, so that relevant personnel can conveniently adjust the network coverage.
In an exemplary embodiment of the present application, the determining the azimuth center point according to the comparison result by the position determining unit includes:
if the comparison result shows that the distance between the base station coordinate and the engineering coordinate is greater than the preset distance, determining the base station coordinate as an azimuth center point;
and if the comparison result shows that the distance is less than or equal to the preset distance, determining the engineering coordinate as the azimuth center point.
Therefore, by implementing the optional embodiment, the correct cell coordinate can be determined through the engineering parameters, so that the cell azimuth angle can be determined according to the correct cell coordinate, the cell reverse connection and the handover judgment can be performed, and the rationality of the cell network coverage can be improved.
In an exemplary embodiment of the present application, the apparatus further includes:
a capacity calculating unit (not shown) configured to determine capacities corresponding to different cells according to radio resource utilization rates in each measurement data in the measurement data set after the sampling point positioning unit 1402 positions the grid to which each sampling point in the sampling point set belongs in the rasterized preset region; the capacity is used for representing the busy degree of a cell in one day;
a cell marking unit (not shown) for differentially marking cells in the preset area according to the corresponding capacities of different cells.
Therefore, by implementing the optional embodiment, relevant personnel can be helped to know the busy and idle degree of the cell more quickly and intuitively through the analyzed cell capacity, so that the capacity expansion of the super-busy cell by the relevant personnel is facilitated in time, and the network use experience of a user is improved.
In an exemplary embodiment of the present application, the apparatus further includes:
a busy duration calculation unit (not shown) configured to determine a current busy duration of each cell in the preset area after the sampling point positioning unit 1402 positions the grid to which each sampling point in the sampling point set belongs in the rasterized preset area; and calculating the current busy duration of each grid in the preset area according to the sampling point of each grid in the preset area, the cell corresponding to each sampling point in the sampling point set and the current busy duration of each cell in the preset area.
Therefore, by implementing the optional embodiment, the analyzed current busy duration of each grid can further help related personnel to know the busy and free degree of the cell faster and more intuitively, so that the capacity of the super-busy cell can be expanded in time by the related personnel.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the application. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
For details which are not disclosed in the embodiments of the apparatus of the present application, please refer to the embodiments of the method of analyzing measured data described above for the details which are not disclosed in the embodiments of the apparatus of the present application.
As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by an electronic device, cause the electronic device to implement the method described in the above embodiments.
It should be noted that the computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice in the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
Claims (10)
1. A method of analyzing measurement data, comprising:
determining sampling points corresponding to the measurement data in the measurement data set to obtain a sampling point set;
positioning a grid to which each sampling point in the sampling point set belongs in a rasterized preset region;
and generating a cell coverage result of each grid in the preset area according to the cell corresponding to each sampling point in the sampling point set.
2. The method of claim 1, wherein locating the grid to which each sample point in the set of sample points belongs in a pre-set area of rasterization comprises:
positioning the grid to which each sampling point in the sampling point set belongs according to the grid numbering rule and the rasterization parameter; wherein the rasterization parameters at least include a grid size and a grid degree.
3. The method of claim 1, wherein generating the cell coverage result of each grid in the preset area according to the cell corresponding to each sample point in the set of sample points comprises:
determining to screen a target grid from the grids according to a screening rule corresponding to a preset frequency band;
determining the number of sampling points corresponding to different cells in the target grid and the total number of sampling points in the target grid;
generating a cell coverage result of the target grid according to the ratio of the number of the sampling points corresponding to different cells to the total number of the sampling points;
the cell coverage result includes non-overlapping coverage or overlapping coverage with preset strength, and the preset strength is used for representing the degree of the overlapping coverage.
4. The method of claim 1, wherein after locating the grid to which each sample point in the set of sample points belongs in the pre-set area of rasterization, the method further comprises:
screening target grids from the grids according to a preset screening rule;
clustering the target grids and removing the noisy point grids in the target grids according to the clustering result to obtain a multi-cluster grid to be processed;
determining the coordinates of a base station according to the grid number and the grid center coordinates in each cluster of grids to be processed;
comparing the base station coordinates with the engineering coordinates, and determining an azimuth center point according to a comparison result;
and analyzing and calculating the azimuth angle of the cell according to the azimuth center point and outputting the azimuth angle.
5. The method of claim 4, wherein determining the azimuthal center point based on the comparison comprises:
if the comparison result shows that the distance between the base station coordinate and the engineering coordinate is greater than a preset distance, determining the base station coordinate as the azimuth center point;
if the comparison result shows that the distance is smaller than or equal to the preset distance, determining the engineering coordinate as the azimuth center point;
and checking the coordinate correctness of the cell according to the acquired engineering parameter data, and determining a cell azimuth angle according to a checking result to serve as a judgment basis for cell reversal and cell crossing.
6. The method of claim 1, wherein after locating the grid to which each sample point in the set of sample points belongs in the pre-set region of rasterization, the method further comprises:
determining the capacity corresponding to different cells according to the wireless resource utilization rate in each measurement data in the measurement data set; the capacity is used for representing the busy degree of a cell in one day;
and carrying out differentiated marking on the cells in the preset area according to the capacities corresponding to the different cells.
7. The method of claim 1, wherein after locating the grid to which each sample point in the set of sample points belongs in the pre-set region of rasterization, the method further comprises:
determining the current busy duration of each cell in the preset area;
and calculating the current busy duration of each grid in the preset area according to the sampling point of each grid in the preset area, the cell corresponding to each sampling point in the sampling point set and the current busy duration of each cell in the preset area.
8. A measurement data analysis apparatus, characterized by comprising:
the sampling point acquisition unit is used for determining sampling points corresponding to the measurement data in the measurement data set to obtain a sampling point set;
the sampling point positioning unit is used for positioning the grids to which the sampling points in the sampling point set belong in a rasterized preset region;
and the cell coverage result determining unit is used for generating a cell coverage result of each grid in the preset area according to the cell corresponding to each sampling point in the sampling point set.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of any one of claims 1 to 7.
10. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the method of any of claims 1-7 via execution of the executable instructions.
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Citations (5)
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| CN107580337A (en) * | 2016-07-05 | 2018-01-12 | 中兴通讯股份有限公司 | Hot spot area identification method and device |
| CN107623920A (en) * | 2016-07-15 | 2018-01-23 | 中兴通讯股份有限公司 | The determination methods and device of a kind of overlapping covering of wireless network |
| CN109548041A (en) * | 2017-09-22 | 2019-03-29 | 中国移动通信集团浙江有限公司 | A kind of wireless coverage analysis method and system |
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