CN113891378B - Method and device for calculating signal coverage of base station and calculating equipment - Google Patents
Method and device for calculating signal coverage of base station and calculating equipment Download PDFInfo
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Abstract
The embodiment of the invention relates to the technical field of computers, and discloses a method, a device and equipment for calculating a base station signal coverage range, wherein the method comprises the following steps: acquiring and preprocessing original measurement report data, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information; splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes; according to the longitude and latitude information, sampling points in the data to be processed fall on corresponding grids; and performing space fitting based on a space clustering algorithm according to the grids to form the coverage range of the wireless cell of the base station. By means of the method, the embodiment of the invention can truly calculate the coverage of the wireless cell of the base station through the actual sampling point clustering and combining with the traditional electromagnetic wave ray algorithm, and the accuracy is high.
Description
Technical Field
The embodiment of the invention relates to the technical field of computers, in particular to a method, a device and equipment for calculating a base station signal coverage range.
Background
In the mobile communication engineering design, the coverage of a base station is determined to be a key point and an important index for base station construction and network optimization. In the prior art, taking long term evolution (Long Term Evolution, LTE) as an example, the radio coverage is represented by a radio coverage radius, which can be determined by the following procedure: firstly, performing a base station remote test, and acquiring wireless parameters including uplink reference signal received power (Reference Signal Receiving Power, RSRP) and downlink signal-to-interference plus noise ratio (Signalto Interference plus Noise Ratio, SINR) at a dotting position in the remote process; next, respectively obtaining the data relationship between the wireless parameters and the coverage distance (i.e. the distance between the base station and the dotting position), and respectively fitting the functional relationship between the uplink RSRP parameter, the downlink SINR parameter and the coverage distance according to the data relationship: coverage distance=f (RSRP) and coverage distance=f (SINR); then, the function values f (RSRP) and f (SINR) are obtained from the uplink RSRP parameter value and the downlink SINR parameter value set by the operator and the above-mentioned functional relationship, and these two function values are compared, and the smaller function value is determined as the radio coverage radius.
The existing technical proposal is based on the cell coverage simulation of electromagnetic wave propagation algorithm, and can not remove the interference factors such as buildings, terrains and the like, and the obtained cell coverage is not accurate and complete enough.
Disclosure of Invention
In view of the above problems, embodiments of the present invention provide a method, an apparatus, and a computing device for computing a base station signal coverage, which overcome or at least partially solve the above problems.
According to an aspect of an embodiment of the present invention, there is provided a method for calculating a coverage area of a base station signal, the method including: acquiring and preprocessing original measurement report data, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information; splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes; according to the longitude and latitude information, sampling points in the data to be processed fall on corresponding grids; and performing space fitting based on a space clustering algorithm according to the grids to form the coverage range of the wireless cell of the base station.
In an alternative manner, the acquiring and preprocessing raw measurement report data includes: acquiring the original measurement report data acquired by a base station; carrying out big data analysis on the original measurement report data, and eliminating abnormal sampling point data; for partial non-critical data missing sampling point data, the existing data is utilized for correlation; and converting numerical values and regulating the whole data for the fields which are partially required to be processed.
In an optional manner, splitting or merging the files where the preprocessed original measurement report data is located by using a Java multithreading manner to form to-be-processed data of a plurality of files with preset sizes, where the to-be-processed data includes: merging files which are smaller than a preset size and comprise the preprocessed original measurement report data in a Java multithreading mode; when the file size of the preprocessed original measurement report data reaches a preset size, splitting the file, creating a new file, and forming the data to be processed of a plurality of files with the preset size.
In an optional manner, the dropping the sampling point in the data to be processed to the corresponding grid according to the longitude and latitude information includes: loading the files needing to be associated through the distributedcache characteristics of the measurement data; and carrying out trend-based machine learning on the data to be processed according to the longitude and latitude information, and dropping the sampling points in the data to be processed to the corresponding grids.
In an optional manner, the performing spatial fitting according to the grid based on a spatial clustering algorithm to form a coverage area of a wireless cell of a base station includes: extracting map elements, combining the grids according to the coverage range of the wireless cell of the same base station with the map elements, and performing space fitting based on a space clustering algorithm to form the coverage range of the wireless cell of the base station; and checking the cells of the plurality of base stations, and modifying the coverage range of the wireless cells of the base stations.
In an alternative, the method further comprises: and when the base station industrial parameters are changed, changing the coverage range of the wireless cell of the base station.
In an optional manner, when the base station parameter changes, changing the coverage of the wireless cell of the base station includes: if the base station angle is changed, the angle of the wireless cell is adjusted, a trend learning algorithm is adopted to compare the trend with the original coverage according to the original angle, and the coverage of the wireless cell of the base station is calculated; if the base station coordinates change, combining map elements according to a ray simulation model, and calculating the coverage of the wireless cell of the base station; if the power of the base station is changed, adopting a ray simulation model to perform trend analysis according to the original coverage, and calculating the coverage of the wireless cell of the base station; and integrating the wireless cells of the plurality of base stations with the peripheral change, and performing mutual check superposition and modifying the coverage range of the wireless cells of the base stations.
According to another aspect of an embodiment of the present invention, there is provided a computing device for a signal coverage of a base station, the device including: the data acquisition unit is used for acquiring original measurement report data and preprocessing the original measurement report data, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information; the file merging unit is used for splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes; the grid positioning unit is used for dropping sampling points in the data to be processed to corresponding grids according to the longitude and latitude information; and the space fitting unit is used for performing space fitting based on a space clustering algorithm according to the grids to form the coverage range of the wireless cell of the base station.
According to another aspect of an embodiment of the present invention, there is provided a computing device including: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is configured to store at least one executable instruction, where the executable instruction causes the processor to perform the steps of the method for calculating the signal coverage of the base station.
According to yet another aspect of the embodiments of the present invention, there is provided a computer storage medium having stored therein at least one executable instruction for causing the processor to perform the steps of the above-described method for calculating a base station signal coverage.
According to the embodiment of the invention, the original measurement report data is obtained and preprocessed, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information; splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes; according to the longitude and latitude information, sampling points in the data to be processed fall on corresponding grids; and space fitting is performed based on a space clustering algorithm according to the grids, so that the coverage area of the wireless cell of the base station is formed, the coverage area of the wireless cell of the base station can be calculated more truly through real sampling point clustering and combining with a traditional electromagnetic wave ray algorithm, and the accuracy is high.
The foregoing description is only an overview of the technical solutions of the embodiments of the present invention, and may be implemented according to the content of the specification, so that the technical means of the embodiments of the present invention can be more clearly understood, and the following specific embodiments of the present invention are given for clarity and understanding.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
fig. 1 is a flow chart illustrating a method for calculating a base station signal coverage according to an embodiment of the present invention;
fig. 2 shows a schematic diagram of a method for calculating a base station signal coverage area according to an embodiment of the present invention, where sampling points fall on corresponding grids;
fig. 3 is a schematic diagram showing a coverage area of a wireless cell of a base station for changing a calculation method of a signal coverage area of the base station according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a computing device for base station signal coverage according to an embodiment of the present invention;
FIG. 5 illustrates a schematic diagram of a computing device provided by an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Fig. 1 is a flow chart illustrating a method for calculating a base station signal coverage according to an embodiment of the present invention. The method for calculating the signal coverage of the base station is mainly applied to a server. As shown in fig. 1, the method for calculating the signal coverage of the base station includes:
step S11: raw measurement report data is acquired and preprocessed, wherein the raw measurement report data comprises a plurality of sampling points containing longitude and latitude information.
In particular, the raw measurement report (Measurement Report, MR) data acquired by the base station is acquired. In the embodiment of the invention, the coverage of the wireless cell of the base station is acquired by subsequently applying the mapreduce program according to the original measurement report data, and as the original measurement report data acquired by the base station has few available fields, partial fields need to be extracted by the mapreduce program and landed on a Hadoop distributed file system (Hadoop Distributed File System, HDFS) for later data flow, so that the later calculation performance can be improved.
In the embodiment of the invention, the original MR data is preprocessed, and the method mainly aims at the conditions of data missing, data abnormality and the like. And carrying out big data analysis on the original measurement report data, and removing abnormal sampling point data, wherein the method mainly combines the transmitting power and the direction angle in the wireless industrial parameter, and removes the flying spot which is too far so as not to influence the final graph. For the sampling point data with partial non-critical data missing, such as no base station coordinates, the existing data is utilized for correlation. And converting numerical values and regulating the whole data of the fields needing to be processed, such as time, dictionary values and the like.
In the embodiment of the invention, the processing data is stored in each folder of the HDFS in units of days. The data collected by the base station daily later can be used as daily gain data to supplement the existing data.
Step S12: splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes.
In the embodiment of the invention, since one file block (block) in mapreduce2.X is 256M, if there are too many fragmented files, one small file occupies one map, so that the machine performance is not fully exerted, and the processing speed is slowed down, and therefore, small file merging is performed on the preprocessed and distributed file including the preprocessed original measurement report data before the coverage task is defined. Specifically, merging files which are smaller than a preset size and comprise the preprocessed original measurement report data in a Java multithreading mode; when the file size of the preprocessed original measurement report data reaches a preset size, splitting the file, creating a new file, and forming the data to be processed of a plurality of files with the preset size. The preset size is preferably 256M. Files smaller than 256M are merged into one file, and when the file size reaches 256M, a new file is created, thereby reducing the impact of small files on performance.
Step S13: and according to the longitude and latitude information, the sampling points in the data to be processed fall to the corresponding grids.
Specifically, loading a file needing to be associated with the file through the distributedcache characteristic of the measurement data; and carrying out trend-based machine learning on the data to be processed according to the longitude and latitude information, and dropping the sampling points in the data to be processed to the corresponding grids. In the embodiment of the invention, some dictionary tables and base station ID tables are used in a mapreduce program for delineating the coverage of the wireless cell of the base station, and if a relevance operation is carried out during reduction (reduction), the risk of data inclination exists possibly, and as the data quantity of the dictionary tables is acceptable, the data needing the joint is distributed to the machine of each map by utilizing the distributedcache characteristic of MR data through a life cycle before the task of delineating the wireless cell of the base station is started, so that the condition that the task is blocked at 99% of the reduction because the data quantity of a certain base station is particularly large is avoided. After loading the file to be associated, as shown in fig. 2, trend-based machine learning training is performed on the data to be processed according to longitude and latitude information, and sampling points in the data to be processed fall on corresponding grids.
Step S14: and performing space fitting based on a space clustering algorithm according to the grids to form the coverage range of the wireless cell of the base station.
Specifically, extracting map elements, combining the grids according to the coverage range of the wireless cell of the same base station with the map elements, and performing space fitting based on a space clustering algorithm to form the coverage range of the wireless cell of the base station; and then checking the cells of the plurality of base stations with each other and modifying the coverage of the wireless cells of the base stations, so as to obtain the initialized coverage of the wireless cells of the base stations based on the original MR data. According to the embodiment of the invention, through xy coordinate information (namely longitude and latitude information) input by map, generating base station graphic data by taking the base station ID as a dimension, constructing a geometry factor object, and outputting the geometry factor object to a reduction process. And carrying out oracle batch warehousing operation on the generated base station graphic data, and carrying out landing on the processed data.
In the embodiment of the present invention, as shown in fig. 3, when the base station parameter changes, the coverage area of the base station wireless cell is changed. Specifically, if the base station angle is changed, the wireless cell angle is adjusted, a trend learning algorithm is adopted to compare the trend with the original coverage according to the original angle, and the coverage of the wireless cell of the base station is calculated. If the base station coordinates change, the coverage of the wireless cell of the base station is calculated according to the ray simulation model and combining with the map elements. If the power of the base station is changed, adopting a ray simulation model to perform trend analysis according to the original coverage, and calculating the coverage of the wireless cell of the base station. And finally, integrating the wireless cells of the plurality of base stations with the peripheral change, and performing mutual check superposition and modifying the coverage range of the wireless cells of the base stations. The ray simulation model may be any existing ray simulation model, such as a two-path (two-path) model, a ten-ray model, a general ray tracking model, a cross wave ray tracking model, and the like, which are not limited herein.
According to the embodiment of the invention, the sampling points in the sector are accumulated based on the wireless Measurement Report (MR), the sampling points are clustered according to longitude and latitude of the sampling points, and the coverage area of the base station wireless cell is drawn and simulated through a specific algorithm. The main difference with the traditional measurement method is that the coverage area of the wireless cell of the base station is drawn through the longitude and latitude clustering of the real sampling points, and the interference factors such as buildings, terrains and the like can be removed through the real sampling point clustering and the traditional electromagnetic wave ray algorithm, so that the coverage area of the wireless cell can be calculated more truly.
According to the embodiment of the invention, the original measurement report data is obtained and preprocessed, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information; splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes; according to the longitude and latitude information, sampling points in the data to be processed fall on corresponding grids; and space fitting is performed based on a space clustering algorithm according to the grids, so that the coverage area of the wireless cell of the base station is formed, the coverage area of the wireless cell of the base station can be calculated more truly through real sampling point clustering and combining with a traditional electromagnetic wave ray algorithm, and the accuracy is high.
Fig. 4 is a schematic structural diagram of a computing device for base station signal coverage according to an embodiment of the present invention. As shown in fig. 4, the apparatus for calculating the signal coverage of the base station includes: a data acquisition unit 401, a file merging unit 402, a grid positioning unit 403, and a space fitting unit 404. Wherein:
the data acquisition unit 401 is configured to acquire and pre-process raw measurement report data, where the raw measurement report data includes a plurality of sampling points including latitude and longitude information; the file merging unit 402 is configured to split or merge the files where the preprocessed original measurement report data is located by using a Java multithreading manner, so as to form to-be-processed data of a plurality of files with preset sizes; the grid positioning unit 403 is configured to drop the sampling point in the data to be processed to a corresponding grid according to the latitude and longitude information; the spatial fitting unit 404 is configured to perform spatial fitting according to the grid based on a spatial clustering algorithm, so as to form a coverage area of a wireless cell of the base station.
In an alternative way, the data acquisition unit 401 is configured to: acquiring the original measurement report data acquired by a base station; carrying out big data analysis on the original measurement report data, and eliminating abnormal sampling point data; for partial non-critical data missing sampling point data, the existing data is utilized for correlation; and converting numerical values and regulating the whole data for the fields which are partially required to be processed.
In an alternative way, the file merging unit 402 is configured to: merging files which are smaller than a preset size and comprise the preprocessed original measurement report data in a Java multithreading mode; when the file size of the preprocessed original measurement report data reaches a preset size, splitting the file, creating a new file, and forming the data to be processed of a plurality of files with the preset size.
In an alternative way, the grid positioning unit 403 is configured to: loading the files needing to be associated through the distributedcache characteristics of the measurement data; and carrying out trend-based machine learning on the data to be processed according to the longitude and latitude information, and dropping the sampling points in the data to be processed to the corresponding grids.
In an alternative way, the spatial fitting unit 404 is configured to: extracting map elements, combining the grids according to the coverage range of the wireless cell of the same base station with the map elements, and performing space fitting based on a space clustering algorithm to form the coverage range of the wireless cell of the base station; and checking the cells of the plurality of base stations, and modifying the coverage range of the wireless cells of the base stations.
In an alternative way, the spatial fitting unit 404 is further configured to: and when the base station industrial parameters are changed, changing the coverage range of the wireless cell of the base station.
In an alternative way, the spatial fitting unit 404 is further configured to: if the base station angle is changed, the angle of the wireless cell is adjusted, a trend learning algorithm is adopted to compare the trend with the original coverage according to the original angle, and the coverage of the wireless cell of the base station is calculated; if the base station coordinates change, combining map elements according to a ray simulation model, and calculating the coverage of the wireless cell of the base station; if the power of the base station is changed, adopting a ray simulation model to perform trend analysis according to the original coverage, and calculating the coverage of the wireless cell of the base station; and integrating the wireless cells of the plurality of base stations with the peripheral change, and performing mutual check superposition and modifying the coverage range of the wireless cells of the base stations.
According to the embodiment of the invention, the original measurement report data is obtained and preprocessed, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information; splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes; according to the longitude and latitude information, sampling points in the data to be processed fall on corresponding grids; and space fitting is performed based on a space clustering algorithm according to the grids, so that the coverage area of the wireless cell of the base station is formed, the coverage area of the wireless cell of the base station can be calculated more truly through real sampling point clustering and combining with a traditional electromagnetic wave ray algorithm, and the accuracy is high.
The embodiment of the invention provides a non-volatile computer storage medium, which stores at least one executable instruction, and the computer executable instruction can execute the method for calculating the base station signal coverage in any of the method embodiments.
The executable instructions may be particularly useful for causing a processor to:
acquiring and preprocessing original measurement report data, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information;
splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes;
according to the longitude and latitude information, sampling points in the data to be processed fall on corresponding grids;
and performing space fitting based on a space clustering algorithm according to the grids to form the coverage range of the wireless cell of the base station.
In one alternative, the executable instructions cause the processor to:
acquiring the original measurement report data acquired by a base station;
carrying out big data analysis on the original measurement report data, and eliminating abnormal sampling point data;
for partial non-critical data missing sampling point data, the existing data is utilized for correlation;
and converting numerical values and regulating the whole data for the fields which are partially required to be processed.
In one alternative, the executable instructions cause the processor to:
merging files which are smaller than a preset size and comprise the preprocessed original measurement report data in a Java multithreading mode;
when the file size of the preprocessed original measurement report data reaches a preset size, splitting the file, creating a new file, and forming the data to be processed of a plurality of files with the preset size.
In one alternative, the executable instructions cause the processor to:
loading the files needing to be associated through the distributedcache characteristics of the measurement data;
and carrying out trend-based machine learning on the data to be processed according to the longitude and latitude information, and dropping the sampling points in the data to be processed to the corresponding grids.
In one alternative, the executable instructions cause the processor to:
extracting map elements, combining the grids according to the coverage range of the wireless cell of the same base station with the map elements, and performing space fitting based on a space clustering algorithm to form the coverage range of the wireless cell of the base station;
and checking the cells of the plurality of base stations, and modifying the coverage range of the wireless cells of the base stations.
In one alternative, the executable instructions cause the processor to:
and when the base station industrial parameters are changed, changing the coverage range of the wireless cell of the base station.
In one alternative, the executable instructions cause the processor to:
if the base station angle is changed, the angle of the wireless cell is adjusted, a trend learning algorithm is adopted to compare the trend with the original coverage according to the original angle, and the coverage of the wireless cell of the base station is calculated;
if the base station coordinates change, combining map elements according to a ray simulation model, and calculating the coverage of the wireless cell of the base station;
if the power of the base station is changed, adopting a ray simulation model to perform trend analysis according to the original coverage, and calculating the coverage of the wireless cell of the base station;
and integrating the wireless cells of the plurality of base stations with the peripheral change, and performing mutual check superposition and modifying the coverage range of the wireless cells of the base stations.
According to the embodiment of the invention, the original measurement report data is obtained and preprocessed, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information; splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes; according to the longitude and latitude information, sampling points in the data to be processed fall on corresponding grids; and space fitting is performed based on a space clustering algorithm according to the grids, so that the coverage area of the wireless cell of the base station is formed, the coverage area of the wireless cell of the base station can be calculated more truly through real sampling point clustering and combining with a traditional electromagnetic wave ray algorithm, and the accuracy is high.
An embodiment of the present invention provides a computer program product comprising a computer program stored on a computer storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the method for calculating a base station signal coverage in any of the method embodiments described above.
The executable instructions may be particularly useful for causing a processor to:
acquiring and preprocessing original measurement report data, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information;
splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes;
according to the longitude and latitude information, sampling points in the data to be processed fall on corresponding grids;
and performing space fitting based on a space clustering algorithm according to the grids to form the coverage range of the wireless cell of the base station.
In one alternative, the executable instructions cause the processor to:
acquiring the original measurement report data acquired by a base station;
carrying out big data analysis on the original measurement report data, and eliminating abnormal sampling point data;
for partial non-critical data missing sampling point data, the existing data is utilized for correlation;
and converting numerical values and regulating the whole data for the fields which are partially required to be processed.
In one alternative, the executable instructions cause the processor to:
merging files which are smaller than a preset size and comprise the preprocessed original measurement report data in a Java multithreading mode;
when the file size of the preprocessed original measurement report data reaches a preset size, splitting the file, creating a new file, and forming the data to be processed of a plurality of files with the preset size.
In one alternative, the executable instructions cause the processor to:
loading the files needing to be associated through the distributedcache characteristics of the measurement data;
and carrying out trend-based machine learning on the data to be processed according to the longitude and latitude information, and dropping the sampling points in the data to be processed to the corresponding grids.
In one alternative, the executable instructions cause the processor to:
extracting map elements, combining the grids according to the coverage range of the wireless cell of the same base station with the map elements, and performing space fitting based on a space clustering algorithm to form the coverage range of the wireless cell of the base station;
and checking the cells of the plurality of base stations, and modifying the coverage range of the wireless cells of the base stations.
In one alternative, the executable instructions cause the processor to:
and when the base station industrial parameters are changed, changing the coverage range of the wireless cell of the base station.
In one alternative, the executable instructions cause the processor to:
if the base station angle is changed, the angle of the wireless cell is adjusted, a trend learning algorithm is adopted to compare the trend with the original coverage according to the original angle, and the coverage of the wireless cell of the base station is calculated;
if the base station coordinates change, combining map elements according to a ray simulation model, and calculating the coverage of the wireless cell of the base station;
if the power of the base station is changed, adopting a ray simulation model to perform trend analysis according to the original coverage, and calculating the coverage of the wireless cell of the base station;
and integrating the wireless cells of the plurality of base stations with the peripheral change, and performing mutual check superposition and modifying the coverage range of the wireless cells of the base stations.
According to the embodiment of the invention, the original measurement report data is obtained and preprocessed, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information; splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes; according to the longitude and latitude information, sampling points in the data to be processed fall on corresponding grids; and space fitting is performed based on a space clustering algorithm according to the grids, so that the coverage area of the wireless cell of the base station is formed, the coverage area of the wireless cell of the base station can be calculated more truly through real sampling point clustering and combining with a traditional electromagnetic wave ray algorithm, and the accuracy is high.
FIG. 5 illustrates a schematic diagram of a computing device according to an embodiment of the present invention, and the embodiment of the present invention is not limited to the specific implementation of the device.
As shown in fig. 5, the computing device may include: a processor 502, a communication interface (Communications Interface) 504, a memory 506, and a communication bus 508.
Wherein: processor 502, communication interface 504, and memory 506 communicate with each other via communication bus 508. A communication interface 504 for communicating with network elements of other devices, such as clients or other servers. The processor 502 is configured to execute the program 510, and may specifically perform relevant steps in the above-mentioned embodiment of the method for calculating the signal coverage of the base station.
In particular, program 510 may include program code including computer-operating instructions.
The processor 502 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The device includes one or each processor, which may be the same type of processor, such as one or each CPU; but may also be different types of processors such as one or each CPU and one or each ASIC.
A memory 506 for storing a program 510. Memory 506 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
The program 510 may be specifically operable to cause the processor 502 to:
acquiring and preprocessing original measurement report data, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information;
splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes;
according to the longitude and latitude information, sampling points in the data to be processed fall on corresponding grids;
and performing space fitting based on a space clustering algorithm according to the grids to form the coverage range of the wireless cell of the base station.
In an alternative, the program 510 causes the processor to:
acquiring the original measurement report data acquired by a base station;
carrying out big data analysis on the original measurement report data, and eliminating abnormal sampling point data;
for partial non-critical data missing sampling point data, the existing data is utilized for correlation;
and converting numerical values and regulating the whole data for the fields which are partially required to be processed.
In an alternative, the program 510 causes the processor to:
merging files which are smaller than a preset size and comprise the preprocessed original measurement report data in a Java multithreading mode;
when the file size of the preprocessed original measurement report data reaches a preset size, splitting the file, creating a new file, and forming the data to be processed of a plurality of files with the preset size.
In an alternative, the program 510 causes the processor to:
loading the files needing to be associated through the distributedcache characteristics of the measurement data;
and carrying out trend-based machine learning on the data to be processed according to the longitude and latitude information, and dropping the sampling points in the data to be processed to the corresponding grids.
In an alternative, the program 510 causes the processor to:
extracting map elements, combining the grids according to the coverage range of the wireless cell of the same base station with the map elements, and performing space fitting based on a space clustering algorithm to form the coverage range of the wireless cell of the base station;
and checking the cells of the plurality of base stations, and modifying the coverage range of the wireless cells of the base stations.
In an alternative, the program 510 causes the processor to:
and when the base station industrial parameters are changed, changing the coverage range of the wireless cell of the base station.
In an alternative, the program 510 causes the processor to:
if the base station angle is changed, the angle of the wireless cell is adjusted, a trend learning algorithm is adopted to compare the trend with the original coverage according to the original angle, and the coverage of the wireless cell of the base station is calculated;
if the base station coordinates change, combining map elements according to a ray simulation model, and calculating the coverage of the wireless cell of the base station;
if the power of the base station is changed, adopting a ray simulation model to perform trend analysis according to the original coverage, and calculating the coverage of the wireless cell of the base station;
and integrating the wireless cells of the plurality of base stations with the peripheral change, and performing mutual check superposition and modifying the coverage range of the wireless cells of the base stations.
According to the embodiment of the invention, the original measurement report data is obtained and preprocessed, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information; splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes; according to the longitude and latitude information, sampling points in the data to be processed fall on corresponding grids; and space fitting is performed based on a space clustering algorithm according to the grids, so that the coverage area of the wireless cell of the base station is formed, the coverage area of the wireless cell of the base station can be calculated more truly through real sampling point clustering and combining with a traditional electromagnetic wave ray algorithm, and the accuracy is high.
The algorithms or displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems may also be used with the teachings herein. The required structure for a construction of such a system is apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It will be appreciated that the teachings of the present invention described herein may be implemented in a variety of programming languages, and the above description of specific languages is provided for disclosure of enablement and best mode of the present invention.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the above description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the intention that: i.e., the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features but not others included in other embodiments, 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 can 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 use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specifically stated.
Claims (8)
1. A method for calculating signal coverage of a base station, the method comprising:
acquiring and preprocessing original measurement report data, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information;
splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes;
and dropping sampling points in the data to be processed to a corresponding grid according to the longitude and latitude information, wherein the method comprises the following steps: loading the files needing to be associated through the distributedcache characteristics of the measurement data; performing trend-based machine learning on the data to be processed according to the longitude and latitude information, and falling the sampling points in the data to be processed to corresponding grids;
performing space fitting based on a space clustering algorithm according to the grid to form coverage of a base station wireless cell, including: extracting map elements, combining the grids according to the coverage range of the wireless cell of the same base station with the map elements, and performing space fitting based on a space clustering algorithm to form the coverage range of the wireless cell of the base station; and checking the cells of the plurality of base stations, and modifying the coverage range of the wireless cells of the base stations.
2. The method of claim 1, wherein the acquiring and preprocessing raw measurement report data comprises:
acquiring the original measurement report data acquired by a base station;
carrying out big data analysis on the original measurement report data, and eliminating abnormal sampling point data;
for partial non-critical data missing sampling point data, the existing data is utilized for correlation;
and converting numerical values and regulating the whole data for the fields which are partially required to be processed.
3. The method according to claim 1, wherein splitting or merging the files where the preprocessed original measurement report data is located by Java multithreading to form the to-be-processed data of a plurality of files with preset sizes, includes:
merging files which are smaller than a preset size and comprise the preprocessed original measurement report data in a Java multithreading mode;
when the file size of the preprocessed original measurement report data reaches a preset size, splitting the file, creating a new file, and forming the data to be processed of a plurality of files with the preset size.
4. The method according to claim 1, wherein the method further comprises:
and when the base station industrial parameters are changed, changing the coverage range of the wireless cell of the base station.
5. The method of claim 1, wherein changing the base station radio cell coverage when the base station parameter changes comprises:
if the base station angle is changed, the angle of the wireless cell is adjusted, a trend learning algorithm is adopted to compare the trend with the original coverage according to the original angle, and the coverage of the wireless cell of the base station is calculated;
if the base station coordinates change, combining map elements according to a ray simulation model, and calculating the coverage of the wireless cell of the base station;
if the power of the base station is changed, adopting a ray simulation model to perform trend analysis according to the original coverage, and calculating the coverage of the wireless cell of the base station;
and integrating the wireless cells of the plurality of base stations with the peripheral change, and performing mutual check superposition and modifying the coverage range of the wireless cells of the base stations.
6. A computing device for base station signal coverage, the device comprising:
the data acquisition unit is used for acquiring original measurement report data and preprocessing the original measurement report data, wherein the original measurement report data comprises a plurality of sampling points containing longitude and latitude information;
the file merging unit is used for splitting or merging the files where the preprocessed original measurement report data are located in a Java multithreading mode to form to-be-processed data of a plurality of files with preset sizes;
the grid positioning unit is used for dropping sampling points in the data to be processed to a corresponding grid according to the longitude and latitude information, and comprises the following steps: loading the files needing to be associated through the distributedcache characteristics of the measurement data; performing trend-based machine learning on the data to be processed according to the longitude and latitude information, and falling the sampling points in the data to be processed to corresponding grids;
the space fitting unit is used for performing space fitting based on a space clustering algorithm according to the grid to form coverage of a base station wireless cell, and comprises the following steps: extracting map elements, combining the grids according to the coverage range of the wireless cell of the same base station with the map elements, and performing space fitting based on a space clustering algorithm to form the coverage range of the wireless cell of the base station; and checking the cells of the plurality of base stations, and modifying the coverage range of the wireless cells of the base stations.
7. A computing device, comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is configured to store at least one executable instruction that causes the processor to perform the steps of the method for calculating signal coverage of a base station according to any one of claims 1-5.
8. A computer storage medium having stored therein at least one executable instruction for causing a processor to perform the steps of the method of calculating base station signal coverage according to any one of claims 1-5.
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