CN104602271B - The generation method and device of problem area in a kind of coverage optimization - Google Patents
The generation method and device of problem area in a kind of coverage optimization Download PDFInfo
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Abstract
The present invention provides the generation methods and device of problem area in a kind of coverage optimization.The invention belongs to wireless communication technology fields.The generation method of problem area in the coverage optimization, including：Obtain the sampling point information in coverage optimization；Sampling point information progress grid is summarized；Summarized according to the grid and generates problem area figure layer.The repetition being likely to occur when said program solves the problems, such as to count using sampled point judges or fails to judge, by carrying out grid aggregation process to sampling point information, problem area can be accurately generated, and the GIS that can intuitively carry out zone boundary is rendered, and facilitates the quick orientation problem region of technical staff.
Description
Technical field
The present invention relates to wireless communication technology field, more particularly in a kind of coverage optimization the generation method of problem area and
Device.
Background technology
In current wireless communication technique, coverage optimization is particularly important in wireless optimization, frequently with sweeping in coverage optimization
Frequency is not influenced according to as optimum data source this is because frequency sweep data are high to the analytical sensitivity of signal by parameter, adjacent area,
The coverage condition of true reflection wireless signal.It is more the covering for analyzing network when carrying out coverage optimization with frequency sweep data
Situation, orientation problem region, weak overlay area, high overlapping coverage region etc..
Frequency sweep data are all the statistical reports as unit of sampled point at present, when carrying out the analysis of problem area, and
It is for statistical analysis as unit of sampled point, usually according to timing separation continuous sampling point, filter out continuous problem sampling
Point carries out classification statistics.Such as the analysis to weak covering section, the weak continuous sampling point of statistical signal level on time dimension,
These sampling point sets are subjected to classification number.
And there are following problems using sampled point statistical for the positioning of present problems section.
1）Statistical result is often not accurate enough
The problem of being carried out with sampled point statistical section analysis, due to being to report timing separation sampled point according to sampled point
It is whether continuous, it is easy to be influenced by the fluctuation and retest of signal measurements, the statistics in problem section is caused to be susceptible to
It fails to judge or repeats.
2）Rendering result is not intuitive enough
Since sampled point is in GIS（Geographic information system）It is to be shown as a point, therefore, problem according to longitude and latitude when rendering
The GIS in region is rendered, be typically shown as groups of samples at series of discrete point set, when multiple problem areas global renders
It is not intuitive enough.
3）It needs manually to carry out region delineation
When being rendered due to problem area, be shown as groups of samples at series of discrete point set, need manually to go delineation each
A problem area boundary, it is not smart enough.
Invention content
The technical problem to be solved in the present invention is to provide the generation methods and device of problem area in a kind of coverage optimization, lead to
It crosses and grid aggregation process is carried out to sampling point information, problem area can be accurately generated, and can intuitively carry out regional edge
The GIS on boundary is rendered, and facilitates the quick orientation problem region of technical staff.
In order to solve the above-mentioned technical problem, the embodiment of the present invention provides a kind of generation side of problem area in coverage optimization
Method, including：
Obtain the sampling point information in coverage optimization；
Sampling point information progress grid is summarized；
Summarized according to the grid and generates problem area figure layer.
Further, the step of sampling point information obtained in coverage optimization is specially：From the frequency sweep data of load
It is middle to obtain the sampling point information.
The generation method of problem area in the coverage optimization, wherein the grid be thing, north and south respectively across it is default away from
From three-dimensional sphere region.
Further, the specific steps that sampling point information progress grid is summarized include：
The longitude and latitude of the sampling point information is converted into grid index；
Grid is carried out to the identical sampled point of the grid index to summarize.
Further, the grid index format is：It compiles in the UTM longitudes area latitudinal regions number+UTM number+MGRS longitudes area
Number latitudinal regions+MGRS, which number+normalizing MGRS longitudes east to bias+and normalize MGRS longitudes north, biases the+the first grid precision,
In,
Normalize MGRS longitudes east biasing=int（MGRS longitudes east biases the/the first grid precision）；
Normalize MGRS longitudes north biasing=int（MGRS longitudes north biases the/the first grid precision）.
The generation method of problem area in the coverage optimization, wherein the grid, which summarizes, to be identified according to frequency/base station
Each information that the identical sampled point of the grid index includes is carried out average grid and summarized by code/scrambler/peripheral hardware interconnection standard.
Further, described the step of summarizing generation problem area figure layer according to the grid, includes：
Screen the grid summarize generation there are the grid collection of covering problem；
The grid collection there are covering problem is subjected to classification intersection, generates problem area collection；
Grid region range determined by grid index in each problem area concentrated to described problem region carries out
Region extends out；
Raster map layer is generated according to the grid index extended out；
Merge the raster map layer according to grid index value and generates problem area figure layer.
The generation method of problem area in the coverage optimization, wherein it is described generate problem area collection specific method be：
Judge if two grid centers are smaller than or equal to X the first grid precision for there are the grid collection of covering problem
The two grids belong to the same problem area, wherein X is the constant more than 1.
Further, grid determined by the grid index in each problem area concentrated to described problem region
Regional extent carries out region the step of extending out and is specially：
Normalization MGRS longitudes east after extending out bias=normalize MGRS longitudes east biasing-(（X-1）/ 2) the * the first grid
Precision-Y；
Normalization MGRS longitudes north after extending out bias=normalize MGRS longitudes north biasing-(（X-1）/ 2) the * the first grid
Precision-Y；
Second grid precision=X* the first grid precision+2*Y；
Wherein X is the grid length of side number for being more than 1 in problem area decision rule, and the value of Y is the constant more than 0.
The device of problem area is generated in the coverage optimization, including：
Acquisition module, for obtaining the sampling point information in coverage optimization；
Analysis module, for summarizing sampling point information progress grid；
Generation module generates problem area figure layer for summarizing according to the grid.
Further, the acquisition module obtains the sampling point information from the frequency sweep data of load.
Wherein, the grid is the three-dimensional sphere region that pre-determined distance is respectively crossed in thing, north and south.
Further, the analysis module includes：
Convert module, for the longitude and latitude of the sampling point information to be converted into grid index；
Summarizing module summarizes for carrying out grid to the identical sampled point of the grid index.
Further, the grid index format is：It compiles in the UTM longitudes area latitudinal regions number+UTM number+MGRS longitudes area
Number latitudinal regions+MGRS, which number+normalizing MGRS longitudes east to bias+and normalize MGRS longitudes north, biases the+the first grid precision,
In,
Normalize MGRS longitudes east biasing=int（MGRS longitudes east biases the/the first grid precision）；
Normalize MGRS longitudes north biasing=int（MGRS longitudes north biases the/the first grid precision）.
Wherein, the summarizing module according to frequency/base station identification code/scrambler/peripheral hardware interconnection standard by the grid index
Each information that identical sampled point includes carries out average grid and summarizes.
Further, the generation module includes：
Screening module, for screen the grid summarize generation there are the grid collection of covering problem；
Intersection module of classifying generates problem area for the grid collection there are covering problem to be carried out classification intersection
Collection；
Module is extended out, grid determined by the grid index in each problem area for being concentrated to described problem region
Regional extent carries out region and extends out；
Figure layer generation module, the grid index for being extended out according to generate raster map layer；
Area generation module generates problem area figure layer for merging the raster map layer according to grid index value.
Further, the classification intersection module is for there are the grid collection of covering problem, if between two grid centers
Away from less than or equal to X the first grid precision, then judge that the two grids belong to the same problem area；Wherein, X is more than 1
Constant.
Further, described to extend out module foundation：
Normalization MGRS longitudes east after extending out bias=normalize MGRS longitudes east biasing-(（X-1）/ 2) the * the first grid
Precision-Y；
Normalization MGRS longitudes north after extending out bias=normalize MGRS longitudes north biasing-(（X-1）/ 2) the * the first grid
Precision-Y；
Second grid precision=X* the first grid precision+2*Y；
Wherein X is the grid length of side number for being more than 1 in problem area decision rule, and the value of Y is the constant more than 0；
Grid region range determined by grid index in each problem area concentrated to described problem region carries out
Region extends out.
The above-mentioned technical proposal of the present invention has the beneficial effect that：
In said program, problem area can be accurately generated, and the GIS that can intuitively carry out zone boundary is rendered,
Facilitate the quick orientation problem region of technical staff.
Description of the drawings
Fig. 1 is the overview flow chart of the method for the present invention；
Fig. 2 is the problem Area generation flow chart of the present invention.
Specific implementation mode
To keep the technical problem to be solved in the present invention, technical solution and advantage clearer, below in conjunction with attached drawing and tool
Body embodiment is described in detail.
The problem of present invention is directed to the existing repetition judgement being likely to occur when being counted using sampled point or failed to judge, provides
The generation method and device of problem area in a kind of coverage optimization can by carrying out grid aggregation process to sampling point information
Problem area is accurately generated, and the GIS that can intuitively carry out zone boundary is rendered, and is facilitated technical staff and is quickly positioned
Problem area.
As shown in Figure 1, in a kind of coverage optimization of the embodiment of the present invention problem area generation method, including：
Step 10, the sampling point information in coverage optimization is obtained；
Step 20, sampling point information progress grid is summarized；
Step 30, summarized according to the grid and generate problem area figure layer.
It should be noted that the grid is the three-dimensional sphere region that pre-determined distance is respectively crossed in thing, north and south.
Above-described embodiment can accurately generate problem area by carrying out grid aggregation process to sampling point information.
In another embodiment of the present invention, the step 10 is specially：The sampling is obtained from the frequency sweep data of load
Point information.It should be noted that the step 10 is to implement the basis of entire method.
In another embodiment of the present invention, the step 20 specifically includes：
Step 21, the longitude and latitude of the sampling point information is converted into grid index；
Step 22, grid is carried out to the identical sampled point of the grid index to summarize.
Wherein, the specific conversion method from the sampled point to grid index is：The latitude and longitude coordinates of sampled point are converted
For Military Grid coordinate, grid precision is then recycled to normalize Military Grid coordinate to grid index.
It is as follows to the above conversion method concrete example：
Here with based on transverse Mercator projection（UTM）Military Grid referential（MGRS）To divide grid zone
The specific format in domain, Military Grid coordinate is：The UTM longitudes area latitudinal regions number+UTM number+MGRS longitudes area number+MGRS latitudes
The biasing of area number+MGRS longitudes east biasing+MGRS longitudes north is spent, for example, latitude and longitude coordinates（110.3456,31.2468）Conversion
It is 49RDQ3768757138 for Military Grid coordinate, wherein 49 number for the longitude area of UTM, R numbers for the latitudinal regions UTM, and D is
MGRS longitudes area numbers, and Q numbers for the latitudinal regions MGRS, and 37687 bias for MGRS longitudes east, and 57138 bias for MGRS longitudes north,
Transformed Military Grid coordinate shares 15 characters, and precision is 1 meter.The grid index is to be based on militarization grid coordinate
Definition, the grid index format is：Normalize Military Grid coordinate-grid precision.Specially：UTM longitudes area number+
The latitudinal regions UTM number+MGRS longitudes area, which numbers the latitudinal regions number+MGRS ,+normalizing MGRS longitudes east to bias+normalizes MGRS warps
The+the first grid precision of degree north biasing, wherein
Normalize MGRS longitudes east biasing=int（MGRS longitudes east biases the/the first grid precision）；
Normalize MGRS longitudes north biasing=int（MGRS longitudes north biases the/the first grid precision）.
Such as：Latitude and longitude coordinates（110.3456,31.2468）The sampled point gone out, the grid rope after being converted with 50 meters of precision
Be cited as 49RDQ07531142-50, the grid index after being converted with 100 meters of precision is 49RDQ376571-100, it is above only with
Illustrate for 50 and 100 two grid precision, finally it should be noted that any satisfactory grid precision belongs to the present invention's
Protection domain.
The conversion that sampled point longitude and latitude and grid index can easily be carried out according to above-mentioned reduction formula, it is identical to indexing
Sampled point is summarized, and ensures the uniqueness for summarizing rear grid region, eliminating sample point data, there are brought when retest
Influence.Wherein frequency sweep sampled point is according to frequency/base station identification code when progress grid summarizes（BSIC）/ scrambler/peripheral hardware is mutual
Connection standard（PCI）Each information that the identical sampled point of the grid index includes is carried out average grid to summarize.
It is the generation of problem area after having carried out grid and having summarized.In another embodiment of the present invention, the step 30
Including：
Step 31, screen the grid summarize generation there are the grid collection of covering problem；
Step 32, the grid collection there are covering problem is subjected to classification intersection, generates problem area collection；
Step 33, grid region model determined by the grid index in each problem area concentrated to described problem region
Progress region is enclosed to extend out；
Step 34, raster map layer is generated according to the grid index extended out；
Step 35, the raster map layer is merged according to grid index value and generates problem area figure layer.
Wherein, screen that described there are the grid collection of covering problem, those skilled in the art in step 31 according to judgment condition
It should be understood that the judgment condition and by the judgment condition screening there are the specific sides of the grid collection of covering problem
Method is not described in detail herein.
It should be noted that the decision rule of the problems in described step 32 region collection is：For there are covering problems
Grid collection judges that the two grids belong to same if two grid centers are smaller than or equal to X the first grid precision
A problem area, wherein X is the constant more than 1, and the first grid precision is grid precision specified in above-described embodiment.
In another embodiment of the present invention, the grid index institute in each problem area concentrated to described problem region is really
Fixed grid region range carries out the step of region extends out and is specially：
Normalization MGRS longitudes east after extending out bias=normalize MGRS longitudes east biasing-(（X-1）/ 2) the * the first grid
Precision-Y；
Normalization MGRS longitudes north after extending out bias=normalize MGRS longitudes north biasing-(（X-1）/ 2) the * the first grid
Precision-Y；
Second grid precision=X* the first grid precision+2*Y；
Wherein X is the grid length of side number for being more than 1 in problem area decision rule, and the value of Y is the constant more than 0.
Formula is extended out according to above-mentioned, the regional extent that the grid index determines is extended out to ensure between grid region
Adjacent or intersection, according to extending out the second grid index newly defined afterwards in cartographic information（MapInfo）Middle generation grid map
These raster map layers are finally carried out region merging technique according to index value and just generate last problem region figure layer by layer.
As shown in Fig. 2, the detailed process of described problem Area generation is：Load frequency sweep data；It obtains in frequency sweep data
Sampling point information；The sampling point information is converted into grid index according to the sampling point information, is then summarized according to grid
The sampling point information that principle is converted into grid index is aggregated into grid, and is stored in the first grid collection table；According to what is summarized
Grid collection filters out that there are the grid collection of covering problem to be stored in the second grid collection table, for there are the grid collection of covering problem
Classification intersection is carried out according to the grid collection in decision algorithm pair the second grid collection table, problem area collection is generated and is stored in problem area
Collect in table；Successively from each problem area is taken out in the collection table of region the problem of generation, own to include in the problem area
Grid index is extended out according to formula progress region is extended out, then according to the grid index redefined after extending out in MapInfo
Raster map layer is generated, and is imported into raster map layer table, and the grid of each new importing is numbered successively；Judge whether pair
Each problem area in problem area collection table is extended out, if do not extended out all, is continued to remaining problem area
Domain is extended out, and otherwise, region classification merging is carried out according to the index value redefined to raster map layer table in MapInfo,
Generate problem area figure layer.
Above example of the present invention, by carrying out grid aggregation process, Neng Goujing to the sampling point information in frequency sweep data
Problem area is really generated, and the GIS that can intuitively carry out zone boundary is rendered, and improves treatment effeciency so that problem area
The statistical result in domain more intuitively with accurately, facilitate the quick orientation problem region of technical staff.
The embodiment of the present invention additionally provides the device that problem area is generated in a kind of coverage optimization, including：
Acquisition module, for obtaining the sampling point information in coverage optimization；
Analysis module, for summarizing sampling point information progress grid；
Generation module generates problem area figure layer for summarizing according to the grid.
In another embodiment of the present invention, the acquisition module obtains the sampled point letter from the frequency sweep data of load
Breath.
Wherein, the grid is the three-dimensional sphere region that pre-determined distance is respectively crossed in thing, north and south.
In another embodiment of the present invention, the analysis module includes：
Convert module, for the longitude and latitude of the sampling point information to be converted into grid index；
Summarizing module summarizes for carrying out grid to the identical sampled point of the grid index.
Further, the grid index format is：It compiles in the UTM longitudes area latitudinal regions number+UTM number+MGRS longitudes area
Number latitudinal regions+MGRS, which number+normalizing MGRS longitudes east to bias+and normalize MGRS longitudes north, biases the+the first grid precision,
In,
Normalize MGRS longitudes east biasing=int（MGRS longitudes east biases the/the first grid precision）；
Normalize MGRS longitudes north biasing=int（MGRS longitudes north biases the/the first grid precision）.
Wherein, the summarizing module according to frequency/base station identification code/scrambler/peripheral hardware interconnection standard by the grid index
Each information that identical sampled point includes carries out average grid and summarizes.
In another embodiment of the present invention, the generation module includes：
Screening module, for screen the grid summarize generation there are the grid collection of covering problem；
Intersection module of classifying generates problem area for the grid collection there are covering problem to be carried out classification intersection
Collection；
Module is extended out, grid determined by the grid index in each problem area for being concentrated to described problem region
Regional extent carries out region and extends out；
Figure layer generation module, the grid index for being extended out according to generate raster map layer；
Area generation module generates problem area figure layer for merging the raster map layer according to grid index value.
It should be noted that the classification intersection module is for there are the grid collection of covering problem, if in two grids
In the heart away from less than or equal to X the first grid precision, then judge that the two grids belong to the same problem area；Wherein, X is big
In 1 constant.
It should be noted that described extend out module foundation：
Normalization MGRS longitudes east after extending out bias=normalize MGRS longitudes east biasing-(（X-1）/ 2) the * the first grid
Precision-Y；
Normalization MGRS longitudes north after extending out bias=normalize MGRS longitudes north biasing-(（X-1）/ 2) the * the first grid
Precision-Y；
Second grid precision=X* the first grid precision+2*Y；
Wherein X is the grid length of side number for being more than 1 in problem area decision rule, and the value of Y is the constant more than 0；
Grid region range determined by grid index in each problem area concentrated to described problem region carries out
Region extends out.
It should be noted that the device embodiment is device corresponding with the above method, all realization sides of the above method
Formula can also reach technique effect same as mentioned above suitable for the device embodiment.
Above-described is the preferred embodiment of the present invention, it should be pointed out that the ordinary person of the art is come
It says, under the premise of not departing from principle of the present invention, can also make several improvements and retouch, these improvements and modifications should also regard
For protection scope of the present invention.
Claims (12)
1. the generation method of problem area in a kind of coverage optimization, which is characterized in that including：
Obtain the sampling point information in coverage optimization；
Sampling point information progress grid is summarized；
Summarized according to the grid and generates problem area figure layer；
Wherein, described the step of summarizing generation problem area figure layer according to the grid, includes：
Screen the grid summarize generation there are the grid collection of covering problem；
The grid collection there are covering problem is subjected to classification intersection, generates problem area collection；
Grid region range determined by grid index in each problem area concentrated to described problem region carries out region
It extends out；
Raster map layer is generated according to the grid index extended out；
Merge the raster map layer according to grid index value and generates problem area figure layer；
Wherein, the specific method for generating problem area collection is：For there are the grid collection of covering problem, if two grids
Center is smaller than or equal to X the first grid precision, then judges that the two grids belong to the same problem area, wherein X is
Constant more than 1；
Grid region range carries out determined by grid index in each problem area concentrated to described problem region
The step of region extends out be specially：
Normalization MGRS longitudes east after extending out biases=normalizes MGRS longitudes east biasing-((X-1)/2) * the first grid essence
Degree-Y；
Normalization MGRS longitudes north after extending out biases=normalizes MGRS longitudes north biasing-((X-1)/2) * the first grid essence
Degree-Y；
Second grid precision=X* the first grid precision+2*Y；
Wherein X is the grid length of side number for being more than 1 in problem area decision rule, and the value of Y is the constant more than 0.
2. the generation method of problem area in coverage optimization according to claim 1, which is characterized in that the acquisition covering
The step of sampling point information in optimization is specially：The sampling point information is obtained from the frequency sweep data of load.
3. the generation method of problem area in coverage optimization according to claim 1, which is characterized in that the grid is east
The three-dimensional sphere region of pre-determined distance is respectively crossed in west, north and south.
4. the generation method of problem area in coverage optimization according to claim 1, which is characterized in that described to be adopted described
Sampling point information carries out the specific steps that grid summarizes：
The longitude and latitude of the sampling point information is converted into grid index；
Grid is carried out to the identical sampled point of the grid index to summarize.
5. the generation method of problem area in coverage optimization according to claim 4, which is characterized in that the grid index
Format is：Number+normalize in the latitudinal regions number+MGRS MGRS warps in the UTM longitudes area latitudinal regions number+UTM number+MGRS longitudes area
Eastern biasing+normalization MGRS longitudes the north of degree biases the+the first grid precision, wherein
Normalize MGRS longitudes east biasing=int (MGRS longitudes east biases the/the first grid precision)；
Normalize MGRS longitudes north biasing=int (MGRS longitudes north biases the/the first grid precision).
6. the generation method of problem area in coverage optimization according to claim 4, which is characterized in that the grid summarizes
It is each information for including by the identical sampled point of the grid index according to frequency/base station identification code/scrambler/peripheral hardware interconnection standard
Average grid is carried out to summarize.
7. generating the device of problem area in a kind of coverage optimization, which is characterized in that including：
Acquisition module, for obtaining the sampling point information in coverage optimization；
Analysis module, for summarizing sampling point information progress grid；
Generation module generates problem area figure layer for summarizing according to the grid；
Wherein, the generation module includes：
Screening module, for screen the grid summarize generation there are the grid collection of covering problem；
Intersection module of classifying generates problem area collection for the grid collection there are covering problem to be carried out classification intersection；
Module is extended out, grid region determined by the grid index in each problem area for being concentrated to described problem region
Range carries out region and extends out；
Figure layer generation module, the grid index for being extended out according to generate raster map layer；
Area generation module generates problem area figure layer for merging the raster map layer according to grid index value；
Wherein, the classification intersection module is for there are the grid collection of covering problem, if two grid centers be smaller than or
Equal to X the first grid precision, then judge that the two grids belong to the same problem area；Wherein, X is the constant more than 1；
It is described to extend out module foundation：
Normalization MGRS longitudes east after extending out biases=normalizes MGRS longitudes east biasing-((X-1)/2) * the first grid essence
Degree-Y；
Normalization MGRS longitudes north after extending out biases=normalizes MGRS longitudes north biasing-((X-1)/2) * the first grid essence
Degree-Y；
Second grid precision=X* the first grid precision+2*Y；
Wherein X is the grid length of side number for being more than 1 in problem area decision rule, and the value of Y is the constant more than 0；
Grid region range determined by grid index in each problem area concentrated to described problem region carries out region
It extends out.
8. device according to claim 7, which is characterized in that the acquisition module obtains institute from the frequency sweep data of load
State sampling point information.
9. device according to claim 7, which is characterized in that the grid is that pre-determined distance is respectively crossed in thing, north and south
Three-dimensional sphere region.
10. device according to claim 7, which is characterized in that the analysis module includes：
Convert module, for the longitude and latitude of the sampling point information to be converted into grid index；
Summarizing module summarizes for carrying out grid to the identical sampled point of the grid index.
11. device according to claim 10, which is characterized in that the grid index format is：UTM longitudes area number+
The latitudinal regions UTM number+MGRS longitudes area, which numbers the latitudinal regions number+MGRS ,+normalizing MGRS longitudes east to bias+normalizes MGRS warps
The+the first grid precision of degree north biasing, wherein
Normalize MGRS longitudes east biasing=int (MGRS longitudes east biases the/the first grid precision)；
Normalize MGRS longitudes north biasing=int (MGRS longitudes north biases the/the first grid precision).
12. device according to claim 10, which is characterized in that the summarizing module is according to frequency/base station identification code/disturb
Each information that the identical sampled point of the grid index includes is carried out average grid and summarized by code/peripheral hardware interconnection standard.
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| CN108243445A (en) * | 2016-12-27 | 2018-07-03 | ***通信集团湖北有限公司 | A kind of method and system for determining weak overlay area |
| CN109495897B (en) * | 2017-09-12 | 2021-09-07 | ***通信集团公司 | Regional aggregation method and device for LTE network problems |
| CN108133485B (en) * | 2017-12-21 | 2020-08-07 | 重庆玖舆博泓科技有限公司 | GIS rasterization connection problem area identification method, device, terminal and medium |
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