CN111818532B - Base station antenna downward inclination angle optimizing method based on user distribution - Google Patents
Base station antenna downward inclination angle optimizing method based on user distribution Download PDFInfo
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- H04W24/02—Arrangements for optimising operational condition
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- H—ELECTRICITY
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
In order to improve the accuracy of the antenna downward inclination angle and optimize the communication quality, the invention discloses a base station antenna downward inclination angle optimizing method based on user distribution, which comprises the following steps: s1: determining the coverage area of the target cell through the MR data of the target cell and the work parameter information of the target cell and the adjacent cells; s2: dividing a target cell into a plurality of fan-shaped intervals; s3: calculating the probability density of the MR sampling points of each sector annular interval; s4: determining the primary coverage direction of the main lobe of the base station antenna according to the probability density of the MR sampling points of each sector annular interval; s5: judging whether each sector ring-shaped interval is split or not according to the map information, and if the sector ring-shaped interval is split, executing S3; if all the fan ring-shaped intervals do not need to be split, executing S6; s6: determining the final coverage direction of the main lobe of the base station antenna according to the probability density of the MR sampling points of each sector-ring interval in the S5; and obtaining a downward inclination angle according to the normal of the coverage direction of the final main lobe of the base station antenna.
Description
Technical Field
The invention relates to the field of wireless communication, in particular to a base station antenna downward inclination angle optimizing method based on user distribution.
Background
In the existing wireless communication construction process, the downward inclination angle of the base station antenna needs to be optimized. The coverage quality of the wireless network is directly influenced due to the arrangement of the downward inclination angle of the base station antenna. Unreasonable arrangement of the downward inclination angle may cause problems such as overlapping coverage or coverage blind areas. The current technical scheme for optimizing the downward inclination angle mainly adopts methods such as network optimization test, field census or user complaint.
The net quality test has the following disadvantages: the road test index reflects the network quality in the current channel environment, the static index can only guide the downward inclination angle optimization work of universality, the actual cell user distribution cannot be combined, targeted fine optimization is carried out, and a large amount of manpower and material resources are consumed in the network optimization test process.
The field census has the following disadvantages: the problem of optimizing the downtilt angle of the antenna is solved through field general survey, more manpower and material resources are consumed, the optimization result is greatly influenced by subjective judgment of a surveyor, and the requirement of network coverage cannot be really matched.
The customer complaints have the following disadvantages: the method has the advantages that the user complaints trigger the base station antenna downward inclination angle optimization work, the current user complaints are prone to be solved, the antenna downward inclination angle is adjusted to be deviated to the position of the complaint user, other users in the same cell are ignored, and therefore certain network quality hidden dangers are caused.
Patent application No. 2017101176692, entitled a configuration method and system for 5G base station 3DMIMO antenna vertical downtilt angle value, has the following disadvantages: the above patent needs to collect the geographic position and the geographic height data of the user and perform cluster analysis, and the related calculation is complicated. The method needs the support of a user intelligent terminal height sensor for acquiring the geographical height data, is greatly limited, and may have errors due to the problems of an algorithm or the performance of the terminal. In addition, the user distribution obtained in the above patent is only a static distribution at a certain time, and cannot represent a dynamic user distribution.
Disclosure of Invention
The invention overcomes the defects of the prior art and provides a base station antenna downward inclination angle optimizing method based on user distribution. The method and the device represent the user distribution density through the MR (Measurement Report) sampling point data, complete the fine optimization of the base station antenna downtilt based on the user distribution, have higher optimization efficiency and more accurate coverage direction compared with the traditional methods based on network optimization test, field general survey or user complaint and the like, reduce errors possibly caused by artificial subjective judgment, dynamically capture the coverage direction change caused by user flow, and realize accurate coverage by adjusting the downtilt angle through a network manager.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a base station antenna downward inclination angle optimizing method based on user distribution comprises the following steps:
s1: determining the coverage area of the target cell through the MR data of the target cell, the work parameter information of the target cell and the work parameter information of the adjacent cell of the target cell;
s2: dividing the projection of the downward-looking coverage space of the target cell on a horizontal plane into a plurality of fan-shaped intervals;
s3: calculating the probability density of the MR sampling points in each sector annular interval;
s4: determining the primary coverage direction of the main lobe of the base station antenna according to the probability density of the MR sampling points of each sector annular interval;
s5: judging whether each sector annular interval is split or not according to the map information, and if the sector annular interval is split, executing S3; if all the fan annular sections do not need to be split, S6 is executed;
s6: determining the final coverage direction of the main lobe of the base station antenna according to the probability density of the MR sampling points of each sector-shaped interval in the S5; and obtaining a downward inclination angle according to the normal of the coverage direction of the main lobe of the final base station antenna.
According to the method, the distribution density of the users is represented through the MR sampling point data, fine optimization of the base station antenna downtilt based on the user distribution is completed, compared with the traditional methods based on network optimization testing, field general survey or user complaints and the like, the optimization efficiency is higher, the coverage direction is more accurate, errors possibly caused by artificial subjective judgment are reduced, the coverage direction change caused by user flow can be dynamically captured, and the accurate coverage is realized by adjusting the downtilt through a network manager.
In a preferred embodiment, the MR data includes a physical cell ID, a longitude and a latitude.
In a preferred embodiment, the MR data further comprises one or more of the following:
in a preferred embodiment, the parameter information includes longitude, latitude, azimuth and antenna hanging height.
In a preferred embodiment, the step S1 includes the following substeps:
s1.1: acquiring MR data of a target cell, power parameter information of the target cell and power parameter information of a cell adjacent to the target cell;
s1.2: mapping the target cell and the adjacent cells of the target cell into discrete points on the space through the work parameter information of the target cell and the work parameter information of the adjacent cells of the target cell;
s1.3: connecting the discrete points into a triangular net;
s1.4: connecting the discrete point corresponding to the target cell with the center of a circumscribed circle of a triangle of the target cell adjacent to the triangulation network to obtain a Thiessen polygon corresponding to the target cell, and defining the Thiessen polygon corresponding to the target cell as the coverage area of the target cell;
s1.5: and dividing the coverage range of the target cell into a plurality of sector coverage areas by combining the angle bisectors of the azimuth angles of the discrete points of the target cell.
In a preferred embodiment, the step S2 includes the following substeps:
s2.1: defining the circumscribed circle of the Thiessen polygon corresponding to the target cell as an outer ring line, and defining D max The horizontal distance between any point on the outer ring line and the base station;
s2.2: randomly selecting any point on an outer ring line corresponding to a sector coverage area of a target cell as a reference point, defining a reference line as a connecting line between the reference point and the top end of a base station antenna, and defining a sector depression angle beta as an included angle between the reference line and a normal of a horizontal plane;
s2.3: dividing the sector depression angle beta into N, thereby dividing the projection of the horizontal plane of the corresponding angle space into N fan-shaped intervals, wherein the angle of each fan-shaped interval is xi i - β -i θ, said i =0,1,2, …, N-1, said N being a positive integer; the theta is an artificial preset value.
In a preferred scheme, the theta is the width of a vertical half-power lobe of the base station antenna.
In a preferred embodiment, the step S5 includes the following substeps:
s5.1: obtaining physical parameters of all buildings in the target area according to the map information, and obtaining the span A of each building according to the physical parameters of the buildings k ；
S5.2: through the span a of each building k Obtaining the average span A of all buildings in the sector annular interval N ；
S5.3: obtaining the span A of the fan annular interval according to the map information;
s5.4: a and A are reacted N Making a comparison, if A N If the temperature is less than or equal to 0.5A, the corresponding fan-shaped annular interval is not split, and S5.6 is executed; if A N >0.5A, executing S5.5 in the corresponding fan-shaped interval;
s5.5: the corresponding fan ring section is further divided into M fan ring sections, and the span of the M-1 fan ring section is defined as A- (M-1) × A N (ii) a The span of the sector ring section except the M-1 is defined as A N Executing S3;
s5.6: and traversing all the fan-shaped intervals until all the fan-shaped intervals do not need to be split, and executing S6.
In a preferred embodiment, the map information includes the following fields of the building:
| serial number | Including field names |
| 1 | Building ID |
| 2 | Longitude of building |
| 3 | Building latitude |
| 4 | Number of stories in building |
In a preferred embodiment, A is k The calculation is made by the following formula:
A k ＝|lon max -lon min |
the lon max Is the maximum longitude of the building; the lon min Is the minimum longitude of the building.
In a preferred embodiment, A is N The calculation is made by the following formula:
in the formula, n represents the number of all buildings in the fan-shaped interval; a is described Ki Representing the span A of the ith building within the sector annulus k 。
In a preferred embodiment, a is calculated by the following formula:
A＝|lonQ max -lonQ min |
the lonQ max Is the maximum longitude of the sector-shaped interval; the lonQ min Is the minimum longitude of the sector annulus.
In a preferred embodiment, the step S6 includes the following substeps:
s6.1: collecting probability densities of MR sampling points of all the sector-shaped intervals of S5, and defining the sector-shaped interval with the highest probability density of the MR sampling points as the final coverage direction of the main lobe of the base station antenna;
s6.2: taking the middle part of the sector-ring-shaped interval with the highest probability density of the MR sampling points as the optimal direction of the normal of the main lobe of the base station antenna to obtain the included angle gamma between the normal of the main lobe of the base station antenna and the horizontal plane, wherein the gamma is calculated by the following formula:
γ＝arctan(h/a)
in the formula, h is the hanging height of the base station antenna, and the radius of the sector annular section corresponding to a;
s6.3: obtaining the downward inclination angle of the base station antenna through the included angle gamma
Is->
The calculation is made by the following formula:
wherein, the sigma is the zero power wave width of the base station antenna.
In a preferred embodiment, said S3 includes the following:
the probability density of the MR sampling points in the fan-shaped interval in S3 = the number of MR sampling points in the fan-shaped interval/the area of the fan-shaped interval.
In a preferred embodiment, said S4 includes the following:
and defining the sector interval with the highest probability density of the MR sampling points as the coverage direction of the primary main lobe of the base station antenna.
Compared with the prior art, the technical scheme of the invention has the beneficial effects that:
(1) Cost reduction and efficiency improvement are realized, user data are directly obtained through a wireless management system, manual acquisition of basic data is not needed, labor cost is reduced, user flow is dynamically captured, flexible adjustment is realized, and efficiency is improved.
(2) The fitting is practical, the MR data and the web crawler technology are utilized, the current network user data and the online map data can be captured, the fitting is practical, and errors of artificial subjective judgment are reduced.
(3) And fine planning, namely establishing an antenna projection interval by subdividing the antenna angle and the building span, and determining the optimal antenna downward inclination angle by combining the MR data so that the coverage direction is more accurate.
Drawings
FIG. 1 is a flow chart of an embodiment.
FIG. 2 is a schematic diagram of a sector coverage area of an embodiment;
FIG. 3 is a schematic view of the fan-shaped section of the embodiment shown in a disassembled state;
FIG. 4 is a schematic diagram illustrating the calculation of the down tilt angle in the embodiment.
The drawings are for illustrative purposes only and are not to be construed as limiting the patent;
for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product;
it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The technical solution of the present invention is further described below with reference to the accompanying drawings and examples.
Examples
As shown in fig. 1, a method for optimizing a downtilt of a base station antenna based on user distribution includes the following steps:
s1: determining the coverage area of the target cell according to the MR data of the target cell, the work parameter information of the target cell and the work parameter information of the adjacent cell of the target cell;
s2: dividing the projection of the downward-looking coverage space of the target cell on a horizontal plane into a plurality of fan-shaped annular sections;
s3: calculating the probability density of the MR sampling points of each sector annular interval;
s4: determining the primary coverage direction of the main lobe of the base station antenna according to the probability density of the MR sampling points of each sector annular interval;
s5: judging whether each sector annular interval is split or not according to the map information, and if the sector annular interval is split, executing S3; if all the fan annular sections do not need to be split, S6 is executed;
s6: determining the final coverage direction of the main lobe of the base station antenna according to the probability density of the MR sampling points of each sector-ring interval in the S5; and obtaining a downward inclination angle according to the normal of the coverage direction of the final main lobe of the base station antenna.
In the embodiment, the distribution density of users is represented by MR sampling point data, fine optimization of the downtilt of the base station antenna based on user distribution is completed, compared with the traditional methods based on network optimization test, field general survey or user complaint, the optimization efficiency is higher, the coverage direction is more accurate, errors possibly caused by artificial subjective judgment are reduced, the coverage direction change caused by user flow can be dynamically captured, and accurate coverage is realized by adjusting the downtilt through a network manager.
In an embodiment, the following extensions may also be made: the MR data contains a physical cell ID, longitude, and latitude.
In the embodiment and the above improved embodiment, the following extension can be made: the MR data further comprises one or more of the following:
in the embodiment and the above improved embodiment, the following extension can be made: the work parameter information comprises longitude, latitude, azimuth and antenna hanging height.
In the embodiment and the above improved embodiment, the following extension can be made: s1 comprises the following substeps:
s1.1: acquiring MR data of a target cell, work parameter information of the target cell and work parameter information of adjacent cells of the target cell;
s1.2: mapping the target cell and the adjacent cells of the target cell into discrete points on the space through the work parameter information of the target cell and the work parameter information of the adjacent cells of the target cell;
s1.3: connecting the discrete points into a triangular net;
s1.4: connecting the discrete point corresponding to the target cell with the center of a circumscribed circle of a triangle of the target cell adjacent to the triangulation network to obtain a Thiessen polygon corresponding to the target cell, and defining the Thiessen polygon corresponding to the target cell as the coverage area of the target cell;
s1.5: the coverage area of the target cell is divided into several sector coverage areas by combining the bisectors of the azimuths of the discrete points of the target cell, as shown in fig. 2.
In the embodiment and the above improved embodiment, the following extension can be made: s2 comprises the following substeps:
s2.1: defining the circumscribed circle of the Thiessen polygon corresponding to the target cell as an outer ring line, and defining D max The horizontal distance between any point on the outer ring line and the base station;
s2.2: randomly selecting any point on an outer ring line corresponding to a sector coverage area of a target cell as a reference point, defining a reference line as a connecting line between the reference point and the top end of a base station antenna, and defining a sector depression angle beta as an included angle between the reference line and a normal of a horizontal plane;
s2.3: dividing the sector depression angle beta into N, thereby dividing the projection of the horizontal plane of the corresponding angle space into N fan-shaped intervals, wherein the angle of each fan-shaped interval is xi i = β -i θ, i =0,1,2, …, N-1,N is a positive integer; theta is an artificial preset value, as shown in fig. 3.
In the embodiment and the above improved embodiment, the following extension can be made: theta is the vertical half-power lobe width of the base station antenna.
In the embodiment and the above improved embodiment, the following extension can be made: s5 comprises the following substeps:
s5.1: obtaining physical parameters of all buildings in the target area according to the map information, and obtaining the span A of each building according to the physical parameters of the buildings k ；
S5.2: through the span a of each building k Obtaining the average span A of all buildings in the sector annular interval N ；
S5.3: obtaining the span A of the fan annular interval according to the map information;
s5.4: a and A are reacted N Making a comparison, if A N If the temperature is less than or equal to 0.5A, the corresponding fan-shaped annular interval is not split, and S5.6 is executed; if A N >0.5A, executing S5.5 in the corresponding fan annular interval;
s5.5: the corresponding fan-shaped ring section is further divided into M fan-shaped ring sections, and the span of the M-1 th fan-shaped ring section is defined as A- (M-1) × A N (ii) a The span of the sector ring section except the M-1 is defined as A N Executing S3;
s5.6: and traversing all the fan-shaped intervals until all the fan-shaped intervals do not need to be split, and executing S6.
In the embodiment and the above improved embodiment, the following extension can be made: the map information includes the following fields of the building:
| serial number | Including field names |
| 1 | Building ID |
| 2 | Building longitude |
| 3 | Building latitude |
| 4 | Number of stories in building |
In the embodiment and the above improved embodiment, the following extension can be made: a. The k The calculation is made by the following formula:
A k ＝|lon max -lon min |
lon max is the maximum longitude of the building; lon min Is the minimum longitude of the building.
In the embodiment and the above improved embodiment, the following extension can be made: a. The N The calculation is made by the following formula:
in the formula, n represents the number of all buildings in the fan-shaped interval; a. The Ki Representing the span A of the ith building within the sector annulus k 。
In the embodiment and the above improved embodiment, the following extension can be made: a is calculated by the following formula:
A＝|lonQ max -lonQ min |
lonQ max is the maximum longitude of the sector annulus; lonQ min Is the minimum longitude of the sector annulus.
In the embodiment and the above improved embodiment, the following extension can be made: s6 comprises the following substeps:
s6.1: collecting probability densities of MR sampling points of all the sector-shaped intervals of S5, and defining the sector-shaped interval with the highest probability density of the MR sampling points as the final coverage direction of the main lobe of the base station antenna;
s6.2: as shown in fig. 4, the middle of the sector-shaped interval with the highest probability density of MR sampling points is used as the optimal direction of the normal of the main lobe of the base station antenna, and the included angle γ between the normal of the main lobe of the base station antenna and the horizontal plane is obtained, and γ is calculated by the following formula:
γ＝arctan(h/a)
in the formula, h is the hanging height of the base station antenna, and a is the radius of the corresponding sector annular section;
s6.3: obtaining the downward inclination angle of the base station antenna through the included angle gamma
The calculation is made by the following formula:
where σ is the zero-power bandwidth of the base station antenna.
In the embodiment and the above improved embodiment, the following extension can be made: s3 comprises the following contents:
the probability density of the MR sampling points of the fan-shaped interval in S3 = the number of MR sampling points of the fan-shaped interval/the area of the fan-shaped interval.
In the embodiment and the above improved embodiment, the following extension can be made: s4 comprises the following contents:
and defining the sector interval with the highest probability density of the MR sampling points as the coverage direction of the primary main lobe of the base station antenna.
In the detailed description of the embodiments, various technical features may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The same or similar reference numerals correspond to the same or similar parts;
the terms describing positional relationships in the drawings are for illustrative purposes only and should not be construed as limiting the patent;
it should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (9)
1. A base station antenna downward inclination angle optimizing method based on user distribution is characterized by comprising the following steps:
s1: determining the coverage area of the target cell according to the MR data of the target cell, the work parameter information of the target cell and the work parameter information of the adjacent cell of the target cell;
s2: dividing the projection of the downward-looking coverage space of the target cell on a horizontal plane into a plurality of fan-shaped intervals;
s3: calculating the probability density of the MR sampling points of each sector annular interval;
s4: determining the primary coverage direction of the main lobe of the base station antenna according to the probability density of the MR sampling points of each sector annular interval;
s5: judging whether each sector ring-shaped interval is split or not according to the map information, and if the sector ring-shaped interval is split, executing S3; if all the fan annular sections do not need to be split, S6 is executed;
s6: determining the final coverage direction of the main lobe of the base station antenna according to the probability density of the MR sampling points of each sector-ring interval in the S5; obtaining a down dip angle according to the final normal of the coverage direction of the main lobe of the base station antenna;
the step S5 comprises the following substeps:
s5.1: obtaining a target area according to map informationObtaining the span A of each building according to the physical parameters of the buildings k ；
S5.2: through the span a of each building k Obtaining the average span A of all buildings in the sector annular interval N ；
S5.3: obtaining the span A of the fan annular interval according to the map information;
s5.4: a and A are reacted N Making a comparison, if A N If the temperature is less than or equal to 0.5A, the corresponding fan-shaped annular interval is not split, and S5.6 is executed; if A is N >0.5A, executing S5.5 in the corresponding fan annular interval;
s5.5: the corresponding fan ring section is further divided into M fan ring sections, and the span of the M-1 fan ring section is defined as A- (M-1) × A N (ii) a Defining the span of the sector-shaped interval except the M-1 st one as A N Executing S3;
s5.6: and traversing all the fan-shaped intervals until all the fan-shaped intervals do not need to be split, and executing S6.
2. The method for optimizing the downtilt of a base station antenna according to claim 1, wherein S1 comprises the following substeps:
s1.1: acquiring MR data of a target cell, work parameter information of the target cell and work parameter information of adjacent cells of the target cell;
s1.2: mapping the target cell and the adjacent cells of the target cell into discrete points on the space through the work parameter information of the target cell and the work parameter information of the adjacent cells of the target cell;
s1.3: connecting the discrete points into a triangular net;
s1.4: connecting the discrete point corresponding to the target cell with the center of a circumscribed circle of a triangle of the target cell adjacent to the triangulation network to obtain a Thiessen polygon corresponding to the target cell, and defining the Thiessen polygon corresponding to the target cell as the coverage area of the target cell;
s1.5: and dividing the coverage range of the target cell into a plurality of sector coverage areas by combining the angle bisectors of the azimuth angles of the discrete points of the target cell.
3. The method for optimizing the downtilt of a base station antenna according to claim 2, wherein the step S2 comprises the substeps of:
s2.1: defining the circumscribed circle of the Thiessen polygon corresponding to the target cell as an outer ring line, and defining D max The horizontal distance between any point on the outer ring line and the base station;
s2.2: randomly selecting any point on an outer ring line corresponding to a sector coverage area of a target cell as a reference point, defining a reference line as a connecting line between the reference point and the top end of a base station antenna, and defining a sector depression angle beta as an included angle between the reference line and a normal of a horizontal plane;
s2.3: dividing the sector depression angle beta into N, thereby dividing the projection of the horizontal plane of the corresponding angle space into N fan-shaped intervals, wherein the angle of each fan-shaped interval is xi i - β -i θ, said i =0,1,2, …, N-1, said N being a positive integer; the theta is an artificial preset value.
4. The method of claim 3, wherein θ is a vertical half power lobe width of the base station antenna.
5. The method as claimed in claim 1, wherein said A is a k The calculation is made by the following formula:
A k ＝|lon max -lon min |
the lon max Is the maximum longitude of the building; the lon min Is the minimum longitude of the building.
6. The method as claimed in claim 1, wherein said A is a N The calculation is made by the following formula:
in the formula, n represents the number of all buildings in the fan-shaped interval; a is described Ki Representing the span A of the ith building within the sector k 。
7. The method as claimed in claim 1, wherein a is calculated by the following formula:
A＝|lonQ max -lonQ min |
the lonQ max Is the maximum longitude of the sector-shaped interval; the lonQ min Is the minimum longitude of the sector annulus.
8. The method for optimizing the downtilt angle of a base station antenna according to claim 1, wherein the step S6 comprises the following substeps:
s6.1: collecting probability densities of MR sampling points of all the sector-shaped intervals of S5, and defining the sector-shaped interval with the highest probability density of the MR sampling points as the final coverage direction of the main lobe of the base station antenna;
s6.2: taking the middle part of the sector-ring-shaped interval with the highest probability density of the MR sampling points as the optimal direction of the normal of the main lobe of the base station antenna to obtain the included angle gamma between the normal of the main lobe of the base station antenna and the horizontal plane, wherein the gamma is calculated by the following formula:
γ＝arctan(h/a)
in the formula, h is the hanging height of the base station antenna, and the radius of the sector annular section corresponding to a;
s6.3: obtaining the downward inclination angle of the base station antenna through the included angle gamma
Is->
The calculation is made by the following formula:
wherein, the sigma is the zero power wave width of the base station antenna.
9. The method for optimizing the downtilt of a base station antenna according to any one of claims 1 to 8, wherein S3 comprises the following steps:
the probability density of the MR sampling points in the fan-shaped interval in S3 = the number of MR sampling points in the fan-shaped interval/the area of the fan-shaped interval.
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