CN107466043B - Method and equipment for determining azimuth angle of base station antenna - Google Patents
Method and equipment for determining azimuth angle of base station antenna Download PDFInfo
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- CN107466043B CN107466043B CN201610390449.2A CN201610390449A CN107466043B CN 107466043 B CN107466043 B CN 107466043B CN 201610390449 A CN201610390449 A CN 201610390449A CN 107466043 B CN107466043 B CN 107466043B
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H—ELECTRICITY
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- H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
Abstract
The invention discloses a method and equipment for determining an azimuth angle of a base station antenna, wherein the method comprises the following steps: acquiring MR data, and acquiring the position information of each MR sampling point in the MR data and a cell in which the MR sampling point is positioned; determining a grid where each MR sampling point is located in a map dividing a plurality of grids based on the position information of each MR sampling point; obtaining the service flow of the corresponding cell in each grid based on the number of MR sampling points in any cell in each grid; determining the position of a coverage center of a corresponding cell based on the obtained service flow; and determining the azimuth angle of the base station antenna corresponding to each cell based on the position of the coverage center of each cell and the position of the corresponding base station.
Description
Technical Field
The invention relates to the field of wireless mobile network planning optimization, in particular to a method and equipment for determining an azimuth angle of a base station antenna.
Background
Based on the fact that the rural area is impacted by the heat tide of the mobile internet, the rural market becomes a new growth blue sea of mobile operators, and 4G network construction continuously extends to the vast rural areas; however, in rural areas, due to the wide area, operators cannot achieve high-density seamless coverage in the aspect of network construction like cities, and when network coverage is performed, it is necessary to ensure that a place where users are relatively concentrated can be covered, so that coverage optimization is very important.
In coverage optimization, the azimuth angle of the base station antenna is a very important parameter, and the azimuth angle of the base station antenna determines the main coverage direction of a cell; the main coverage direction of the cell can be changed by adjusting the azimuth angle of the base station antenna, the signal intensity of the main coverage direction is enhanced, the overlapping coverage can be reduced, the network interference is reduced, and the service quality is improved.
Currently, the setting of the azimuth angle of the base station antenna mainly comes from a planning scheme, that is, an azimuth angle parameter value is output through coverage simulation in a network planning stage, and the setting is performed according to a given azimuth angle when the base station antenna is installed.
Fig. 1 is a schematic flowchart of a method for setting an antenna azimuth angle of a base station in the prior art, as shown in fig. 1, the flowchart includes:
step 101: network planning data is collected.
Here, the network planning data includes a map, a site list of base stations, a cell list, and road test data; the station address list of the base station comprises longitude and latitude information of the base station, and the cell list comprises longitude and latitude of the cell and preset antenna parameters.
Step 102: and selecting and correcting a propagation model.
Illustratively, by examining the field environment, a wireless propagation model suitable for the geographic environment is selected and model corrections are made with the road test data.
Step 103: network planning simulation and pre-optimization.
Illustratively, network planning simulation is performed, and parameters of the base station antenna are pre-optimized under the set network coverage target.
Step 104: and judging whether the planned network reaches a network coverage target, if so, jumping to the step 105, otherwise, returning to the step 103, and continuing to perform simulation and pre-optimization.
Step 105: and outputting the network planning scheme.
Here, the outputted network planning scheme includes a result of pre-optimization of parameters of the base station antenna.
Step 106: the azimuth angle setting values of the base station antennas are obtained from the network planning scheme.
Here, after obtaining the azimuth angle setting value of the base station antenna, when the base station antenna is installed, the installation may be performed according to the azimuth angle setting value of the base station antenna.
The above-mentioned method for setting the azimuth angle of the antenna of the base station has the following disadvantages or shortcomings:
1) the precision of the azimuth angle parameter value is low. The antenna azimuth angle parameter value depends on the simulation accuracy of the network planning, and the simulation accuracy is limited by the map accuracy and the propagation model, which generally have a larger error from the actual situation, so that the azimuth angle parameter value of the base station antenna does not reach the expected coverage range.
2) Network coverage efficiency may be reduced. Because the network planning simulation does not consider the distribution condition of the actual flow of the current network, the main coverage direction of the base station antenna deviates from the flow concentration area by simply taking the network coverage rate as a target, and the places with flow needing concentrated coverage are not covered or are covered poorly; and the area with little or no flow is well covered, thus reducing the network coverage efficiency and wasting the coverage resources.
Disclosure of Invention
In order to solve the above technical problem, embodiments of the present invention provide a method and an apparatus for determining an azimuth angle of a base station antenna, which can improve setting accuracy of the azimuth angle of the base station antenna and network coverage efficiency.
The embodiment of the invention provides a method for determining an azimuth angle of a base station antenna, which comprises the following steps:
acquiring Measurement Report (MR) data, and acquiring position information of each MR sampling point in the MR data and a cell in which the MR sampling point is located;
determining a grid where each MR sampling point is located in a map dividing a plurality of grids based on the position information of each MR sampling point;
obtaining the service flow of the corresponding cell in each grid based on the number of MR sampling points in any cell in each grid;
determining the position of a coverage center of a corresponding cell based on the obtained service flow;
and determining the azimuth angle of the base station antenna corresponding to each cell based on the position of the coverage center of each cell and the position of the corresponding base station.
In the foregoing solution, the obtaining the service traffic of the corresponding cell in each grid based on the number of MR sampling points in any cell in each grid includes: and obtaining the service flow of the corresponding cell in each grid based on the number of the MR sampling points in the corresponding cell in each grid, the total number of the MR sampling points in the corresponding cell and the service flow of the corresponding cell.
In the foregoing solution, the determining the position of the coverage center of the corresponding cell based on the obtained service traffic includes:
performing weighted average calculation on the position coordinates of the central point of each grid by using the service flow of the corresponding cell in each grid to obtain the position coordinates of the coverage center of the corresponding cell;
or, the service flow of the corresponding cell in each grid is utilized to obtain the perceptibility of the corresponding cell in each grid; carrying out weighted average calculation on the position coordinates of the central point of each grid by using the perceptibility of the corresponding cell in each grid to obtain the position coordinates of the coverage center of the corresponding cell; and the perceptibility of the corresponding cell in each grid is positively correlated with the service flow of the corresponding cell in each grid.
In the above scheme, after determining the grid where each MR sampling point is located, the method further includes: obtaining the packet loss rate of the corresponding cell in each grid;
correspondingly, the determining the position of the coverage center of the corresponding cell based on the obtained service flow comprises: determining the perception degree of the corresponding cell in each grid based on the service flow of the corresponding cell in each grid and the packet loss rate of the corresponding cell in each grid, and performing weighted average calculation on the position coordinates of the central point of each grid by using the perception degree of the corresponding cell in each grid to obtain the position coordinates of the coverage center of the corresponding cell; and the perceptibility of the corresponding cell in each grid is positively correlated with the service flow of the corresponding cell in each grid, and positively correlated with the packet loss rate of the corresponding cell in each grid.
In the foregoing solution, the determining an azimuth angle of a base station antenna corresponding to each cell based on a position of a coverage center of each cell and a position of a corresponding base station includes:
based on the position of the coverage center of each cell and the position of the corresponding base station, determining the direction from the base station corresponding to each cell to the coverage center as follows: a main beam direction of a base station antenna corresponding to each cell; and determining the azimuth angle of the base station antenna corresponding to each cell based on the main beam direction of the base station antenna corresponding to each cell.
The embodiment of the invention provides equipment for determining an azimuth angle of a base station antenna, which comprises an acquisition module and a determination module; wherein the content of the first and second substances,
the acquisition module is used for acquiring measurement report MR data and acquiring the position information of each MR sampling point in the MR data and the cell in which the MR sampling point is positioned;
the determining module is used for determining a grid where each MR sampling point is located in a map which is divided into a plurality of grids based on the position information of each MR sampling point; obtaining the service flow of the corresponding cell in each grid based on the number of MR sampling points in any cell in each grid; determining the position of a coverage center of a corresponding cell based on the obtained service flow; and determining the azimuth angle of the base station antenna corresponding to each cell based on the position of the coverage center of each cell and the position of the corresponding base station.
In the foregoing solution, the determining module is specifically configured to obtain the traffic flow of the corresponding cell in each grid based on the number of MR sampling points located in the corresponding cell in each grid, the total number of MR sampling points located in the corresponding cell, and the traffic flow of the corresponding cell.
In the above scheme, the determining module is specifically configured to perform weighted average calculation on the position coordinates of the center point of each grid by using the service traffic of the corresponding cell in each grid, so as to obtain the position coordinates of the coverage center of the corresponding cell; or, the service flow of the corresponding cell in each grid is utilized to obtain the perceptibility of the corresponding cell in each grid; carrying out weighted average calculation on the position coordinates of the central point of each grid by using the perceptibility of the corresponding cell in each grid to obtain the position coordinates of the coverage center of the corresponding cell; and the perceptibility of the corresponding cell in each grid is positively correlated with the service flow of the corresponding cell in each grid.
In the above scheme, the determining module is further configured to obtain a packet loss rate of a cell corresponding to each grid after determining the grid where each MR sampling point is located;
correspondingly, the determining module is specifically configured to determine the perceptibility of the corresponding cell in each grid based on the service flow of the corresponding cell in each grid and the packet loss rate of the corresponding cell in each grid, and perform weighted average calculation on the position coordinates of the center point of each grid by using the perceptibility of the corresponding cell in each grid to obtain the position coordinates of the coverage center of the corresponding cell; and the perceptibility of the corresponding cell in each grid is positively correlated with the service flow of the corresponding cell in each grid, and positively correlated with the packet loss rate of the corresponding cell in each grid.
In the foregoing solution, the determining module is specifically configured to determine, based on the position of the coverage center of each cell and the position of the corresponding base station, a direction from the base station corresponding to each cell to the coverage center as: a main beam direction of a base station antenna corresponding to each cell; and determining the azimuth angle of the base station antenna corresponding to each cell based on the main beam direction of the base station antenna corresponding to each cell.
According to the technical scheme of the embodiment of the invention, MR data are obtained, and the position information of each MR sampling point in the MR data and the cell in which the MR sampling point is located are obtained; determining a grid where each MR sampling point is located in a map dividing a plurality of grids based on the position information of each MR sampling point; obtaining the service flow of the corresponding cell in each grid based on the number of MR sampling points in any cell in each grid; determining the position of a coverage center of a corresponding cell based on the obtained service flow; determining the azimuth angle of the base station antenna corresponding to each cell based on the position of the coverage center of each cell and the position of the corresponding base station; therefore, the embodiment of the invention does not depend on the precision of the map and the propagation model, and the output azimuth angle parameter is more consistent with the actual network condition based on the measured data, so that the parameter setting precision is higher; the embodiment of the invention aims the main coverage direction to the place with large service flow and poor service perception based on the geographical distribution of the flow and considering the place actually needed to be covered by the cell, thereby improving the efficiency of network coverage.
Drawings
Fig. 1 is a schematic flow chart of a method for setting an azimuth angle of an antenna of a base station in the prior art;
FIG. 2 is a flow chart of a method for determining an azimuth angle of a base station antenna according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a first component structure of an apparatus for determining an azimuth angle of a base station antenna according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of the position of an MR sampling point relative to a base station according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of the position relationship between the MR sampling points and the grid according to the embodiment of the present invention;
fig. 6 is a schematic diagram of a main beam direction of a base station antenna corresponding to a cell a in the embodiment of the present invention;
fig. 7 is a schematic diagram of a second component structure of an apparatus for determining an azimuth angle of a base station antenna according to an embodiment of the present invention.
Detailed Description
So that the manner in which the features and aspects of the embodiments of the present invention can be understood in detail, a more particular description of the embodiments of the invention, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings.
First embodiment
Fig. 2 is a flowchart of a method for determining an azimuth angle of a base station antenna according to an embodiment of the present invention, as shown in fig. 2, the flowchart includes:
step 201: acquiring Measurement Report (MR) data, and acquiring position information of each MR sampling point in the MR data and a cell in which the MR sampling point is located.
Here, the MR sampling points represent locations where User Equipments (UEs) are located; the cell in which the MR sampling point is located represents a serving cell of the UE corresponding to the MR sampling point, and further, for a Long Term Evolution (LTE) system that employs a carrier aggregation technology, the cell in which the MR sampling point is located may represent a primary serving cell or a secondary serving cell of the UE corresponding to the MR sampling point.
In actual implementation, the MR data may be acquired from a Network Management System (NMS); specifically, the terminal and the base station measure and report to the NMS periodically during the service process, and the MR data reflects the service existence of the location where the UE is located and the authenticity of the wireless environment, where the base station may be an evolved node b (eNB, eNodeB).
Illustratively, deriving the cell in which each MR sample point in the MR data is located may include: and determining the cell where each MR sampling point in the MR data is located according to the cell identifier of the UE serving cell corresponding to each MR sampling point.
Illustratively, deriving the position information of each MR sample point in the MR data may include: and obtaining the position information of the corresponding MR sampling point based on the time Advance (Tadv, Timing Advance) and the antenna Arrival Angle (AOA, Angle-of-Arrival) of each MR sampling point in the MR data.
In a specific implementation manner, obtaining the position information of each MR sampling point based on the time advance and the antenna arrival angle of each MR sampling point in the MR data includes:
based on the time lead corresponding to each MR sampling point in the MR data, the distance from the corresponding MR sampling point to the base station is obtained; obtaining the direction of the corresponding MR sampling point relative to the base station based on the antenna arrival angle corresponding to each MR sampling point in the MR data; and obtaining the position information of the corresponding MR sampling point according to the distance from the corresponding MR sampling point to the base station and the direction of the corresponding MR sampling point relative to the base station.
Here, the direction of the MR sampling point relative to the base station can be represented by an azimuth angle of the MR sampling point relative to the base station, the azimuth angle representing a horizontal angle between a north-pointing direction line of a certain point and a target direction line along a clockwise direction, that is, the azimuth angle of the MR sampling point relative to the base station is used to represent: from the north direction line of the base station, the horizontal included angle is formed between the direction lines from the clockwise direction to the MR sampling point, the direction line of the MR sampling point refers to a connecting line between the MR sampling point and the base station, and the value range of the azimuth angle in the embodiment of the invention is [0,2 pi ].
Here, after the distance from the corresponding MR sampling point to the base station and the direction of the corresponding MR sampling point with respect to the base station are obtained, the position information of the corresponding MR sampling point is obtained based on the position information of the base station, the distance from the corresponding MR sampling point to the base station, and the direction of the corresponding MR sampling point with respect to the base station, thereby completing the positioning of the MR sampling point.
Step 202: and determining a grid where each MR sampling point is positioned in a map dividing a plurality of grids based on the position information of each MR sampling point.
In actual implementation, a map is firstly divided into a plurality of grids according to a preset division strategy, and preferably, the sizes of the grids can be the same or different; the shape of each grid may be rectangular, diamond, fan, etc. The map here is a scene map corresponding to MR data, and the map here may be a two-dimensional map or a three-dimensional map.
It can be seen that each of the divided grids represents a geographical area, so that the grid in which each MR sample is located can be determined based on the position information of each MR sample.
Step 203: and obtaining the service flow of the corresponding cell in each grid based on the number of the MR sampling points in any cell in each grid.
Further, before this step, the number of MR sampling points in each cell in each grid is obtained based on the cell in which each MR sampling point in the MR data is located; that is, for each grid, there may be no MR sampling points, one MR sampling point, or multiple MR sampling points; if there are MR samples in a grid, the cell in which each MR sample in the grid is located can be determined from the cell in which each MR sample in the MR data is located.
Illustratively, the deriving the traffic flow of the corresponding cell in each grid based on the number of MR sampling points in any one cell in each grid includes: and obtaining the service flow of the corresponding cell in each grid based on the number of the MR sampling points in the corresponding cell in each grid, the total number of the MR sampling points in the corresponding cell and the service flow of the corresponding cell.
In one implementation, the traffic flow of the corresponding cell in the ith grid can be obtained according to the following formula:
TGi＝CGi/Call*T
wherein, TGiRepresenting the service flow of a corresponding cell in the ith grid, wherein i is a natural number less than or equal to n, and n represents the total number of the divided grids; cGiDenotes the number of MR sample points in the corresponding cell in the ith grid, CallIn summary, T represents the traffic flow of the corresponding cell, which represents the MR sampling point of the corresponding cell.
Further, the packet loss rate of the corresponding cell in each grid can be obtained based on the number of MR sampling points in any cell in each grid.
Illustratively, the number of MR sampling points in any cell in each grid is used to obtain the packet loss rate of the corresponding cell in each grid, and the method includes: and obtaining the packet loss rate of the corresponding cell in each grid based on the number of the MR sampling points of the corresponding cell in each grid, the uplink packet loss rate of each MR sampling point of the corresponding cell in each grid and the downlink packet loss rate of each MR sampling point of the corresponding cell in each grid.
Here, the uplink packet loss rate of each MR sampling point is used to indicate a packet loss rate when the UE uploads data to the corresponding base station, and the downlink packet loss rate of each MR sampling point is used to indicate a packet loss rate when the corresponding base station transmits data to the UE; in practical implementation, the uplink packet loss rate and the downlink packet loss rate of the MR sampling point can be obtained from the MR data.
In one implementation, the packet loss rate of the corresponding cell in the ith grid can be obtained according to the following formula:
wherein, PGiRepresenting the packet loss rate of a corresponding cell in the ith grid, wherein i is a natural number less than or equal to n, and n represents the total number of the divided grids; ULQciX(s) represents the uplink packet loss rate of the s-th MR sampling point of the corresponding cell in the i-th grid, and s is less than or equal to CGiNatural number of (C)GiRepresenting the number of MR sampling points in the corresponding cell in the ith grid; DLQciX(s) denotes the location of the ith grid below the s-th MR sample point of the corresponding cellAnd (4) line packet loss rate.
It can be understood that, for the same cell, the number and packet loss rate of MR sampling points in each grid represent the traffic flow and the traffic quality of the grid, respectively; here, the greater the number of MR sampling points in a grid of the same cell, the greater the traffic flow of the cell corresponding to the grid, and conversely, the smaller the traffic flow of the cell corresponding to the grid; the larger the packet loss rate of the cell corresponding to each grid is, the worse the service quality of the cell corresponding to the grid is, otherwise, the better the service quality of the cell corresponding to the grid is.
Obviously, if the service flow of the corresponding cell in one grid is larger and the packet loss rate of the corresponding cell is larger, it is indicated that the grid belongs to a grid with concentrated service flow of the cell and poor user perception, and the grid belongs to an area needing to be heavily covered.
Step 204: based on the derived traffic flow, the location of the coverage center of the corresponding cell is determined.
Illustratively, the position of the coverage center of the corresponding cell may be determined in three ways as follows.
First implementation
The position coordinates of the center point of each grid can be calculated by weighted average according to the service flow of the corresponding cell in each grid, and the position coordinates of the coverage center of the corresponding cell can be obtained.
Second implementation
The service flow of the corresponding cell in each grid can be utilized to obtain the perceptibility of the corresponding cell in each grid; and performing weighted average calculation on the position coordinates of the central point of each grid by using the perceptibility of the corresponding cell in each grid to obtain the position coordinates of the coverage center of the corresponding cell.
Here, the perceptibility of the corresponding cell in each grid is positively correlated with the traffic flow of the corresponding cell in each grid; for example, the perceptibility of a cell in the ith grid is positively correlated with the service traffic of the corresponding cell in the ith grid; preferably, the perceptibility of a cell in the ith grid is proportional to the traffic flow of the corresponding cell in the ith grid.
Third implementation
The perceptibility of the corresponding cell in each grid can be determined based on the service flow of the corresponding cell in each grid and the packet loss rate of the corresponding cell in each grid, and the position coordinates of the center point of each grid are weighted and averaged to obtain the position coordinates of the coverage center of the corresponding cell by utilizing the perceptibility of the corresponding cell in each grid.
The perceptibility of the corresponding cell in each grid is positively correlated with the service flow of the corresponding cell in each grid, and is positively correlated with the packet loss rate of the corresponding cell in each grid; for example, the service traffic of the corresponding cell in each grid may be multiplied by the packet loss rate of the corresponding cell, so as to obtain the perceptibility of the corresponding cell in each grid.
Step 205: and determining the azimuth angle of the base station antenna corresponding to each cell based on the position of the coverage center of each cell and the position of the corresponding base station.
Illustratively, based on the position of the coverage center of each cell and the position of the corresponding base station, the direction from the coverage center of the corresponding base station of each cell is determined as: a main beam direction of a base station antenna corresponding to each cell; and determining the azimuth angle of the base station antenna corresponding to each cell based on the main beam direction of the base station antenna corresponding to each cell.
For example, the direction from the base station corresponding to the a cell to the coverage center of the a cell may be determined as: a, a main beam direction of a base station antenna corresponding to a cell; and determining the azimuth angle of the base station antenna corresponding to the cell A based on the main beam direction of the base station antenna corresponding to the cell A.
In the technical scheme provided by the embodiment of the invention, a method for determining the azimuth angle of a base station antenna in a rural scene suitable for cell traffic flow distribution can be provided, specifically, an MR sampling point is positioned based on the time advance of MR data and the arrival angle of the antenna, and a map grid where the MR sampling point is located is determined according to the position information of the MR sampling point; the method comprises the steps of taking the number of MR sampling points contained in each grid as weight to evaluate the cell service flow of the grid, evaluating the service quality of a corresponding cell in the grid according to the average packet loss rate of the corresponding cell in each grid, carrying out weighted average on position coordinates of a central point of each grid according to the evaluated cell service flow and the evaluated cell service quality to obtain the position of a coverage center of each cell, and finally determining the azimuth angle parameter value of a base station antenna of the corresponding cell according to the position of the coverage center of each cell.
Compared with the prior art, the embodiment of the invention has the following advantages:
1) the precision of the azimuth angle parameter value is higher; the embodiment of the invention does not depend on the precision of the map and the propagation model, and the output azimuth angle parameter is more consistent with the actual network condition based on the measured data, and the parameter setting precision is higher.
2) The efficiency of network coverage is better; the embodiment of the invention aims the main coverage direction to the place with large service flow and poor service perception based on the geographical distribution of the flow and considering the place actually needed to be covered by the cell, thereby improving the efficiency of network coverage.
Second embodiment
To further illustrate the object of the present invention, the first embodiment of the present invention is further illustrated.
A second embodiment of the present invention provides a method for determining an azimuth angle of a base station antenna, which may be implemented by using a device for determining an azimuth angle of a base station antenna.
Fig. 3 is a schematic diagram of a first component structure of an apparatus for determining an azimuth angle of a base station antenna according to an embodiment of the present invention, as shown in fig. 3, the apparatus includes: the functions and functions of the data analysis module 301, the MR localization and gridding module 302, the gridding evaluation module 303, the coverage direction generation module 304, and the azimuth parameter value output module 305 are described below, respectively.
1. Data analysis module
A data analysis module 301, configured to obtain MR data and cell parameters; here, the cell operation parameter may be Global System for Mobile communications (GSM) cell operation parameter, Time Division-Synchronous Code Division Multiple Access (TD-SCDMA) cell operation parameter, Long Term Evolution (LTE) cell operation parameter, and the like, and the cell operation parameter generally includes the following information: base station name, Cell name, base station number (eNodeBID), Cell Identity (CI), Cell longitude, Cell latitude, azimuth of base station antenna, Cell traffic, and the like.
Here, the manner of acquiring MR data has already been described in the first embodiment of the present invention, and is not described here again.
The data analysis module 301 is configured to analyze the cell parameters and the MR data to obtain multiple fields, values and uses of each field, and place analysis results in units of cells.
For example, the fields obtained by the data parsing module through parsing include: the ue includes enodeb corresponding to a serving cell, CI of the serving cell, reference signal received power (mr. ltescrsrp) measured in the serving cell, Time advance (mr. ltesctadv) measured by the serving cell, antenna arrival angle (mr. ltescaoa) of a base station corresponding to the serving cell, uplink packet loss rate (mr. ltescplrulqcix) of the serving cell, and downlink packet loss rate (mr. ltescplrdqcix) of the serving cell, where the serving cell may be a GSM serving cell, a TD-SCDMA serving cell, a Time Division duplex Long Term Evolution (TD-LTE, Time Division duplex Long Term Evolution) serving cell, and the like.
Table 1 exemplarily illustrates a parsing result of the data parsing module.
TABLE 1
2. MR localization and gridding module
In some scenes such as rural scenes, due to the fact that the terrain is wide, buildings are sparse, most wireless signals are transmitted in line of sight, reflection, diffraction and the like do not exist or rarely exist, signal transmission time and distance form a linear relation, and the positioning method is particularly suitable for positioning by adopting time advance and antenna arrival angles.
Specifically, the MR positioning and grid module 302 is configured to calculate a distance d from each MR sampling point to the base station based on a timing advance corresponding to each MR sampling point in the MR data; obtaining the direction of the corresponding MR sampling point relative to the base station based on the antenna arrival angle corresponding to each MR sampling point in the MR data; and obtaining the position information of the corresponding MR sampling point according to the distance d from the corresponding MR sampling point to the base station and the direction of the corresponding MR sampling point relative to the base station.
Here, the direction of the corresponding MR sampling point with respect to the base station may be represented by an azimuth angle θ of the MR sampling point with respect to the base station, and the range of the azimuth angle θ is [0,2 π ].
In practical implementation, the vector (d, θ) can be obtained based on the distance d from the corresponding MR sampling point to the base station and the azimuth angle θ of the corresponding MR sampling point relative to the base station; and then, taking the coordinates of the base station as reference to obtain the position information of the corresponding MR sampling point.
The MR localization and grid module 302 is further configured to determine a grid where each MR sample point is located in a map divided into a plurality of grids based on the position information of each MR sample point.
The following describes implementation of the following processes: calculating the distance between the MR sampling points and the base station, obtaining the azimuth angles of the MR sampling points relative to the base station, obtaining the position information of the MR sampling points, and determining the grids where each MR sampling point is located.
1) Calculating the distance from the MR sampling point to the base station
In actual implementation, a value of an mr.ltesctadv field in the MR data indicates a time advance corresponding to an MR sampling point, where the mr.ltesctadv field may be defined as a time for the UE to adjust Uplink transmission of its primary serving cell on a Physical Uplink Control Channel (PUCCH)/Physical Uplink Shared Channel (PUSCH)/Channel Sounding Reference Signal (SRS), and the mr.ltesctadv field reflects a Signal propagation time from the UE to the base station and is a main index reflecting a distance between the UE and the base station.
In a specific implementation manner, a distance corresponding to one Ts is first calculated, where Ts is a minimum time unit of the TD-LTE system, where 1Ts is 1/(15000 × 2048) s, and the distance corresponding to 1Ts is:
(3*108*1/15000*2048))/2＝4.89m
that is, considering the sum of the uplink and downlink paths, the distance corresponding to 1Ts is equal to half the product of the propagation speed (light speed) and the distance corresponding to 1 Ts.
Then, the distances corresponding to 1Tadv are calculated, where 1Tadv is 16Ts 16 × 4.89m 78.12m, where 1Tadv represents the distance corresponding to 1 Tadv.
Finally, the distance d from the MR sample point to the base station is obtained, d is mr.ltesctaddv × 78.12m, where mr.ltesctaddv denotes the value of the mr.ltesctaddv field.
2) And obtaining the azimuth angle of the MR sampling point relative to the base station.
An MR.LtescAOA field in the MR data is defined as an estimated angle of UE relative to a measurement reference direction, and the measurement reference direction is the true north direction of the base station; here, the azimuth angle θ of the MR sampling point with respect to the base station can be calculated by the following formula:
θ＝360-MR.LteScAOA/2
wherein, mr. ltescaoa denotes the value of the mr. ltescaoa field.
3) And obtaining the position information of the MR sampling points.
Fig. 4 is a schematic diagram of the position of the MR sampling point relative to the base station in the embodiment of the present invention, and as shown in fig. 4, (d, θ) represents a two-dimensional polar coordinate of the MR sampling point relative to the base station; converting the two-dimensional polar coordinates (d, theta) into coordinates under a rectangular coordinate system, and specifically, setting the coordinates of the base station under the rectangular coordinate system as (x)0，y0) The coordinates of the MR sampling point in the rectangular coordinate system are (x ', y'), where x ═ x0+dsinθ，y’＝y0+dcosθ。
4) Determining the grid in which each MR sample lies
Fig. 5 is a schematic diagram of a position relationship between an MR sampling point and a grid according to an embodiment of the present invention, and as shown in fig. 5, a three-dimensional map or a two-dimensional map may be divided into a plurality of square grids having the same size, and a side length of each square grid is denoted as L.
After the grid is divided, the divided grid chalks can be marked as 1 st to nth grids, wherein n represents the total number of the divided grids; the coordinate of the center point of the ith grid is marked as Gi(x, y), i ═ 1,2, … n; here, the size of each grid can be defined, for example, for a rural scene, the side length of the grid is 20m, obviously, one MR sampling point will fall into one grid, referring to fig. 5, the black point represents the MR sampling point, here, if the cell of the cell in which one MR sampling point of the ith grid is located is identified as a, the cell in which the MR sampling point is located can be recorded as a
Here, the cell identity may include eNodeBID and CI.
3. Grid evaluation module
The data of the MR samples in the geographical grid indicate the presence of traffic at the geographical location and the wireless environment at the geographical location. According to the related communication protocol, in the service process, the UE measures the wireless environment and periodically reports MR data to the base station (the period can be defined, generally 5 seconds), so that the more times the service is performed and the longer the duration is, the more MR data is reported, and the higher the probability of the service traffic is; therefore, the number of the MR sampling points contained in the grid can be used as the weight to distribute the cell service flow into the grid, and the geography of the flow can be completed.
Specifically, the grid evaluation module 303 is configured to obtain the traffic flow of the corresponding cell in each grid based on the number of MR sampling points located in the corresponding cell in each grid, the number of MR sampling points of the corresponding cell, and the traffic flow of the corresponding cell; obtaining the packet loss rate of the corresponding cell in each grid based on the number of the MR sampling points of the corresponding cell in each grid, the uplink packet loss rate of each MR sampling point of the corresponding cell in each grid and the downlink packet loss rate of each MR sampling point of the corresponding cell in each grid; and obtaining the perceptibility of the corresponding cell in each grid based on the service flow and the packet loss rate of the corresponding cell in each grid.
For example, the traffic flow of cell a in the ith grid can be derived according to the following formula:
wherein the content of the first and second substances,
the service flow of the cell A in the ith grid is represented, i is a natural number less than or equal to n, and n represents the total number of the divided grids;
represents the total number of MR sample points in the cell a in the ith grid,
number of MR sampling points, T, representing cell AAIndicating the traffic flow of cell a.
The packet loss rate of the cell a in the ith grid can be obtained according to the following formula:
wherein the content of the first and second substances,
the packet loss rate of the cell A in the ith grid is represented, i is a natural number less than or equal to n, and n represents the total number of the divided grids; LteScPlrULQciX(s) represents the uplink packet loss rate of the s < th > MR sampling point in the A cell in the i < th > grid, and s is less than or equal to
The number of the first and second images,
representing the number of MR sampling points in the cell A in the ith grid; ltecscplrdlqcix(s) indicates the downlink packet loss rate at the s-th MR sample point in the a cell in the i-th grid.
In a specific implementation, grids may be evaluated by using grid perceptibility, where the service traffic of the corresponding cell in each grid may be multiplied by the packet loss rate of the corresponding cell to obtain the perceptibility of the corresponding cell in each grid.
For example, the perceptibility of cell a in the ith grid is:
wherein the content of the first and second substances,
indicating the perceptibility of a-cells in the ith grid.
4. Coverage direction generation module
It can be understood that, the larger the perceptibility of a cell in any grid is, the better the grid should be to preferentially cover, and based on this basic idea, the coverage direction generating module calculates the main beam direction of the base station antenna corresponding to each cell (i.e. the main coverage direction of the cell) according to the perceptibility of the grid.
Specifically, the coverage direction generating module 304 is specifically configured to perform weighted average calculation on the position coordinates of the center point of each grid by using the perceptibility of the corresponding cell in each grid, so as to obtain the position coordinates of the coverage center of the corresponding cell; based on the position of the coverage center of each cell and the position of the corresponding base station, determining the direction from the base station corresponding to each cell to the coverage center as follows: the main beam direction of the base station antenna corresponding to each cell.
Here, the position coordinates may be expressed in latitude and longitude.
For example, taking a cell as an example, m grids include MR sampling points at the cell a, that is, the MR sampling points at the cell a correspond to the m gridsM is greater than or equal to 1; in the m grids, the longitude and latitude of the center of the jth grid are Gj(x, y), j is a natural number less than or equal to m; the perceptibility of the A cell in the jth grid is
And calculating the longitude and latitude coordinates CenA (x, y) of the coverage center of the cell A by taking the grid perceptibility as a weight according to the following formula:
wherein the content of the first and second substances,
fig. 6 is a schematic diagram of a main beam direction of a base station antenna corresponding to a cell a in the embodiment of the present invention, where as shown in fig. 6, black dots indicate MR sampling points, a (x)0，y0) And expressing longitude and latitude coordinates of a base station corresponding to the cell A, and CenA (x, y) expressing the longitude and latitude coordinates of the coverage center of the cell A.
Referring to fig. 6, after obtaining longitude and latitude coordinates CenA (x, y) of the coverage center of the cell a, the direction from the base station corresponding to the cell a to the coverage center of the cell a is determined as follows: the main beam direction of the base station antenna corresponding to the a cell, where the main beam direction of the base station antenna corresponding to the a cell is the main coverage direction of the a cell.
5. Azimuth angle parameter value output module
Specifically, the azimuth parameter value output module 305 is configured to determine an azimuth of a base station antenna corresponding to each cell based on a main beam direction of the base station antenna corresponding to each cell; and outputting the azimuth angle of the base station antenna corresponding to each cell.
In a specific implementation manner, the azimuth parameter value output module determines a direction vector from a base station corresponding to a cell to a coverage center of the cell, and further converts an azimuth represented by a radian in a rectangular coordinate system into an angle using a north direction of the base station as a reference direction, so as to obtain an azimuth parameter value of a base station antenna corresponding to the cell.
For example, the longitude and latitude coordinates of the base station corresponding to the B cell are (x0, y0), the longitude and latitude coordinates of the coverage center of the B cell are (x, y), and the radian R of the azimuth angle of the base station antenna corresponding to the B cell is determined, where R ═ pi/2-Arctan ((y-y0)/(x-x 0));
then, the radian R is converted into an angle, and an azimuth B of the base station antenna corresponding to the B cell can be obtained, where B is R × 180/pi.
It should be understood by those skilled in the art that the functions implemented by the modules in the apparatus for determining the azimuth angle of the base station antenna shown in fig. 3 can be understood by referring to the related description of the aforementioned method for determining the azimuth angle of the base station antenna. The functions of the modules of the apparatus for determining the azimuth angle of the base station antenna shown in fig. 3 may be implemented by a program running on a processor, or may be implemented by specific logic circuits.
In practical applications, the data analysis module 301, the MR positioning and grid module 302, the grid evaluation module 303, the coverage direction generation module 304, and the azimuth parameter value output module 305 may be implemented by a Central Processing Unit (CPU), a microprocessor Unit (MPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), or the like in a terminal.
Third embodiment
A third embodiment of the present invention provides an apparatus for determining an azimuth angle of a base station antenna, which is directed to a method for determining an azimuth angle of a base station antenna according to the first embodiment of the present invention.
Fig. 7 is a schematic diagram of a second component structure of an apparatus for determining an azimuth angle of a base station antenna according to an embodiment of the present invention, as shown in fig. 7, the apparatus includes: an acquisition module 701 and a determination module 702; wherein the content of the first and second substances,
an obtaining module 701, configured to obtain measurement report MR data, and obtain position information of each MR sampling point in the MR data and a cell where the MR sampling point is located;
a determining module 702, configured to determine, based on the position information of each MR sample point, a grid in which each MR sample point is located in a map in which a plurality of grids are divided; obtaining the service flow of the corresponding cell in each grid based on the number of MR sampling points in any cell in each grid; determining the position of a coverage center of a corresponding cell based on the obtained service flow; and determining the azimuth angle of the base station antenna corresponding to each cell based on the position of the coverage center of each cell and the position of the corresponding base station.
Specifically, the determining module 702 is configured to obtain the traffic flow of the corresponding cell in each grid based on the number of MR sampling points located in the corresponding cell in each grid, the total number of MR sampling points located in the corresponding cell, and the traffic flow of the corresponding cell.
The determining module 702 is configured to perform weighted average calculation on the position coordinates of the center point of each grid by using the service traffic of the corresponding cell in each grid, so as to obtain position coordinates of the coverage center of the corresponding cell; or, the service flow of the corresponding cell in each grid is utilized to obtain the perceptibility of the corresponding cell in each grid; carrying out weighted average calculation on the position coordinates of the central point of each grid by using the perceptibility of the corresponding cell in each grid to obtain the position coordinates of the coverage center of the corresponding cell; and the perceptibility of the corresponding cell in each grid is positively correlated with the service flow of the corresponding cell in each grid.
Further, the determining module 702 is further configured to obtain a packet loss rate of a corresponding cell in each grid after determining the grid where each MR sampling point is located;
correspondingly, the determining module 702 is specifically configured to determine the perceptibility of the corresponding cell in each grid based on the service traffic of the corresponding cell in each grid and the packet loss rate of the corresponding cell in each grid, and perform weighted average calculation on the position coordinates of the center point of each grid by using the perceptibility of the corresponding cell in each grid to obtain the position coordinates of the coverage center of the corresponding cell; and the perceptibility of the corresponding cell in each grid is positively correlated with the service flow of the corresponding cell in each grid, and positively correlated with the packet loss rate of the corresponding cell in each grid.
Specifically, the determining module 702 is configured to determine, based on the position of the coverage center of each cell and the position of the corresponding base station, a direction from the base station corresponding to each cell to the coverage center as: a main beam direction of a base station antenna corresponding to each cell; and determining the azimuth angle of the base station antenna corresponding to each cell based on the main beam direction of the base station antenna corresponding to each cell.
It should be understood by those skilled in the art that the functions implemented by the modules in the apparatus for determining the azimuth angle of the base station antenna shown in fig. 7 can be understood by referring to the related description of the method for determining the azimuth angle of the base station antenna. The functions of the modules of the apparatus for determining the azimuth angle of the base station antenna shown in fig. 7 may be implemented by a program running on a processor, or may be implemented by specific logic circuits.
In practical applications, the obtaining module 701 and the determining module 702 may be implemented by a Central Processing Unit (CPU), a microprocessor Unit (MPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), or the like in the terminal.
The technical schemes described in the embodiments of the present invention can be combined arbitrarily without conflict.
In the embodiments provided in the present invention, it should be understood that the disclosed method and intelligent device may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one second processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention.
Claims (6)
1. A method of determining an azimuth angle of a base station antenna, the method comprising:
acquiring measurement report MR data, and acquiring position information of each MR sampling point in the MR data and a cell where the MR sampling point is located;
determining a grid where each MR sampling point is located in a map dividing a plurality of grids based on the position information of each MR sampling point;
obtaining the service flow of the corresponding cell in each grid based on the number of MR sampling points in any cell in each grid;
determining the position of a coverage center of a corresponding cell based on the obtained service flow;
wherein the determining the position of the coverage center of the corresponding cell based on the obtained traffic flow comprises: multiplying the service flow of the corresponding cell in each grid by the packet loss rate of the corresponding cell to obtain the perceptibility of the corresponding cell in each grid; taking each grid perceptibility of the corresponding cell as a weight, and carrying out weighted average calculation on the position coordinates of the central point of each grid to obtain the position coordinates of the coverage center of the corresponding cell; the perceptibility of the corresponding cell in each grid is positively correlated with the service flow of the corresponding cell in each grid, and is positively correlated with the packet loss rate of the corresponding cell in each grid;
and determining the azimuth angle of the base station antenna corresponding to each cell based on the position of the coverage center of each cell and the position of the corresponding base station.
2. The method of claim 1, wherein deriving the traffic flow of the corresponding cell in each grid based on the number of MR samples in any one cell in each grid comprises: and obtaining the service flow of the corresponding cell in each grid based on the number of the MR sampling points in the corresponding cell in each grid, the total number of the MR sampling points in the corresponding cell and the service flow of the corresponding cell.
3. The method of claim 1, wherein determining the azimuth angle of the base station antenna corresponding to each cell based on the position of the coverage center of each cell and the position of the corresponding base station comprises:
based on the position of the coverage center of each cell and the position of the corresponding base station, determining the direction from the base station corresponding to each cell to the coverage center as follows: a main beam direction of a base station antenna corresponding to each cell; and determining the azimuth angle of the base station antenna corresponding to each cell based on the main beam direction of the base station antenna corresponding to each cell.
4. An apparatus for determining an azimuth angle of a base station antenna, the apparatus comprising an acquisition module and a determination module; wherein the content of the first and second substances,
the acquisition module is used for acquiring measurement report MR data and acquiring the position information of each MR sampling point in the MR data and the cell in which the MR sampling point is positioned;
the determining module is used for determining a grid where each MR sampling point is located in a map which is divided into a plurality of grids based on the position information of each MR sampling point; obtaining the service flow of the corresponding cell in each grid based on the number of MR sampling points in any cell in each grid; determining the position of a coverage center of a corresponding cell based on the obtained service flow; determining the azimuth angle of the base station antenna corresponding to each cell based on the position of the coverage center of each cell and the position of the corresponding base station;
the determining module is specifically configured to multiply the service traffic of the corresponding cell in each grid by the packet loss rate of the corresponding cell to obtain the perceptibility of the corresponding cell in each grid; taking each grid perceptibility of the corresponding cell as a weight, and carrying out weighted average calculation on the position coordinates of the central point of each grid to obtain the position coordinates of the coverage center of the corresponding cell; and the perceptibility of the corresponding cell in each grid is positively correlated with the service flow of the corresponding cell in each grid, and positively correlated with the packet loss rate of the corresponding cell in each grid.
5. The device according to claim 4, wherein the determining module is specifically configured to derive the traffic flow of the corresponding cell in each grid based on the number of MR sampling points in the corresponding cell in each grid, the total number of MR sampling points in the corresponding cell, and the traffic flow of the corresponding cell.
6. The apparatus according to claim 4, wherein the determining module is specifically configured to determine, based on the location of the coverage center of each cell and the location of the corresponding base station, a direction from the base station corresponding to each cell to the coverage center as: a main beam direction of a base station antenna corresponding to each cell; and determining the azimuth angle of the base station antenna corresponding to each cell based on the main beam direction of the base station antenna corresponding to each cell.
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