CN107466043B - A method and device for determining the azimuth angle of a base station antenna - Google Patents

Abstract

The invention discloses a method and device for determining the azimuth angle of a base station antenna. The method includes: acquiring MR data, and acquiring the location information and the cell where each MR sampling point in the MR data is located; based on each MR The location information of sampling points, in the map divided into multiple grids, determine the grid where each MR sampling point is located; based on the number of MR sampling points in any cell in each grid, we can get Calculate the service flow of the corresponding cell in each grid; determine the location of the coverage center of the corresponding cell based on the obtained service flow; determine the base station corresponding to each cell based on the location of the coverage center of each cell and the location of the corresponding base station Azimuth of the antenna.

Description

A method and device for determining the azimuth angle of a base station antenna

technical field

The present invention relates to the field of wireless mobile network planning and optimization, in particular to a method and device for determining the azimuth angle of a base station antenna.

Background technique

As the boom of mobile Internet hits rural areas, the rural market has become a new blue ocean for mobile operators, and 4G network construction continues to extend to rural areas. However, due to the vast area of rural areas, it is impossible for operators to build networks like urban areas. In the same way to achieve high-density seamless coverage, when performing network coverage, it is necessary to ensure that the places where users are relatively concentrated can be covered, so coverage optimization is very important.

In coverage optimization, the azimuth angle of the base station antenna is a very important parameter. The azimuth angle of the base station antenna determines the main coverage direction of the cell; adjusting the azimuth angle of the base station antenna can change the main coverage direction of the cell and enhance the signal in the main coverage direction. It can also reduce overlapping coverage, reduce network interference, and improve service quality.

At present, the setting of the azimuth angle of the base station antenna mainly comes from the planning scheme, that is, the azimuth angle parameter value is output through the coverage simulation in the network planning stage, and the azimuth angle is set according to the given azimuth angle when the base station antenna is installed.

FIG. 1 is a schematic flowchart of a method for setting an antenna azimuth of a base station in the prior art. As shown in FIG. 1 , the process includes:

Step 101: Collect network planning data.

Here, the network planning data includes a map, a site list of base stations, a cell list, and road test data; the site list of base stations includes latitude and longitude information of the base station, and the cell list includes latitude and longitude of cells and preset antenna parameters.

Step 102: Select and correct the propagation model.

Exemplarily, by examining the field environment, a wireless propagation model suitable for the geographical environment is selected, and the model is calibrated with road test data.

Step 103: Network planning simulation and pre-optimization.

Exemplarily, network planning simulation is performed, and under the set network coverage target, the parameters of the base station antenna are pre-optimized.

Step 104: Determine whether the planned network reaches the network coverage target, if so, skip to step 105, otherwise, return to step 103, and continue to perform simulation and pre-optimization.

Step 105: Output the network planning scheme.

Here, the output network planning scheme includes the pre-optimization results of the parameters of the base station antennas.

Step 106: Obtain the azimuth angle setting value of the base station antenna from the network planning scheme.

Here, after the azimuth angle setting value of the base station antenna is obtained, when the base station antenna is installed, the installation can be performed according to the azimuth angle setting value of the base station antenna.

The method for setting the antenna azimuth of the base station described above has the following shortcomings or deficiencies:

1) The azimuth parameter value has low precision. The parameter value of the antenna azimuth angle depends on the simulation accuracy of the network planning, and the simulation accuracy is limited by the map accuracy and the propagation model. Usually, there is a large error with the actual situation. Therefore, the parameter value of the azimuth angle of the base station antenna does not reach the expected coverage. scope.

2) It will reduce the network coverage efficiency. Because the network planning simulation does not consider the actual traffic distribution of the existing network, and simply meets the network coverage as the goal, the main coverage direction of the base station antenna will deviate from the traffic concentration area, resulting in no coverage or poor coverage where there is traffic that needs to be concentrated. Areas with less or no traffic have good coverage, which reduces network coverage efficiency and wastes coverage resources.

SUMMARY OF THE INVENTION

In order to solve the above technical problem, the embodiments of the present invention provide a method and device for determining the azimuth angle of the base station antenna, which can improve the setting accuracy of the azimuth angle of the base station antenna and the network coverage efficiency.

An embodiment of the present invention provides a method for determining an azimuth angle of a base station antenna, the method comprising:

Obtain measurement report (MR, Measurement Report) data, and obtain the location information of each MR sampling point in the MR data and the cell where it is located;

Based on the position information of each MR sampling point, in the map divided into multiple grids, determine the grid where each MR sampling point is located;

Based on the number of MR sampling points in any cell in each grid, the service flow of the corresponding cell in each grid is obtained;

Based on the obtained traffic flow, determine the location of the coverage center of the corresponding cell;

Based on the location of the coverage center of each cell and the location of the corresponding base station, the azimuth angle of the base station antenna corresponding to each cell is determined.

In the above solution, the business flow of the corresponding cell in each grid is obtained based on the number of MR sampling points in any cell in each grid, including: based on the number of MR sampling points in the corresponding cell in each grid. The number of MR sampling points, the total number of MR sampling points in the corresponding cell, and the service flow of the corresponding cell, the service flow of the corresponding cell in each grid is obtained.

In the above scheme, the determination of the location of the coverage center of the corresponding cell based on the obtained service flow includes:

Using the business traffic of the corresponding cell in each grid, the position coordinates of the center point of each grid are calculated by weighted average, and the position coordinates of the coverage center of the corresponding cell are obtained;

Or, use the traffic flow of the corresponding cell in each grid to obtain the perception degree of the corresponding cell in each grid; use the perception degree of the corresponding cell in each grid to determine the position of the center point of each grid The coordinates are weighted and averaged to obtain the location coordinates of the coverage center of the corresponding cell; the perception degree of the corresponding cell in each grid is positively correlated with the service flow of the corresponding cell in each grid.

In the above solution, 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, determining the location of the coverage center of the corresponding cell based on the obtained service flow includes: determining the corresponding cell based on the service flow of the corresponding cell in each grid and the packet loss rate of the corresponding cell in each grid. The perception degree of the cell in each grid, using the perception degree of the corresponding cell in each grid, the weighted average calculation of the position coordinates of the center point of each grid is performed to obtain the position coordinates of the coverage center of the corresponding cell; The perception degree 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.

In the above scheme, the azimuth angle of the base station antenna corresponding to each cell is determined based on the location of the coverage center of each cell and the location of the corresponding base station, including:

Based on the location of the coverage center of each cell and the location of the corresponding base station, the direction from the base station corresponding to each cell to the coverage center is determined as: the main beam direction of the base station antenna corresponding to each cell; The main beam direction of the antenna determines the azimuth angle of the base station antenna corresponding to each cell.

An embodiment of the present invention provides a device for determining the azimuth angle of a base station antenna, the device includes an acquisition module and a determination module; wherein,

The acquisition module is used to acquire the MR data of the measurement report, and to acquire the location information of each MR sampling point in the MR data and the cell where it is located;

The determining module is used to determine the grid where each MR sampling point is located in the map divided into multiple grids based on the position information of each MR sampling point; based on the location of each MR sampling point in any cell According to the number of MR sampling points, the service flow of the corresponding cell in each grid is obtained; based on the obtained service flow, the location of the coverage center of the corresponding cell is determined; based on the location of the coverage center of each cell and the corresponding base station position, determine the azimuth angle of the base station antenna corresponding to each cell.

In the above scheme, the determining module is specifically configured to obtain each grid based on the number of MR sampling points in the corresponding cell, the total number of MR sampling points in the corresponding cell, and the traffic flow of the corresponding cell. The service traffic of the corresponding cell in each grid.

In the above solution, 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 traffic flow of the corresponding cell in each grid to obtain the position coordinates of the coverage center of the corresponding cell; Or, use the traffic flow of the corresponding cell in each grid to obtain the perception degree of the corresponding cell in each grid; use the perception degree of the corresponding cell in each grid to determine the position of the center point of each grid The coordinates are weighted and averaged to obtain the location coordinates of the coverage center of the corresponding cell; the perception degree 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 the packet loss rate of the corresponding cell in each grid after determining the grid where each MR sampling point is located;

Correspondingly, the determining module is specifically configured to determine the perception degree of the corresponding cell in each grid based on the traffic flow of the corresponding cell in each grid and the packet loss rate of the corresponding cell in each grid, using Corresponding to the perception degree of the cell in each grid, the weighted average calculation is performed on the position coordinates of the center point of each grid to obtain the position coordinates of the coverage center of the corresponding cell; the perception of the corresponding cell in each grid The degree is positively correlated with the traffic flow of the corresponding cell in each grid, and is positively correlated with the packet loss rate of the corresponding cell in each grid.

In the above solution, the determining module is specifically configured to determine the direction from the base station corresponding to each cell to the coverage center based on the position of the coverage center of each cell and the position of the corresponding base station as: the base station antenna corresponding to each cell. Based on the main beam direction of the base station antenna corresponding to each cell, the azimuth angle of the base station antenna corresponding to each cell is determined.

In the technical solution of the embodiment of the present invention, MR data is acquired, and the location information of each MR sampling point in the MR data and the cell where it is located are acquired; based on the location information of each MR sampling point, a plurality of grids are divided Determine the grid where each MR sampling point is located in the map of The obtained traffic flow determines the location of the coverage center of the corresponding cell; based on the location of the coverage center of each cell and the location of the corresponding base station, the azimuth angle of the base station antenna corresponding to each cell is determined; thus, the embodiment of the present invention does not depend on Due to the accuracy of the map and the propagation model, and based on the measured data, the output azimuth parameter is more in line with the actual situation of the network, and the parameter setting accuracy is higher; the embodiment of the present invention is based on the geographic distribution of traffic, and takes into account the places that the cell actually needs to cover, The main coverage direction is aimed at places with large service traffic and poor service perception, thereby improving the efficiency of network coverage.

Description of drawings

1 is a schematic flowchart of a method for setting an antenna azimuth of a base station in the prior art;

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;

3 is a schematic structural diagram of a first composition of a device 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 in an embodiment of the present invention;

5 is a schematic diagram of the positional relationship between MR sampling points and grids according to an embodiment of the present invention;

6 is a schematic diagram of a main beam direction of a base station antenna corresponding to cell A according to an embodiment of the present invention;

FIG. 7 is a schematic diagram of a second composition structure of a device for determining an azimuth angle of a base station antenna according to an embodiment of the present invention.

Detailed ways

In order to understand the features and technical contents of the embodiments of the present invention in more detail, the implementation of the embodiments of the present invention will be described in detail below with reference to the accompanying 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: Acquire measurement report (MR, Measurement Report) data, and acquire the location information and the cell where each MR sampling point in the MR data is located.

Here, the MR sampling point represents the location where the user equipment (UE, User Equipment) is located; the cell where the MR sampling point is located represents the serving cell of the UE corresponding to the MR sampling point. In a Long Term Evolution (LTE, Long Term Evolution) system, the cell where the MR sampling point is located may represent the primary serving cell or the secondary serving cell of the UE corresponding to the MR sampling point.

In actual implementation, MR data can be obtained from a network management system (NMS, Network Management System); specifically, the terminal and the base station measure and periodically report to the NMS during the service process, and the MR data reflects the presence of the service at the location of the UE. and the authenticity of the wireless environment, here, the base station may be an evolved base station (eNB, eNodeB).

Exemplarily, obtaining the cell where each MR sampling point in the MR data is located may include: determining, according to the cell identifier of the serving cell of the UE corresponding to each MR sampling point, where each MR sampling point in the MR data is located. in the neighborhood.

Exemplarily, deriving the position information of each MR sampling point in the MR data may include: based on the timing advance (Tadv, Timing Advance) and the antenna angle-of-arrival (AOA, Angle-of- ) of each MR sampling point in the MR data Arrival) to obtain the location information of the corresponding MR sampling points.

In a specific implementation manner, based on the timing advance and the antenna arrival angle of each MR sampling point in the MR data, the position information of the corresponding MR sampling point is obtained, including:

Based on the time advance corresponding to each MR sampling point in the MR data, the distance from the corresponding MR sampling point to the base station is obtained; based on the antenna arrival angle corresponding to each MR sampling point in the MR data, the corresponding MR sampling point relative to the base station is obtained. 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, the position information of the corresponding MR sampling point is obtained.

Here, the direction of the MR sampling point relative to the base station can be represented by the azimuth angle of the MR sampling point relative to the base station. The azimuth angle represents the horizontal angle between the clockwise direction line and the target direction line from the north direction line of a certain point. , that is to say, the azimuth angle of the MR sampling point relative to the base station is used to represent: the horizontal included angle between the direction line of the MR sampling point in a clockwise direction from the true north direction line of the base station, the direction line of the MR sampling point Refers to the connection between the MR sampling point and the base station. In the embodiment of the present invention, the value range of the azimuth angle is [0, 2π].

Here, after 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 are obtained, based on the location information of the base station, the distance from the corresponding MR sampling point to the base station, and the corresponding MR sampling point relative to the base station direction to obtain the position information of the corresponding MR sampling point, so as to complete the positioning of the MR sampling point.

Step 202: Based on the position information of each MR sampling point, in the map divided into multiple grids, determine the grid where each MR sampling point is located.

In actual implementation, the map is firstly divided into multiple grids according to the preset division strategy. Preferably, the size of each grid can be the same or different; the shape of each grid can be a rectangle, a diamond, a fan, etc. Wait. The map here is the scene map corresponding to the MR data, and the map here may be a two-dimensional map or a three-dimensional map.

It can be seen that, among the divided grids, each grid represents a geographic area. In this way, based on the position information of each MR sampling point, the grid where each MR sampling point is located can be determined.

Step 203: Based on the number of MR sampling points located in any cell in each grid, the service flow of the corresponding cell in each grid is obtained.

Further, before this step, it is also necessary to obtain the number of MR sampling points in each cell in each grid based on the cell where each MR sampling point is located in the MR data; that is, for For each grid, there may be no MR sampling point, there may be one MR sampling point, or there may be multiple MR sampling points; if there are MR sampling points in a grid, each MR sampling point in the MR data can be The cell where it is located, the cell where each MR sampling point in the grid is located is determined.

Exemplarily, the 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 includes: based on the number of MR sampling points in the corresponding cell in each grid The number of MR sampling points, the total number of MR sampling points in the corresponding cell, and the service flow of the corresponding cell, the service flow of the corresponding cell in each grid is obtained.

In an implementation manner, the service flow of the corresponding cell in the i-th grid can be obtained according to the following formula:

T _Gi =C _Gi /C _all *T

Among them, T _Gi represents the service flow of the corresponding cell in the ith grid, i is a natural number less than or equal to n, n represents the total number of divided grids; C _Gi represents the MR in the corresponding cell in the ith grid The number of sampling points, C _all represents the sum of the MR sampling points of the corresponding cell, and T represents the service flow of the corresponding cell.

Further, based on the number of MR sampling points located in any cell in each grid, the packet loss rate of the corresponding cell in each grid can be obtained.

Exemplarily, the number of MR sampling points located in any cell in each grid, to obtain the packet loss rate of the corresponding cell in each grid, including: based on the MR located in the corresponding cell in each grid The number of sampling points, the uplink packet loss rate of each MR sampling point located in the corresponding cell in each grid, and the downlink packet loss rate of each MR sampling point located in the corresponding cell in each grid, obtain each The packet loss rate of the corresponding cell in the grid.

Here, the uplink packet loss rate of each MR sampling point is used to indicate the 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 the packet loss rate when the corresponding base station transmits data to the UE In actual implementation, the uplink packet loss rate and downlink packet loss rate of the MR sampling point can be obtained from the MR data.

In an implementation manner, the packet loss rate of the corresponding cell in the i-th grid can be obtained according to the following formula:

Among them, P _Gi represents the packet loss rate of the corresponding cell in the ith grid, i is a natural number less than or equal to n, and n represents the total number of divided grids; ULQciX(s) represents the corresponding cell in the ith grid. Uplink packet loss rate of the s-th MR sampling point of the cell, s is a natural number less than or equal to C _Gi , C _Gi represents the number of MR sampling points in the corresponding cell in the i-th grid; DLQciX(s) represents the The downlink packet loss rate of the s-th MR sampling point in the corresponding cell in the i grids.

It can be understood that, for the same cell, the number of MR sampling points in each grid and the packet loss rate respectively represent the service traffic size and service quality of the grid; here, the MR of the same cell in a grid The greater the number of sampling points, the greater the traffic flow of the cell corresponding to the grid; otherwise, the smaller the traffic flow of the cell corresponding to the grid; the greater the packet loss rate of the corresponding cell in each grid, the grid The poorer the service quality of the cell corresponding to the grid, on the contrary, the better the service quality of the cell corresponding to the grid.

Obviously, if the service traffic of the corresponding cell in a grid is larger and the packet loss rate of the corresponding cell is larger, it means that the grid is a grid with concentrated service traffic in the cell and poor user perception. covered area.

Step 204: Determine the location of the coverage center of the corresponding cell based on the obtained traffic flow.

Exemplarily, the following three ways can be used to determine the location of the coverage center of the corresponding cell.

The first implementation

The position coordinates of the coverage center of the corresponding cell can be obtained by performing a weighted average calculation on the position coordinates of the center point of each grid by using the service flow of the corresponding cell in each grid.

The second implementation

The service flow of the corresponding cell in each grid can be used to obtain the perception degree of the corresponding cell in each grid; using the perception degree of the corresponding cell in each grid, the position coordinates of the center point of each grid can be obtained A weighted average calculation is performed to obtain the location coordinates of the coverage center of the corresponding cell.

Here, the perception degree of the corresponding cell in each grid is positively correlated with the traffic flow of the corresponding cell in each grid; for example, the perception degree of a cell in the i-th grid corresponds to the i-th grid The service flow of the cell is positively correlated; preferably, the perception degree of a cell in the ith grid is proportional to the service flow of the corresponding cell in the ith grid.

The third way of implementation

Based on the traffic flow of the corresponding cell in each grid and the packet loss rate of the corresponding cell in each grid, the perception degree of the corresponding cell in each grid can be determined, and the perception of the corresponding cell in each grid can be used. The weighted average calculation of the position coordinates of the center point of each grid is carried out to obtain the position coordinates of the coverage center of the corresponding cell.

The perception degree of the corresponding cell in each grid is positively correlated with the traffic flow of the corresponding cell in each grid, and is positively correlated with the packet loss rate of the corresponding cell in each grid; The service flow of the corresponding cell in the grid is multiplied by the packet loss rate of the corresponding cell to obtain the perception degree of the corresponding cell in each grid.

Step 205: Based on the location of the coverage center of each cell and the location of the corresponding base station, determine the azimuth angle of the base station antenna corresponding to each cell.

Exemplarily, based on the location of the coverage center of each cell and the location of the corresponding base station, the direction from the base station corresponding to each cell to the coverage center is determined as: the main beam direction of the base station antenna corresponding to each cell; The main beam direction of the base station antenna corresponding to the cell determines the azimuth angle of the base station antenna corresponding to each cell.

For example, the direction from the base station corresponding to cell A to the coverage center of cell A may be determined as: the main beam direction of the base station antenna corresponding to cell A; and the base station antenna corresponding to cell A is determined based on the main beam direction of the base station antenna corresponding to cell A azimuth angle.

In the technical solutions provided by the embodiments of the present invention, a method for determining the azimuth angle of a base station antenna in a rural scenario that adapts to cell service traffic distribution can be provided. The sampling points are located, and the map grid where the MR sampling points are located is determined according to the location information of the MR sampling points; the number of MR sampling points contained in each grid is used as the weight to evaluate the cell service traffic size of the grid. The average packet loss rate of the corresponding cell in each grid evaluates the service quality of the corresponding cell in the grid, and performs a weighted average of the position coordinates of the center point of each grid according to the estimated service traffic and service quality of the cell. The position of the coverage center of each cell is obtained, and finally, the azimuth angle parameter value of the base station antenna of the corresponding cell is determined according to the position of the coverage center of each cell.

Compared with the prior art, the embodiment of the present invention has the following advantages:

1) The azimuth parameter value has higher accuracy; the embodiment of the present invention does not depend on the accuracy of the map and the propagation model, and based on the measured data, the output azimuth parameter is more in line with the actual situation of the network, and the parameter setting accuracy is higher.

2) The efficiency of network coverage is better; in the embodiment of the present invention, based on the geographical distribution of traffic, taking into account where the cell actually needs to be covered, the main coverage direction is aimed at the place where the service traffic is large and the service perception is poor, thereby improving the network coverage. efficiency.

Second Embodiment

In order to better reflect the purpose of the present invention, further examples are given on the basis of the first embodiment of the present invention.

The second embodiment of the present invention provides a method for determining the azimuth angle of a base station antenna, and the method can be implemented by using a device for determining the azimuth angle of the base station antenna.

FIG. 3 is a schematic diagram of the first structure of a device for determining the azimuth angle of a base station antenna according to an embodiment of the present invention. As shown in FIG. 3 , the device includes: a data analysis module 301 , an MR positioning and grid module 302 , and a grid evaluation module 303 , the coverage direction generation module 304, the azimuth parameter value output module 305, 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 are respectively described below. The role and function are explained.

1. Data analysis module

The data parsing module 301 is used to obtain MR data and cell engineering parameters; here, the cell engineering parameters may be Global System for Mobile Communication (GSM, Global System for Mobile communication) cell engineering parameters, Time Division Synchronous Code Division Multiple Access (TD-SCDMA, Time Division-Synchronous Code Division Multiple Access) cell work parameters, Long Term Evolution (LTE, Long Term Evolution) cell work parameters, etc. The cell work parameters usually include the following information: base station name, cell name, base station number (eNodeBID), cell ID Code (CI, Cell Identity), cell longitude, cell latitude, azimuth angle of base station antenna, cell traffic and so on.

Here, the manner of acquiring the MR data has been described in the first embodiment of the present invention, and will not be repeated here.

The data analysis module 301 is used to analyze the cell parameters and MR data, obtain a number of fields and the value and purpose of each field, and place the analysis results in cell units.

For example, the fields obtained by the data parsing module include: the eNodeBID corresponding to the serving cell, the CI of the serving cell, the reference signal received power (MR.LteScRSRP) measured in the serving cell, and the timing advance measured by the serving cell. (MR.LteScTadv), the antenna angle of arrival of the base station corresponding to the serving cell (MR.LteScAOA), the uplink packet loss rate of the serving cell (MR.LteScPlrULQciX), the downlink packet loss rate of the serving cell (MR.LteScPlrDLQciX), here, the service The cell may be a GSM serving cell, a TD-SCDMA serving cell, a Time Division Duplexing Long Term Evolution (TD-LTE, Time Division Duplexing Long Term Evolution) serving cell, and the like.

Table 1 exemplifies the parsing results of the data parsing module.

Table 1

2. MR positioning and grid module

In some scenarios such as rural scenes, due to the open terrain and sparse buildings, most wireless signals are transmitted through line-of-sight, and there is no or little reflection, diffraction, etc. Therefore, the signal propagation time has a linear relationship with the distance, which is particularly It is suitable for positioning using timing advance and antenna arrival angle.

Specifically, the MR positioning and grid module 302 is used to calculate the distance d from the corresponding MR sampling point to the base station based on the time advance corresponding to each MR sampling point in the MR data; The direction of the corresponding MR sampling point relative to the base station is obtained; 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, the position information of the corresponding MR sampling point is obtained.

Here, the direction of the corresponding MR sampling point relative to the base station can be represented by the azimuth angle θ of the MR sampling point relative to the base station, and the value range of the azimuth angle θ is [0, 2π].

In actual 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 using the base station coordinates as a reference, the corresponding MR sampling can be obtained. location information of the point.

The MR positioning and grid module 302 is further configured to, based on the position information of each MR sampling point, determine the grid where each MR sampling point is located in the map divided into multiple grids.

The following describes the implementation of the following processes: calculating the distance from the MR sampling point to the base station, obtaining the azimuth angle of the MR sampling point relative to the base station, obtaining the location information of the MR sampling point, and determining the location of each MR sampling point. the grid at.

1) Calculate the distance from the MR sampling point to the base station

In actual implementation, the value of a MR.LteScTadv field in the MR data represents the timing advance corresponding to an MR sampling point. Here, the MR.LteScTadv field can be defined as a value used by the UE to adjust the physical uplink of its primary serving cell. Control Channel (PUCCH, Physical Uplink Control Channel) / Physical Uplink Shared Channel (PUSCH, Physical Uplink Shared Channel) / Channel Sounding Reference Signal (SRS, Sounding Reference Signal) uplink transmission time, the MR.LteScTadv field reflects the signal propagation from the UE to the base station Time is the main indicator reflecting the distance between the UE and the base station.

In a specific implementation, first calculate the distance corresponding to a Ts, where Ts is the smallest time unit of the TD-LTE system. Here, 1Ts=1/(15000*2048)s, and the distance corresponding to 1Ts is:

(3*10 ⁸ *1/15000*2048))/2＝4.89m

That is to say, considering the sum of the uplink and downlink paths, the distance corresponding to 1Ts is equal to half of the product of the propagation speed (speed of light) and the distance corresponding to 1Ts.

Then, the distance corresponding to one Tadv is calculated, 1Tadv=16Ts=16*4.89m=78.12m, where 1Tadv represents the distance corresponding to one Tadv.

Finally, the distance d from the MR sampling point to the base station is obtained, where d=MR.LteScTadv*78.12m, where MR.LteScTadv represents the value of the MR.LteScTadv field.

2) Obtain the azimuth angle of the MR sampling point relative to the base station.

A MR.LteScAOA field in the MR data is defined as the estimated angle of a UE relative to the measurement reference direction, and the measurement reference direction should be the true north direction of the base station; here, the azimuth angle of the MR sampling point relative to the base station can be calculated by the following formula theta:

θ=360-MR.LteScAOA/2

Among them, MR.LteScAOA represents the value of the MR.LteScAOA field.

3) Obtain the location information of the MR sampling point.

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. As shown in FIG. 4 , it can be seen that (d, θ) represents the two-dimensional polar coordinate of the MR sampling point relative to the base station; , θ), converted into coordinates in the rectangular coordinate system, specifically, if the coordinates of the base station in the rectangular coordinate system are (x ₀ , y ₀ ), then the coordinates of the MR sampling point in the rectangular coordinate system are (x', y'), where x'=x ₀ +dsinθ, y'=y ₀ +dcosθ.

4) Determine the grid where each MR sampling point is located

FIG. 5 is a schematic diagram of the positional relationship between MR sampling points and grids according to an embodiment of the present invention. As shown in FIG. 5 , a three-dimensional map or a two-dimensional map can be divided into multiple square grids with the same size. The side length is recorded as L.

这里，小区标识可以包括eNodeBID和CI。After dividing the grids, the divided grids can be written as the first grid to the nth grid, where n represents the total number of divided grids; the coordinates of the center point of the i-th grid are marked as G _i (x,y), i=1,2,...n; here, the size of each grid can be defined. For example, for rural scenes, the side length of the grid is 20m. Obviously, an MR sampling point will fall into a In the grid, referring to FIG. 5 , the black dots represent the MR sampling points. Here, if the cell identification of the cell where an MR sampling point of the i-th grid is located is A, the cell where the MR sampling point is located can be identified as A. marked as

Here, the cell identity may include eNodeBID and CI.

3. Grid evaluation module

The data of the MR sampling points in the geographic grid represents the presence of services at that geographic location and the wireless environment of that geographic location. According to the relevant communication protocol, during the service process, the UE measures the wireless environment and periodically reports the MR data to the base station (the period can be defined, generally 5 seconds). The more data there are, the higher the probability of greater service traffic; therefore, the number of MR sampling points contained in the grid can be used as the weight to allocate cell service traffic to the grid to complete traffic geography.

Specifically, the grid evaluation module 303 is configured to obtain each grid based on the number of MR sampling points in the corresponding cell, the number of MR sampling points in the corresponding cell, and the traffic flow of the corresponding cell in each grid. The service traffic of the corresponding cell in the grid; based on the number of MR sampling points in the corresponding cell in each grid, the uplink packet loss rate of each MR sampling point in the corresponding cell in each grid, and each grid The downlink packet loss rate of each MR sampling point in the corresponding cell in the grid is obtained, and the packet loss rate of the corresponding cell in each grid is obtained; based on the traffic flow and packet loss rate of the corresponding cell in each grid, the corresponding The perception of the cell in each grid.

For example, the service flow of cell A in the ith grid can be obtained according to the following formula:

表示第i个栅格中A小区的业务流量，i为小于等于n的自然数，n表示划分出的栅格的总数；

表示第i个栅格中处在A小区的MR采样点的总数，

表示A小区的MR采样点的个数，T_A表示A小区的业务流量。in,

Indicates the service flow of cell A in the ith grid, i is a natural number less than or equal to n, and n represents the total number of divided grids;

represents the total number of MR sampling points in cell A in the i-th grid,

Indicates the number of MR sampling points in cell A, and T _A represents the service traffic in cell A.

The packet loss rate of cell A in the ith grid can be obtained according to the following formula:

表示第i个栅格中A小区的丢包率，i为小于等于n的自然数，n表示划分出的栅格的总数；MR.LteScPlrULQciX(s)表示第i个栅格中处在A小区的第s个MR采样点的上行丢包率，s为小于等于

的自然数，

表示第i个栅格中处在A小区的MR采样点的个数；MR.LteScPlrDLQciX(s)表示第i个栅格中处在A小区的第s个MR采样点的下行丢包率。in,

Indicates the packet loss rate of cell A in the i-th grid, i is a natural number less than or equal to n, and n represents the total number of divided grids; MR.LteScPlrULQciX(s) represents the i-th grid in the A cell Upstream packet loss rate of the s-th MR sampling point, where s is less than or equal to

the natural numbers of ,

Indicates the number of MR sampling points in cell A in the i-th grid; MR.LteScPlrDLQciX(s) represents the downlink packet loss rate of the s-th MR sampling point in cell A in the i-th grid.

In a specific implementation manner, the grid perception can be used to evaluate the grid. Here, the service flow of the corresponding cell in each grid can be multiplied by the packet loss rate of the corresponding cell to obtain the corresponding cell in each grid. Perceptivity in the grid.

For example, the perception of cell A in the ith grid is:

表示A小区在第i个栅格中的感知度。in,

Indicates the perception degree of cell A in the ith grid.

4. Coverage direction generation module

It can be understood that the greater the perception of a cell in any grid, the more priority the grid should cover. Based on this basic idea, the coverage direction generation module calculates the base station corresponding to each cell according to the perception of the grid. The main beam direction of the antenna (ie the main coverage direction of the cell).

Specifically, the coverage direction generation module 304 is specifically configured to use the perception of the corresponding cell in each grid to perform a weighted average calculation on the position coordinates of the center point of each grid to obtain the position of the coverage center of the corresponding cell Coordinates; based on the location of the coverage center of each cell and the location of the corresponding base station, the direction from the base station corresponding to each cell to the coverage center is determined as: the main beam direction of the base station antenna corresponding to each cell.

Here, the location coordinates can be represented by latitude and longitude.

For example, taking cell A as an example, there are m grids containing MR sampling points in cell A, that is, the MR sampling points in cell A correspond to m grids, and m is greater than or equal to 1; In the grid, the center latitude and longitude of the jth grid is G _j (x, y), and j is a natural number less than or equal to m; the perception of cell A in the jth grid is

Taking the grid perception as the weight, the latitude and longitude coordinates CenA(x,y) of the coverage center of cell A are calculated according to the following formula:

in,

FIG. 6 is a schematic diagram of the main beam direction of the base station antenna corresponding to cell A according to an embodiment of the present invention. As shown in FIG. 6 , black dots represent MR sampling points, and A(x ₀ , y ₀ ) represents the latitude and longitude coordinates of the base station corresponding to cell A , CenA(x,y) represents the latitude and longitude coordinates of the coverage center of cell A.

6, after obtaining the latitude and longitude coordinates CenA(x, y) of the coverage center of the A cell, the direction from the base station corresponding to the A cell to the coverage center of the A cell is determined as: the main beam direction of the base station antenna corresponding to the A cell , here, 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 parameter value output module

Specifically, the azimuth parameter value output module 305 is used to determine 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; output the azimuth angle of the base station antenna corresponding to each cell .

In a specific implementation, the azimuth parameter value output module determines the direction vector from the base station corresponding to the cell to the coverage center of the cell, and further, converts the azimuth represented by radians in the Cartesian coordinate system into the reference direction with the true north direction of the base station as the reference direction The azimuth parameter value of the base station antenna corresponding to the cell is obtained.

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. R=π/2-Arctan((y-y0)/(x-x0));

Then, the radian R is converted into an angle, and the azimuth angle b of the base station antenna corresponding to the B cell can be obtained, where b=R*180/π.

Those skilled in the art should understand that the implementation function of each module in the device for determining the azimuth angle of the base station antenna shown in FIG. The functions of each module of the device for determining the azimuth angle of the base station antenna shown in FIG. 3 can be implemented by a program running on the processor, or can be implemented by a specific logic circuit.

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 can all be performed by a central processing unit (Central Processing Unit) located in the terminal. Processing Unit, CPU), Micro Processor Unit (MPU), Digital Signal Processor (Digital Signal Processor, DSP), or Field Programmable Gate Array (Field Programmable Gate Array, FPGA) etc.

Third Embodiment

For the method for determining the azimuth angle of the base station antenna according to the first embodiment of the present invention, the third embodiment of the present invention provides a device for determining the azimuth angle of the base station antenna.

FIG. 7 is a schematic diagram of the second structure of a device for determining the azimuth angle of a base station antenna according to an embodiment of the present invention. As shown in FIG. 7 , the device includes: an acquisition module 701 and a determination module 702; wherein,

An acquisition module 701, configured to acquire measurement report MR data, and acquire the location information and the cell where each MR sampling point in the MR data is located;

The determining module 702 is configured to, based on the position information of each MR sampling point, in the map divided into multiple grids, determine the grid where each MR sampling point is located; The number of MR sampling points of the cell, the service flow of the corresponding cell in each grid is obtained; based on the obtained service flow, the location of the coverage center of the corresponding cell is determined; based on the location of the coverage center of each cell and the corresponding base station position, and determine the azimuth angle of the base station antenna corresponding to each cell.

Specifically, the determining module 702 is configured to obtain each grid based on the number of MR sampling points located in the corresponding cell, the total number of MR sampling points located in the corresponding cell, and the traffic flow of the corresponding cell in each grid. The service traffic of the corresponding cell in the grid.

The determining module 702 is configured to use the traffic flow of the corresponding cell in each grid to perform weighted average calculation on the position coordinates of the center point of each grid to obtain the position coordinates of the coverage center of the corresponding cell; The service flow of the corresponding cell in each grid is obtained, and the perception degree of the corresponding cell in each grid is obtained; using the perception degree of the corresponding cell in each grid, the position coordinates of the center point of each grid are weighted and averaged The calculation is performed to obtain the position coordinates of the coverage center of the corresponding cell; the perception degree 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 the packet loss rate of the 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 perception degree of the corresponding cell in each grid based on the traffic flow of the corresponding cell in each grid and the packet loss rate of the corresponding cell in each grid, Using the perception degree of the corresponding cell in each grid, the weighted average calculation is performed on the position coordinates of the center point of each grid to obtain the position coordinates of the coverage center of the corresponding cell; The perception degree is positively correlated with the traffic 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, based on the location of the coverage center of each cell and the location of the corresponding base station, determine the direction from the base station corresponding to each cell to the coverage center as: Main beam direction: Based on the main beam direction of the base station antenna corresponding to each cell, determine the azimuth angle of the base station antenna corresponding to each cell.

Those skilled in the art should understand that the implementation function of each module in the device for determining the azimuth angle of the base station antenna shown in FIG. The functions of each module of the device for determining the azimuth angle of the base station antenna shown in FIG. 7 can be implemented by a program running on the processor, or can be implemented by a specific logic circuit.

In practical applications, the acquiring module 701 and the determining module 702 can both be composed of a central processing unit (Central Processing Unit, CPU), a microprocessor (Micro Processor Unit, MPU), a digital signal processor (Digital Signal Processor) located in the terminal , DSP), or Field Programmable Gate Array (Field Programmable GateArray, FPGA) etc.

The technical solutions described in the embodiments of the present invention may be combined arbitrarily if there is no conflict.

In the several embodiments provided by the present invention, it should be understood that the disclosed method and smart device may be implemented in other manners. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined, or Can be integrated into another system, or some features can be ignored, or not implemented. In addition, the coupling, or direct coupling, or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be electrical, mechanical or other forms. of.

The unit described above as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units; Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present invention may all be integrated into one second processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; The above-mentioned integrated units can be implemented in the form of hardware, or can be implemented in the form of hardware plus software functional units.

The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited to this. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention. should be included within the protection 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 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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