CN115243279A - Network optimization method and device and electronic equipment - Google Patents
Network optimization method and device and electronic equipment Download PDFInfo
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Abstract
The application discloses a network optimization method, a network optimization device and electronic equipment, which are used for solving the problems that the existing network optimization mode is low in efficiency and the optimization effect is difficult to achieve the optimal effect. The method comprises the following steps: acquiring network coverage information of a target building, wherein the network coverage information is obtained by measuring the target building by an unmanned aerial vehicle based on a network coverage measurement scheme matched with the target building, and the network coverage information comprises sampling point information corresponding to a cell covering the target building and signal intensity information of the cell measured at the sampling point; determining a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building based on the network coverage information of the target building; acquiring relative position information between a base station antenna corresponding to a cell to be optimized and a target building; and adjusting the antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a network optimization method and apparatus, and an electronic device.
Background
With the coming of the 5G era, networks are more and more efficient and convenient, and the public is more and more influenced by the networks, so that the network behavior habits of the public also change, for example, users can require to be able to access the networks anytime and anywhere, and the requirements on network perception are higher and higher. The main task of 5G network operation is to meet the increasing network requirements of users, the frequency of the 5G network is high, the coverage area is small, the sites are dense, if an effective coverage optimization means is lacked, the network coverage is easily disordered, the original network coverage effect such as high-rise residential buildings is poor, and the network coverage problem is more easily caused. Therefore, a solution capable of performing coverage optimization on network signals such as 5G in each scene is important.
Currently, there are two main methods for network optimization: one is that the traditional manual mode is adopted to carry out traversing test or fixed point test on the building, and then network optimization is carried out according to the test result; the other method is to collect Measurement Report (MR) data of a user, present the network coverage condition of the building through an MR data presentation technology, and then perform network optimization according to the network coverage condition of the building.
However, in the traditional manual mode, testers need to traverse the network coverage data of the internal and external environment fields of the building, the efficiency is low, and meanwhile, the comprehensive test data cannot be collected due to the influence of objective factors such as the environment and the like, so that the network optimization result is difficult to achieve the optimal result. The MR coverage presentation mode requires enough users in a building, otherwise, the coverage presentation is subject to statistical deviation due to a small MR sample amount, and the network optimization effect is difficult to achieve the optimum. Therefore, how to efficiently and accurately optimize the network coverage effect of a building still needs further solutions.
Disclosure of Invention
The embodiment of the application provides a network optimization method, a network optimization device and electronic equipment, and aims to solve the problems that an existing network optimization mode is low in efficiency and the optimization effect is difficult to achieve the optimal effect.
The embodiment of the application adopts the following technical scheme:
in a first aspect, an embodiment of the present application provides a network optimization method, including:
acquiring network coverage information of a target building, wherein the network coverage information is obtained by measuring the target building by an unmanned aerial vehicle based on a network coverage measurement scheme matched with the target building, and comprises sampling point information corresponding to a cell covering the target building and signal intensity information of the cell measured at the sampling point;
determining a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building based on the network coverage information of the target building;
obtaining relative position information between a base station antenna corresponding to the cell to be optimized and the target building;
adjusting antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range.
In a second aspect, an embodiment of the present application provides a network optimization apparatus, including:
the network coverage information acquisition unit is used for acquiring network coverage information of a target building, wherein the network coverage information is obtained by measuring the target building by an unmanned aerial vehicle based on a network coverage measurement scheme matched with the target building, and comprises sampling point information corresponding to a cell covering the target building and signal intensity information of the cell measured at the sampling point;
the first determining unit is used for determining a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building based on the network coverage information of the target building;
a second obtaining unit, configured to obtain relative position information between the base station antenna corresponding to the cell to be optimized and the target building;
and the adjusting unit is used for adjusting the antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range.
In a third aspect, an embodiment of the present application provides an electronic device, including:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the method of the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, where instructions, when executed by a processor of an electronic device, enable the electronic device to perform the method of the first aspect.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects:
the target building is measured by the unmanned aerial vehicle based on the network measurement scheme matched with the target building, so that the measurement error caused by insufficient acquired data volume in the MR coverage presentation mode or the influence of factors on the manual test mode can be effectively reduced, the obtained network coverage information of the target building is more comprehensive, objective, accurate and reliable, the efficiency of the whole measurement process is higher, and the efficiency of the whole network optimization process is further improved; and based on the network coverage information of the target building, determining a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building, and adjusting the antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range, so that the network of the target building can be optimized more effectively, comprehensively and finely, and the network of the target building is ensured to be optimal.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flowchart of a network optimization method according to an exemplary embodiment of the present application;
fig. 2 is a schematic view of a flight trajectory of a drone according to an exemplary embodiment of the present application;
fig. 3 is a schematic diagram of a measurement scenario of an unmanned aerial vehicle according to an exemplary embodiment of the present application;
fig. 4 is a schematic flowchart of a network optimization method according to another exemplary embodiment of the present application;
fig. 5 is a schematic diagram of a coverage signal mapping matrix of a secondary coverage cell according to an exemplary embodiment of the present application;
FIG. 6 is a schematic diagram of a target optimization scope provided by an exemplary embodiment of the present application;
fig. 7 is a schematic diagram illustrating a coverage area of a beam broadcast by a base station antenna according to an exemplary embodiment of the present application;
fig. 8A is a schematic diagram of a relative position relationship between a base station antenna and a boundary point of a width optimization range according to an exemplary embodiment of the present application;
fig. 8B is a schematic diagram of a relative position relationship between a base station antenna and a boundary point of a width optimization range according to another exemplary embodiment of the present application;
fig. 9A is a schematic diagram of a relative position relationship between a base station antenna and a boundary point of a highly optimized range according to an exemplary embodiment of the present application;
fig. 9B is a schematic diagram of a relative position relationship between a base station antenna and a boundary point of a highly optimized range according to another exemplary embodiment of the present application;
fig. 10 is a schematic coverage area diagram of a main lobe of a base station antenna according to an exemplary embodiment of the present application;
FIG. 11 is a diagram illustrating a relative position relationship between a base station antenna and a center point of a highly optimized range according to an exemplary embodiment of the present application;
fig. 12 is a schematic structural diagram of an electronic device according to an exemplary embodiment of the present application;
fig. 13 is a schematic structural diagram of a network optimization device according to an exemplary embodiment of the present application.
Detailed Description
To make the objects, technical solutions and advantages of the present application more clear, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In order to solve the problems that an existing network optimization mode is low in efficiency and the optimization effect is difficult to achieve the optimal effect, the embodiment of the application provides a network optimization method. The execution subject of the method provided by the embodiment of the present application may include, but is not limited to, a base station, a computer and a server connected to the base station, and the like, which can be configured to execute at least one of the method apparatuses provided by the embodiment of the present application.
For convenience of description, the following description will be made of an embodiment of the method taking as an example a computer capable of executing the method an execution subject of the method. It is to be understood that the implementation of the method by a computer is merely an exemplary illustration and should not be construed as a limitation of the method.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
Referring to fig. 1, a flow chart of a network optimization method according to an exemplary embodiment of the present application is shown, where the method includes the following steps:
s102, network coverage information of the target building is obtained, and the network coverage information is obtained by measuring the target building by the unmanned aerial vehicle based on a network coverage measurement scheme matched with the target building.
The target building refers to a building needing network optimization. Specifically, the network coverage measurement scheme matched with the target building may include a flight route of the unmanned aerial vehicle, position information of each sampling point, network coverage information to be measured, and the like, which may be preset based on basic information such as a width, a height, a shape, and the like of the target building. Alternatively, taking the target building shown in fig. 2 as an example, the flight route in the network coverage measurement scheme matched with the target building is shown by a dotted arrow in fig. 2, that is, the target building is flown back and forth along the width direction of the target building for a plurality of times with the width of the target building as a horizontal distance, and the height interval is 1 meter. For example, assuming a target building has a width of 45 meters and a height of 84 meters, the network coverage measurement scheme matched with the target building may be: the horizontal distance of 45 meters is used, and the flight is carried out 84 times along the width of the target building, and the height interval is 1 meter.
In specific implementation, as shown in fig. 3, the unmanned aerial vehicle may carry a device with a network signal acquisition function, such as a 5G test terminal, a 5G sweep generator, and the like, the computer may acquire a network coverage measurement scheme matched with a target building and send the network coverage measurement scheme to the unmanned aerial vehicle, the unmanned aerial vehicle flies around the target building according to a flight route indicated by the received network coverage measurement scheme, the network coverage information at different positions of the target building is measured by testing communication data between the carried network signal acquisition device and a communication base station, and a measurement result is returned to the computer, and is analyzed and subjected to network optimization by calculation. Further, in order to guarantee the accuracy of the result obtained by the measurement of the unmanned aerial vehicle, before the target building is measured by the unmanned aerial vehicle, the unmanned aerial vehicle is calibrated in the modes of a compass, a Global Positioning System (GPS), a level meter and the like, so that the unmanned aerial vehicle can fly stably and accurately.
In the embodiment of the present application, the network coverage information of the target building refers to information for characterizing a network coverage condition of the target building, and may include sampling point information corresponding to a cell covering the target building and Signal strength information of the cell measured at the sampling point, where the Signal strength information may include, but is not limited to, reference Signal Received Power (RSRP), reference Signal Received Quality (RSRQ), and other sampling point information, and may include, but is not limited to, the number of sampling points, location information, and the like. Specifically, in the flight process of the unmanned aerial vehicle, the network signal sampling device carried by the unmanned aerial vehicle can measure information such as cells (including a main service cell and an auxiliary service cell) covering each sampling point and signal intensity of the cells, and by classifying and integrating the information, the main service cell corresponding to the target building, sampling point information corresponding to the main service cell and signal intensity information of the main service cell measured at the sampling point corresponding to the main service cell can be determined.
And S104, determining a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building based on the network coverage information of the target building.
In general, there are a plurality of cells covering the target building, and all the cells may be used as the cells to be optimized corresponding to the target building. Of course, in a more preferred scheme, to implement accurate optimization of network coverage of the target building, a representative cell may be selected from a plurality of cells covering the target building as a cell to be optimized corresponding to the target building based on the sampling point information of the cell corresponding to the target building and the signal strength information of the cell measured by the sampling point, and a target optimization range of the cell to be optimized in the target building may be determined. Optionally, as shown in fig. 4, determining a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building includes:
and S141, determining the sampling point number ratio of the main service cell covering the target building based on the number of the sampling points corresponding to each cell covering the target building.
Specifically, for each main serving cell, the ratio of the sampling point number of the main serving cell to the total sampling point number of the target building is the sampling point number ratio of the main serving cell. For example, table 1 shows an example of the number of sampling points and the sampling point ratio of each main serving cell of a target building.
TABLE 1
| Main service cell of target building | Number of sampling points | Number of sampling points |
| Cell A | 1688 | 24.21％ |
| Cell B | 1042 | 14.94％ |
| Cell C | 793 | 11.37％ |
| Cell D | 587 | 8.42％ |
| …… | …… | …… |
And S142, determining a main coverage cell and an auxiliary coverage cell from the main service cell covering the target building based on the sampling point ratio of the main service cell covering the target building.
Specifically, the main service cells corresponding to the target building may be sorted in the order from high to low in sampling point ratio, the main service cell with the higher sampling point ratio and the front preset number exceeding the preset ratio threshold is selected, the main service cell with the highest sampling point ratio is used as the main coverage cell, and the remaining main service cells are used as the auxiliary coverage cells. The preset digit and the preset proportion threshold value may be set according to actual needs, for example, the preset digit is 3, and the preset proportion threshold value is 5%. Taking the primary serving cell shown in table 1 as an example, a cell a may be selected as the primary coverage cell, and a cell B and a cell C may be selected as the secondary coverage cells.
And S143, determining the main coverage cell as a cell to be optimized, and determining a coverage signal mapping matrix corresponding to the auxiliary coverage cell based on the position information of the sampling point corresponding to the auxiliary coverage cell and the signal intensity information of the auxiliary coverage cell measured at the sampling point.
The coverage mapping matrix is used for indicating the signal intensity of the secondary coverage cell corresponding to different positions of the target building.
In specific implementation, the target building can be divided into different sub-areas based on basic information such as the width and the height of the target building, the number of sampling points corresponding to the different sub-areas of the auxiliary coverage area is determined based on the position information of the sampling points corresponding to the auxiliary coverage area, then the signal intensity mean value of the auxiliary coverage area measured at the sampling points corresponding to the different sub-areas of the auxiliary coverage area is used as the signal intensity of the auxiliary coverage area at the central points of the different sub-areas, and further a coverage signal mapping matrix corresponding to the auxiliary coverage area can be established.
For example, the width of the target building is 45 meters, the height of the target building is 84 meters, the target building may be divided into sub-areas with width and height of 1 meter, and based on the following formula (1), a coverage signal mapping matrix corresponding to the secondary coverage cell may be established, as shown in table 2.
Wherein, matrix cell Representing a covering signal mapping matrix corresponding to the secondary covering cell; rsrp of avg XY Indicating the signal strength of the secondary coverage cell at (X, Y), X indicating the location in the elevation direction of the target building, Y indicating the location in the target buildingIn the width direction.
TABLE 2
It should be noted that the number of the secondary coverage cells may be one or more, and in the case that the number of the secondary coverage cells is multiple, the coverage signal mapping matrix corresponding to each secondary coverage cell may be determined based on the above manner for each secondary coverage cell.
And S144, determining a target optimization range of the cell to be optimized corresponding to the target building based on the coverage signal mapping matrix corresponding to the secondary coverage cell.
In order to ensure that the signal strength of the primary coverage cell serving as the cell to be optimized in the target optimization range is better than the signal strength of other cells in the target optimization range, in a preferred embodiment, a position where the signal strength of the secondary coverage cell in the target coverage building is smaller than a preset strength threshold may be selected based on a coverage signal mapping matrix corresponding to the secondary coverage cell, the position is determined as an optimization position corresponding to the cell to be optimized in the target building, and further, the target optimization range corresponding to the cell to be optimized in the target building is determined based on the determined optimization position. The preset intensity threshold may be set according to actual needs, for example, the preset intensity threshold may be set to-105 dBm. The target optimization range may include a height optimization range and a width optimization range.
More specifically, if the number of the secondary coverage cells is one, the position corresponding to the element, of which the signal intensity is smaller than the preset intensity threshold value, in the coverage signal mapping matrix corresponding to the secondary coverage cell may be used as the optimized position corresponding to the target building of the cell to be optimized; if the number of the auxiliary coverage cells is multiple, the elements at the same position can be subjected to a large-scale operation to obtain a new coverage signal mapping matrix, and then the position corresponding to the element with the signal intensity smaller than a preset intensity threshold value in the new coverage signal mapping matrix is used as the optimized position corresponding to the target building of the cell to be optimized. Further, the width optimization range of the cell to be optimized corresponding to the target building is determined based on the coordinates of the optimization positions in the width direction of the target building, and the height optimization range of the cell to be optimized corresponding to the target building is determined based on the coordinates of the optimization positions in the height direction of the target building.
For example, as shown in fig. 5, the leftmost diagram represents the coverage signal mapping matrix for the secondary coverage cell B B The middle diagram represents the coverage signal mapping matrix for the secondary coverage cell C C The rightmost diagram shows a new coverage signal mapping matrix matrixBC obtained by carrying out a large operation on elements at the same position in the secondary coverage cells B and C max The darker the color of each element, the greater the value (i.e., signal strength at that location) representing that element. Further, the new coverage signal may be mapped to matrix MatrixBC max The position with the medium signal intensity smaller than the preset intensity threshold value is determined as the optimized position of the cell to be optimized in the target building, and further the target optimization range of the cell to be optimized in the target building can be determined as a new coverage signal mapping matrix MatrixBC max The dark areas in (a).
Further, in order to further improve the network optimization precision of the target building, after the optimization position is determined, the outlier optimization position is removed, so that a more accurate target optimization range is obtained. Specifically, the Outlier optimized position may be screened from the determined optimized positions based on an Outlier Factor detection (LOF) algorithm, and a target optimized range corresponding to the cell to be optimized in the target building may be determined based on the screened optimized position. It should be noted that the specific implementation of rejecting outliers based on the outlier detection algorithm is the prior art in the art, and will not be described in detail here.
For example, with a new cover signal mapping matrix matrixBC as shown in FIG. 5 max For example, after the outlier optimization positions are removed, the final target optimization range is shown as the dark region in fig. 6, that is, the target optimization range is {49 }<X|1<Y<45}。
It can be understood that, through the above embodiment, based on the sampling point number ratio of the main service cell covering the target building, the main coverage cell and the auxiliary coverage cell are selected from all the main service cells, the main coverage cell is used as the cell to be optimized, based on the position information of the sampling point corresponding to the auxiliary coverage cell and the signal intensity information of the auxiliary coverage cell measured at the sampling point, the signal intensities corresponding to the auxiliary coverage cell at different positions of the target building are determined, further based on the signal intensities corresponding to the auxiliary coverage cell at different positions of the target building, the target optimization range corresponding to the optimization cell at the target building is determined, the cell to be optimized for optimizing the network signal of the target building and the target optimization range corresponding to the cell at the target building can be determined more accurately, and based on this, the network of the target building can be optimized more effectively, comprehensively and finely, and the network of the target building is ensured to be optimal.
And S106, acquiring relative position information between the base station antenna corresponding to the cell to be optimized and the target building.
In specific implementation, the relative position information between the base station antenna and the target building can be determined based on the respective engineering parameters of the base station antenna and the target building corresponding to the cell to be optimized. The engineering parameters of the base station antenna may include the hanging height, the longitude and latitude information and the like of the base station antenna, and the engineering parameters of the target building may include the longitude and latitude information, the width, the height and the like of the target building. Accordingly, the above-mentioned relative position information may include a distance between the base station antenna and the target building, a relative position of the base station antenna in a height direction of the target building, a height difference of the base station antenna and the target building, and the like.
And according to different network systems to be optimized, the base station antennas corresponding to the cells to be optimized are different. For example, if the network system to be optimized is a 5G network, the base station Antenna corresponding to the cell to be optimized is an Active Antenna Unit (AAU).
And S108, adjusting the antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range.
In the embodiment of the present application, the antenna parameters of the base station antenna may include, for example, but are not limited to, an electrical tilt angle, a mechanical tilt angle, and the like of the antenna.
In an alternative embodiment, the electronic tilt of the base station antenna may be preferentially adjusted. As the electronic inclination angle of the base station antenna corresponding to the cell to be optimized affects the coverage range of the beam broadcasted by the base station antenna, and further affects the coverage of the target building, as shown in fig. 7, the left side represents the coverage condition of the base station antenna in the width direction of the building under the current electronic inclination angle, and the right side represents the coverage condition of the base station antenna in the height direction of the building under the current electronic inclination angle, for this reason, in order to ensure that the beam broadcasted by the base station antenna can better cover the target optimization range, so as to improve the signal intensity of the cell to be optimized in the target optimization range, the electronic inclination angle of the base station antenna can be adjusted by adjusting the horizontal wave width and the vertical wave width of the beam broadcasted by the base station antenna. In a specific implementation, as shown in fig. 4, the step S108 may include:
and S181, determining relative position information between the base station antenna and a boundary point of the target optimization range based on the relative position information between the base station antenna and the target building and the target optimization range.
The relative position information between the base station antenna and the boundary point of the target optimization range may include a relative position relationship between a center point of the base station antenna and the boundary point of the target optimization range, a distance between the boundary point and a center line of the base station antenna, a distance between the base station antenna and the target building, and the like.
Specifically, the target optimization range includes a width optimization range and a height optimization range. The relative position information between the base station antenna and the boundary point of the width-optimized range (hereinafter referred to as "first boundary point") such as the distance L between the base station antenna and the target building, the distance W between the first boundary point A1 and the center line of the base station antenna shown in fig. 8A and 8B, and the relative position information between the base station antenna and the boundary point of the width-optimized range (hereinafter referred to as "first boundary point") may be determined based on the relative position information between the base station antenna and the target building and the width-optimized range α1 And a distance W between the first boundary point B1 and the center line of the base station antenna β1 And the like. In addition, the method can also be based on base station antenna and targetRelative position information between buildings and the altitude optimization range, and a relative positional relationship between the base station antenna and a boundary point (hereinafter referred to as "second boundary point") of the altitude optimization range, such as a distance L between the base station antenna and the target building, a distance W between the second boundary point A2 and a center line of the base station antenna shown in fig. 9A and 9B α2 And the distance W between the second boundary point B2 and the center line of the base station antenna β2 And the like.
And S182, determining the target 3dB beam width of the base station antenna based on the relative position information between the base station antenna and the boundary point.
Specifically, in the width direction (i.e., horizontal direction) of the target building, the target horizontal 3dB beam width of the base station antenna may be determined based on the relative position information between the base station antenna and the first boundary point.
For example, if the relative position relationship between the base station antenna and the first boundary point is shown in fig. 8A, i.e. the center point O of the base station antenna is located between two first boundary points A1 and B1, angle Δ 1 ＝∠α 1 +∠β 1 Then the target horizontal 3dB beamwidth HDB of the base station antenna can be determined by the following equation (2) min (ii) a If the relative position relationship between the base station antenna and the first boundary point is shown in fig. 8B, that is, the two first boundary points A1 and B1 are located on the same side of the center line passing through the center point O, angle Δ 1 ＝∠α 1 -∠β 1 Or < delta 1 ＝∠β 1 -∠α 1 Then the target horizontal 3dB beamwidth HDB of the base station antenna can be determined by the following equation (3) or (4) min . Therefore, the beam of the base station antenna in the horizontal direction can completely cover the width optimization range, and the network coverage effect in the width direction of the target building is improved.
A target vertical 3dB beamwidth of the base station antenna is determined in a height direction (i.e., vertical direction) of the target building and based on the relative position information between the base station antenna and the second boundary point.
For example, if the relative position relationship between the base station antenna and the second boundary point is shown in fig. 9A, i.e. the center point O of the base station antenna is located between two first boundary points A2 and B2, angle Δ 2 ＝∠α 2 +∠β 2 Then the target vertical 3dB beamwidth VDB of the base station antenna can be determined by the following equation (5) min (ii) a If the relative position relationship between the base station antenna and the second boundary point is shown in fig. 9B, i.e. the two first boundary points A2 and B2 are located on the same side of the center line passing through the center point O, angle Δ 2 ＝∠α 2 -∠β 2 Or < delta 2 ＝∠β 2 -∠α 2 Then the target vertical 3dB beamwidth VDB of the base station antenna can be determined by the following equation (6) or (7) min . Therefore, the wave beams of the base station antenna in the vertical direction can completely cover the optimized range of the width, and the network coverage effect in the height direction of the target building is improved.
And S183, adjusting the electronic inclination angle of the base station antenna based on the target 3dB beam width of the base station antenna.
Specifically, after the target 3dB beamwidth of the base station antenna is determined, the electronic tilt angle of the base station antenna may be adjusted with the target 3dB beamwidth as a target until the horizontal 3dB beamwidth of the base station antenna reaches the target horizontal 3dB beamwidth and the vertical 3dB beamwidth reaches the target vertical 3dB beamwidth.
Further, considering that the network coverage of the target building can be optimized only by adjusting the electronic inclination angle of the base station antenna, the target building can be measured again after the electronic inclination angle of the base station antenna is adjusted, and if the index data of the target building in the specified network coverage index does not reach the preset optimization, the mechanical inclination angle of the base station antenna is adjusted. For example, as shown in fig. 10, by adjusting the mechanical tilt angle of the base station antenna, the main lobe direction of the base station antenna can be changed, and then the coverage area of the main lobe of the base station antenna in the height direction of the target building is changed, thereby achieving the purpose of improving the network coverage effect of the target building.
Specifically, as shown in fig. 4, the step S108 further includes:
and S184, controlling the unmanned aerial vehicle to measure the target building according to the network coverage measurement scheme again to obtain index data of the target building in the specified network coverage index.
The specified network coverage index may include, but is not limited to, an RSRP integrated coverage rate, a number of floors with RSRP less than a preset strength threshold, a File Transfer Protocol (FTP) download rate, a File Transfer Protocol upload rate, and the like.
And S185, judging whether the measured index data reach a preset optimization target.
If the judgment result is no, the following step S186 is executed; if the judgment result is yes, the adjustment of the antenna parameters of the base station antenna is finished.
And S186, determining the relative position information between the base station antenna and the central point of the height optimization range based on the relative position information between the base station antenna and the target building and the height optimization range.
And S187, determining the target mechanical inclination angle of the base station antenna based on the relative position information between the base station antenna and the central point of the height optimization range.
For example, as shown in fig. 11, the relative position information between the base station antenna and the center point of the height optimization range may include a distance H between the center point P of the height range and the center line of the base station antenna α . Further, the target mechanical tilt angle MDA of the base station antenna may be determined by the following formula (8). Therefore, the main lobe beam of the base station antenna can completely cover the height optimization range, and the network coverage effect in the width direction of the target building is improved.
S189, adjust the mechanical tilt of the base station antenna to the target mechanical tilt.
By adopting the network optimization method provided by the embodiment of the application, the target building is measured by the unmanned aerial vehicle based on the network measurement scheme matched with the target building, so that the measurement error caused by insufficient acquired data volume in the MR coverage presentation mode or the influence of factors on the manual test mode can be effectively reduced, the obtained network coverage information of the target building is more comprehensive, objective, accurate and reliable, the efficiency of the whole measurement process is higher, and the efficiency of the whole network optimization process is further improved; and based on the network coverage information of the target building, determining a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building, and adjusting the antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range, so that the network of the target building can be optimized more effectively, comprehensively and finely, and the network of the target building is ensured to be optimal.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
Fig. 12 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 12, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 12, but that does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form the network optimization device on the logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
acquiring network coverage information of a target building, wherein the network coverage information is obtained by measuring the target building by an unmanned aerial vehicle based on a network coverage measurement scheme matched with the target building, and comprises sampling point information corresponding to a cell covering the target building and signal intensity information of the cell measured at the sampling point;
determining a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building based on the network coverage information of the target building;
obtaining relative position information between a base station antenna corresponding to the cell to be optimized and the target building;
and adjusting the antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range.
The method performed by the network optimization device according to the embodiment shown in fig. 1 of the present application may be applied to a processor, or may be implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may also execute the method in fig. 1, and implement the functions of the network optimization apparatus in the embodiments shown in fig. 1 and fig. 4, which are not described herein again.
Of course, besides the software implementation, the electronic device of the present application does not exclude other implementations, such as a logic device or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may also be hardware or a logic device.
Embodiments of the present application also provide a computer-readable storage medium storing one or more programs, where the one or more programs include instructions, which when executed by a portable electronic device including a plurality of application programs, enable the portable electronic device to perform the method of the embodiment shown in fig. 1, and are specifically configured to:
the method comprises the steps of obtaining network coverage information of a target building, wherein the network coverage information is obtained by measuring the target building by an unmanned aerial vehicle based on a network coverage measurement scheme matched with the target building, and comprises sampling point information corresponding to a cell covering the target building and signal intensity information of the cell measured at the sampling point;
determining a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building based on the network coverage information of the target building;
obtaining relative position information between a base station antenna corresponding to the cell to be optimized and the target building;
and adjusting the antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range.
Fig. 13 is a schematic structural diagram of a network optimization device according to an embodiment of the present application. Referring to fig. 4, in a software implementation, the network optimization apparatus 1300 may include:
a first obtaining unit 1310, configured to obtain network coverage information of a target building, where the network coverage information is obtained by an unmanned aerial vehicle measuring the target building based on a network coverage measurement scheme matched with the target building, and the network coverage information includes sampling point information corresponding to a cell covering the target building and signal intensity information of the cell measured at the sampling point;
a first determining unit 1320, configured to determine, based on the network coverage information of the target building, a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building;
a second obtaining unit 1330, configured to obtain relative position information between the base station antenna corresponding to the cell to be optimized and the target building;
an adjusting unit 1340, configured to adjust antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range.
In one embodiment, the sampling point information includes the number and position information of the sampling points;
the first determination unit 1320 includes:
the proportion determining subunit is used for determining the proportion of the sampling points of the main service cell covering the target building based on the number of the sampling points corresponding to each cell covering the target building;
a coverage cell selection subunit, configured to select a primary coverage cell and an auxiliary coverage cell from the primary service cells covering the target building based on a sampling point count ratio of the primary service cell;
a mapping matrix determining subunit, configured to use the primary coverage cell as a cell to be optimized, determine a coverage signal mapping matrix corresponding to the secondary coverage cell based on position information of a sampling point corresponding to the secondary coverage cell and signal strength information of the secondary coverage cell measured at the sampling point corresponding to the secondary coverage cell, where the coverage signal mapping matrix is used to indicate signal strengths corresponding to different positions of the target building of the secondary coverage cell;
and the optimization range determining subunit is configured to determine, based on the coverage signal mapping matrix corresponding to the secondary coverage cell, a target optimization range corresponding to the target building for the cell to be optimized.
In one embodiment, the optimization range determining subunit is specifically configured to:
selecting a position in the target building, where the signal intensity of the auxiliary coverage cell is smaller than a preset intensity threshold value, based on a coverage signal mapping matrix corresponding to the auxiliary coverage cell, and determining the position as an optimized position corresponding to the cell to be optimized in the target building;
and determining a target optimization range corresponding to the cell to be optimized in the target building based on the determined optimization position.
In one embodiment, the optimization range determining subunit is specifically configured to:
screening the outlier optimized positions from the determined optimized positions based on an outlier factor detection algorithm;
and determining a target optimization range of the cell to be optimized corresponding to the target building based on the optimized position obtained after screening.
In one embodiment, the target optimization range includes a width optimization range and a height optimization range;
the adjusting unit 1340 includes:
a first relative position determining subunit configured to determine, based on the relative position information between the base station antenna and the target building and the target optimization range, relative position information between the base station antenna and a boundary point of the target optimization range;
a beam width determining subunit, configured to determine a target 3dB beam width of the base station antenna based on relative position information between the base station antenna and the boundary point;
a first adjusting subunit, configured to adjust an electronic tilt angle of the base station antenna based on a target 3dB beam width of the base station antenna.
In one embodiment, the target 3dB beamwidth comprises a target horizontal 3dB beamwidth and a target vertical 3dB beamwidth;
the first relative position determining subunit is specifically configured to:
determining relative position information between the base station antenna and a first boundary point based on the relative position information between the base station antenna and the target building and the width optimization range, wherein the first boundary point is a boundary point of the width optimization range;
determining relative position information between the base station antenna and a second boundary point based on the relative position information between the base station antenna and the target building and the altitude optimization range, wherein the second boundary point is a boundary point of the altitude optimization range;
the wave width determining subunit is specifically configured to:
determining a target horizontal 3dB beamwidth for the base station antenna based on relative position information between the base station antenna and the first boundary point;
determining a target vertical 3dB beamwidth of the base station antenna based on the relative position information between the base station antenna and the second boundary point.
In one embodiment, the adjusting unit 1340 further comprises:
the measurement sub-unit is used for controlling the unmanned aerial vehicle to measure the target building based on the network coverage measurement scheme again after the electronic inclination angle of the base station antenna is adjusted, so that index data of the target building in an appointed network coverage index can be obtained;
a second relative position determining subunit, configured to determine, if the index data does not reach a preset optimization target, relative position information between the base station antenna and a central point of the altitude optimization range based on the relative position information between the base station antenna and the target building and the altitude optimization range;
a mechanical tilt determining subunit, configured to determine a target mechanical tilt of the base station antenna based on the relative position information between the base station antenna and the central point;
and the second adjusting subunit is used for adjusting the mechanical inclination angle of the base station antenna to the target mechanical inclination angle.
In short, the above description is only a preferred embodiment of the present application, and is not intended to limit the scope of the present application. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
Claims (10)
1. A method for network optimization, comprising:
acquiring network coverage information of a target building, wherein the network coverage information is obtained by measuring the target building by an unmanned aerial vehicle based on a network coverage measurement scheme matched with the target building, and comprises sampling point information corresponding to a cell covering the target building and signal intensity information of the cell measured at the sampling point;
determining a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building based on the network coverage information of the target building;
obtaining relative position information between a base station antenna corresponding to the cell to be optimized and the target building;
and adjusting the antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range.
2. The method of claim 1, wherein the sample point information includes the number and position information of sample points;
the determining, based on the network coverage information of the target building, a cell to be optimized corresponding to the target building and a target optimization range corresponding to the target building in the cell to be optimized includes:
determining the sampling point number ratio of a main service cell covering the target building based on the number of sampling points corresponding to each cell covering the target building;
selecting a main coverage cell and an auxiliary coverage cell from the main service cells covering the target building based on the sampling point number ratio of the main service cells;
determining a coverage signal mapping matrix corresponding to the auxiliary coverage cell based on the position information of the sampling point corresponding to the auxiliary coverage cell and the signal intensity information of the auxiliary coverage cell measured at the sampling point corresponding to the auxiliary coverage cell, wherein the coverage signal mapping matrix is used for indicating the signal intensity of the auxiliary coverage cell corresponding to different positions of the target building;
and determining a target optimization range of the cell to be optimized corresponding to the target building based on the coverage signal mapping matrix corresponding to the secondary coverage cell.
3. The method of claim 2, wherein the determining a target optimization range of the cell to be optimized corresponding to the target building based on the coverage signal mapping matrix corresponding to the secondary coverage cell comprises:
selecting a position in the target building, where the signal intensity of the auxiliary coverage cell is smaller than a preset intensity threshold value, based on a coverage signal mapping matrix corresponding to the auxiliary coverage cell, and determining the position as an optimized position corresponding to the cell to be optimized in the target building;
and determining a target optimization range of the cell to be optimized corresponding to the target building based on the determined optimization position.
4. The method of claim 3, wherein the determining a target optimization range of the cell to be optimized corresponding to the target building based on the determined optimization position comprises:
screening the outlier optimized positions from the determined optimized positions based on an outlier factor detection algorithm;
and determining a target optimization range of the cell to be optimized corresponding to the target building based on the optimized position obtained after screening.
5. The method of claim 1, wherein the target optimization range comprises a width optimization range and a height optimization range;
the adjusting the antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range comprises:
determining relative position information between the base station antenna and a boundary point of the target optimization range based on the relative position information between the base station antenna and the target building and the target optimization range;
determining a target 3dB beam width of the base station antenna based on relative position information between the base station antenna and the boundary point;
adjusting an electronic tilt angle of the base station antenna based on a target 3dB beam width of the base station antenna.
6. The method of claim 5, wherein the target 3dB beamwidth comprises a target horizontal 3dB beamwidth and a target vertical 3dB beamwidth;
the determining, based on the relative position information between the base station antenna and the target building and the target optimization range, the relative position information between the base station antenna and a boundary point of the target optimization range includes:
determining relative position information between the base station antenna and a first boundary point based on the relative position information between the base station antenna and the target building and the width optimization range, wherein the first boundary point is a boundary point of the width optimization range;
determining relative position information between the base station antenna and a second boundary point based on the relative position information between the base station antenna and the target building and the altitude optimization range, wherein the second boundary point is a boundary point of the altitude optimization range;
the determining a target 3dB beamwidth of the base station antenna based on the relative location information between the base station antenna and the boundary point comprises:
determining a target horizontal 3dB beamwidth for the base station antenna based on relative position information between the base station antenna and the first boundary point;
determining a target vertical 3dB beamwidth of the base station antenna based on the relative position information between the base station antenna and the second boundary point.
7. The method of claim 5, wherein the adjusting the antenna parameters of the base station antenna based on the relative location information between the base station antenna and the target building and the target optimization range further comprises:
after the electronic inclination angle of the base station antenna is adjusted, controlling the unmanned aerial vehicle to measure the target building again based on the network coverage measurement scheme so as to obtain index data of the target building in a specified network coverage index;
if the index data does not reach a preset optimization target, determining relative position information between the base station antenna and the central point of the height optimization range based on the relative position information between the base station antenna and the target building and the height optimization range;
determining a target mechanical tilt angle of the base station antenna based on relative position information between the base station antenna and the center point;
and adjusting the mechanical inclination angle of the base station antenna to the target mechanical inclination angle.
8. A network optimization apparatus, comprising:
the network coverage information acquisition unit is used for acquiring network coverage information of a target building, wherein the network coverage information is obtained by measuring the target building by an unmanned aerial vehicle based on a network coverage measurement scheme matched with the target building, and comprises sampling point information corresponding to a cell covering the target building and signal intensity information of the cell measured at the sampling point;
the first determining unit is used for determining a cell to be optimized corresponding to the target building and a target optimization range of the cell to be optimized corresponding to the target building based on the network coverage information of the target building;
a second obtaining unit, configured to obtain relative position information between the base station antenna corresponding to the cell to be optimized and the target building;
and the adjusting unit is used for adjusting the antenna parameters of the base station antenna based on the relative position information between the base station antenna and the target building and the target optimization range.
9. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the method of any one of claims 1 to 7.
10. A computer-readable storage medium, wherein instructions in the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the method of any of claims 1-7.
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