CN113131974A - Method and device for automatically optimizing antenna weight based on 3DMIMO - Google Patents
Method and device for automatically optimizing antenna weight based on 3DMIMO Download PDFInfo
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- CN113131974A CN113131974A CN201911391025.8A CN201911391025A CN113131974A CN 113131974 A CN113131974 A CN 113131974A CN 201911391025 A CN201911391025 A CN 201911391025A CN 113131974 A CN113131974 A CN 113131974A
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Abstract
The invention discloses an automatic antenna weight value optimizing method based on 3DMIMO, which aims to solve the problem of low efficiency of manually adjusting the antenna weight value in the prior art. The method comprises the following steps: respectively predicting signal coverage field intensity values of a target 3DMIMO cell in a target geographic area when different antenna weights are adopted; acquiring reference signal receiving power of each sampling point in the target geographic area for a neighboring cell of the target 3DMIMO cell; determining the number of sampling points taking a target 3DMIMO cell as a service cell in the sampling points in the target geographic area; and selecting the target antenna weight from different antenna weights according to the number. By adopting the method, the automatic optimization of the antenna weight of the 3DMIMO is realized, and the efficiency of optimizing the antenna weight is improved. The invention also discloses a device for automatically optimizing the antenna weight based on the 3D MIMO, electronic equipment and a computer readable storage medium.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a method and an apparatus for automatically optimizing an antenna weight based on 3d mimo, an electronic device, and a computer-readable storage medium.
Background
Three-Dimensional Multiple Input Multiple Output (3D MIMO) technology is a key technology in the 5G technology 4G. The 3D MIMO utilizes the space freedom degree of the vertical dimension and the horizontal dimension provided by the large-scale multi-antenna array to improve the space division multiplexing capability of multiple users, realize three-dimensional beam shaping and multi-stream multi-user resource multiplexing, and greatly improve the system capacity and the three-dimensional coverage.
In an initial stage of 3d mimo network establishment, since user distribution in a coverage area cannot be obtained, the antenna weight of the 3d mimo generally adopts default settings, and different antenna weights cannot be matched according to different coverage scenarios (e.g., high telephone traffic, high-level coverage, etc.), that is, the broadcast beam of the 3d mimo cannot be optimally covered, so that the antenna weight of the 3d mimo generally needs to be optimized.
In the prior art, in the actual optimization work, a high-load cell is generally determined according to big data statistics, then field exploration is performed to determine an area with high user traffic, and then a worker needs to make an antenna weight optimization scheme according to information obtained by field exploration and the like.
Because the antenna weight of the 3d MIMO has a plurality of selectable values, the optimization mode is configured by selecting by the staff according to experience, and the optimization efficiency is low because the adjustment and verification are required repeatedly.
Disclosure of Invention
Embodiments of the present description provide a method, an apparatus, an electronic device, and a computer-readable storage medium for automatically optimizing an antenna weight based on 3d mimo, so as to solve a problem in the prior art that optimization efficiency is low due to repeated adjustment and verification in a manner of manually adjusting an antenna weight.
The embodiment of the specification adopts the following technical scheme:
a method for automatically optimizing antenna weight based on 3DMIMO comprises the following steps:
respectively predicting signal coverage field intensity values of a target three-dimensional multi-input multi-output (3 DMIMO) cell in a target geographic area when different antenna weights are adopted, and taking the signal coverage field intensity values as target 3DMIMO cell reference signal receiving power of each sampling point in the target geographic area;
acquiring reference signal receiving power of each sampling point for a neighboring cell of the target 3DMIMO cell in the target geographic area;
determining the number of sampling points taking the target 3DMIMO cell as a service cell in the sampling points in the target geographic region when the target 3DMIMO cell adopts different antenna weights according to the reference signal receiving power of the adjacent cell and the signal receiving power of the target 3DMIMO cell;
selecting a target antenna weight from the different antenna weights according to the number; and the selected target antenna weight is used as a target value for setting the antenna weight of the target 3DMIMO cell.
An antenna weight automatic optimization device based on 3DMIMO comprises:
the device comprises a prediction module, a power module and a power module, wherein the prediction module is used for respectively predicting signal coverage field intensity values of a target three-dimensional multi-input multi-output 3DMIMO cell in a target geographic area when different antenna weights are adopted, and the signal coverage field intensity values are used as target 3DMIMO cell reference signal receiving power of each sampling point in the target geographic area;
an obtaining module, configured to obtain reference signal received power of each sampling point for a neighboring cell of the target 3d mimo cell in the target geographic area;
a determining module, configured to determine, according to the reference signal receiving power of the neighboring cell and the target 3DMIMO cell signal receiving power, the number of sampling points in the target geographic area, where the target 3DMIMO cell is used as a serving cell, among the sampling points in the target geographic area when the target 3DMIMO cell adopts the different antenna weights;
a selecting module, configured to select a target antenna weight from the different antenna weights according to the number; and the selected target antenna weight is used as a target value for setting the antenna weight of the target 3DMIMO cell.
An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the computer program when executed by the processor implements the method for automatic optimization of antenna weights based on 3d mimo as described above.
A computer readable storage medium having stored thereon a computer program which, when being executed by a processor, implements the method for automatic antenna weight optimization based on 3d mimo as described above.
The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects:
the method and the device can predict the reference signal receiving power of the target 3DMIMO cell under different antenna weights, determine the number of sampling points which take the 3DMIMO cell as a service cell in the target geographic area, and select the target antenna weight from the antenna weights of the 3DMIMO according to the determined number.
On the other hand, the invention can realize the combination of a plurality of cells covered by signals to a target geographic area and the setting of the antenna weight of the target 3DMIM cell by determining the number of sampling points taking the target 3DMIMO cell as a service cell according to the reference signal receiving power of the adjacent cell and the signal receiving power of the target 3DMIMO cell. Compared with the prior art that the manual adjustment of the antenna weight can only aim at the 3DMIMO cell of the current base station, the comprehensive optimization can be realized, so that the selected target antenna weight is more suitable.
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 method for automatically optimizing antenna weights based on 3d mimo according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a three-dimensional grid model provided in an embodiment of the present disclosure;
FIG. 3 is a flowchart illustrating a method for predicting a signal coverage field strength value according to an embodiment of the present disclosure;
FIG. 4 is a schematic diagram of a method for calculating a relative downtilt angle and a relative azimuth angle according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an apparatus for automatically optimizing antenna weights based on 3d mimo according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of an electronic device provided in an embodiment of this specification.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following 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.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
In the prior art, the actual optimization of the antenna weight usually determines a high-load cell according to big data statistics, then performs field exploration to determine an area with high user traffic, and then needs a worker to make an antenna weight optimization scheme according to information obtained by field exploration and the like.
Because the antenna weight of the 3d MIMO has a plurality of selectable values, the optimization mode is configured by selecting by the staff according to experience, and the optimization efficiency is low because the adjustment and verification are required repeatedly.
In order to solve the foregoing technical problems, embodiments of the present specification provide a method, an apparatus, an electronic device, and a computer-readable storage medium for automatically optimizing an antenna weight based on 3d mimo, which are used to improve the efficiency of optimizing the antenna weight of 3d mimo. It should be noted that the execution subject of the method may be a 3d mimo base station device or other hardware devices in a mobile communication network, or a software system running on the 3d mimo base station device or the other hardware devices, and the like. The embodiments in this specification do not limit the specific implementation subject of the method. The flow diagram of the method is shown in figure 1, and comprises the following steps:
step 11: and respectively predicting the signal coverage field intensity values of the target 3DMIMO cell in the target geographic area when different antenna weights are adopted.
The target 3d mimo cell may refer to a 3d mimo cell for which an antenna weight is to be adjusted.
The target geographical area may be a geographical area covered by the target 3d mimo cell, or a geographical area to be covered by the target 3d mimo cell, or a certain area in the geographical area. In practical applications, the geographic area may be an area with a higher traffic volume according to big data statistics in a mobile communication network, for example, a shopping mall, a station, and the like, and it is understood that, to optimize an antenna weight of the target 3DMIMO, that is, to make a broadcast beam of the target 3DMIMO cell achieve optimal coverage in an area with a higher traffic volume, the area with a higher traffic volume may be a geographic area already covered by the target 3DMIMO cell or to be covered by the target 3DMIMO cell.
In practical applications, the current 3d mimo antenna has 13 sets of broadcast beam weights, and 31 electrical downtilt adjustments are provided under each set of broadcast beam weights, and there are 283 combinations, that is, 283 antenna weights, so that different antenna weights in this embodiment may refer to the 283 antenna weights. Of course, the method provided in the embodiments of the present description may also be applied to weight determination of antennas with 3d mimo having other number of antenna weight combinations.
In this embodiment, the signal coverage field strength values of the target 3DMIMO cells in the target geographic area when different antenna weights are adopted by the target 3DMIMO cells that are predicted respectively may be used as the target 3DMIMO cell reference signal received power of each sampling point in the target geographic area.
The sampling point may be a mobile terminal accessing a mobile communication network in a target geographic area. In practical applications, a sampling point may also be understood as a user in a target geographic area who holds a mobile terminal accessing a mobile communication network.
In the embodiment of the present specification, the sampling point in the target geographic area may be a mobile terminal accessing the mobile communication network, which is obtained according to the measurement report MR. The measurement report MR may be an important function in a Long Term Evolution (LTE) system, and may be used to obtain measurement data reported by a mobile terminal in a mobile communication network, where the measurement data mainly includes: the data shown in table 1, for example, may be specifically acquired measurement data, such as Global Positioning System (GPS) location information of the mobile terminal, reference signal received power of the serving cell and the neighboring cell, and the like.
Table 1: ME measurement data field
| Chinese character identification of field | Identification of field variables |
| Base station number | s_eNB_ID |
| Sector number of serving cell | s_Sector |
| Physical cell identity of serving cell | s_PCI |
| Reference signal received power of serving cell | s_RSRP |
| Reference signal received power of |
N1_RSRP |
| Reference signal received power of neighbor 2 | N2_RSRP |
| Reference signal received power of neighbor 3 | N3_RSRP |
| Reference signal received power of neighbor 4 | N4_RSRP |
| Reference signal received power of neighbor 5 | N5_RSRP |
| Reference signal received power of neighbor cell 6 | N6_RSRP |
| Longitude of sample point | lon |
| Dimension of sampling point | lat |
| Altitude of sampling point | alt |
In practical situation, the actual reference signal received power of the target 3d mimo cell at each sampling point in the target geographic area under a certain antenna weight can be obtained through the measurement report MR, however, since the antenna weight has various selectable options, it takes time, labor, material resources, etc. to actually obtain the reference signal received power under different antenna weights of the target 3d mimo cell through the measurement report MR, and, after configuring different antenna weights, may affect the online users currently accessing the mobile communication network in the target geographical area, therefore, in the embodiment of the specification, by predicting the signal coverage field strength value of the target 3d mimo cell in the target geographic area when different antenna weights are adopted, taking the predicted signal coverage field strength value as the reference information receiving power of the target 3d mimo cell, and then determining the serving cell of the sampling point according to the reference information receiving power of the target 3DMIMO cell and the reference signal receiving power of the adjacent cell.
In this embodiment, in order to respectively predict the signal coverage field strength value of the target 3DMIMO cell in the target geographic area when different antenna weights are used and to prevent interference to the online user, in one or more embodiments of the present description, a geographic Information system (for example, maprinfo, a desktop geographic Information system software of maprinfo company, which is a geographic Information system) may be further used to construct a three-dimensional grid model representing the space occupied by the geographic area, and based on the constructed three-dimensional grid model, the signal coverage field strength value of the target 3DMIMO cell in the target geographic area when different antenna weights are used is respectively predicted.
Wherein the geographic region comprises a target geographic region, the space occupied by the target geographic region may be characterized by at least one grid contained by the three-dimensional volumetric grid model. In practical applications, the size and the number of grids in the three-dimensional grid model may be determined according to the size of the space occupied by the geographic region. For example, as shown in fig. 2, a geographic area "500 meters by 500 meters" may be divided into grids "50 meters by 50 meters", and at least one grid in each grid "50 meters by 50 meters" may be used to characterize the target geographic area. It will be appreciated that if a geographic area is characterized by only one grid, then that one grid characterizes the target geographic area; if the geographic area is divided by a plurality of grids, each grid in the plurality of grids represents the target geographic area, and how to divide the geographic area can be determined according to actual conditions, which is not limited in the present application.
In one embodiment, after the building of the three-dimensional stereoscopic grid model representing the geographic area, the method may further include: and acquiring the spatial information of the sampling points in the geographic area from the measurement report MR aiming at the geographic area, determining the grids of the sampling points in the geographic area in the three-dimensional grid model according to the spatial information of the sampling points, and determining the sampling points belonging to at least one grid as the sampling points in the target geographic area. The sampling point in the obtained geographic area is matched into the grid of the three-dimensional grid model according to the spatial information of the sampling point so as to represent the spatial distribution of the mobile terminal in the target geographic area, so that the serving cell of the sampling point in the target geographic area can be determined.
The spatial information of the sampling point may be GPS location information characterizing the sampling point, and specifically may include: latitude and longitude, poster height and the like. In practical application, MR measurement data of multiple days in a geographic area can be obtained, so that the target antenna weight can be selected more accurately according to the number of sampling points in the target geographic area.
In practical applications, the orientation of the target geographic area with respect to the antenna of the target 3d mimo cell may be different, but the geographic location of the antenna and the position of the target geographic area are fixed, i.e., the orientation of the center point of the grid corresponding to the target geographic area in the three-dimensional volumetric grid model with respect to the antenna of the target 3d mimo cell may be fixed. Then, in this embodiment of the present specification, based on the constructed three-dimensional stereo grid model, a relative position of a center point of a grid corresponding to the target geographic area with respect to an antenna of the target 3DMIMO cell may be calculated, and according to the calculated relative position, signal coverage field strength values of the target 3DMIMO cell in the corresponding grid under different antenna weights are predicted, and the signal coverage field strength values are used as reference signal receiving powers of the target 3DMIMO cell belonging to each sampling point in the corresponding grid, that is, the reference signal receiving powers of the target 3DMIMO cell of each sampling point in the target geographic area.
Step 12: and acquiring the reference signal receiving power of each sampling point in the target geographic area for the adjacent cell of the target 3DMIMO cell.
The sampling points here may be obtained by measurement report MR for the reference signal received power of the neighborhood of the target 3d mimo cell.
In the embodiment of the present specification, for a certain sampling point, the neighboring cell herein may refer to other cells except the target 3d mimo cell, to which signals can be overlaid. It can be understood that the neighboring cell where the signal can cover the sampling point may be other 3d mimo cells, or may be a non-3 d mimo cell. The number and types of cells that the signal can cover to each sampling point can be determined according to measurement data acquired by the measurement report MR. For example, the reference signal receiving power tables of the serving cell and the neighboring cell of each sampling point that can be obtained through the measurement report MR shown in table 2, where the MR sampling point represents each sampling point in the target geographic area that is obtained through the measurement report, for the sampling point MR1, the reference signal receiving power of the serving cell may be-90, the neighboring cell whose signal covers the MR1 sampling point has neighboring cells 1 to 6, and the reference signal receiving powers of the neighboring cells 1 to 6 of the sampling point MR1 are-92, -93, -95, -96 in this order. It can be understood that the serving cell, the neighboring cell 1, the neighboring cell 2, the neighboring cell 3, the neighboring cell 4, the neighboring cell 5, and the neighboring cell 6 described in the first column in table 2 are an expression manner for distinguishing each cell, and for the neighboring cell 1, the serving cell, the neighboring cell 2, the neighboring cell 3, the neighboring cell 4, the neighboring cell 5, and the neighboring cell 6 are all neighboring cells of the neighboring cell 1.
Table 2: reference signal receiving power meter of service cell and adjacent cell of MR sampling point
Step 13: and determining the number of sampling points with the target 3DMIMO cell as a service cell in each sampling point in the target geographic area.
In practical applications, each sampling point in the target geographic area may be covered by signals of multiple cells. Since the spatial positions of the sampling points may be different, the reference signal received power of each sampling point may be different for different cells, and in general, the cell with the highest reference signal received power for each sampling point may be used as the serving cell of the sampling point.
In practical cases, the serving cell of each sampling point in the target geographic area acquired by the measurement report MR may be a target 3DMIMO cell, may also be another 3DMIMO cell other than the target 3DMIMO cell, or may also be a non-3 DMIMO cell. In the embodiment of the present specification, by comparing the reference signal received power of the target 3DMIMO cell under different antenna weights predicted in step 11 with the reference information received power of the neighboring cell obtained in step 12, it can be determined whether the serving cell of each sampling point is a 3DMIMO cell when the target 3DMIMO adopts different antenna weights, and it can be determined which serving cell the serving cell of each sampling point is specifically when the target 3DMIMO adopts different antenna weights.
In one embodiment, determining the number of sampling points with the target 3d mimo cell as the serving cell among the sampling points in the target geographic area may include: and determining the number of sampling points taking the target 3DMIMO cell as a service cell in each sampling point in the target geographic area when the target 3DMIMO cell adopts different antenna weights according to the reference signal receiving power of the adjacent cell and the signal receiving power of the target 3DMIMO cell. One specific algorithm may include:
when the target 3DMIMO cell adopts different antenna weights, respectively executing specified operation aiming at each sampling point in each sampling point; the specifying operation includes: determining a cell with the maximum reference signal receiving power as a service cell of the sampling point from the reference signal receiving power of the target 3DMIMO cell and the reference signal receiving power of the adjacent cell;
and calculating the number of sampling points which take the target 3DMIMO cell as the serving cell when the target 3DMIMO cell adopts different antenna weights according to the serving cell determined by aiming at each sampling point.
The determining, from the reference signal received power of the target 3d mimo cell and the reference signal received power of the neighboring cell, the cell with the largest reference signal received power as the serving cell of the sampling point may include: and aiming at each sampling point, performing descending or ascending sequence arrangement on the reference signal receiving power of the target 3DMIMO cell of the sampling point and the reference signal receiving power of the adjacent cell, and selecting the cell corresponding to the maximum reference signal receiving power in the arrangement result as the service cell of the sampling point.
In practical applications, in order to facilitate calculating the number of sampling points using the target 3d mimo cell as the serving cell, the sampling points using the target 3d mimo cell as the serving cell may be marked for each determined serving cell, for example, the "MR" may be marked for such sampling points3D", then calculating the number of sample points for which the target 3d mimo cell is the serving cell may be equivalent to calculating the number of sample points labeled" MR3D"number of sample points.
Step 14: the target antenna weights are selected from the different antenna weights according to the number determined by step 13.
The number here may be the number of sampling points with the target 3MIMO cell as the serving cell under different antenna weights determined by step 13.
In an embodiment, selecting the target antenna weight from the different antenna weights according to the number determined in step 13 may specifically include:
determining the maximum number among the numbers determined by step 13;
and selecting the antenna weight corresponding to the maximum number as the target antenna weight.
Wherein, the maximum number in the determined numbers may be that the number corresponding to the weight of each antenna obtained in step 13 is sorted in an ascending order or in a descending order, and the maximum number is determined according to the sorting result, for example: as described above for the 283 kinds of antenna weights, each kind of antenna weight corresponds to one number, the 283 kinds of antenna weights respectively correspond to 283 numbers, the 283 numbers are sorted in a descending order, the first bit of the sorting result is the maximum number, the antenna weight corresponding to the maximum number is the target antenna weight, and the application is not limited on how to determine the maximum number from the numbers.
In practical application, because the total number of sampling points in a geographic area may be fixed, or the total number of sampling points in a constructed three-dimensional grid model may be fixed, then an antenna weight corresponding to a maximum value in the number of sampling points using a target 3MIMO cell as a serving cell is selected as a target antenna weight, it can be understood that, on the premise that the total number of sampling points is fixed, the number of sampling points served by 3DMIMO cells under different antenna weights is greater, then the signal coverage of the 3DMIMO cell under the antenna weight is better, and the antenna weight corresponding to the optimal selected signal coverage may be the target antenna weight.
In this embodiment, the selected target antenna weight may be used as a target value for setting an antenna weight of a target 3d mimo cell. In practical application, after the antenna weight of the 3d mimo cell is actually set, the implementation effect of the antenna weight can be checked according to the obtained index data by obtaining index data (such as telephone traffic, ITE network wireless resource utilization rate, cell service user number, and the like) reflecting the network performance of the target 3d mimo cell.
In the implementation of the present description, the number of sampling points in the target geographic area, which use the 3DMIMO cell as a serving cell, is determined by predicting the reference signal received power of the target 3DMIMO cell under different antenna weights, and then the target antenna weight is selected from the antenna weights of the 3DMIMO according to the determined number.
On the other hand, in the embodiments of the present specification, the number of sampling points using the target 3DMIMO cell as a serving cell is determined according to the reference signal received power of the neighboring cell and the signal received power of the target 3DMIMO cell, so that the antenna weight of the target 3DMIM cell can be set in combination with multiple cells of a peripheral base station. Compared with the prior art that the manual adjustment of the antenna weight can only aim at the 3DMIMO cell of the current base station, the comprehensive optimization can be realized, so that the selected target antenna weight is more suitable.
In one or more embodiments of the present specification, based on the three-dimensional grid model established above, the respectively predicting the signal coverage field strength values of the target 3d mimo cell in the target geographic area when different antenna weights are adopted may specifically include the following steps, as shown in fig. 3:
step 121: and calculating an angle value of a relative azimuth angle and an angle value of a relative downtilt angle of the central point of at least one grid relative to the antenna of the target 3DMIMO cell according to the azimuth angle and the downtilt angle of the antenna of the target 3DMIMO cell.
In practical applications, the azimuth angle of the antenna may be an included angle between a sagittal plane of the antenna and a north direction, and the downward inclination angle of the antenna may be an included angle between a horizontal plane of the antenna and a vertical direction. In this embodiment, since the geographic location of the antenna of the target 3d mimo cell is fixed, and the azimuth angle and the downtilt angle of the antenna of the target 3d mimo cell can be adjusted and fixed in advance, the angle value of the center point of any grid with respect to the relative azimuth angle and the angle value of the relative downtilt angle of the antenna can be calculated according to the azimuth angle and the downtilt angle of the antenna which are fixed in advance.
For example, a three-dimensional coordinate system may be constructed, the antenna and the three-dimensional grid model may be placed in the three-dimensional coordinate system, the position of the antenna and the position of the center point of any grid in the three-dimensional grid may be represented by three-dimensional coordinates, and the angle value of the center point of any grid with respect to the relative azimuth angle and the angle value of the relative downtilt angle of the antenna may be calculated based on the coordinate system. Specifically, as shown in fig. 4, AB is the hanging height of the antenna, point a is the position of the antenna, point E is the position of the center point of the grid, the azimuth angle of the antenna is ψ ═ DBC, and the down-tilt angle is ═ BAC, then the angle value of the center point E of the grid relative to the relative azimuth angle of the antenna
Comprises the following steps:
wherein x1And y1Respectively, the abscissa and ordinate, x, of the point a antenna in fig. 4 in the coordinate system3And y3The abscissa and ordinate of the point D in fig. 4.
The angular value of the relative downtilt angle θ is:
it is understood that the angle value of the relative azimuth angle and the angle value of the relative downtilt angle of the center point of any grid in the three-dimensional grid model with respect to the antenna can be calculated based on the above method, which is not exhaustive. It should be noted that the above method for calculating the angle value of the center point of the grid with respect to the relative azimuth angle and the angle value of the relative downtilt angle of the antenna is a specific implementation manner provided in the embodiments of the present specification, and does not represent all implementation manners of the embodiments of the present specification, and of course, other calculation manners may also be adopted, which does not limit the present application.
Step 122: and inquiring an antenna gain configuration table corresponding to different antenna weights according to the angle value of the relative azimuth angle and the angle value of the relative downtilt angle so as to obtain the antenna gain of the central point.
Here, the angle value with respect to the azimuth angle and the angle value with respect to the downtilt angle may be calculated through step 121.
It can be understood that, under different antenna weights, the antennas have different capabilities of transmitting and receiving signals in different directions, i.e., the antenna gains of the antennas are different under different antenna weights. In practical applications, the antenna gain configuration table may be data predetermined according to signal receiving capabilities of different signal sending directions, and the antenna gain configuration table may correspond to different antenna gain configuration tables under different antenna weights, for example: table 3 may be an antenna gain configuration table corresponding to a certain antenna weight.
Table 3: antenna gain configuration table corresponding to certain antenna weight
In the embodiment of the present description, according to different antenna weights, and the calculated relative azimuth angle and relative downtilt angle, a corresponding antenna gain configuration table is queried, and the antenna gain of the center point of the grid is obtained. For example, as shown in the antenna gain configuration table corresponding to a certain antenna weight in table 3, if the calculated angle value of the center point of a certain grid with respect to the relative azimuth angle of the antenna is 2 ° and the angle value of the relative downtilt angle is 178 ° under the antenna weight, the antenna gain data at the center point of the grid is obtained as-27.1917 by querying the antenna gain configuration table.
In practical application, in order to facilitate querying antenna gains, antenna gain configuration tables corresponding to different antenna weights may be stored in a database or other readable storage media in advance, which is not limited in this application.
Step 123: and calculating the signal coverage field intensity value of the target 3DMIMO cell in the target geographic area when different antenna weights are adopted according to the antenna gain of the central point of the grid.
The antenna gain at the center point may be determined by step 122.
In this embodiment of the present specification, a signal coverage field strength value of the target 3DMIMO cell in the target geographic area when different antenna weights are used is calculated, that is, a signal coverage field strength value of the target 3DMIMO cell in the three-dimensional grid when different antenna weights are used is calculated, which may specifically adopt the following formula:
signal coverage field strength value: rxlev ═ 10 × lg (p) -epsilon + g-beta Lb
Wherein P is the known output power of the target 3d mimo cell;
ε is the known feeder loss;
g is the antenna gain at the center point of the grid determined by step 122;
beta is a preset weight coefficient;
lb is a known median of radio propagation path loss.
It can be understood that the signal coverage field strength value of each grid in the three-dimensional grid model under different antenna weights can be obtained through a calculation formula of the signal coverage field strength value. In practical applications, in order to distinguish which grid's signal coverage field strength value is calculated, as shown in fig. 2, each grid may be numbered with i, j, k, with a certain vertex of the three-dimensional stereo model as a starting point, where i (i ═ 1,2,3 … … n) denotes the number of grids arranged in the horizontal direction, and n denotes the maximum number of grids arranged in the horizontal direction; j (j ═ 1,2,3 … … m) denotes the number of the grids aligned in the vertical direction, and m denotes the maximum number of the grids aligned in the vertical direction; k (k is 1,2,3 … … f) represents the number of the grids arranged in the vertical direction, and f represents the maximum number of the grids arranged in the vertical direction, the antenna gain of the center point of a certain grid in the three-dimensional stereo grid model can be represented as gijkThen, the calculation formula of the signal coverage field strength value can be expressed as:
signal coverage field strength value: 10 xlg (P) - ε + gijk-β*Lb
In the embodiment of the present specification, based on the established three-dimensional grid model representing the space occupied by the geographic area, on the premise of not affecting the use of the users of the online mobile communication network, the signal coverage field strength values under different antenna weights are predicted by using the above calculation formula of the signal coverage field strength values, so as to serve as the reference signal receiving power of the target 3d mimo cell under different antenna weights.
Based on the same inventive concept, the embodiment of the present specification further provides a corresponding apparatus for automatically optimizing the antenna weight based on 3d mimo. As shown in fig. 5, the apparatus specifically includes:
the prediction module 21 is configured to predict, respectively, signal coverage field strength values of a target three-dimensional multiple-input multiple-output 3DMIMO cell in a target geographic area when different antenna weights are adopted, and use the signal coverage field strength values as target 3DMIMO cell reference signal receiving powers of respective sampling points in the target geographic area;
an obtaining module 22, configured to obtain reference signal received power of each sampling point for a neighboring cell of the target 3d mimo cell in the target geographic area;
a determining module 23, configured to determine, according to the reference signal receiving power of the neighboring cell and the target 3DMIMO cell signal receiving power, the number of sampling points in the target geographic area, where the target 3DMIMO cell is used as a serving cell, in each sampling point when the target 3DMIMO cell adopts the different antenna weights;
a selecting module 24, configured to select a target antenna weight from the different antenna weights according to the number; and the selected target antenna weight is used as a target value for setting the antenna weight of the target 3DMIMO cell.
The specific workflow of the above device embodiment may include: a prediction module 21 for predicting the signal coverage field strength value of a target three-dimensional multiple-input multiple-output 3DMIMO cell in a target geographic area when different antenna weights are adopted, and using the signal coverage field strength value as the target 3DMIMO cell reference signal receiving power of each sampling point in the target geographic area, an obtaining module 22 for obtaining the reference signal receiving power of each sampling point in the target geographic area to the adjacent cell of the target 3DMIMO cell, a determining module 23 for determining the number of sampling points in the target geographic area, which take the target 3DMIMO cell as a service cell, among the sampling points in the target geographic area when different antenna weights are adopted, according to the reference signal receiving power of the adjacent cell and the target 3DMIMO cell signal receiving power, a selecting module 24 for selecting the target antenna weight from different antenna weights according to the number, and the selected target antenna weight, for use as a target value for setting the antenna weights of the target 3d mimo cell.
In an embodiment, the apparatus may further include a model building module, where the model building module specifically includes:
the three-dimensional grid model establishing unit is used for establishing a three-dimensional grid model for representing the space occupied by the geographic area by utilizing a geographic information system; the geographic region comprises the target geographic region, and the space occupied by the target geographic region is characterized by at least one grid contained in the three-dimensional stereoscopic grid model;
the spatial information acquisition unit is used for acquiring spatial information of sampling points positioned in a geographic area from a measurement report MR aiming at the geographic area;
the grid determining unit is used for determining a grid to which the sampling points in the geographic area belong in the three-dimensional grid model according to the spatial information;
and the sampling point determining unit is used for determining the sampling points belonging to at least one grid as the sampling points in the target geographic area.
In an embodiment, the prediction module 21 specifically includes:
the first calculating unit is used for calculating an angle value of a relative azimuth angle and an angle value of a relative downtilt angle of a central point of at least one grid relative to the antenna of the target 3DMIMO cell according to the azimuth angle and the downtilt angle of the antenna of the target 3DMIMO cell;
the query unit is used for querying antenna gain tables corresponding to different antenna weights according to the angle value relative to the azimuth angle and the angle value relative to the downtilt angle so as to obtain the antenna gain of the central point;
and the second calculation unit is used for calculating the signal coverage field intensity value of the target 3DMIMO cell in the target geographic area when different antenna weights are adopted according to the antenna gain of the central point.
In an embodiment, a calculation formula of the signal coverage field strength value Rxlev specifically adopted in the second calculation unit is as follows:
Rxlev＝10×lg(P)-ε+g-β*Lb
wherein, P is the output power of the target 3DMIMO cell;
epsilon is the feeder loss;
g is the antenna gain at the center point;
beta is a preset weight coefficient;
lb is the median of the radio propagation path loss.
In an embodiment, the determining module 23 specifically includes:
the service cell determining unit is used for respectively executing specified operation aiming at each sampling point in each sampling point when the target 3DMIMO cell adopts different antenna weights; the specifying operation includes: determining a cell with the maximum reference signal receiving power as a service cell of the sampling point from the reference signal receiving power of the target 3DMIMO cell and the reference signal receiving power of the adjacent cell;
and the sampling point quantity determining unit is used for calculating the quantity of the sampling points which take the target 3DMIMO cell as the service cell when the target 3DMIMO cell adopts different antenna weights according to the service cell determined by aiming at each sampling point.
In an embodiment, the selecting module 24 specifically includes:
a maximum number determination unit for determining a maximum number of the numbers;
and the selecting unit is used for selecting the antenna weight corresponding to the maximum number as the target antenna weight.
In this embodiment of the present specification, by using the apparatus for automatically optimizing an antenna weight based on 3d mimo, it may be implemented to predict reference signal received power of a target 3d mimo cell under different antenna weights, determine the number of sampling points in the target geographic area using the 3d mimo cell as a serving cell, and then select a target antenna weight from the antenna weights of the 3d mimo according to the determined number.
On the other hand, the number of sampling points taking the target 3DMIMO cell as a service cell is determined according to the reference signal receiving power of the adjacent cell and the signal receiving power of the target 3DMIMO cell, so that the antenna weight of the target 3DMIM cell can be set by combining a plurality of cells covered by signals to a target geographic area. Compared with the prior art that the manual adjustment of the antenna weight can only aim at the 3DMIMO cell of the current base station, the comprehensive optimization can be realized, so that the selected target antenna weight is more suitable.
An embodiment of this specification further provides an electronic device, and referring to fig. 6, in 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. 6, 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 a corresponding computer program from the nonvolatile memory into the memory and then runs the computer program, and the automatic antenna weight optimizing device based on the 3D MIMO is formed on the logic level. A processor executing the program stored in the memory and configured to perform at least the following: respectively predicting signal coverage field intensity values of a target three-dimensional multi-input multi-output (3 DMIMO) cell in a target geographic area when different antenna weights are adopted, and taking the signal coverage field intensity values as target 3DMIMO cell reference signal receiving power of each sampling point in the target geographic area; acquiring reference signal receiving power of each sampling point in a target geographic area for a neighboring cell of a target 3DMIMO cell; determining the number of sampling points taking the target 3DMIMO cell as a service cell in each sampling point in the target geographic area when the target 3DMIMO cell adopts different antenna weights according to the reference signal receiving power of the adjacent cell and the signal receiving power of the target 3DMIMO cell; selecting a target antenna weight from different antenna weights according to the number; and the selected target antenna weight is used as a target value for setting the antenna weight of the target 3DMIMO cell.
The method for automatically optimizing the antenna weights based on the 3d mimo disclosed in the embodiment of fig. 1 of the present application may be applied to or 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 (FP), 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 specification 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 a method disclosed in connection with the embodiments of the present specification may be embodied directly in a hardware decoding processor, or in 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 further execute the method for automatically optimizing the antenna weight based on 3d mimo in fig. 1, and implement the functions of the apparatus for automatically optimizing the antenna weight based on 3d mimo in the embodiment shown in fig. 1, which are not described herein again.
The embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements each process of the above-mentioned method for automatically optimizing an antenna weight based on 3d mimo, and can achieve the same technical effect, and in order to avoid repetition, details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the specification. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
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 an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A method for automatically optimizing antenna weight based on 3DMIMO is characterized by comprising the following steps:
respectively predicting signal coverage field intensity values of a target three-dimensional multi-input multi-output (3 DMIMO) cell in a target geographic area when different antenna weights are adopted, and taking the signal coverage field intensity values as target 3DMIMO cell reference signal receiving power of each sampling point in the target geographic area;
acquiring reference signal receiving power of each sampling point for a neighboring cell of the target 3DMIMO cell in the target geographic area;
determining the number of sampling points taking the target 3DMIMO cell as a service cell in the sampling points in the target geographic region when the target 3DMIMO cell adopts different antenna weights according to the reference signal receiving power of the adjacent cell and the signal receiving power of the target 3DMIMO cell;
selecting a target antenna weight from the different antenna weights according to the number; and the selected target antenna weight is used as a target value for setting the antenna weight of the target 3DMIMO cell.
2. The method of claim 1, wherein prior to obtaining the reference signal received power for the sample points for the neighborhood of the target 3d mimo cell within the target geographic area, the method further comprises:
establishing a three-dimensional grid model for representing the space occupied by the geographic area by utilizing a geographic information system; the geographic region comprises the target geographic region, the space occupied by the target geographic region being characterized by at least one grid contained by the three-dimensional volumetric grid model;
acquiring spatial information of sampling points located in the geographic area from a measurement report MR aiming at the geographic area;
determining a grid of the sampling points in the geographic area in the three-dimensional grid model according to the spatial information;
and determining the sampling points belonging to the at least one grid as the sampling points in the target geographic area.
3. The method of claim 2, wherein the step of predicting the signal coverage field strength values of the target three-dimensional multiple-input multiple-output (3 d mimo) cell in the target geographic area when different antenna weights are used comprises:
calculating an angle value of a relative azimuth angle and an angle value of a relative downtilt angle of a center point of at least one grid with respect to an antenna of the target 3DMIMO cell according to the azimuth angle and the downtilt angle of the antenna of the target 3DMIMO cell;
inquiring an antenna gain configuration table corresponding to the different antenna weights according to the angle value of the relative azimuth angle and the angle value of the relative downtilt angle so as to obtain the antenna gain of the central point;
and calculating the signal coverage field intensity value of the target 3DMIMO cell in the target geographic area when different antenna weights are adopted according to the antenna gain of the central point.
4. The method according to claim 3, wherein the calculating, according to the antenna gain of the central point, a signal coverage field strength value of the target 3d mimo cell in the target geographical area when different antenna weights are applied includes:
calculating a signal coverage field intensity value Rxlev of the target 3DMIMO cell in the three-dimensional grid when different antenna weights are adopted by adopting the following formula:
Rxlev＝10×lg(P)-ε+g-β*Lb
wherein P is the output power of the target 3DMIMO cell;
epsilon is the feeder loss;
g is the antenna gain of the center point;
beta is a preset weight coefficient;
lb is the median of the radio propagation path loss.
5. The method according to claim 1, wherein the determining, according to the reference signal received power of the neighboring cell and the target 3DMIMO cell signal received power, the number of sampling points in the target geographic area, of which the target 3DMIMO cell is used as a serving cell, when the target 3DMIMO cell employs the different antenna weights, specifically includes:
when the target 3DMIMO cell adopts the different antenna weights, respectively executing specified operation aiming at each sampling point in each sampling point; the specifying operation includes: determining a cell with the maximum reference signal receiving power as a serving cell of the sampling point from the reference signal receiving power of the target 3DMIMO cell and the reference signal receiving power of the adjacent cell;
and calculating the number of sampling points which take the target 3DMIMO cell as a service cell when the target 3DMIMO cell adopts the different antenna weights according to the service cell determined by aiming at each sampling point.
6. The method according to claim 1, wherein the selecting the target antenna weight from the different antenna weights according to the number specifically comprises:
determining a maximum number of the numbers;
and selecting the antenna weight corresponding to the maximum number as the target antenna weight.
7. An antenna weight automatic optimization device based on 3DMIMO is characterized by comprising:
the device comprises a prediction module, a power module and a power module, wherein the prediction module is used for respectively predicting signal coverage field intensity values of a target three-dimensional multi-input multi-output 3DMIMO cell in a target geographic area when different antenna weights are adopted, and the signal coverage field intensity values are used as target 3DMIMO cell reference signal receiving power of each sampling point in the target geographic area;
an obtaining module, configured to obtain reference signal received power of each sampling point for a neighboring cell of the target 3d mimo cell in the target geographic area;
a determining module, configured to determine, according to the reference signal receiving power of the neighboring cell and the target 3DMIMO cell signal receiving power, the number of sampling points in the target geographic area, where the target 3DMIMO cell is used as a serving cell, among the sampling points in the target geographic area when the target 3DMIMO cell adopts the different antenna weights;
a selecting module, configured to select a target antenna weight from the different antenna weights according to the number; and the selected target antenna weight is used as a target value for setting the antenna weight of the target 3DMIMO cell.
8. The apparatus of claim 7, wherein the determining module specifically comprises:
a serving cell determining unit, configured to perform a specified operation on each of the sampling points when the target 3d mimo cell employs the different antenna weights; the specifying operation includes: determining a cell with the maximum reference signal receiving power as a serving cell of the sampling point from the reference signal receiving power of the target 3DMIMO cell and the reference signal receiving power of the adjacent cell;
and the sampling point number determining unit is used for calculating the number of sampling points which take the target 3DMIMO cell as a service cell when the target 3DMIMO cell adopts the different antenna weights according to the service cell determined by aiming at each sampling point.
9. An electronic device, comprising: memory, processor and computer program stored on the memory and executable on the processor, the computer program when executed by the processor implementing the method for automatic optimization of antenna weights based on 3d mimo according to any of claims 1 to 6.
10. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, implements the method for automatic optimization of antenna weights based on 3d mimo according to any of claims 1 to 6.
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