CN112203318B - Network coverage analysis method and device - Google Patents

Network coverage analysis method and device Download PDF

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CN112203318B
CN112203318B CN202011123382.9A CN202011123382A CN112203318B CN 112203318 B CN112203318 B CN 112203318B CN 202011123382 A CN202011123382 A CN 202011123382A CN 112203318 B CN112203318 B CN 112203318B
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grid
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CN112203318A (en
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曹艳霞
王金石
冯毅
李福昌
钟志刚
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China United Network Communications Group Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/06—Testing, supervising or monitoring using simulated traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/08—Testing, supervising or monitoring using real traffic
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The embodiment of the application provides a network coverage analysis method and device, relates to the technical field of communication, and solves the technical problems of lower accuracy and higher cost of a method for determining the coverage quality of a wireless mobile communication network in the prior art. The network coverage analysis method comprises the following steps: acquiring a first coverage level of a target three-dimensional grid through system simulation, and acquiring level deviation of the target three-dimensional grid through a calibration library; determining a sum of the first overlay level and the level deviation as a standard level value of the target stereoscopic grid; the target three-dimensional grid is any one of M three-dimensional grids divided according to the antenna of the target cell, the calibration library comprises level deviation of each three-dimensional grid of the M three-dimensional grids, and M is a positive integer.

Description

Network coverage analysis method and device
Technical Field
The present disclosure relates to the field of communications technologies, and in particular, to a network coverage analysis method and apparatus.
Background
The coverage quality of a wireless mobile communication network is an important factor related to the communication quality, and is also an important index for a mobile operator to check the network quality.
In general, the prior art may determine the coverage quality of a wireless mobile communication network by sweep testing the network coverage level by a drive test device. However, this approach requires a lot of manpower, material resources and time costs, and is often limited by the area, so that the traversal test of the entire coverage area of the network cannot be implemented, and thus, the accuracy of the method for determining the coverage quality of the wireless mobile communication network in the prior art is low and the cost is high.
Disclosure of Invention
The application provides a network coverage analysis method and device, which solve the technical problems of lower accuracy and higher cost of a method for determining the coverage quality of a wireless mobile communication network in the prior art.
In order to achieve the above purpose, the present application adopts the following technical scheme:
in a first aspect, a network coverage analysis method is provided, including: acquiring a first coverage level of a target three-dimensional grid through system simulation, and acquiring level deviation of the target three-dimensional grid through a calibration library; determining a sum of the first overlay level and the level deviation as a standard level value of the target stereoscopic grid; the target three-dimensional grid is any one of M three-dimensional grids divided according to the antenna of the target cell, the calibration library comprises level deviation of each three-dimensional grid of the M three-dimensional grids, and M is a positive integer.
In the embodiment of the application, the first coverage level of the target three-dimensional grid can be obtained through system simulation, and the level deviation of the target three-dimensional grid can be obtained through a calibration library; and determining a sum of the first overlay level and the level deviation as a standard level value of the target stereoscopic grid; the target three-dimensional grid is any one of M three-dimensional grids divided according to the antenna of the target cell, and the calibration library comprises level deviations of each three-dimensional grid of the M three-dimensional grids. According to the scheme, the first coverage level obtained by system simulation can be calibrated through level deviation in the calibration library, so that the standard level value of the target three-dimensional grid can be determined, and the accuracy of the analysis result of the coverage quality of the wireless mobile communication network is improved.
In a second aspect, there is provided a network coverage analysis apparatus comprising: an acquisition unit and a processing unit. The acquisition unit is used for acquiring a first coverage level of the target three-dimensional grid through system simulation and acquiring level deviation of the target three-dimensional grid through a calibration library; the processing unit is used for determining the sum of the first coverage level and the level deviation as a standard level value of the target stereoscopic grid; the target three-dimensional grid is any one of M three-dimensional grids divided according to the antenna of the target cell, the calibration library comprises level deviation of each three-dimensional grid of the M three-dimensional grids, and M is a positive integer.
In a third aspect, a network coverage analysis apparatus is provided that includes a memory and a processor. The memory is used for storing computer execution instructions, and the processor is connected with the memory through a bus. When the network coverage analysis device is operated, the processor executes computer-executable instructions stored in the memory to cause the network coverage analysis device to perform the network coverage analysis method provided in the first aspect.
In a fourth aspect, there is provided a computer-readable storage medium comprising computer-executable instructions which, when run on a computer, cause the computer to perform the network coverage analysis method provided in the first aspect.
In a fifth aspect, a computer program product is provided, the computer program product comprising computer instructions which, when run on a computer, cause the computer to perform the network coverage analysis method as provided in the first aspect and its various possible implementations.
It should be noted that the above-mentioned computer instructions may be stored in whole or in part on a computer-readable storage medium. The computer readable storage medium may be packaged together with the processor of the network coverage analysis device or may be packaged separately from the processor of the network coverage analysis device, which is not limited in this application.
The descriptions of the second aspect, the third aspect, the fourth aspect, and the fifth aspect in the present application may refer to the detailed description of the first aspect, which is not repeated herein; moreover, the advantages described in the second aspect, the third aspect, the fourth aspect and the fifth aspect may refer to the analysis of the advantages of the first aspect, and are not described herein.
In the present application, the names of the above-mentioned network coverage analysis apparatuses do not constitute limitations on the devices or function modules themselves, and in actual implementations, these devices or function modules may appear under other names. Insofar as the function of each device or function module is similar to the present application, it is within the scope of the claims of the present application and the equivalents thereof.
These and other aspects of the present application will be more readily apparent from the following description.
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Fig. 1 is a schematic hardware structure diagram of a network coverage analysis device according to an embodiment of the present application;
FIG. 2 is a second schematic hardware structure of a network coverage analysis device according to an embodiment of the present disclosure;
fig. 3 is a schematic flow chart of a network coverage analysis method according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a coordinate system according to an embodiment of the present disclosure;
FIG. 5 is a second flow chart of a network coverage analysis method according to the embodiment of the present application;
fig. 6 is a schematic structural diagram of a network coverage analysis device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
It should be noted that, in the embodiments of the present application, words such as "exemplary" or "such as" are used to mean serving as an example, instance, or illustration. Any embodiment or design described herein as "exemplary" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete fashion.
In order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first", "second", and the like are used to distinguish the same item or similar items having substantially the same function and effect, and those skilled in the art will understand that the terms "first", "second", and the like are not limited in number and execution order.
The embodiment of the application provides a network coverage analysis method, which can be applied to a network coverage analysis device shown in fig. 1, wherein the network coverage analysis device comprises a processor 11, a memory 12, a communication interface 13 and a bus 14. The processor 11, the memory 12 and the communication interface 13 may be connected by a bus 14.
The processor 11 is a control center of the network coverage analysis device, and may be one processor or a collective name of a plurality of processing elements. For example, the processor 11 may be a general-purpose central processing unit (central processing unit, CPU), or may be another general-purpose processor. Wherein the general purpose processor may be a microprocessor or any conventional processor or the like.
As an example, processor 11 may include one or more CPUs, such as CPU 0 and CPU 1 shown in fig. 1.
Memory 12 may be, but is not limited to, read-only memory (ROM) or other type of static storage device that can store static information and instructions, random access memory (random access memory, RAM) or other type of dynamic storage device that can store information and instructions, as well as electrically erasable programmable read-only memory (EEPROM), magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
In a possible implementation, the memory 12 may exist separately from the processor 11, and the memory 12 may be connected to the processor 11 through the bus 14 for storing instructions or program code. The processor 11, when calling and executing instructions or program code stored in the memory 12, is capable of implementing the network coverage analysis method provided in the embodiments of the present application.
In another possible implementation, the memory 12 may also be integrated with the processor 11.
A communication interface 13 for connecting with other devices via a communication network. The communication network may be an ethernet, a radio access network, a wireless local area network (wireless local area networks, WLAN), etc. The communication interface 13 may include a receiving unit for receiving data, and a transmitting unit for transmitting data.
Bus 14 may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in fig. 1, but not only one bus or one type of bus.
It should be noted that the structure shown in fig. 1 does not constitute a limitation of the network coverage analysis device. The network coverage analysis means may comprise more or less components than shown in fig. 1, or may be combined with certain components, or may be arranged in a different arrangement of components.
Fig. 2 shows another hardware structure of the network coverage analysis apparatus in the embodiment of the present application. As shown in fig. 2, the network coverage analysis means may comprise a processor 21 and a communication interface 22. The processor 21 is coupled to a communication interface 22.
The function of the processor 21 may be as described above with reference to the processor 11. The processor 21 also has a memory function, and the function of the memory 12 can be referred to.
The communication interface 22 is used to provide data to the processor 21. The communication interface 22 may be an internal interface of the network coverage analysis device or an external interface of the network coverage analysis device (corresponding to the communication interface 13).
It should be noted that the structure shown in fig. 1 (or fig. 2) does not constitute a limitation of the network coverage analysis apparatus, and the network coverage analysis apparatus may include more or less components than those shown in fig. 1 (or fig. 2), or may combine some components, or may be arranged in different components.
The network coverage analysis method provided in the embodiment of the present application will be described in detail below with reference to the network coverage analysis apparatuses shown in fig. 1 and 2.
As shown in fig. 3, the embodiment of the present application provides a network coverage analysis method, which may be applied to a network coverage analysis apparatus, and may include S301 and S302 described below.
S301, the network coverage analysis device acquires a first coverage level of the target three-dimensional grid through system simulation, and acquires level deviation of the target three-dimensional grid through a calibration library.
The target three-dimensional grid is any one of M three-dimensional grids divided according to the antenna of the target cell, and the calibration library comprises level deviations of each three-dimensional grid of the M three-dimensional grids. The level deviation refers to the difference between the level simulation value and the true level value, and M is a positive integer.
The network coverage analysis means may first determine the location coordinates (longitude) of the target cell antenna b ,latitude b ,z b ) Wherein, longitude b Representing the longitude of the target cell antenna b Representing longitude, z of target cell antenna b Representing the suspension height of the target cell antenna. The network coverage analysis means may then convert the position coordinates into geodetic coordinates (x b ,y b ,z b )，x b Representing the x-axis coordinate, y, converted to geodetic coordinate b Representing the y-axis coordinate, z, converted to geodetic coordinates b Representing z-axis coordinates converted to geodetic coordinates. As shown in fig. 4, after determining the geodetic coordinates, the network coverage analysis device may use the vertical projection point of the target cell antenna on the ground plane as the origin, i.e. the coordinate point O (x b ,y b 0) as an origin, the positive east direction as an X axis, the positive north direction as a Y axis, the upward direction perpendicular to the XOY plane as a Z axis, and on the basis of the coordinate system, a cylindrical coverage analysis space is established with the origin O as the center, D as the radius and H as the height. Wherein, D can take 2-3 times of cell coverage distance according to the coverage of the cell, for example, dense urban area can select d=1000m, rural suburban area can select d=2000 m; h can take the height of the covered building as a reference, and has a value of 60-80 m.
After the coverage analysis space is obtained, the network coverage analysis device can determine coordinate points in the coverage analysis space(x p ,y p ,z p ) Relative three-dimensional coordinates with target cell antenna
Figure BDA0002732786830000051
Wherein (1)>
Figure BDA0002732786830000061
θ represents the coordinate point (x p ,y p ,z p ) Horizontal offset angle, θ ', relative to target cell antenna azimuth' AZ ＝mod(450-θ AZ ,360)，mod(450-θ AZ 360) represents 450-theta AZ And 360-phase division to obtain remainder value of remainder, theta AZ Represents azimuth (i.e., angle of 0 degrees in the north direction and clockwise direction) of the target cell,>
Figure BDA0002732786830000062
representing the negation cut angle over the angular range (-180, 180). And when θ exceeds the angle range (-180, 180), the angle conversion can be performed on θ, specifically: if θ is less than-180, θ=θ+360; if θ is greater than 180, θ=θ -360./>
Figure BDA0002732786830000063
Figure BDA0002732786830000064
Represents the coordinate point (x p ,y p ,z p ) Vertical offset angle relative to downtilt of target cell antenna,/->
Figure BDA0002732786830000065
Representing the downtilt (including the sum of the electronic downtilt and the mechanical downtilt) of the target cell antenna>
Figure BDA0002732786830000066
The range of values of (-180, 180). />
Figure BDA0002732786830000067
dis represents the coordinate point (x p ,y p ,z p ) Linear distance relative to the target cell antenna.
Determining relative three-dimensional coordinates
Figure BDA0002732786830000068
After that, the network coverage analysis means may split θ by (m+0.5) ×Δθ, where m= -a, -a+1, 0, a-1>
Figure BDA0002732786830000069
Δθ is a value divisible by 180, and the default value may be 5; to->
Figure BDA00027327868300000610
For->
Figure BDA00027327868300000611
A cut is made, where n= -B, -B +1, once again, 0, B-1, d>
Figure BDA00027327868300000612
Figure BDA00027327868300000613
A default value may be 3, which is a value divisible by 180; splitting dis with k x Δdis, where k=0, 1, 2..c, +.>
Figure BDA00027327868300000614
The default value for Δdis may be 10.
The network coverage analysis device can divide the coverage analysis space into M grids according to the above dividing points, wherein M=2A×2B (C+1) is calculated according to each coordinate point
Figure BDA00027327868300000615
Take the value, the coordinate point can be belonged to the corresponding grid and
Figure BDA00027327868300000616
as the centroid coordinates of the individual grids. Then, the network coverage analysis device can simulate the network coverage according to a dynamic system simulation method or a static system simulation methodA reference signal received power (Reference Signal Receiving Power, RSRP) covering the centroid of the target volumetric grid within the analysis space is simulated to obtain a first coverage level of the target volumetric grid.
It should be noted that, in the simulation process, the path loss may be based on a calibrated empirical path loss propagation model and a propagation model software of ray tracing, and the antenna model may be based on a formula model or may be based on a manner of an actual antenna gain pattern; the configuration of wireless parameters such as the simulated site-site spacing and the like can adopt the configuration of the actual site.
The calibration library comprises level deviations of each of the M three-dimensional grids, wherein one level deviation corresponds to one grid coordinate. The network coverage analysis means may determine the level deviation of the target stereoscopic grid from the grid coordinates.
S302, the network coverage analysis device determines the sum of the first coverage level and the level deviation as a standard level value of the target stereoscopic grid.
The network coverage analysis means may be according to the formula:
Figure BDA0002732786830000071
a standard level value is determined for the target stereoscopic grid. Wherein (1)>
Figure BDA0002732786830000072
Representing standard level values, +.>
Figure BDA0002732786830000073
Representing a first override level,/->
Figure BDA0002732786830000074
Indicating the level deviation.
Because the target stereoscopic grid is any one of the M stereoscopic grids, repeating the steps S301 to S302 can obtain standard level values of the M stereoscopic grids, so that overall analysis and evaluation of network coverage can be realized.
The embodiment of the application provides a network coverage analysis method, which can calibrate a first coverage level obtained by system simulation through level deviation in a calibration library, so that a standard level value of a target three-dimensional grid can be determined, and the accuracy of an analysis result of coverage quality of a wireless mobile communication network is improved.
Optionally, in combination with fig. 3, as shown in fig. 5, before S301, the network coverage analysis method provided in the embodiment of the present application may further include S303 to S305 described below.
S303, the network coverage analysis device determines a first coverage level of each of the M stereoscopic grids through system simulation.
The method for determining the first coverage level of each of the M stereoscopic grids by the network coverage analysis device may refer to the description related to determining the first coverage level of the target stereoscopic grid in S301, which is not described herein.
S304, the network coverage analysis device acquires a second coverage level of each of the N calibration grids, and obtains a level deviation between the first coverage level and the second coverage level of each of the N calibration grids.
The N calibration grids are grids in the M three-dimensional grids, and N is a positive integer smaller than M.
The network coverage analysis means may determine the location information of the calibration grid corresponding to the terminal device and the second coverage level of the calibration grid based on the real-time location information of the terminal device, the measurement reports (Measurement Report, MR) reported by the terminal device and the signaling information extracted from the telecom operator device interface.
Specifically, the network coverage analysis device may extract real-time location information of the terminal device from the OTT (Over The Top) service platform, extract signaling information from the telecom operator device interface, for example, may be signaling extracted from the S1-MME interface, and extract MR information from the network management device, where the MR information may include MR information reported by the terminal device when the target cell is used as a serving cell and a neighboring cell. By carrying out key field association on the information, the network coverage analysis device can obtain calibration point information accurately positioned based on the user terminal equipment, wherein the calibration point information comprises position information of the calibration point and second coverage level of the calibration point, and the position information of the calibration point can be extracted from an OTT service platform and comprises longitude, latitude, altitude and other information of the terminal equipment; the second coverage level of the calibration point may be determined in combination with the terminal device location information, MR information and signaling information.
The network coverage analysis means may then convert the position information of the calibration points into geodetic coordinates (x e ,y e ,z e ) And the same transformed coordinate system as in S301 is used to transform the geodetic coordinates (x e ,y e ,z e ) Transformed into coordinates (x) in a coordinate system XOYZ e -x b ,y e -y b ,z e ). Coordinates (x) e -x b ,y e -y b ,z e ) Converting relative three-dimensional coordinates with respect to a target cell antenna
Figure BDA0002732786830000081
Thereby being based on the relative three-dimensional coordinates of the calibration point +.>
Figure BDA0002732786830000082
N calibration grids are determined from the M stereoscopic grids, and a first coverage level of the N calibration grids is obtained.
After the network coverage analysis means determines the second coverage level and the first coverage level of each of the N calibration grids, the level deviation between the first coverage level and the second coverage level of each of the N calibration grids may be obtained by differencing the two.
When a plurality of calibration points exist in the same grid, the average value of the second coverage levels of the plurality of calibration points may be selected as the second coverage level of the grid, and the value-taking method includes, but is not limited to, a direct average method, a probability median method, a level linear value average method, and the like. For example, the average value of the levels may be
Figure BDA0002732786830000083
Alternatively, level averagingThe value may be +.>
Figure BDA0002732786830000084
Wherein RSRP i A sequence ordered in order from major to minor or from minor to major; alternatively, the average value of the levels may be +.>
Figure BDA0002732786830000085
Where X represents the number of calibration points included in one grid.
And S305, the network coverage analysis device determines the level deviation of each three-dimensional grid in the (M-N) three-dimensional grids according to the level deviations of the N calibration grids to obtain a calibration library.
The network coverage analysis means may perform curve fitting on different dimensions of the level deviations of the N stereoscopic grids, respectively, to thereby determine the level deviation of each of the (M-N) stereoscopic grids. And a calibration library including level deviations of M stereoscopic grids is obtained.
Specifically, the network coverage analysis device may determine the level deviations of the N stereoscopic grids first, and then sequentially pair the dis dimension, the θ dimension, and the θ dimension
Figure BDA0002732786830000091
The dimensions are curve fitted.
(1) Curve fitting was performed on dis dimensions.
The N calibration grids are primary calibration grids, and the network coverage analysis device can traverse theta of the primary calibration grids amend And
Figure BDA0002732786830000092
for each pair of combinations, for a different dis amend The corresponding level deviation ΔRSRP is based on log (dis) amend ) Curve fitting was performed.
Alternatively, the fitting method may include, but is not limited to, least squares fitting, gaussian fitting, polynomial fitting, and the like.
The network coverage analysis means fits the level deviations Δrsrp and log (dis) amend ) After the fitting relation between the two is usedFor theta amend And
Figure BDA0002732786830000093
the grid level bias of the next non-primary calibration grid is combined for computational evaluation.
For example, if fitting is performed by the least squares method, the fitting curve may be: Δrsrp=f (log (dis) amend ) At least one of the following) in
Figure BDA0002732786830000094
In the minimum case, the curve is a least square fitting curve, namely DeltaRSRP and dis amend The relation between the two is used to calculate the level deviation of the non-primary calibration grid.
The grid of the level deviation obtained by using the above fitting relation may be used as a secondary calibration grid, and the secondary calibration grid may be used as a calibration grid in the next dimension.
(2) And performing curve fitting on the theta dimension.
The network coverage analysis means may traverse dis of the calibration grid amend And
Figure BDA0002732786830000095
for each pair of combinations, for different theta amend Corresponding ΔRSRP is based on θ amend Curve fitting was performed.
The calibration grid in this step is the union of the primary calibration grid and the secondary calibration grid in (1) above. The grid of level deviations obtained by this step can be used as a three-stage calibration grid.
(3) For a pair of
Figure BDA0002732786830000096
The dimensions are curve fitted.
The network coverage analysis means may traverse dis of the calibration grid amend And theta amend Combinations, for each pair of combinations, to different
Figure BDA0002732786830000097
Corresponding Δrsrp basis +.>
Figure BDA0002732786830000098
Curve fitting was performed.
The calibration grid in this step is the union of the primary calibration grid, the secondary calibration grid, and the tertiary calibration grid in (2).
The foregoing description of the solution provided in the embodiments of the present application has been mainly presented in terms of a method. To achieve the above functions, it includes corresponding hardware structures and/or software modules that perform the respective functions. Those of skill in the art will readily appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is implemented as hardware or computer software driven hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
According to the network coverage analysis method provided by the embodiment of the application, the execution subject can be a network coverage analysis device or a control module used for executing network coverage analysis service in the network coverage analysis device. In the embodiment of the present application, a network coverage analysis device executes a network coverage analysis method as an example, and a service device for executing network coverage analysis provided in the embodiment of the present application is described.
It should be noted that, in the embodiment of the present application, the network coverage analysis device may be divided into functional modules according to the above method example, for example, each functional module may be divided corresponding to each function, or two or more functions may be integrated into one processing module. The integrated modules may be implemented in hardware or in software functional modules. Optionally, the division of the modules in the embodiments of the present application is schematic, which is merely a logic function division, and other division manners may be actually implemented.
As shown in fig. 6, an embodiment of the present application provides a network coverage analysis device. The network coverage analysis device 600 may include an acquisition unit 601 and a processing unit 602. The acquiring unit 601 may be configured to acquire a first coverage level of a target stereoscopic grid through system simulation, and acquire a level deviation of the target stereoscopic grid through a calibration library. The processing unit 602 may be configured to determine a sum of the first overlay level and the level deviation as a standard level value of the target stereoscopic grid; the target three-dimensional grid is any one of M three-dimensional grids divided according to the antenna of the target cell, the calibration library comprises level deviation of each three-dimensional grid of the M three-dimensional grids, and M is a positive integer. For example, in connection with fig. 3, the acquisition unit 601 may be used to perform S301, and the processing unit 602 may be used to perform S302.
Optionally, the processing unit 602 may be further configured to determine, through system simulation, a first coverage level of each of the M stereoscopic grids. For example, in connection with fig. 5, the processing unit 602 may be configured to perform S303. The obtaining unit 601 may be further configured to obtain a second coverage level of each of N calibration grids, and obtain a level deviation between the first coverage level and the second coverage level of each of the N calibration grids, where the N calibration grids are grids in the M stereoscopic grids. For example, in connection with fig. 5, the obtaining unit 601 may be configured to perform S304, and the processing unit 602 may be further configured to determine a level deviation of each of the (M-N) stereoscopic grids according to the level deviations of the N calibration grids, to obtain the calibration library, where N is a positive integer smaller than M. For example, in connection with fig. 5, the processing unit 602 may be used to perform S305.
Optionally, the processing unit 602 may specifically be configured to: and respectively performing curve fitting on different dimensions of the level deviations of the N stereoscopic grids, and determining the level deviation of each stereoscopic grid in the (M-N) stereoscopic grids.
Alternatively, the above-mentioned acquiring unit 601 may specifically be configured to: and determining the position information of the calibration grid corresponding to the terminal equipment and the second coverage level of the calibration grid according to the real-time position information of the terminal equipment, the measurement report MR information reported by the terminal equipment and the signaling information extracted from the telecom operator equipment interface.
Of course, the network coverage analysis device 600 provided in the embodiment of the present application includes, but is not limited to, the above modules.
In actual implementation, the processing unit 602 may be implemented by the processor 11 shown in fig. 1 invoking program code in the memory 12. The specific implementation process may refer to the description of the network coverage analysis method shown in fig. 3 or fig. 5, and will not be repeated here.
The embodiment of the application provides a network coverage analysis device, which can calibrate a first coverage level obtained by system simulation through level deviation in a calibration library, so that the network coverage analysis device can determine a standard level value of a target three-dimensional grid, thereby improving the accuracy of an analysis result of coverage quality of a wireless mobile communication network.
Embodiments of the present application also provide a computer-readable storage medium including computer-executable instructions. When the computer executes the instructions on the computer, the computer is caused to perform the steps performed by the network coverage analysis device in the network coverage analysis method provided in the above embodiment.
The embodiment of the application also provides a computer program product, which can be directly loaded into a memory and contains software codes, and the computer program product can realize each step executed by the network coverage analysis device in the network coverage analysis method provided by the embodiment after being loaded and executed by a computer.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using a software program, it may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer-executable instructions are loaded and executed on a computer, the processes or functions in accordance with embodiments of the present application are fully or partially produced. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, a website, computer, server, or data center via a wired (e.g., coaxial cable, fiber optic, digital subscriber line (digital subscriber line, DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. Computer readable storage media can be any available media that can be accessed by a computer or data storage devices including one or more servers, data centers, etc. that can be integrated with the media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a Solid State Disk (SSD)), or the like.
From the foregoing description of the embodiments, it will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of functional modules is illustrated, and in practical application, the above-described functional allocation may be implemented by different functional modules according to needs, i.e. the internal structure of the apparatus is divided into different functional modules to implement all or part of the functions described above.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and the division of modules or units is merely a logical function division, and other manners of division may be implemented in practice. For example, multiple units or components may be combined or may be integrated into another device, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form. The units described as separate parts may or may not be physically separate, and the parts shown as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed in a plurality of different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units. The integrated units may be stored in a readable storage medium if implemented in the form of software functional units and sold or used as stand-alone products. Based on such understanding, the technical solution of the embodiments of the present application may be essentially or a part contributing to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, including several instructions for causing a device (may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions easily conceivable by those skilled in the art within the technical scope of the present application should be covered in the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims (6)

1. A network coverage analysis method, comprising:
acquiring a first coverage level of a target three-dimensional grid through system simulation, and acquiring level deviation of the target three-dimensional grid through a calibration library;
determining a sum of the first overlay level and the level deviation as a standard level value of the target stereoscopic grid;
the target three-dimensional grid is any one of M three-dimensional grids divided according to a target cell antenna, the calibration library comprises level deviation of each three-dimensional grid in the M three-dimensional grids, and M is a positive integer;
any one grid of the M three-dimensional grids divided according to the target cell antenna comprises: determining a coverage analysis space according to the coverage area and the coverage height of the cell;
determining a coordinate point (x p ,y p ,z p ) Relative three-dimensional coordinates with target cell antenna
Figure FDA0004272540130000011
Wherein (1)>
Figure FDA0004272540130000012
θ represents the coordinate point (x p ,y p ,z p ) A horizontal offset angle, θ ', relative to the target cell antenna azimuth' AZ ＝mod(450-θ AZ ,360)，mod(450-θ AZ 360) represents 450-theta AZ And 360-phase division to obtain remainder value of remainder, theta AZ Representing azimuth angle, +_of the target cell>
Figure FDA0004272540130000013
Representing the negation cut angle over a range of angles (-180, 180); when θ exceeds the angle range (-180, 180), the angle conversion is performed on θ, specifically: if θ is less than-180, θ=θ+360; if θ is greater than 180, θ=θ -360; />
Figure FDA0004272540130000014
Figure FDA0004272540130000015
Representing the sitting positionPunctuation (x) p ,y p ,z p ) Vertical offset angle relative to downtilt of target cell antenna,/->
Figure FDA0004272540130000016
Representing the downtilt of the target cell antenna, +.>
Figure FDA0004272540130000017
The range of values of (-180, 180); />
Figure FDA0004272540130000018
dis represents the coordinate point (x p ,y p ,z p ) A linear distance relative to the target cell antenna; θ was split by (m+0.5) ×Δθ, where m= -a, -a+1,..0, …, a-1,/-1,>
Figure FDA0004272540130000019
Δθ is a value divided by 180, and the default value is 5; to->
Figure FDA00042725401300000110
For->
Figure FDA00042725401300000111
A cut is made, where n= -B, -B +1, once again, 0, B-1, d>
Figure FDA00042725401300000112
Figure FDA00042725401300000113
A value divided by 180, the default value is 3; splitting dis with k x Δdis, where k=0, 1, 2..c, +.>
Figure FDA00042725401300000114
Δdis default is 10; dividing the coverage analysis space into M grids according to the segmentation points, wherein m=2a×2b (c+1), and the coverage analysis space is divided into M grids according to the +/C of each coordinate point>
Figure FDA00042725401300000115
Assigning values to coordinate points in corresponding grids to +.>
Figure FDA00042725401300000116
As centroid coordinates of the respective grids;
the method further comprises the steps of:
determining a first coverage level of each of the M stereoscopic grids by system simulation;
acquiring a second coverage level of each of N calibration grids, and acquiring level deviation between a first coverage level and a second coverage level of each of the N calibration grids, wherein the N calibration grids are grids in the M stereoscopic grids;
determining the level deviation of each three-dimensional grid in the (M-N) three-dimensional grids according to the level deviations of the N calibration grids to obtain the calibration library;
wherein N is a positive integer less than M;
the determining the level deviation of each of the (M-N) stereoscopic grids according to the level deviations of the N calibration grids includes:
dis-dimension, θ -dimension of level deviation for the N stereoscopic grids, respectively
Figure FDA0004272540130000021
The dimensions are curve fitted to determine the level deviation for each of the (M-N) stereoscopic grids.
2. The network coverage analysis method of claim 1, wherein said obtaining a second coverage level for each of the N calibration grids comprises:
and determining the position information of the calibration grid corresponding to the terminal equipment and the second coverage level of the calibration grid according to the real-time position information of the terminal equipment, the measurement report MR information reported by the terminal equipment and the signaling information extracted from a telecom operator equipment interface.
3. A network coverage analysis apparatus, comprising: an acquisition unit and a processing unit;
the acquisition unit is used for acquiring a first coverage level of the target three-dimensional grid through system simulation and acquiring level deviation of the target three-dimensional grid through a calibration library;
the processing unit is used for determining the sum of the first coverage level and the level deviation as a standard level value of the target stereoscopic grid;
the target three-dimensional grid is any one of M three-dimensional grids divided according to a target cell antenna, the calibration library comprises level deviation of each three-dimensional grid in the M three-dimensional grids, and M is a positive integer;
any one grid of the M three-dimensional grids divided according to the target cell antenna comprises: determining a coverage analysis space according to the coverage area and the coverage height of the cell;
determining a coordinate point (x p ,y p ,z p ) Relative three-dimensional coordinates with target cell antenna
Figure FDA0004272540130000022
Wherein (1)>
Figure FDA0004272540130000023
θ represents the coordinate point (x p ,y p ,z p ) A horizontal offset angle, θ ', relative to the target cell antenna azimuth' AZ ＝mod(450-θ AZ ,360)，mod(450-θ AZ 360) represents 450-theta AZ And 360-phase division to obtain remainder value of remainder, theta AZ Representing azimuth angle, +_of the target cell>
Figure FDA0004272540130000031
Representing the negation cut angle over a range of angles (-180, 180); when theta exceeds (-180)180), angle conversion is performed on θ, specifically: if θ is less than-180, θ=θ+360; if θ is greater than 180, θ=θ -360; />
Figure FDA0004272540130000032
Figure FDA0004272540130000033
Represents the coordinate point (x p ,y p ,z p ) Vertical offset angle relative to downtilt of target cell antenna,/->
Figure FDA0004272540130000034
Representing the downtilt of the target cell antenna, +.>
Figure FDA0004272540130000035
The range of values of (-180, 180); />
Figure FDA0004272540130000036
dis represents the coordinate point (x p ,y p ,z p ) A linear distance relative to the target cell antenna; slicing theta by (m + 0.5) delta theta, wherein m= -a, -a+1,..0, a-1,/-a>
Figure FDA0004272540130000037
Δθ is a value divided by 180, and the default value is 5; to->
Figure FDA0004272540130000038
For->
Figure FDA0004272540130000039
A cut is made, where n= -B, -B +1, once again, 0, B-1, d>
Figure FDA00042725401300000310
Figure FDA00042725401300000311
A value divided by 180, the default value is 3; splitting dis with k x Δdis, where k=0, 1, 2..c, +.>
Figure FDA00042725401300000312
Δdis default is 10; dividing the coverage analysis space into M grids according to the segmentation points, wherein m=2a×2b (c+1), and the coverage analysis space is divided into M grids according to the +/C of each coordinate point>
Figure FDA00042725401300000313
Assigning values to coordinate points in corresponding grids to +.>
Figure FDA00042725401300000314
As centroid coordinates of the respective grids;
the processing unit is further used for determining a first coverage level of each of the M stereoscopic grids through system simulation;
the acquiring unit is further configured to acquire a second coverage level of each of N calibration grids, and obtain a level deviation between a first coverage level and a second coverage level of each of the N calibration grids, where the N calibration grids are grids in the M stereoscopic grids;
the processing unit is further configured to determine a level deviation of each of the (M-N) three-dimensional grids according to the level deviations of the N calibration grids, so as to obtain the calibration library;
wherein N is a positive integer less than M;
the processing unit is specifically configured to: dis-dimension, θ -dimension of level deviation for the N stereoscopic grids, respectively
Figure FDA00042725401300000315
The dimensions are curve fitted to determine the level deviation for each of the (M-N) stereoscopic grids.
4. The network coverage analysis device of claim 3, wherein the acquisition unit is specifically configured to: and determining the position information of the calibration grid corresponding to the terminal equipment and the second coverage level of the calibration grid according to the real-time position information of the terminal equipment, the measurement report MR information reported by the terminal equipment and the signaling information extracted from a telecom operator equipment interface.
5. A network coverage analysis device, comprising a memory and a processor; the memory is used for storing computer execution instructions, and the processor is connected with the memory through a bus;
the processor, when executed by the network coverage analysis device, executes the computer-executable instructions stored by the memory to cause the network coverage analysis device to perform the network coverage analysis method of any one of claims 1-2.
6. A computer readable storage medium comprising computer executable instructions which, when run on a computer, cause the computer to perform the network coverage analysis method of any of claims 1-2.
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