CN114079930B - Method and device for identifying cell overlapping coverage - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/18—Network planning tools
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/22—Traffic simulation tools or models
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- 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
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
Abstract
The invention discloses a method and a device for identifying cell overlapping coverage, wherein the method comprises the following steps: collecting MR sampling point information of all cells in an area to be identified; according to the MR sampling point information, calculating the number of adjacent cells of each MR sampling point and the level difference value between the main cell and each adjacent cell; aiming at each MR sampling point, the number of adjacent cells of each MR sampling point and the level difference value between the main cell and each adjacent cell are input into a pre-constructed carrier frequency overlapping degree processing model for calculation to obtain the carrier frequency overlapping degree value of the MR sampling point.
Description
Technical Field
The present invention relates to the field of communications technologies, and in particular, to a method and an apparatus for identifying cell overlapping coverage.
Background
Each network service cell may correspond to a plurality of adjacent cells, and the overlapping coverage reflects the overlapping degree of the signals of the cells, the overlapping coverage reflects how many strong signal cells of the area are repeatedly covered, and the area with higher overlapping coverage is defined as an excessive coverage area. The existing wireless carrier frequency overlapping coverage recognition methods mainly comprise two types: one is based on the difference between MR.LteScRSRP and MR.LteNcRSRP in the sampling points of the measurement report (Measurement Report, MR), if the difference meets the preset self-defined threshold condition, the sampling points are marked as overlapping coverage sampling points, and the number of the overlapping coverage sampling points is divided by the total number of the sampling points to obtain overlapping coverage; another is to use raster division with the ratio of the number of grids affected by overlap coverage to the total number of grids as overlap coverage.
The above method for identifying overlapping coverage only considers whether a certain MR sampling point (or grid) belongs to overlapping coverage MR sampling points (or grids), and does not evaluate and judge the overlapping coverage of each MR sampling point (or grid); however, in fact, even though they all belong to overlapping coverage MR sampling points, the overlapping coverage is differentiated, and thus the prior art method of identifying overlapping coverage is not accurate and complete enough.
Disclosure of Invention
The present invention has been made in view of the above problems, and it is an object of the present invention to provide a method and apparatus for identifying cell overlap coverage that overcomes or at least partially solves the above problems.
According to one aspect of the present invention, there is provided a method for identifying cell overlap coverage, including:
collecting MR sampling point information of all cells in an area to be identified;
calculating the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell according to the MR sampling point information;
and inputting the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell into a pre-constructed carrier frequency overlapping degree processing model for calculation to obtain the carrier frequency overlapping degree value of the MR sampling point.
According to another aspect of the present invention, there is provided an apparatus for identifying coverage of cell overlap, including:
the sampling point information acquisition module is used for acquiring MR sampling point information of all cells in the area to be identified;
the sampling point level difference value calculation module is used for calculating the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell according to the MR sampling point information;
the sampling point carrier frequency overlapping degree value calculation module is used for inputting the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell into a pre-constructed carrier frequency overlapping degree processing model for calculation to obtain the carrier frequency overlapping degree value of the MR sampling point.
According to yet another aspect of the present invention, there is provided a computing device comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is configured to store at least one executable instruction, where the executable instruction causes the processor to execute an operation corresponding to the method for identifying cell overlap coverage.
According to still another aspect of the present invention, there is provided a computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the above-described method of identifying cell overlap coverage.
According to the method and the device for identifying the cell overlapping coverage, MR sampling point information of all cells in an area to be identified is acquired; according to the MR sampling point information, calculating the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell; aiming at each MR sampling point, the number of adjacent cells corresponding to the MR sampling point and the level difference value between the main cell and each adjacent cell are input into a pre-built carrier frequency overlapping degree processing model for calculation to obtain the carrier frequency overlapping degree value of the MR sampling point.
The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
fig. 1 shows a flowchart of a method for identifying cell overlapping coverage according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an apparatus for identifying cell overlapping coverage according to an embodiment of the present invention;
FIG. 3 illustrates a schematic diagram of a computing device provided by an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Fig. 1 shows a flowchart of an embodiment of a method for identifying cell overlap coverage according to the present invention, as shown in fig. 1, the method includes the following steps:
s110: and collecting MR sampling point information of all cells in the area to be identified.
In an alternative way, the MR sample point information includes one or more of the following: MR sampling point longitude and latitude information, a main cell identification code, a main cell frequency point, a main cell level value, a neighbor cell identification code, a neighbor cell frequency point and a neighbor cell level value.
For example, table 1 is an acquired MR sampling point information table, assuming that m MR sampling points are in total in the region to be identified, the MR sampling point information acquired through step S110 may be as shown in table 1:
| MR sampling point | Longitude of MR sampling point | MR sampling point latitude | Master cell list | Primary cell level | Neighbor cell list | Neighbor cell level |
| MR sampling Point 1 | Longitude 1 | Latitude 1 | Primary cell 1 | Main level 1 | Neighbor cell 11 | Adjacent level 11 |
| MR sampling Point 1 | Longitude 1 | Latitude 1 | Primary cell 1 | Main level 1 | Neighbor cell 12 | Adjacent level 12 |
| MR sampling Point 1 | Longitude 1 | Latitude 1 | Primary cell 1 | Main level 1 | Neighbor cell 13 | Neighbor level 13 |
| MR sampling Point 1 | Longitude 1 | Latitude 1 | Primary cell 1 | Main level 1 | ··· | ··· |
| MR sampling Point 1 | Longitude 1 | Latitude 1 | Primary cell 1 | Main level 1 | Neighbor cell 1x | Adjacent level 1x |
| MR sampling Point 2 | Longitude 2 | Latitude 2 | Primary cell 2 | Main level 2 | Neighbor cell 21 | Neighbor level 21 |
| MR sampling Point 2 | Longitude 2 | Latitude 2 | Primary cell 2 | Main level 2 | Neighbor cell 22 | Adjacent level 22 |
| MR sampling Point 2 | Longitude 2 | Latitude 2 | Primary cell 2 | Main level 2 | Neighbor cell 23 | Neighbor level 23 |
| MR sampling Point 2 | Longitude 2 | Latitude 2 | Primary cell 2 | Main level 2 | ··· | ··· |
| MR sampling Point 2 | Longitude 2 | Latitude 2 | Primary cell 2 | Main level 2 | Neighbor cell 2y | Neighbor level 2y |
| ··· | ··· | ··· | ··· | ··· | ··· | ··· |
| MR sampling Point m | Longitude m | Latitude m | Primary cell m | Main level m | Neighbor cell m1 | Neighbor level m1 |
| MR sampling Point m | Longitude m | Latitude m | Primary cell m | Main level m | Neighbor cell m2 | Neighbor level m2 |
| MR sampling Point m | Longitude m | Latitude m | Primary cell m | Main level m | Neighbor cell m3 | Neighbor level m3 |
| MR sampling Point m | Longitude m | Latitude m | Primary cell m | Main level m | ··· | ··· |
| MR sampling Point m | Longitude m | Latitude m | Primary cell m | Main level m | Neighbor cell mz | Neighbor level mz |
Table 1 MR sample point information table
In general, m should be large enough to help to make the accuracy of identifying the cell overlap coverage of the area to be identified higher, and MR sample point information of the area to be identified in a longer time range may be acquired, so that the number of MR sample point information samples is large enough.
As shown in table 1, wherein m >0; x, y and z are more than or equal to 0; and x, y and z represent the number of neighbor cells corresponding to a certain corresponding MR sampling point, when the value of x, y or z is 0, the MR sampling point only has main cell coverage but has no effective neighbor cell coverage, and in order to ensure that the identification comprehensiveness of the cell overlapping coverage of the area to be identified is higher, the value of x, y and z should be larger than or equal to 1 in general.
S120: and calculating the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell according to the MR sampling point information.
Specifically, each MR sampling point includes a main cell and one or more neighbor cells, and one of the MR sampling points is taken as an example for the step S120 to perform an example, and the remaining MR sampling points are performed by the same method.
Table 2 is a level difference value comparison table between the main cell and each neighboring cell of MR sample point 1, and as shown in table 2, assuming that MR sample point 1 includes x neighboring cells, then: level difference= |primary cell level-neighbor cell level|, i.e. the level difference value is equal to the absolute value of the difference between the primary cell level and the neighbor cell level. As shown in table 2, the number of neighboring cells corresponding to the MR sampling point 1 is x, the level difference between the main cell 1 and the neighboring cell 11 is |main level 1-neighboring level 11|, the level difference between the main cell 1 and the neighboring cell 12 is |main level 1-neighboring level 12|, the level difference between the main cell 1 and the neighboring cell 13 is |main level 1-neighboring level 13|, … …, and the level difference between the main cell 1 and the neighboring cell 1x is |main level 1-neighboring level 1x|.
| MR sampling point | Master cell list | Primary cell level | Neighbor cell list | Neighbor cell level | Level difference value |
| MR sampling Point 1 | Primary cell 1 | Main level 1 | Neighbor cell 11 | Adjacent level 11 | Main level 1-adjacent level 11| |
| MR sampling Point 1 | Primary cell 1 | Main level 1 | Neighbor cell 12 | Adjacent level 12 | Main level 1-adjacent level 12| |
| MR sampling Point 1 | Primary cell 1 | Main level 1 | Neighbor cell 13 | Neighbor level 13 | Main level 1-adjacent level 13| |
| MR sampling Point 1 | Primary cell 1 | Main level 1 | ··· | ··· | ··· |
| MR sampling Point 1 | Primary cell 1 | Main level 1 | Neighbor cell 1x | Adjacent level 1x | Main level 1-adjacent level 1x| |
Table 2 MR level difference value comparison table between the main cell of sample point 1 and each neighbor cell
S130: and inputting the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell into a pre-constructed carrier frequency overlapping degree processing model for calculation to obtain the carrier frequency overlapping degree value of the MR sampling point.
In an alternative manner, step S130 further includes: taking the MR sampling point as a target sampling point; calculating a level difference value average value according to the number of adjacent cells corresponding to the target sampling points and the level difference value between the main cell and each adjacent cell; and inputting the number of adjacent cells and the average value of the level difference values into a carrier frequency overlapping degree value calculation formula of a carrier frequency overlapping degree processing model to calculate so as to obtain the carrier frequency overlapping degree value of the target sampling point.
In an alternative manner, the carrier frequency overlap degree value calculation formula is formula (1):
wherein μ is a carrier frequency overlap degree value; k and b are constants, and k is more than or equal to b >0; x is the number of adjacent cells corresponding to the target sampling point; θ is the average value of the level differences corresponding to the target sampling points.
In general, the degree of carrier frequency overlap is related to two factors: 1) The number of overlapping carrier frequencies; the more the carrier frequency overlap number is, the higher the carrier frequency overlap degree is; 2) The absolute value of the level difference of the overlapping carrier frequencies; the smaller the absolute value of the level difference, the higher the degree of carrier frequency overlap.
Thus, a carrier frequency overlapping degree value calculation formula of a certain MR sampling point is defined as formula (1).
θ represents the average value of the level difference values corresponding to the target sampling point, taking the target sampling point as the MR sampling point 1 as an example, and the calculation formula can be as formula (2):
wherein θ is greater than or equal to 0, x represents the number of neighbor cells which do not contain the main cell in the target sampling point, and x is greater than or equal to 0.
As shown in equation (1), when x=0,indicating that the MR sampling point does not have an overlapped adjacent cell, wherein the carrier frequency overlapping degree value is 0, and the value of theta at the moment has no meaning;
when x is not equal to 0, if θ=0The carrier frequency overlapping degree value only has relation with the number x of adjacent cells, and when the value x is larger, the value μ is larger, which means that the carrier frequency overlapping degree value is higher.
When x is not equal to 0, if θ is not equal to 0The carrier frequency overlapping degree value is related to the adjacent cell number x and the level difference average value theta, and when the value of x is larger, the value of mu is larger, which means that the carrier frequency overlapping degree value is higher, so when the value of x is fixed and the value of theta is smaller, the value of mu is larger, which means that the carrier frequency overlapping range is also higherThe higher the degree value.
When x is approximately ≡infinity,
therefore, the carrier frequency overlap degree value μ can be quantized within the range of [0,1 ] by the carrier frequency overlap degree value calculation formula described above.
In an alternative manner, the method further comprises step S140: and calculating the region carrier frequency overlapping degree value of the region to be identified according to the carrier frequency overlapping degree values of all the MR sampling points in the region to be identified.
In an alternative way, the region carrier frequency overlap value of the region to be identified is calculated using formula (3):
wherein, gamma is the region carrier frequency overlapping degree value of the region to be identified; m is the total number of MR sampling points in the region to be identified; mu (mu) 1 To mu m The carrier frequency overlapping degree values of m MR sampling points are respectively obtained.
As shown in the formula (3), when the value of gamma is equal to 0, the signal of the area to be identified is pure, and no carrier frequency overlapping coverage exists.
When the value of gamma is close to 0, carrier frequency signals representing the area to be identified are relatively less, the level difference between carrier frequencies is larger, primary and secondary coverage cells can be distinguished, and the carrier frequency overlapping degree is lighter;
when the value of gamma is close to 1, the region to be identified has more wireless carrier frequencies, the signal strength difference of adjacent carrier frequencies is smaller, and the carrier frequency overlapping degree is serious.
By adopting the method of the embodiment, the MR sampling point information of all cells in the area to be identified is acquired; according to the MR sampling point information, calculating the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell; aiming at each MR sampling point, the number of adjacent cells corresponding to the MR sampling point and the level difference value between the main cell and each adjacent cell are input into a pre-built carrier frequency overlapping degree processing model for calculation to obtain the carrier frequency overlapping degree value of the MR sampling point.
Fig. 2 is a schematic structural diagram of an embodiment of a cell overlap coverage identification device according to the present invention. As shown in fig. 2, the apparatus includes: the system comprises a sampling point information acquisition module 210, a sampling point level difference value calculation module 220, a sampling point carrier frequency overlapping degree value calculation module 230 and a regional carrier frequency overlapping degree value calculation module 240.
The sampling point information acquisition module 210 is configured to acquire MR sampling point information of all cells in the area to be identified.
In an alternative way, the MR sample point information includes one or more of the following: MR sampling point longitude and latitude information, a main cell identification code, a main cell frequency point, a main cell level value, a neighbor cell identification code, a neighbor cell frequency point and a neighbor cell level value.
The sampling point level difference calculating module 220 is configured to calculate, according to the MR sampling point information, the number of neighboring cells corresponding to each MR sampling point and a level difference between the main cell and each neighboring cell.
The sampling point carrier frequency overlapping degree value calculating module 230 is configured to input, for each MR sampling point, the number of neighboring cells corresponding to the MR sampling point and a level difference value between the main cell and each neighboring cell into a carrier frequency overlapping degree processing model that is constructed in advance for calculation, so as to obtain a carrier frequency overlapping degree value of the MR sampling point.
In an alternative manner, the sampling point carrier frequency overlap level value calculation module 230 is further configured to: taking the MR sampling point as a target sampling point; calculating a level difference value average value according to the number of adjacent cells corresponding to the target sampling points and the level difference value between the main cell and each adjacent cell; and inputting the number of adjacent cells and the average value of the level difference values into a carrier frequency overlapping degree value calculation formula of a carrier frequency overlapping degree processing model to calculate so as to obtain the carrier frequency overlapping degree value of the target sampling point.
In an alternative manner, the carrier frequency overlap degree value is calculated as:
wherein μ is a carrier frequency overlap degree value; k and b are constants, and k is more than or equal to b >0; x is the number of adjacent cells corresponding to the target sampling point; θ is the average value of the level differences corresponding to the target sampling points.
In an alternative, the apparatus further comprises: the region carrier frequency overlapping degree value calculating module 240 is configured to calculate a region carrier frequency overlapping degree value of the region to be identified according to the carrier frequency overlapping degree values of all MR sampling points in the region to be identified.
In an alternative way, the area carrier frequency overlap value of the area to be identified is calculated using the following formula:
wherein, gamma is the region carrier frequency overlapping degree value of the region to be identified; m is the total number of MR sampling points in the region to be identified; mu (mu) 1 To mu m The carrier frequency overlapping degree values of m MR sampling points are respectively obtained.
By adopting the device of the embodiment, the MR sampling point information of all cells in the area to be identified is acquired; according to the MR sampling point information, calculating the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell; aiming at each MR sampling point, the number of adjacent cells corresponding to the MR sampling point and the level difference value between the main cell and each adjacent cell are input into a pre-built carrier frequency overlapping degree processing model for calculation to obtain the carrier frequency overlapping degree value of the MR sampling point.
The embodiment of the invention provides a non-volatile computer storage medium, which stores at least one executable instruction, and the computer executable instruction can execute the method for identifying the cell overlapping coverage in any of the method embodiments.
The executable instructions may be particularly useful for causing a processor to:
collecting MR sampling point information of all cells in an area to be identified;
according to the MR sampling point information, calculating the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell;
and inputting the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell into a pre-constructed carrier frequency overlapping degree processing model for calculation to obtain the carrier frequency overlapping degree value of the MR sampling point.
FIG. 3 illustrates a schematic diagram of an embodiment of a computing device of the present invention, and the embodiments of the present invention are not limited to a particular implementation of the computing device.
As shown in fig. 3, the computing device may include:
a processor (processor), a communication interface (Communications Interface), a memory (memory), and a communication bus.
Wherein: the processor, communication interface, and memory communicate with each other via a communication bus. A communication interface for communicating with network elements of other devices, such as clients or other servers, etc. And the processor is used for executing a program, and can specifically execute relevant steps in the embodiment of the method for identifying the cell overlapping coverage.
In particular, the program may include program code including computer-operating instructions.
The processor may be a central processing unit, CPU, or specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included by the server may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
And the memory is used for storing programs. The memory may comprise high-speed RAM memory or may further comprise non-volatile memory, such as at least one disk memory.
The program may be specifically operative to cause the processor to:
collecting MR sampling point information of all cells in an area to be identified;
according to the MR sampling point information, calculating the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell;
and inputting the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell into a pre-constructed carrier frequency overlapping degree processing model for calculation to obtain the carrier frequency overlapping degree value of the MR sampling point.
The algorithms or displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems may also be used with the teachings herein. The required structure for a construction of such a system is apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It will be appreciated that the teachings of the present invention described herein may be implemented in a variety of programming languages, and the above description of specific languages is provided for disclosure of enablement and best mode of the present invention.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the above description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the intention that: i.e., the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.
Various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components according to embodiments of the present invention may be implemented in practice using a microprocessor or Digital Signal Processor (DSP). The present invention can also be implemented as an apparatus or device program (e.g., a computer program and a computer program product) for performing a portion or all of the methods described herein. Such a program embodying the present invention may be stored on a computer readable medium, or may have the form of one or more signals. Such signals may be downloaded from an internet website, provided on a carrier signal, or provided in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specifically stated.
Claims (5)
1. A method for identifying coverage of cell overlap, comprising:
collecting MR sampling point information of all cells in an area to be identified;
calculating the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell according to the MR sampling point information;
for each MR sampling point, inputting the number of adjacent cells corresponding to the MR sampling point and the level difference value between the main cell and each adjacent cell into a pre-constructed carrier frequency overlapping degree processing model for calculation to obtain a carrier frequency overlapping degree value of the MR sampling point;
the step of inputting the number of neighboring cells corresponding to each MR sampling point and the level difference value between the main cell and each neighboring cell into a pre-constructed carrier frequency overlapping degree processing model for calculation, and the step of obtaining the carrier frequency overlapping degree value of the MR sampling point further comprises the following steps: taking the MR sampling point as a target sampling point; calculating a level difference value average value according to the number of adjacent cells corresponding to the target sampling point and the level difference value between the main cell and each adjacent cell; inputting the number of the neighbor cells and the average value of the level difference values into a carrier frequency overlapping degree value calculation formula of the carrier frequency overlapping degree processing model for calculation to obtain a carrier frequency overlapping degree value of the target sampling point; the carrier frequency overlapping degree value calculation formula is as follows:
wherein μ is a carrier frequency overlap degree value; k and b are constants, and k is greater than or equal to b >0; x is the number of adjacent cells corresponding to the target sampling point; θ is the average value of the level difference values corresponding to the target sampling points;
wherein the method further comprises: calculating the region carrier frequency overlapping degree value of the region to be identified according to the carrier frequency overlapping degree values of all MR sampling points in the region to be identified; calculating the region carrier frequency overlapping degree value of the region to be identified by using the following formula:
wherein gamma is the region carrier frequency overlapping degree value of the region to be identified; m is the total number of MR sampling points in the region to be identified; mu (mu) 1 To mu m The carrier frequency overlapping degree values of m MR sampling points are respectively obtained.
2. The method of claim 1, wherein the MR sample point information includes one or more of the following: MR sampling point longitude and latitude information, a main cell identification code, a main cell frequency point, a main cell level value, a neighbor cell identification code, a neighbor cell frequency point and a neighbor cell level value.
3. An apparatus for identifying coverage of overlapping cells, comprising:
the sampling point information acquisition module is used for acquiring MR sampling point information of all cells in the area to be identified;
the sampling point level difference value calculation module is used for calculating the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell according to the MR sampling point information;
the sampling point carrier frequency overlapping degree value calculation module is used for inputting the number of adjacent cells corresponding to each MR sampling point and the level difference value between the main cell and each adjacent cell into a pre-constructed carrier frequency overlapping degree processing model for calculation to obtain the carrier frequency overlapping degree value of the MR sampling point;
the sampling point carrier frequency overlapping degree value calculating module is further used for: taking the MR sampling point as a target sampling point; calculating a level difference value average value according to the number of adjacent cells corresponding to the target sampling point and the level difference value between the main cell and each adjacent cell; inputting the number of the neighbor cells and the average value of the level difference values into a carrier frequency overlapping degree value calculation formula of the carrier frequency overlapping degree processing model for calculation to obtain a carrier frequency overlapping degree value of the target sampling point; the carrier frequency overlapping degree value calculation formula is as follows:
wherein μ is a carrier frequency overlap degree value; k and b are constants, k is greater than or equal to b>0; x is the number of adjacent cells corresponding to the target sampling point; θ is the average value of the level difference values corresponding to the target sampling points;
the device further comprises a region carrier frequency overlapping degree value calculation module, wherein the region carrier frequency overlapping degree value calculation module is used for calculating the region carrier frequency overlapping degree value of the region to be identified according to the carrier frequency overlapping degree values of all MR sampling points in the region to be identified; calculating the region carrier frequency overlapping degree value of the region to be identified by using the following formula:
wherein gamma is the region carrier frequency overlapping degree value of the region to be identified; m is the total number of MR sampling points in the region to be identified; mu (mu) 1 To mu m The carrier frequency overlapping degree values of m MR sampling points are respectively obtained.
4. A computing device, comprising: the device comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete communication with each other through the communication bus;
the memory is configured to store at least one executable instruction that causes the processor to perform operations corresponding to the method for identifying cell overlap coverage according to any one of claims 1-2.
5. A computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the method for identifying cell overlap coverage according to any of claims 1-2.
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