A method and device for geographic evaluation of mobile network 5G traffic offloading capability

Abstract

The application discloses a mobile network 5G traffic shunting capability geographical evaluation method and device, relates to the technical field of communication, and is used for improving the efficiency and accuracy of evaluating the performance of a mobile network cell. The method comprises the following steps: acquiring basic data information corresponding to each grid corresponding to a target area; determining a plurality of first grids from a plurality of grids according to a plurality of first sampling point quantities, a plurality of second sampling point quantities, total traffic of each first cell and total traffic of each second cell in the basic data information corresponding to each grid, and determining target traffic corresponding to the plurality of first grids; determining a third sampling point proportion included in the plurality of first grids according to a target RSRP and the plurality of second sampling point quantities; determining a target distance according to position information of the plurality of first grids and position information of the plurality of second cells; and determining network performance of a second network standard according to the third sampling point proportion, the target distance and the target traffic.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method and apparatus for geographic assessment of 5G traffic offloading capability of mobile networks. Background Technology

[0002] With the continuous development of mobile network technology, both 4G and 5G network standards coexist in the mobile network architecture. Users (i.e., terminals) generate 4G and 5G traffic respectively when using different network standards (4G and 5G networks). To further improve the breadth and depth of 5G network coverage and enhance its traffic offloading capabilities, precise analysis of the performance of 4G and 5G networks in various regions is required. Currently, this is mainly achieved through manual experience, analyzing network complaints, measurement reports (MRs), and 4G and 5G cell-level traffic in the same coverage direction of the same base station at the cell level for each 4G and 5G cell (mobile network cell).

[0003] The methods described above are inefficient for manually analyzing the performance of 4G and 5G networks in various regions. Furthermore, the accuracy of analyzing 4G and 5G cell-level traffic at the cell level is low, making it impossible to accurately calculate the proportion of 4G and 5G traffic within each grid cell covered by each 4G and 5G cell. Therefore, the evaluation of mobile network cell performance is inefficient and inaccurate. Summary of the Invention

[0004] This application provides a method and apparatus for geographic assessment of 5G traffic offloading capabilities of mobile networks, which can improve the efficiency and accuracy of assessing the performance of mobile network cells.

[0005] To achieve the above objectives, this application adopts the following technical solution:

[0006] Firstly, a method for geographically evaluating the 5G traffic offloading capability of a mobile network is provided. The method includes: acquiring basic data information corresponding to a target area, where the target area is covered by a first network standard and a second network standard. The first network standard corresponds to multiple first cells, and the second network standard corresponds to multiple second cells. The target area includes multiple grids. The basic data information includes: the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, the total traffic of each second cell, and the target reference signal received power (RSRP) corresponding to each second sampling point in each grid. The number of first sampling points corresponds to the number of sampling points corresponding to one first cell, and the number of second sampling points corresponds to the number of sampling points corresponding to one second cell. Based on the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid... The second sampling point number, the total traffic of each first cell, and the total traffic of each second cell are used to determine multiple first grids from multiple grids, and the target traffic corresponding to the multiple first grids is determined. The target traffic is the total traffic corresponding to the multiple first cells in the multiple first grids. Based on the target RSRP and the number of multiple second sampling points corresponding to each grid, the proportion of third sampling points included in the multiple first grids is determined. The third sampling point is the second sampling point in each of the multiple first grids whose target RSRP is greater than or equal to a first preset threshold. Based on the location information of the multiple first grids and the location information of the multiple second cells, the target distance is determined. The target distance is the shortest distance between the center point of the multiple first grids and the multiple second cells. Based on the proportion of third sampling points, the target distance, and the target traffic, the network performance of the second network standard is determined.

[0007] In one possible implementation, the first network standard traffic corresponding to each grid is determined based on the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, and the total traffic of each second cell. Then, multiple first grids are determined from the multiple grids, including: determining the first network standard traffic corresponding to each grid based on the number of multiple first sampling points corresponding to each grid and the total traffic of each first cell; determining the second network standard traffic splitting ratio corresponding to each grid based on the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, and the total traffic of each second cell; and determining multiple first grids from the multiple grids whose second network standard traffic splitting ratio is less than or equal to a second preset threshold based on the second network standard traffic splitting ratio corresponding to each grid.

[0008] In one possible implementation, determining the second network standard traffic splitting ratio for each grid cell based on the number of multiple first sampling points corresponding to each grid cell, the number of multiple second sampling points corresponding to each grid cell, the total traffic of each first cell, and the total traffic of each second cell includes: determining the first network standard traffic for each grid cell based on the number of multiple first sampling points corresponding to each grid cell and the total traffic of each first cell; determining the second network standard traffic for each grid cell based on the number of multiple second sampling points corresponding to each grid cell and the total traffic of each second cell; and determining the second network standard traffic splitting ratio for each grid cell based on the first network standard traffic for each grid cell and the second network standard traffic for each grid cell.

[0009] In one possible implementation, the first network type traffic corresponding to each grid is determined based on the number of multiple first sampling points corresponding to each grid and the total traffic of each first cell, including: determining the proportion of multiple first sampling points corresponding to each grid based on the number of multiple first sampling points corresponding to each grid, where one proportion of first sampling points corresponds to one first cell; determining the traffic of each first cell corresponding to each grid based on the proportion of multiple first sampling points corresponding to each grid and the total traffic of each first cell; and determining the first network type traffic corresponding to each grid based on the traffic of each first cell corresponding to each grid.

[0010] In one possible implementation, the second network standard traffic corresponding to each grid is determined based on the number of multiple second sampling points corresponding to each grid and the total traffic of each second cell. This includes: determining the proportion of multiple second sampling points corresponding to each grid based on the number of multiple second sampling points corresponding to each grid, where one proportion of second sampling points corresponds to one second cell; determining the traffic of each second cell corresponding to each grid based on the proportion of multiple second sampling points corresponding to each grid and the total traffic of each second cell; and determining the second network standard traffic corresponding to each grid based on the traffic of each second cell corresponding to each grid.

[0011] In one possible implementation, the network performance of the second network standard is determined based on the proportion of the third sampling points, the target distance, and the target traffic, including: when the proportion of the third sampling points is less than a third threshold and the target distance is less than a fourth threshold, checking the antenna azimuth and downtilt angle of each of the multiple second cells; when the proportion of the third sampling points is less than the third threshold, the target distance is greater than or equal to the fourth threshold, and the target traffic is greater than or equal to the fifth threshold, enhancing the signal strength of each of the multiple second cells; when the proportion of the third sampling points is greater than or equal to the third threshold, the target traffic is greater than or equal to the fifth threshold, and the number of first terminal devices included in the multiple first grids is less than a sixth threshold, increasing the number of first terminal devices accessed in each of the multiple second cells, wherein the first terminal devices are terminal devices that support access to the second network standard; when the proportion of the third sampling points is greater than or equal to the third threshold and the number of second terminal devices included in the multiple first grids is greater than or equal to a seventh threshold, increasing the number of first terminal devices accessed in each of the multiple second cells.

[0012] Secondly, a geographical assessment device for 5G traffic offloading capability of a mobile network is provided. The device includes: an acquisition unit and a processing unit; the acquisition unit is used to acquire basic data information corresponding to a target area, the target area being covered by a first network standard and a second network standard, the first network standard corresponding to multiple first cells, the second network standard corresponding to multiple second cells, the target area including multiple grids, and the basic data information including: the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, the total traffic of each second cell, and the target reference signal received power (RSRP) corresponding to each second sampling point in each grid, wherein the number of one first sampling point is the number of sampling points corresponding to one first cell, and the number of one second sampling point is the number of sampling points corresponding to one second cell; the processing unit is used to acquire basic data information corresponding to the multiple first sampling points of each grid, the number of first sampling points corresponding to each grid, the number of second sampling points corresponding to each second cell, the number of first sampling points corresponding to each grid, the number of second sampling points corresponding to each second cell, and the number of second sampling points corresponding to each second cell; the processing unit is used to acquire basic data information corresponding to the target area based on the number of first sampling points corresponding to each grid, the number of first sampling points corresponding to each grid, the number of second sampling points corresponding to each second cell, the number of first sampling points corresponding to each second cell, the number of second sampling points corresponding to each second cell, and the number of second sampling points corresponding to each second cell. The processing unit is further configured to: determine multiple first grids from the multiple grids, based on the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, and the total traffic of each second cell; determine the target traffic corresponding to the multiple first grids, where the target traffic is the total traffic corresponding to the multiple first cells in the multiple first grids; determine the proportion of third sampling points included in the multiple first grids based on the target RSRP and the number of multiple second sampling points corresponding to each grid, where the third sampling point is the second sampling point in each of the multiple first grids whose target RSRP is greater than or equal to a first preset threshold; determine the target distance based on the location information of the multiple first grids and the location information of the multiple second cells, where the target distance is the shortest distance between the center point of the multiple first grids and the multiple second cells; and determine the network performance of the second network standard based on the proportion of third sampling points, the target distance, and the target traffic.

[0013] In one possible implementation, the processing unit is further configured to determine the first network standard traffic corresponding to each grid based on the number of multiple first sampling points corresponding to each grid and the total traffic of each first cell; the processing unit is further configured to determine the second network standard traffic splitting ratio corresponding to each grid based on the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, and the total traffic of each second cell; the processing unit is further configured to determine, based on the second network standard traffic splitting ratio corresponding to each grid, multiple first grids whose second network standard traffic splitting ratio is less than or equal to a second preset threshold from the multiple grids.

[0014] In one possible implementation, the processing unit is further configured to determine the first network standard traffic corresponding to each grid based on the number of multiple first sampling points corresponding to each grid and the total traffic of each first cell; the processing unit is further configured to determine the second network standard traffic corresponding to each grid based on the number of multiple second sampling points corresponding to each grid and the total traffic of each second cell; the processing unit is further configured to determine the second network standard traffic splitting ratio corresponding to each grid based on the first network standard traffic corresponding to each grid and the second network standard traffic corresponding to each grid.

[0015] In one possible implementation, the processing unit is further configured to determine the proportion of multiple first sampling points corresponding to each grid based on the number of multiple first sampling points corresponding to each grid, wherein one proportion of first sampling points corresponds to one first cell; the processing unit is further configured to determine the traffic of each first cell corresponding to each grid based on the proportion of multiple first sampling points corresponding to each grid and the total traffic of each first cell; the processing unit is further configured to determine the first network type traffic corresponding to each grid based on the traffic of each first cell corresponding to each grid.

[0016] In one possible implementation, the processing unit is further configured to determine the proportion of multiple second sampling points corresponding to each grid based on the number of multiple second sampling points corresponding to each grid, wherein one proportion of second sampling points corresponds to one second cell; the processing unit is further configured to determine the traffic of each second cell corresponding to each grid based on the proportion of multiple second sampling points corresponding to each grid and the total traffic of each second cell; the processing unit is further configured to determine the second network standard traffic corresponding to each grid based on the traffic of each second cell corresponding to each grid.

[0017] In one possible implementation, the processing unit is further configured to: verify the antenna azimuth and downtilt angle of each of the multiple second cells when the proportion of the third sampling points is less than a third threshold and the target distance is less than a fourth threshold; enhance the signal strength of each of the multiple second cells when the proportion of the third sampling points is less than the third threshold, the target distance is greater than or equal to the fourth threshold, and the target traffic is greater than or equal to the fifth threshold; increase the number of first terminal devices accessed in each of the multiple second cells when the proportion of the third sampling points is greater than or equal to the third threshold, the target traffic is greater than or equal to the fifth threshold, and the number of first terminal devices included in the multiple first grids is less than a sixth threshold, wherein the first terminal devices are terminal devices that support access to the second network standard; and increase the number of first terminal devices accessed in each of the multiple second cells when the proportion of the third sampling points is greater than or equal to the third threshold and the number of second terminal devices included in the multiple first grids is greater than or equal to a seventh threshold.

[0018] Thirdly, an electronic device includes: a processor and a memory; wherein the memory is used to store one or more programs, the one or more programs including computer-executable instructions, and when the electronic device is running, the processor executes the computer-executable instructions stored in the memory to cause the electronic device to perform a geographical assessment method for mobile network 5G traffic offloading capability as described in the first aspect.

[0019] Fourthly, a computer-readable storage medium is provided for storing one or more programs, the one or more programs including instructions that, when executed by a computer, cause the computer to perform a geographical assessment method for 5G traffic offloading capability of a mobile network as described in the first aspect.

[0020] This application provides a method and apparatus for geographic assessment of 5G traffic offloading capabilities in mobile networks, applied to scenarios for evaluating mobile network cell performance. When assessing mobile network cell performance, the method can obtain the number of multiple first sampling points corresponding to a target area with multiple grids, the number of multiple second sampling points, the total traffic of each first cell, the total traffic of each second cell, and the target RSRP corresponding to each second sampling point. Since the target area is covered by multiple first cells corresponding to a first network standard and multiple second cells corresponding to a second network standard, multiple first grids can be determined from the multiple grids based on the number of multiple first sampling points, the number of multiple second sampling points, the total traffic of each first cell, and the total traffic of each second cell, and the target traffic corresponding to the multiple first grids can be determined. Further, based on the target RSRP and the number of multiple second sampling points, the proportion of third sampling points in the multiple first grids whose target RSRP is greater than or equal to a first preset threshold is determined. Based on the location information of the multiple first grids and the location information of the multiple second cells, the shortest distance between the center point of the multiple first grids and the multiple second cells is determined as the target distance. Therefore, the network performance of the second network standard can be determined based on the proportion of third sampling points, the target distance, and the target traffic. Using the above method, when evaluating mobile network cell performance, multiple first grids can be determined from multiple grids based on the basic data information corresponding to each grid in the target area. Then, based on the proportion of third sampling points corresponding to these multiple first grids, the target distance, and the target traffic, the network performance of the second network standard can be determined. This solves the problems of low efficiency and low accuracy in manually analyzing network performance in various areas, thereby improving the efficiency and accuracy of evaluating mobile network cell performance. Attached Figure Description

[0021] Figure 1 A schematic diagram of the structure of a geographic assessment system for 5G traffic offloading capability of a mobile network provided for an embodiment of this application;

[0022] Figure 2A flowchart illustrating a method for geographic assessment of 5G traffic offloading capabilities in mobile networks, provided as an embodiment of this application. Figure 1 ;

[0023] Figure 3 A flowchart illustrating a method for geographic assessment of 5G traffic offloading capabilities in mobile networks, provided as an embodiment of this application. Figure 2 ;

[0024] Figure 4 A flowchart illustrating a method for geographic assessment of 5G traffic offloading capabilities in mobile networks, provided as an embodiment of this application. Figure 3 ;

[0025] Figure 5 A flowchart illustrating a method for geographic assessment of 5G traffic offloading capabilities in mobile networks, provided as an embodiment of this application. Figure 4 ;

[0026] Figure 6 A flowchart illustrating a method for geographic assessment of 5G traffic offloading capabilities in mobile networks, provided as an embodiment of this application. Figure 5 ;

[0027] Figure 7 A flowchart illustrating a method for geographic assessment of 5G traffic offloading capabilities in mobile networks, provided as an embodiment of this application. Figure 6 ;

[0028] Figure 8 A schematic diagram of a 5G low-traffic area solution provided for an embodiment of this application;

[0029] Figure 9 A schematic diagram of the structure of a geographical assessment device for 5G traffic offloading capability of a mobile network provided for an embodiment of this application;

[0030] Figure 10 This is a schematic diagram of an electronic device structure provided for an embodiment of this application. Detailed Implementation

[0031] The technical solutions in the embodiments of this application will now be described with reference to the accompanying drawings.

[0032] In the description of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. "And / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. Furthermore, "at least one" and "multiple" refer to two or more. The terms "first," "second," etc., do not limit the quantity or order of execution, and "first," "second," etc., do not necessarily imply differences.

[0033] Currently, when evaluating the performance of mobile network cells, human experience is used to analyze network complaints, measurement reports, and 4G and 5G cell-level traffic in the same coverage direction of the same base station for each 4G and 5G cell. However, it is impossible to present and analyze in detail the low 5G traffic offloading, the number of 5G terminals, and the activation of 5G terminals based on geographical location.

[0034] This application provides a method for geographically evaluating the 5G traffic offloading capability of a mobile network. When evaluating the performance of a mobile network cell, it can obtain the number of multiple first sampling points, the number of multiple second sampling points, the total traffic of each first cell, the total traffic of each second cell, and the target RSRP corresponding to each second sampling point for a target area with multiple grids. Since the target area is covered by multiple first cells corresponding to a first network standard and multiple second cells corresponding to a second network standard, multiple first grids can be determined from multiple grids based on the number of multiple first sampling points, the number of multiple second sampling points, the total traffic of each first cell, and the total traffic of each second cell, and the target traffic corresponding to multiple first grids can be determined. Further, based on the target RSRP and the number of multiple second sampling points, the proportion of third sampling points in multiple first grids whose target RSRP is greater than or equal to a first preset threshold is determined. Based on the location information of multiple first grids and the location information of multiple second cells, the shortest distance between the center point of multiple first grids and multiple second cells is determined as the target distance. Thus, the network performance of the second network standard can be determined based on the proportion of third sampling points, the target distance, and the target traffic. Using the above method, when it is necessary to evaluate the performance of a mobile network cell, multiple first grids can be determined from multiple grids based on the basic data information corresponding to each grid in the target area. The network performance of the second network standard can then be determined based on the proportion of third sampling points corresponding to the multiple first grids, the target distance, and the target traffic.

[0035] The embodiments of this application provide a geographical assessment method for 5G traffic offloading capability of mobile networks, which can be applied to a geographical assessment system for 5G traffic offloading capability of mobile networks. Figure 1 A schematic diagram of the structure of a geographically-based assessment system for 5G traffic offloading capabilities in mobile networks is shown. Figure 1 As shown, the 5G traffic offloading capability geographic assessment system 20 includes a server 21 and a terminal device 22. The server 21 stores data information, sends data information and instructions to the terminal device 22, and receives data information sent from the terminal device 22. The terminal device 22 receives data information from the server 21, executes instructions from the server 21, and sends data information to the server 21.

[0036] The following describes a method for geographically assessing the 5G traffic offloading capability of a mobile network, provided by an embodiment of this application, with reference to the accompanying drawings. Figure 2 As shown in the embodiment of this application, a method for geographically assessing the 5G traffic offloading capability of a mobile network is provided and applied to an electronic device. The method includes steps S201-S205:

[0037] S201. Obtain the basic data information corresponding to the target area.

[0038] The target area is covered by a first network standard and a second network standard. The first network standard corresponds to multiple first cells, and the second network standard corresponds to multiple second cells. The target area includes multiple grids. The basic data information includes: the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, the total traffic of each second cell, and the target RSRP corresponding to each second sampling point in each grid. The number of first sampling points is the number of sampling points corresponding to one first cell, and the number of second sampling points is the number of sampling points corresponding to one second cell.

[0039] It is understandable that electronic devices can acquire basic data information corresponding to each grid cell in multiple grid cells within a target area.

[0040] It should be noted that each of the multiple grids is covered by at least one target cell. The at least one target cell is a cell among the multiple first cells and multiple second cells. For each of the multiple first cells, each grid includes multiple first sampling points (i.e., the minimumization of drive tests (MDT) sampling points of the 4G cell) corresponding to each first cell.

[0041] For example, multiple first cells may include: Cell 1, Cell 2, and Cell 3. A certain grid includes 20 first sampling points corresponding to Cell 1, 30 first sampling points corresponding to Cell 2, and 50 first sampling points corresponding to Cell 3. For each of the multiple second cells, each grid includes multiple second sampling points (i.e., MR sampling points of the 5G cell) corresponding to each second cell. For example, multiple second cells may include: Cell 4, Cell 5, and Cell 6. A certain grid includes 25 second sampling points corresponding to Cell 4, 35 second sampling points corresponding to Cell 5, and 55 second sampling points corresponding to Cell 6.

[0042] It should be noted that the Target Reference Signal Receiving Power (RSRP) is a key parameter representing wireless signal strength in Long Term Evolution (LTE) networks and is one of the physical layer measurement requirements. It is the average signal power received on all resource elements (REs) carrying the reference signal within a given symbol. Generally, this metric is used to reflect wireless coverage strength; a higher metric indicates stronger wireless coverage in the area. Coverage is the percentage of signals exceeding a preset threshold (e.g., -110 dBm). That is, signals exceeding -110 dBm are considered to have coverage, while those below this value are considered not covered, thus allowing the calculation of coverage rate within the area.

[0043] Optionally, the basic data information corresponding to the target area may also include: the grid number of each grid, the grid location information (grid longitude, grid latitude), the ID of the 4G cell (i.e., the first cell) corresponding to the grid, the ID of the 5G cell (i.e., the second cell) corresponding to the grid, the level of the first sampling point (i.e., RSRP) in the grid, the level of the second sampling point in the grid, the number of first sampling points in the grid with RSRP greater than or equal to the first level threshold, the number of second sampling points in the grid with RSRP greater than or equal to the first preset threshold, the number of 5G terminals in the grid (i.e., the number of first terminal devices), the number of 5G terminals in the grid whose switches are not turned on (i.e., the number of second terminal devices), and the total number of sampling points in the grid.

[0044] For example, the first level threshold can be -110dBm, and the first preset threshold can be -105dBm.

[0045] S202. Based on the number of first sampling points corresponding to each grid, the number of second sampling points corresponding to each grid, the total traffic of each first cell, and the total traffic of each second cell, determine multiple first grids from the multiple grids, and determine the target traffic corresponding to the multiple first grids.

[0046] The target traffic is the total traffic corresponding to multiple first cells in multiple first grids.

[0047] It is understandable that electronic devices can determine the first network standard traffic corresponding to each grid based on the number of multiple first sampling points corresponding to each grid and the total traffic of each first cell, and determine the second network standard traffic corresponding to each grid based on the number of multiple second sampling points corresponding to each grid and the total traffic of each second cell.

[0048] Furthermore, based on the first network standard traffic and the second network standard traffic corresponding to each grid, the second network standard traffic splitting ratio corresponding to each grid is determined. Then, based on the second network standard traffic splitting ratio corresponding to each grid, multiple first grids with a second network standard traffic splitting ratio less than or equal to a second preset threshold are determined from the multiple grids. Finally, based on the first network standard traffic and the second network standard traffic corresponding to each grid in the multiple first grids, the target traffic corresponding to the multiple first grids is determined.

[0049] Optionally, based on the basic data information corresponding to each of the multiple first grids, a preset clustering algorithm can be used to cluster each of the multiple first grids to remove grids that are not connected to other first grids, thereby obtaining multiple clusters composed of first grids. Each cluster includes multiple interconnected first grids, and a label is generated for each cluster to identify itself.

[0050] Furthermore, based on the label corresponding to each cluster, a preset convex hull operation is performed on the position information of the first grid corresponding to each cluster to obtain the target envelope curve corresponding to each cluster. The target traffic corresponding to multiple first grids can be the sum of the first network mode traffic corresponding to each grid in multiple first grids and the sum of the second network mode traffic corresponding to each grid in multiple first grids.

[0051] For example, multiple clusters may include cluster 1, cluster 2, and cluster 3.

[0052] It should be noted that by using the preset convex hull operation, an irregular closed curve can be drawn for the first edge grid cell in each cluster to obtain the target envelope curve corresponding to each cluster.

[0053] S203. Based on the target RSRP and the number of multiple second sampling points corresponding to each grid, determine the proportion of third sampling points included in multiple first grids.

[0054] The third sampling point is the second sampling point in each of the multiple first grids where the target RSRP of the second sampling point is greater than or equal to the first preset threshold.

[0055] It is understood that the electronic device can determine the number of third sampling points corresponding to each grid based on the target RSRP corresponding to each second sampling point in each grid of multiple first grids, and determine the proportion of third sampling points included in multiple first grids based on the number of third sampling points corresponding to each grid and the number of multiple second sampling points corresponding to each grid.

[0056] Optionally, the proportion of third sampling points included in the plurality of first grids can be the ratio of the sum of the number of third sampling points corresponding to each grid in the plurality of first grids to the sum of the number of second sampling points corresponding to each grid in the plurality of first grids.

[0057] S204. Determine the target distance based on the location information of multiple first grid cells and multiple second cells.

[0058] The target distance is the shortest distance between the center points of multiple first grid cells and multiple second cells.

[0059] It is understandable that the electronic device can determine the center point of multiple first grids based on the position information of multiple first grids, and determine the second cell closest to the center point based on the position information of multiple second cells, and then determine the target distance based on the position information of the center point of multiple first grids and the position information of the second cell closest to the center point.

[0060] Optionally, the longitude corresponding to the center point of the multiple first grids can be the average of the grid longitudes corresponding to each of the multiple first grids, and the latitude corresponding to the center point of the multiple first grids can be the average of the grid latitudes corresponding to each of the multiple first grids.

[0061] S205. Determine the network performance of the second network standard based on the proportion of the third sampling point, the target distance, and the target traffic.

[0062] It is understood that electronic devices can determine the network performance of the second network standard corresponding to the multiple first grids based on the proportion of third sampling points included in the multiple first grids, the target distance corresponding to the multiple first grids, the target traffic corresponding to the multiple first grids, the number of first terminal devices included in the multiple first grids, and the number of second terminal devices included in the multiple first grids.

[0063] This application provides a method for geographically evaluating the 5G traffic offloading capability of a mobile network. When evaluating the performance of a mobile network cell, it can obtain the number of multiple first sampling points, the number of multiple second sampling points, the total traffic of each first cell, the total traffic of each second cell, and the target RSRP corresponding to each second sampling point for a target area with multiple grids. Since the target area is covered by multiple first cells corresponding to a first network standard and multiple second cells corresponding to a second network standard, multiple first grids can be determined from multiple grids based on the number of multiple first sampling points, the number of multiple second sampling points, the total traffic of each first cell, and the total traffic of each second cell, and the target traffic corresponding to multiple first grids can be determined. Further, based on the target RSRP and the number of multiple second sampling points, the proportion of third sampling points in multiple first grids whose target RSRP is greater than or equal to a first preset threshold is determined. Based on the location information of multiple first grids and the location information of multiple second cells, the shortest distance between the center point of multiple first grids and multiple second cells is determined as the target distance. Thus, the network performance of the second network standard can be determined based on the proportion of third sampling points, the target distance, and the target traffic. Using the above method, when it is necessary to evaluate the performance of a mobile network cell, multiple first grids can be determined from multiple grids based on the basic data information corresponding to each grid in the target area. The network performance of the second network standard can then be determined based on the proportion of third sampling points corresponding to the multiple first grids, the target distance, and the target traffic.

[0064] In a design, such as Figure 3 As shown in the embodiment of this application, a method for geographically evaluating the 5G traffic offloading capability of a mobile network is provided and applied to an electronic device. The method in step S202 above, which involves "determining multiple first grids from multiple grids based on the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, and the total traffic of each second cell", specifically includes steps S301-S303:

[0065] S301. Determine the first network type traffic corresponding to each grid based on the number of multiple first sampling points corresponding to each grid and the total traffic of each first cell.

[0066] It is understandable that electronic devices can determine the proportion of first sampling points of each first cell on each grid based on the number of multiple first sampling points corresponding to each grid and the number of sampling points of each first cell.

[0067] Furthermore, based on the proportion of the first sampling points of each first cell in each grid and the total traffic of each first cell, the first network type traffic corresponding to each grid is determined.

[0068] S302. Based on the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, and the total traffic of each second cell, determine the second network type traffic splitting ratio corresponding to each grid.

[0069] It is understandable that the electronic device can determine the sampling point ratio of each first cell on each grid based on the number of multiple first sampling points corresponding to each grid and the number of sampling points of each first cell. Furthermore, based on the sampling point ratio of each first cell on each grid and the total traffic of each first cell, it can determine the first network type traffic corresponding to each grid, and based on the number of multiple second sampling points corresponding to each grid and the number of sampling points of each second cell, it can determine the sampling point ratio of each second cell on each grid.

[0070] Furthermore, based on the sampling point ratio of each second cell in each grid and the total traffic of each second cell, the second network standard traffic corresponding to each grid is determined. Then, based on the first network standard traffic and the second network standard traffic corresponding to each grid, the second network standard traffic splitting ratio corresponding to each grid is determined.

[0071] S303. Based on the second network standard split ratio corresponding to each grid, determine a plurality of first grids from the plurality of grids whose second network standard split ratio is less than or equal to a second preset threshold.

[0072] It is understood that the electronic device can determine a number of first grids from a number of grids whose second network standard shunt ratio is less than or equal to a second preset threshold (e.g., 50%) based on the second network standard shunt ratio corresponding to each grid.

[0073] Optionally, the multiple first grids can be grids whose first network type traffic is greater than a certain preset threshold.

[0074] It should be noted that, in the case of steps S301-S303, the method in step S202 above may specifically include "determining the target traffic corresponding to multiple first grids".

[0075] In a design, such as Figure 4 As shown in the embodiment of this application, a method for geographically assessing the 5G traffic offloading capability of a mobile network is provided and applied to an electronic device. The method in step S302 above specifically includes S401-S403:

[0076] S401. Determine the first network type traffic corresponding to each grid based on the number of multiple first sampling points corresponding to each grid and the total traffic of each first cell.

[0077] It is understandable that electronic devices can determine the proportion of sampling points of each first cell in each grid based on the number of multiple first sampling points corresponding to each grid and the number of sampling points of each first cell. Furthermore, based on the proportion of sampling points of each first cell in each grid and the total traffic of each first cell, the first network type traffic corresponding to each grid can be determined.

[0078] S402. Determine the second network type traffic corresponding to each grid based on the number of multiple second sampling points corresponding to each grid and the total traffic of each second cell.

[0079] It is understandable that electronic devices can determine the proportion of second sampling points of each second cell in each grid based on the number of multiple second sampling points corresponding to each grid and the number of sampling points of each second cell. Furthermore, based on the proportion of second sampling points of each second cell in each grid and the total traffic of each second cell, the second network standard traffic corresponding to each grid can be determined.

[0080] S403. Determine the second network standard traffic splitting ratio for each grid based on the first network standard traffic and the second network standard traffic for each grid.

[0081] Optionally, the sum of the first network standard traffic corresponding to a grid and the second network standard traffic corresponding to the grid can be the total network standard traffic corresponding to the grid, and the second network standard traffic splitting ratio corresponding to each grid can be the ratio of the second network standard traffic corresponding to each grid to the total network standard traffic corresponding to each grid.

[0082] For example, a grid number can be i, and the second network type split ratio corresponding to grid i is P, where P = M. i_5g / (M i_4g +M i_5g ), where M i_5g M represents the second network type traffic corresponding to grid i. i_4g This represents the first network type traffic corresponding to grid i.

[0083] In a design, such as Figure 5 As shown, in the geographical assessment method for 5G traffic offloading capability of mobile networks provided in this application embodiment, applied to electronic devices, the method in step S401 above specifically includes S501-S503:

[0084] S501. Determine the proportion of multiple first sampling points corresponding to each grid based on the number of multiple first sampling points corresponding to each grid.

[0085] In this context, the percentage of a first sampling point corresponds to a first cell.

[0086] It is understandable that electronic devices can determine the proportion of first sampling points of each first cell on each grid based on the number of multiple first sampling points corresponding to each grid and the number of sampling points of each first cell.

[0087] Optionally, the percentage of first sampling points in each first cell on each grid can be the ratio of the number of multiple first sampling points corresponding to each grid to the number of first sampling points in each first cell.

[0088] For example, a grid number can be i, and the ID can be the ID of a first cell. The proportion of the first sampling point of the first cell on grid i can be p. ID_i There is p ID_i =m ID_i / M ID , where m ID_i M represents the number of the first sampling points of a certain first cell on grid i. ID This indicates the number of the first sampling points in a certain first community.

[0089] S502. Determine the traffic of each first cell corresponding to each grid based on the proportion of multiple first sampling points corresponding to each grid and the total traffic of each first cell.

[0090] It is understandable that electronic devices can determine the traffic of each first cell corresponding to each grid based on the proportion of multiple first sampling points corresponding to each grid and the total traffic of each first cell.

[0091] Optionally, the total traffic of each first cell can be calculated according to the network management statistics. The traffic of each first cell corresponding to each grid can be the product of the proportion of multiple first sampling points corresponding to each grid and the total traffic of each first cell.

[0092] For example, the traffic of a certain first cell corresponding to grid i is U. 4g_i_ID , there is U 4g_i_ID =U 4g_ID *p ID_i , among which, U 4g_ID p represents the total traffic flow of a certain first community. ID_i This represents the percentage of the first sampling point corresponding to grid i.

[0093] S503. Determine the first network type traffic corresponding to each grid based on the traffic of each first cell corresponding to each grid.

[0094] It is understandable that electronic devices can determine the first network type traffic corresponding to each grid based on the traffic of each first cell corresponding to each grid.

[0095] Optionally, the first network type traffic corresponding to each grid can be the sum of the traffic of each first cell corresponding to each grid.

[0096] For example, the first network type traffic M corresponding to grid i i_4g As shown in Formula 1:

[0097]

[0098] Among them, M i_4g U represents the first network type traffic corresponding to grid i. 4g_i_ID Let k = 0 represent the traffic of a certain first cell corresponding to grid i, where k = 0 represents the 0th first cell corresponding to grid i, and n represents the nth first cell corresponding to grid i.

[0099] In a design, such as Figure 6 As shown, in the geographical assessment method for 5G traffic offloading capability of mobile networks provided in this application embodiment, the method in step S402 above specifically includes S601-S603:

[0100] S601. Determine the proportion of multiple second sampling points corresponding to each grid based on the number of multiple second sampling points corresponding to each grid.

[0101] In this case, the percentage of a second sampling point corresponds to a second cell.

[0102] Optionally, the proportion of second sampling points in each second cell on each grid can be the ratio of the number of multiple second sampling points corresponding to each grid to the number of second sampling points in each second cell.

[0103] For example, a grid number can be i, the ID can be the ID of a second cell, and the proportion of the second sampling points of the second cell on grid i can be q. ID_i , there is q ID_i =n ID_i / N ID , where n ID_i N represents the number of second sampling points in a second cell on grid i. ID This indicates the number of second sampling points in a certain second community.

[0104] S602. Determine the traffic of each second cell corresponding to each grid based on the proportion of multiple second sampling points corresponding to each grid and the total traffic of each second cell.

[0105] It is understandable that electronic devices can determine the traffic of each second cell corresponding to each grid based on the proportion of multiple second sampling points corresponding to each grid and the total traffic of each second cell.

[0106] Optionally, the total traffic of each second cell can be calculated according to the network management statistics. The traffic of each second cell corresponding to each grid can be the product of the proportion of multiple second sampling points corresponding to each grid and the total traffic of each second cell.

[0107] For example, the traffic of a certain second cell corresponding to grid i is U. 5g_i_ID , there is U 5g_i_ID =U 5g_ID *q ID_i , among which, U 5g_ID q represents the total traffic flow of a certain second cell. ID_i This indicates the percentage of the second sampling point corresponding to grid i.

[0108] S603. Determine the second network type traffic corresponding to each grid based on the traffic of each second cell corresponding to each grid.

[0109] It is understandable that electronic devices can determine the second network standard traffic corresponding to each grid based on the traffic of each second cell corresponding to each grid.

[0110] Optionally, the second network type traffic corresponding to each grid can be the sum of the traffic of each second cell corresponding to each grid.

[0111] For example, the second network type traffic M corresponding to grid i i_5g As shown in Formula 2:

[0112]

[0113] Among them, M i_5g U represents the second network type traffic corresponding to grid i. 5g_i_ID Let k = 0 represent the traffic of a certain second cell corresponding to grid i, where k = 0 represents the 0th second cell corresponding to grid i, and n represents the nth second cell corresponding to grid i.

[0114] In a design, such as Figure 7 As shown, in the geographical assessment method for 5G traffic offloading capability of mobile networks provided in this application embodiment, the method in step S205 above specifically includes S701-S704:

[0115] S701. When the proportion of the third sampling point is less than the third threshold and the target distance is less than the fourth threshold, check the antenna azimuth and downtilt angle of each of the multiple second cells.

[0116] It is understandable that when the proportion of the third sampling points included in multiple first grids is less than the third threshold, and the target distance corresponding to multiple first grids is less than the fourth threshold, the antenna azimuth and downtilt angle of each of the multiple second cells corresponding to multiple first grids can be checked.

[0117] Optionally, the proportion of third sampling points included in multiple first grids can be increased by adjusting the antenna azimuth and downtilt angle corresponding to each second cell.

[0118] S702. When the proportion of the third sampling point is less than the third threshold, the target distance is greater than or equal to the fourth threshold, and the target traffic is greater than or equal to the fifth threshold, the signal strength of each of the multiple second cells is enhanced.

[0119] It is understandable that when the proportion of the third sampling points included in the multiple first grids is less than the third threshold, the target distance corresponding to the multiple first grids is greater than or equal to the fourth threshold, and the target traffic corresponding to the multiple first grids is greater than or equal to the fifth threshold, the signal strength of each of the multiple second cells corresponding to the multiple first grids can be enhanced.

[0120] Optionally, 5G network coverage can be enhanced by planning second cell base stations in multiple first grids, thereby increasing the proportion of third sampling points included in multiple first grids.

[0121] S703. When the proportion of the third sampling point is greater than or equal to the third threshold, the target traffic is greater than or equal to the fifth threshold, and the number of first terminal devices included in the multiple first grids is less than the sixth threshold, the number of first terminal devices accessed in each of the multiple second cells is increased.

[0122] The first terminal device is a terminal device that supports access to the second network standard.

[0123] It is understandable that when the proportion of third sampling points included in multiple first grids is greater than or equal to the third threshold, the target traffic corresponding to multiple first grids is greater than or equal to the fifth threshold, and the number of first terminal devices included in multiple first grids is less than the sixth threshold, the number of first terminal devices accessed in each of the multiple second cells corresponding to multiple first grids can be increased.

[0124] Alternatively, the number of primary terminal devices can be increased by suggesting that the market develop the number of 5G terminals.

[0125] S704. When the proportion of the third sampling point is greater than or equal to the third threshold, and the number of second terminal devices included in the multiple first grids is greater than or equal to the seventh threshold, increase the number of first terminal devices accessed in each of the multiple second cells.

[0126] It is understandable that when the proportion of the third sampling points included in multiple first grids is greater than or equal to the third threshold, and the number of second terminal devices included in multiple first grids is greater than or equal to the seventh threshold, the number of first terminal devices accessed in each of the multiple second cells corresponding to the multiple first grids is increased.

[0127] Optionally, the number of first terminal devices accessed by each of the multiple second cells corresponding to the multiple first grids can be increased by suggesting that the market side assist multiple 5G terminals in the area where the first grids are located to turn on the 5G switch.

[0128] In one implementation, such as Figure 8 The diagram shows a flowchart of a 5G low-passage area solution. First, acquire the 5G low-bandwidth area envelope data. Match the envelope MR sampling points, RSRP threshold sampling point count, 5G terminal user data, number of 5G terminal switches not turned on, envelope center longitude, and envelope center latitude in the 5G low-bandwidth area envelope data to determine the 5G coverage level sampling point ratio. Determine if the 5G coverage level sampling point ratio is lower than a certain threshold. If it is lower, further determine if the distance between the 5G cell and the envelope center is lower than a certain threshold. If it is not lower than a certain threshold, determine if the number of 5G users is lower than a certain threshold. Determine if the distance between the 5G cell and the envelope center is lower than a certain threshold. If it is lower, check the 5G cell antenna azimuth and downtilt angle. If it is not lower than a certain threshold, suggest planning 5G base stations based on traffic volume. Determine if the number of 5G users is lower than a certain threshold. If it is lower than a certain threshold, and 4G traffic is high, suggest the market strengthen business development. If it is not lower than a certain threshold, and the number of 5G terminals not turned on is higher than the threshold, suggest that 5G users in the market-side auxiliary area turn on their 5G switches.

[0129] In one implementation, when multiple target envelope curves corresponding to first grids already exist on the map, the proportion of third sampling points, target distance, target traffic, number of first terminal devices, and number of second terminal devices corresponding to the target envelope curve can be determined based on the basic data information of each grid within the target envelope curve, thereby determining the network performance of the second network standard corresponding to the target envelope curve.

[0130] This application provides a method for geographic assessment of 5G traffic offloading capabilities in mobile networks. It statistically analyzes the sampling points included in the coverage grid of each cell across the entire network, calculates the proportion of sampling points for each cell within its coverage grid at the cell level, and combines this with the total traffic of each cell to calculate the traffic of each cell in each covered grid. Finally, it aggregates the traffic of each cell in each grid to obtain the 4G and 5G traffic of each grid, with high calculation accuracy. Furthermore, based on the 4G and 5G traffic of each grid, the 5G offloading ratio of each grid is calculated. This allows for the selection of grids with high 4G traffic and low 5G offloading for focused analysis. By forming cluster envelopes for the grids with low 5G offloading, and linking this data with grid network coverage, number of user terminals, and whether 5G is enabled, suggested solutions are provided to the network and market sides.

[0131] The foregoing mainly describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, it includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments disclosed herein, the embodiments of this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0132] This application embodiment can divide a method for geographically assessing 5G traffic offloading capabilities of a mobile network into functional modules based on the above method example. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. Optionally, the module division in this application embodiment is illustrative and only represents a logical functional division; other division methods may be used in actual implementation.

[0133] Figure 9 This is a schematic diagram of a geographically-based assessment device for 5G traffic offloading capability in a mobile network, provided as an embodiment of this application. Figure 9 As shown, a geographic assessment device 40 for 5G traffic offloading capability of a mobile network is used to improve the efficiency and accuracy of assessing the performance of mobile network cells, for example, for performing... Figure 2 The diagram illustrates a method for geographic assessment of 5G traffic offloading capabilities in mobile networks. The device 40 for geographic assessment of 5G traffic offloading capabilities in mobile networks includes: an acquisition unit 401 and a processing unit 402;

[0134] The acquisition unit 401 is used to acquire basic data information corresponding to the target area. The target area is covered by a first network standard and a second network standard. The first network standard corresponds to multiple first cells, and the second network standard corresponds to multiple second cells. The target area includes multiple grids. The basic data information includes: the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, the total traffic of each second cell, and the target reference signal received power RSRP corresponding to each second sampling point in each grid. The number of first sampling points is the number of sampling points corresponding to one first cell, and the number of second sampling points is the number of sampling points corresponding to one second cell.

[0135] The processing unit 402 is used to determine multiple first grids from multiple grids based on the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, and the total traffic of each second cell, and to determine the target traffic corresponding to the multiple first grids, wherein the target traffic is the total traffic corresponding to the multiple first cells in the multiple first grids;

[0136] The processing unit 402 is further configured to determine the proportion of third sampling points included in the multiple first grids based on the target RSRP and the number of multiple second sampling points corresponding to each grid, wherein the third sampling point is a second sampling point in each of the multiple first grids whose target RSRP is greater than or equal to a first preset threshold.

[0137] The processing unit 402 is further configured to determine a target distance based on the location information of multiple first grids and multiple second cells, wherein the target distance is the closest distance between the center point of multiple first grids and multiple second cells;

[0138] The processing unit 402 is also used to determine the network performance of the second network mode based on the proportion of the third sampling point, the target distance, and the target traffic.

[0139] In one possible implementation, the processing unit 402 is further configured to determine the first network standard traffic corresponding to each grid based on the number of multiple first sampling points corresponding to each grid and the total traffic of each first cell; the processing unit 402 is further configured to determine the second network standard traffic splitting ratio corresponding to each grid based on the number of multiple first sampling points corresponding to each grid, the number of multiple second sampling points corresponding to each grid, the total traffic of each first cell, and the total traffic of each second cell; the processing unit 402 is further configured to determine, based on the second network standard traffic splitting ratio corresponding to each grid, a plurality of first grids whose second network standard traffic splitting ratio is less than or equal to a second preset threshold from the plurality of grids.

[0140] In one possible implementation, the processing unit 402 is further configured to determine the first network standard traffic corresponding to each grid based on the number of multiple first sampling points corresponding to each grid and the total traffic of each first cell; the processing unit 402 is further configured to determine the second network standard traffic corresponding to each grid based on the number of multiple second sampling points corresponding to each grid and the total traffic of each second cell; the processing unit 402 is further configured to determine the second network standard traffic splitting ratio corresponding to each grid based on the first network standard traffic corresponding to each grid and the second network standard traffic corresponding to each grid.

[0141] In one possible implementation, the processing unit 402 is further configured to determine the proportion of multiple first sampling points corresponding to each grid based on the number of multiple first sampling points corresponding to each grid, wherein one proportion of first sampling points corresponds to one first cell; the processing unit 402 is further configured to determine the traffic of each first cell corresponding to each grid based on the proportion of multiple first sampling points corresponding to each grid and the total traffic of each first cell; the processing unit 402 is further configured to determine the first network type traffic corresponding to each grid based on the traffic of each first cell corresponding to each grid.

[0142] In one possible implementation, the processing unit 402 is further configured to determine the proportion of multiple second sampling points corresponding to each grid based on the number of multiple second sampling points corresponding to each grid, wherein one proportion of second sampling points corresponds to one second cell; the processing unit 402 is further configured to determine the traffic of each second cell corresponding to each grid based on the proportion of multiple second sampling points corresponding to each grid and the total traffic of each second cell; the processing unit 402 is further configured to determine the second network standard traffic corresponding to each grid based on the traffic of each second cell corresponding to each grid.

[0143] In one possible implementation, the processing unit 402 is further configured to: check the antenna azimuth and downtilt angle of each of the multiple second cells when the proportion of the third sampling points is less than the third threshold and the target distance is less than the fourth threshold; enhance the signal strength of each of the multiple second cells when the proportion of the third sampling points is less than the third threshold, the target distance is greater than or equal to the fourth threshold, and the target traffic is greater than or equal to the fifth threshold; increase the number of first terminal devices accessed in each of the multiple second cells when the proportion of the third sampling points is greater than or equal to the third threshold, the target traffic is greater than or equal to the fifth threshold, and the number of first terminal devices included in the multiple first grids is less than the sixth threshold, wherein the first terminal devices are terminal devices that support access to the second network standard; and increase the number of first terminal devices accessed in each of the multiple second cells when the proportion of the third sampling points is greater than or equal to the third threshold and the number of second terminal devices included in the multiple first grids is greater than or equal to the seventh threshold.

[0144] In the case of implementing the functions of the integrated modules described above in hardware, this application provides another possible structural diagram of the electronic device involved in the above embodiments. For example... Figure 10 As shown, an electronic device 60 is used to improve the efficiency and accuracy of evaluating the performance of mobile network cells, for example, for performing... Figure 2This paper presents a method for geographically evaluating the 5G traffic offloading capability of a mobile network. The electronic device 60 includes a processor 601, a memory 602, and a bus 603. The processor 601 and the memory 602 can be connected via the bus 603.

[0145] Processor 601 is the control center of the communication device. It can be a single processor or a collective term for multiple processing elements. For example, processor 601 can be a general-purpose central processing unit (CPU) or other general-purpose processors. Among them, the general-purpose processor can be a microprocessor or any conventional processor.

[0146] As one embodiment, processor 601 may include one or more CPUs, for example Figure 10 CPU 0 and CPU 1 are shown in the diagram.

[0147] The memory 602 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto.

[0148] As one possible implementation, the memory 602 can exist independently of the processor 601. The memory 602 can be connected to the processor 601 via a bus 603 and is used to store instructions or program code. When the processor 601 calls and executes the instructions or program code stored in the memory 602, it can implement the geographical assessment method for mobile network 5G traffic offloading capability provided in this application embodiment.

[0149] In another possible implementation, the memory 602 can also be integrated with the processor 601.

[0150] Bus 603 can be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus. This bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 10 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0151] It should be pointed out that, Figure 10 The structure shown does not constitute a limitation on the electronic device 60. Except... Figure 10 In addition to the components shown, the electronic device 60 may include more or fewer components than illustrated, or combine certain components, or have different component arrangements.

[0152] As an example, combined Figure 9 The functions implemented by the acquisition unit 401 and the processing unit 402 in the electronic device are the same as Figure 10 The processor 601 in it has the same function.

[0153] Optional, such as Figure 10 As shown, the electronic device 60 provided in this application embodiment may further include a communication interface 604.

[0154] Communication interface 604 is used to connect with other devices via a communication network. This communication network can be Ethernet, a wireless access network, a wireless local area network (WLAN), etc. Communication interface 604 may include a receiving unit for receiving data and a transmitting unit for transmitting data.

[0155] In one design, the communication interface in the electronic device provided in this application embodiment can also be integrated into the processor.

[0156] Through the above description of the embodiments, those skilled in the art will clearly understand that, for the sake of convenience and brevity, only the division of the above functional units is used as an example. In practical applications, the above functions can be assigned to different functional units as needed, that is, the internal structure of the device can be divided into different functional units to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0157] This application also provides a computer-readable storage medium storing instructions. When a computer executes these instructions, the computer performs each step of the method flow shown in the above-described method embodiments.

[0158] Embodiments of this application provide a computer program product containing instructions that, when executed on a computer, cause the computer to perform a method for geographic assessment of 5G traffic offloading capabilities in a mobile network as described in the above method embodiments.

[0159] The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), registers, hard disks, optical fibers, compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing, or any other form of computer-readable storage medium in the art.

[0160] An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside within an application-specific integrated circuit (ASIC).

[0161] In the embodiments of this application, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0162] Since the electronic devices, computer-readable storage media, and computer program products in the embodiments of this application can be applied to the above methods, the technical effects they can achieve can also be referred to the above method embodiments. The embodiments of this application will not be repeated here.

[0163] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be covered within the scope of protection of this application.

Claims

1. A method for geographic evaluation of mobile network 5G traffic offloading capability, characterized in that, The method comprises: obtaining basic data information corresponding to a target area, the target area being covered by a first network standard and a second network standard, the first network standard corresponding to a plurality of first cells, the second network standard corresponding to a plurality of second cells, the target area comprising a plurality of grids, the basic data information comprising: a plurality of first sampling point quantities corresponding to each grid, a plurality of second sampling point quantities corresponding to each grid, a total flow of each first cell, a total flow of each second cell, and a target reference signal received power (RSRP) corresponding to each second sampling point in each grid, one first sampling point quantity being a sampling point quantity corresponding to one first cell, and one second sampling point quantity being a sampling point quantity corresponding to one second cell; determining a plurality of first grids from the plurality of grids according to the plurality of first sampling point quantities corresponding to each grid, the plurality of second sampling point quantities corresponding to each grid, the total flow of each first cell, and the total flow of each second cell, and determining a target flow corresponding to the plurality of first grids, the target flow being a total flow corresponding to the plurality of first cells in the plurality of first grids; determining a third sampling point proportion included in the plurality of first grids according to the target RSRP and the plurality of second sampling point quantities corresponding to each grid, the third sampling point being a second sampling point whose target RSRP is greater than or equal to a first preset threshold in each first grid in the plurality of first grids; determining a target distance according to position information of the plurality of first grids and position information of the plurality of second cells, the target distance being a corresponding nearest distance between a center point of the plurality of first grids and the plurality of second cells; determining a network performance of the second network standard according to the third sampling point proportion, the target distance, and the target flow.

2. The method of claim 1, wherein, The determining of the plurality of first grids from the plurality of grids according to the plurality of first sampling point quantities corresponding to each grid, the plurality of second sampling point quantities corresponding to each grid, the total flow of each first cell, and the total flow of each second cell comprises: determining a first network standard flow corresponding to each grid according to the plurality of first sampling point quantities corresponding to each grid and the total flow of each first cell; determining a second network standard shunt ratio corresponding to each grid according to the plurality of first sampling point quantities corresponding to each grid, the plurality of second sampling point quantities corresponding to each grid, the total flow of each first cell, and the total flow of each second cell; determining the plurality of first grids from the plurality of grids according to the second network standard shunt ratio corresponding to each grid, the second network standard shunt ratio being less than or equal to a second preset threshold.

3. The method of claim 2, wherein, The determining of the second network standard shunt ratio corresponding to each grid according to the plurality of first sampling point quantities corresponding to each grid, the plurality of second sampling point quantities corresponding to each grid, the total flow of each first cell, and the total flow of each second cell comprises: determining a first network standard flow corresponding to each grid according to the plurality of first sampling point quantities corresponding to each grid and the total flow of each first cell; The second network type traffic corresponding to each grid is determined based on the number of multiple second sampling points corresponding to each grid and the total traffic of each second cell; Based on the first network type traffic and the second network type traffic corresponding to each grid, determine the second network type traffic splitting ratio for each grid.

4. The method of claim 3, wherein, The step of determining the first network type traffic corresponding to each grid cell based on the number of multiple first sampling points corresponding to each grid cell and the total traffic of each first cell includes: Based on the number of multiple first sampling points corresponding to each grid, the proportion of multiple first sampling points corresponding to each grid is determined, and one proportion of first sampling points corresponds to one first cell; Based on the proportion of multiple first sampling points corresponding to each grid and the total traffic of each first cell, the traffic of each first cell corresponding to each grid is determined; Based on the traffic of each first cell corresponding to each grid, determine the first network type traffic corresponding to each grid.

5. The method of claim 3, wherein, The step of determining the second network type traffic corresponding to each grid cell based on the number of multiple second sampling points corresponding to each grid cell and the total traffic of each second cell includes: Based on the number of multiple second sampling points corresponding to each grid, the proportion of multiple second sampling points corresponding to each grid is determined, and one proportion of second sampling points corresponds to one second cell; Based on the proportion of multiple second sampling points corresponding to each grid and the total traffic of each second cell, the traffic of each second cell corresponding to each grid is determined; Based on the traffic of each second cell corresponding to each grid, determine the second network type traffic corresponding to each grid.

6. The method of claim 1, wherein, The step of determining the network performance of the second network standard based on the proportion of the third sampling points, the target distance, and the target traffic includes: When the proportion of the third sampling point is less than the third threshold and the target distance is less than the fourth threshold, check the antenna azimuth and downtilt angle corresponding to each of the plurality of second cells; When the proportion of the third sampling point is less than the third threshold, the target distance is greater than or equal to the fourth threshold, and the target traffic is greater than or equal to the fifth threshold, the signal strength corresponding to each of the multiple second cells is enhanced; When the proportion of the third sampling point is greater than or equal to the third threshold, the target traffic is greater than or equal to the fifth threshold, and the number of first terminal devices included in the plurality of first grids is less than the sixth threshold, the number of first terminal devices accessed by each of the plurality of second cells is increased, and the first terminal device is a terminal device that supports access to the second network standard; When the proportion of the third sampling point is greater than or equal to the third threshold, and the number of second terminal devices included in the plurality of first grids is greater than or equal to the seventh threshold, the number of first terminal devices accessed by each of the plurality of second cells is increased. 7.A mobile network 5G traffic offloading capability geo-estimation apparatus characterized in that, The geographical assessment device for 5G traffic offloading capability of mobile network includes: an acquisition unit and a processing unit; The acquisition unit is configured to acquire basic data information corresponding to a target area, the target area is covered by a first network standard and a second network standard, the first network standard corresponds to a plurality of first cells, the second network standard corresponds to a plurality of second cells, the target area includes a plurality of grids, and the basic data information includes: a plurality of first sampling point quantities corresponding to each grid, a plurality of second sampling point quantities corresponding to each grid, a total flow of each first cell, a total flow of each second cell, and a target reference signal receiving power (RSRP) corresponding to each second sampling point in each grid, one first sampling point quantity is a sampling point quantity corresponding to one first cell, and one second sampling point quantity is a sampling point quantity corresponding to one second cell. The processing unit is configured to determine a plurality of first grids from the plurality of grids according to the plurality of first sampling point quantities corresponding to each grid, the plurality of second sampling point quantities corresponding to each grid, the total flow of each first cell, and the total flow of each second cell, and determine a target flow corresponding to the plurality of first grids, the target flow being a total flow corresponding to the plurality of first cells in the plurality of first grids. The processing unit is further configured to determine a third sampling point proportion included in the plurality of first grids according to the target RSRP and the plurality of second sampling point quantities corresponding to each grid, the third sampling point being a second sampling point whose target RSRP is greater than or equal to a first preset threshold in each first grid in the plurality of first grids. The processing unit is further configured to determine a target distance according to position information of the plurality of first grids and position information of the plurality of second cells, the target distance being a corresponding nearest distance between center points of the plurality of first grids and the plurality of second cells. The processing unit is further configured to determine network performance of the second network standard according to the third sampling point proportion, the target distance, and the target flow.

8. The mobile network 5G traffic offload capability geo- localization evaluation apparatus according to claim 7, characterized in that, The processing unit is further configured to determine a first network standard flow corresponding to each grid according to the plurality of first sampling point quantities corresponding to each grid and the total flow of each first cell. The processing unit is further configured to determine a second network standard shunt ratio corresponding to each grid according to the plurality of first sampling point quantities corresponding to each grid, the plurality of second sampling point quantities corresponding to each grid, the total flow of each first cell, and the total flow of each second cell. The processing unit is further configured to determine the plurality of first grids in which the second network standard shunt ratio is less than or equal to a second preset threshold from the plurality of grids according to the second network standard shunt ratio corresponding to each grid.

9. The mobile network 5G traffic offload capability geo- localization evaluation apparatus according to claim 8, characterized in that, The processing unit is further configured to determine a first network standard flow corresponding to each grid according to the plurality of first sampling point quantities corresponding to each grid and the total flow of each first cell. The processing unit is further configured to determine a second network standard flow corresponding to each grid according to the plurality of second sampling point quantities corresponding to each grid and the total flow of each second cell. The processing unit is further configured to determine, according to the first network mode traffic corresponding to each grid and the second network mode traffic corresponding to each grid, a second network mode shunt ratio corresponding to each grid.

10. The mobile network 5G traffic offload capability geo- localization evaluation apparatus of claim 9, wherein, The processing unit is further configured to determine, according to the number of first sampling points corresponding to each grid, a first sampling point proportion corresponding to each grid, one first sampling point proportion corresponding to one first cell; The processing unit is further configured to determine, according to the number of first sampling point proportions corresponding to each grid and the total traffic of each first cell, the traffic of each first cell corresponding to each grid; The processing unit is further configured to determine, according to the traffic of each first cell corresponding to each grid, the first network mode traffic corresponding to each grid.

11. The mobile network 5G traffic offload capability geo- localization evaluation apparatus of claim 9, wherein, The processing unit is further configured to determine, according to the number of second sampling points corresponding to each grid, a second sampling point proportion corresponding to each grid, one second sampling point proportion corresponding to one second cell; The processing unit is further configured to determine, according to the number of second sampling point proportions corresponding to each grid and the total traffic of each second cell, the traffic of each second cell corresponding to each grid; The processing unit is further configured to determine, according to the traffic of each second cell corresponding to each grid, the second network mode traffic corresponding to each grid.

12. The mobile network 5G traffic offload capability geo- localization evaluation apparatus of claim 7, wherein, The processing unit is further configured to check the azimuth angle and the downtilt angle of each second cell in the plurality of second cells when the third sampling point proportion is less than a third threshold value and the target distance is less than a fourth threshold value. The processing unit is further configured to enhance the signal strength of each second cell in the plurality of second cells when the third sampling point proportion is less than the third threshold value, the target distance is greater than or equal to the fourth threshold value, and the target traffic is greater than or equal to a fifth threshold value. The processing unit is further configured to increase the number of first terminal devices accessed by each second cell in the plurality of second cells when the third sampling point proportion is greater than or equal to the third threshold value, the target traffic is greater than or equal to a fifth threshold value, and the number of first terminal devices included in the plurality of first grids is less than a sixth threshold value, the first terminal device being a terminal device supporting access to the second network mode. The processing unit is further configured to increase the number of first terminal devices accessed by each second cell in the plurality of second cells when the third sampling point proportion is greater than or equal to the third threshold value and the number of second terminal devices included in the plurality of first grids is greater than or equal to a seventh threshold value.

13. An electronic device, comprising: The electronic device comprises: A processor and a memory; wherein the memory is configured to store one or more programs, the one or more programs comprising computer execution instructions, when the electronic device is running, the processor executes the computer execution instructions stored in the memory, so that the electronic device executes the method for geographic evaluation of mobile network 5G traffic shunt capability according to any one of claims 1-6.

14. A computer-readable storage medium storing one or more programs, the one or more programs comprising instructions for: The one or more programs comprise instructions which, when executed by a computer, cause the computer to perform the method for geographic evaluation of mobile network 5G traffic shunt capability according to any one of claims 1-6.

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