Frequency band allocation method, device, non-volatile storage medium and electronic device

Abstract

The present application discloses a frequency band allocation method, device, non-volatile storage medium and electronic device. The method includes: determining a first type of cell and a second type of cell in a target area, and determining that the frequency band allocated to the second type of cell is a preset frequency band, wherein the second type of cell is a cell covering a fast-moving scene, and the fast-moving scene includes at least one of the following: subway, highway, train; clustering the first type of cell, and determining multiple grids based on the clustering results; determining the first type of cell corresponding to the grid, and determining the corresponding frequency bands allocated to the first type of cell corresponding to the multiple grids based on the relative position relationship between the grids, wherein the frequency bands corresponding to the two grids with a common edge are different, and the frequency bands corresponding to the two grids with a common vertex but no common edge are the same. The present application solves the technical problems of poor network performance and poor user experience caused by the unreasonable frequency band allocation of existing mobile networks.

Description

Technical Field

[0001] The present application relates to the field of wireless communication and terminal technology, and in particular to a frequency band allocation method, device, non-volatile storage medium and electronic device. Background Art

[0002] When optimizing 4G, 5G, and even future xG mobile network performance, frequency band distribution analysis is a crucial yet often overlooked task for both newly planned and existing sites. This is especially true for communications companies operating in a shared infrastructure, multi-frequency coexistence model, and with limited investment, who want to benchmark their network performance against industry leaders. The ability to quickly analyze the rationality of frequency distribution and develop frequency optimization solutions with minimal adjustments and maximum benefits is crucial.

[0003] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0004] The embodiments of the present application provide a frequency band allocation method, apparatus, non-volatile storage medium, and electronic device to at least solve the technical problems of poor network performance and poor user experience caused by unreasonable frequency band allocation in existing mobile networks.

[0005] According to one aspect of an embodiment of the present application, a frequency band allocation method is provided, including: determining a first type of cell and a second type of cell in a target area, and determining that the frequency band allocated to the second type of cell is a preset frequency band, wherein the second type of cell is a cell covering a fast-moving scenario, and the fast-moving scenario includes at least one of the following: a subway, a highway, and a train; clustering the first type of cell, and determining a plurality of grids based on the clustering results; determining the first type of cell corresponding to the grid, and determining the corresponding frequency bands allocated to the first type of cells corresponding to the plurality of grids respectively based on the relative position relationship between the grids, wherein the frequency bands corresponding to two grids having a common edge are different, and the frequency bands corresponding to two grids having a common vertex but not a common edge are the same.

[0006] Optionally, clustering the first type of cells and determining multiple grids based on the clustering results includes: iteratively clustering the first type of cells, and after each iteration, determining the area to be processed based on the target cell set in the clustering results, wherein the area to be processed is a polygonal area constructed based on the cells included in the target cell set, and the target cell set is the cell set with the largest number of first type cells included in the clustering results; after obtaining the area to be processed each time, determining the rectangle to be processed based on the area to be processed, wherein the rectangle to be processed covers the area to be processed, and the rectangle to be processed is the rectangle with the smallest area among the rectangles covering the area to be processed; and rasterizing the rectangle to be processed to obtain multiple grids.

[0007] Optionally, performing iterative clustering processing on the first type of cells, and determining the area to be processed according to the clustering result after each iteration includes: a first step of determining an iteration termination condition, wherein the iteration termination condition includes at least one of the following: the number of iterations reaches a preset number of iterations, and the number of first type cells that are not assigned to the corresponding target cell set is less than a preset number; a second step of determining a set of cells to be clustered, wherein the set of cells to be clustered includes all first type cells that are not assigned to the corresponding target cell set; a third step of clustering the first type cells in the set of cells to be clustered to obtain a target cell set; a fourth step of determining whether the first type cells in the target cell set are clustered or not. The first distance between the cluster centers of the target cell set is determined, and a first preset number of first sample cells are determined and extracted from the target cell set based on the first distance; the fifth step is to determine the second distance between the first type of cells outside the target cell set and the cluster center, and determine a second preset number of second sample cells based on the second distance; the sixth step is to determine the target sample cell among the first sample cell and the second sample cell according to the preset screening condition, and add the target sample cell to the target cell set; the seventh step is to determine the area to be processed based on the target cell set; the eighth step is to determine whether the iteration termination condition is met, and if the iteration termination condition is not met, jump to the second step.

[0008] Optionally, determining a second preset number of second sample cells based on the first distance includes: sorting the first type of cells in the target cell set in order of distance from far to near according to the first distance, and determining the first preset number of first type of cells after sorting as the first sample cells; determining a second preset number of second sample cells based on the second distance includes: sorting the first type of cells outside the target cell set in order of distance from near to far according to the second distance, and determining the second preset number of first type of cells after sorting as the second sample cells.

[0009] Optionally, the preset screening conditions include at least one of the following: cell coverage type, cell site height, cell sector downtilt angle, cell direction angle, cell location, and the angle between the line between the cell and the cluster center and a preset baseline.

[0010] Optionally, rasterizing the rectangle to be processed to obtain multiple grids includes: determining whether there is an overlapping area in the rectangle to be processed obtained in this iteration that overlaps with the rectangle to be processed obtained in the previous iteration; deleting the overlapping area in the rectangle to be processed obtained in this iteration, and rasterizing the rectangle to be processed with the overlapping area deleted.

[0011] Optionally, determining the first-class cell corresponding to the grid includes: determining the distance between each first-class cell and the grid; confirming whether the location information of the first-class cell meets the preset conditions in order from near to far, and determining the first first-class cell that meets the preset conditions as the first-class cell corresponding to the grid, wherein the location information includes at least one of the following: the location coordinates of the first-class cell, the distance, the direction angle of the first-class cell, and the angle between the line between the first-class cell and the grid and the preset baseline.

[0012] According to another aspect of an embodiment of the present application, a frequency band allocation device is also provided, including: a first processing module, used to determine the first type of cell and the second type of cell in the target area, and determine that the frequency band allocated to the second type of cell is a preset frequency band, wherein the second type of cell is a cell covering a fast-moving scenario, and the fast-moving scenario includes at least one of the following: subway, highway, train; a second processing module, used to cluster the first type of cell, and determine multiple grids based on the clustering results; a third processing module, used to determine the first type of cell corresponding to the grid, and determine the corresponding frequency bands allocated to the first type of cells corresponding to the multiple grids based on the relative position relationship between the grids, wherein the frequency bands corresponding to two grids with a common edge are different, and the frequency bands corresponding to two grids with a common vertex but no common edge are the same.

[0013] According to another aspect of an embodiment of the present application, a non-volatile storage medium is provided, in which a program is stored. When the program is executed, a device where the non-volatile storage medium is located is controlled to execute a frequency band allocation method.

[0014] According to another aspect of an embodiment of the present application, an electronic device is provided, including: a memory and a processor, wherein the processor is configured to run a program stored in the memory, wherein the frequency band allocation method is executed when the program is run.

[0015] According to another aspect of an embodiment of the present application, a computer program product is provided, including a computer program, which implements the frequency band allocation method when executed by a processor.

[0016] In an embodiment of the present application, the first type of cells and the second type of cells in the target area are determined, and the frequency band allocated to the second type of cells is determined to be a preset frequency band, wherein the second type of cells are cells covering fast-moving scenarios, and the fast-moving scenarios include at least one of the following: subways, highways, and trains; the first type of cells are clustered, and multiple grids are determined based on the clustering results; the first type of cells corresponding to the grids are determined, and the corresponding frequency bands allocated to the first type of cells corresponding to the multiple grids are determined based on the relative position relationship between the grids, wherein the frequency bands corresponding to two grids with common edges are different, and the frequency bands corresponding to two grids with common vertices but no common edges are the same. Through data acquisition, data preprocessing, cell clustering and "two-color brick" mode planning of frequency band allocation, the purpose of accurate and efficient frequency band allocation is achieved, thereby achieving the technical effect of improving network quality and capacity, reducing switching delay, and improving user experience, thereby solving the technical problems of poor network performance and poor user experience caused by unreasonable frequency band allocation in existing mobile networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 is a structural diagram of a computer terminal provided according to an embodiment of the present application;

[0019] Figure 2 1 is a flow chart of a frequency band allocation method provided according to an embodiment of the present application;

[0020] Figure 3 This is an example diagram of a "two-color brick" provided according to an embodiment of the present application;

[0021] Figure 4 1 is a flow chart of a frequency band allocation method provided according to an embodiment of the present application;

[0022] Figure 5 This is a schematic diagram of a two-color brick planning effect provided according to an embodiment of the present application;

[0023] Figure 6 It is a structural diagram of a frequency band allocation device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] In order to better understand the embodiments of the present application, the technical terms involved in the embodiments of the present application are explained as follows:

[0027] 5G NR (5th Generation New Radio): An air interface technology for the fifth generation mobile communication network.

[0028] In related technologies, mobile network performance optimization typically focuses on RF (Radio Frequency) optimization, system parameter optimization, and terminal device upgrades. However, these technical solutions typically only address the symptoms and not the root cause, resulting in the following drawbacks:

[0029] RF Optimization Solution: After the network is put into production and operation, RF optimization is generally triggered by problem cells, complaints, etc., and is basically an on-site operation. The optimization scope and efficiency are very limited, and there is a high risk of solving problem A but causing problem B.

[0030] System parameter optimization: This solution primarily targets overall network performance, focusing on metrics such as system capacity, access success rate, and call drop rate. Network optimization system parameters often trade off against each other, such as capacity and coverage, and CQI (Channel Quality Indicator) quality and bit error rates. Consequently, extensive comparative analysis is often required, which is time-consuming and difficult to address in all scenarios.

[0031] The upgrading and replacement of terminal equipment requires a large amount of capital investment.

[0032] In order to solve the above problems, relevant solutions are provided in the embodiments of the present application, which are described in detail below.

[0033] According to an embodiment of the present application, a method embodiment of a frequency band allocation method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0034] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 FIG1 shows a hardware structure block diagram of a computer terminal (or mobile device) for implementing a frequency band allocation method. Figure 1 As shown, the computer terminal 10 (or mobile device 10) may include one or more (illustrated as 102a, 102b, ..., 102n) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0035] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry". The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuitry may be a single independent processing module, or may be incorporated in whole or in part into any of the other components of the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0036] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the frequency band allocation method in the embodiments of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby implementing the above-mentioned frequency band allocation method. The memory 104 may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely located relative to the processor 102, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0037] The transmission device 106 is configured to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by the communications provider of the computer terminal 10. In one embodiment, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission device 106 may be a radio frequency (RF) module, which is configured to communicate with the Internet wirelessly.

[0038] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 (or mobile device).

[0039] In the above operating environment, the embodiment of the present application provides a frequency band allocation method, such as Figure 2 As shown, the method includes the following steps:

[0040] Step S202: determining a first type of cell and a second type of cell in a target area, and determining that a frequency band allocated to the second type of cell is a preset frequency band, wherein the second type of cell is a cell covering a fast-moving scenario, and the fast-moving scenario includes at least one of the following: a subway, a highway, and a train;

[0041] Optionally, a distinction is made based on the coverage type of the cells in the target area to determine the first and second type cells in the target area. Both the first and second type cells are outdoor cells. Cells covering ordinary scenes are first type cells, and cells covering fast-moving scenes such as highways, high-speed railways, and subways are second type cells. The target area is the area with frequency bands to be allocated.

[0042] Optionally, before determining the first type of cells and the second type of cells in the target area, data acquisition and data preprocessing are further included:

[0043] (1) Data acquisition: Obtain basic engineering parameters (including latitude and longitude, azimuth, inclination, coverage type) and geospatial data layers for the area where network performance improvement is required.

[0044] (2) Data preprocessing: The recording dimension of longitude and latitude is the base station. Each base station contains an average of three cells. Therefore, the longitude and latitude of each cell need to be shifted by x meters along the azimuth direction (the default value x = 50, which can be adjusted appropriately according to the coverage scenario of the site).

[0045] Optionally, since the same-frequency coverage brings slower switching delay and better user experience in fast-moving scenarios, the F3 frequency band with higher signal purity is uniformly allocated to the cells covering the road surface. At the same time, through road testing, the cells with the top 3 signal strengths where the road surface and other low-speed areas intersect are determined and modified to the F2 frequency band.

[0046] Step S204: clustering the first type of cells, and determining a plurality of grids based on the clustering results;

[0047] Optionally, clustering the first type of cells includes initializing DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering algorithm parameters: eps uses an epsilon neighborhood radius mode, a minimum cluster size of 5, and an algorithm for calculating distances between points is a 'ball_tree' algorithm using a 'haversine' distance metric. Cluster analysis is performed on a set of geographic coordinates coords.

[0048] Optionally, clustering the first type of cells and determining multiple grids based on the clustering results includes: iteratively clustering the first type of cells, and after each iteration, determining the area to be processed based on the target cell set in the clustering results, wherein the area to be processed is a polygonal area constructed based on the cells included in the target cell set, and the target cell set is the cell set with the largest number of first type cells included in the clustering results; after obtaining the area to be processed each time, determining the rectangle to be processed based on the area to be processed, wherein the rectangle to be processed covers the area to be processed, and the rectangle to be processed is the rectangle with the smallest area among the rectangles covering the area to be processed; and rasterizing the rectangle to be processed to obtain multiple grids.

[0049] Optionally, a clustering algorithm is used to automatically find a cell set y1 (ie, a target cell set) with the highest degree of cell clustering.

[0050] Optionally, a polygon a (i.e., the area to be processed) is constructed based on the target cell set y1 in the clustering result and the number of cells N1 to construct a is determined. The polygon is used to construct a rectangle or square a (i.e., the rectangle to be processed) that best fits and completely contains the polygon, which is used as the core area a for frequency optimization first.

[0051] Optionally, performing iterative clustering processing on the first type of cells, and determining the area to be processed according to the clustering result after each iteration includes: a first step of determining an iteration termination condition, wherein the iteration termination condition includes at least one of the following: the number of iterations reaches a preset number of iterations, and the number of first type cells that are not assigned to the corresponding target cell set is less than a preset number; a second step of determining a set of cells to be clustered, wherein the set of cells to be clustered includes all first type cells that are not assigned to the corresponding target cell set; a third step of clustering the first type cells in the set of cells to be clustered to obtain a target cell set; a fourth step of determining whether the first type cells in the target cell set are clustered or not. The first distance between the cluster centers of the target cell set is determined, and a first preset number of first sample cells are determined and extracted from the target cell set based on the first distance; the fifth step is to determine the second distance between the first type of cells outside the target cell set and the cluster center, and determine a second preset number of second sample cells based on the second distance; the sixth step is to determine the target sample cell among the first sample cell and the second sample cell according to the preset screening condition, and add the target sample cell to the target cell set; the seventh step is to determine the area to be processed based on the target cell set; the eighth step is to determine whether the iteration termination condition is met, and if the iteration termination condition is not met, jump to the second step.

[0052] Optionally, determining a second preset number of second sample cells based on the first distance includes: sorting the first type of cells in the target cell set in order of distance from far to near according to the first distance, and determining the first preset number of first type of cells after sorting as the first sample cells; determining a second preset number of second sample cells based on the second distance includes: sorting the first type of cells outside the target cell set in order of distance from near to far according to the second distance, and determining the second preset number of first type of cells after sorting as the second sample cells.

[0053] Optionally, the preset screening conditions include at least one of the following: cell coverage type, cell site height, cell sector downtilt angle, cell direction angle, cell location, and the angle between the line between the cell and the cluster center and a preset baseline.

[0054] Optionally, rasterizing the rectangle to be processed to obtain multiple grids includes: determining whether there is an overlapping area in the rectangle to be processed obtained in this iteration that overlaps with the rectangle to be processed obtained in the previous iteration; deleting the overlapping area in the rectangle to be processed obtained in this iteration, and rasterizing the rectangle to be processed with the overlapping area deleted.

[0055] Optionally, clustering the first type of cells and determining a plurality of grids according to the clustering result includes:

[0056] 1) In the cell set y1 (i.e., the target cell set), select the 10% (i.e., a first preset number) of sample cells with the largest distance from the cluster center (i.e., the first distance) as the first sample cells. In the non-cell set y1, select the 10 sample cells with the smallest distance from the cluster center as the second sample cells. These cells are combined into the to-be-verified cell set y2.

[0057] 2) For the cells in the to-be-checked cell set y2, the following formula is used as a preset screening condition to determine whether to add them to the cell set y1:

[0058] is_label=f1(out_door)*0.1+f2(gnb_high)*0.3+f3(down_angle)*0.1+f4(angle_cell,cell_location,cluster_center_location)*0.5

[0059] If is_label>0, the cell is added to the cell set y1.

[0060] in:

[0061] out_door is the coverage type. If it is a macro site, the value is 1, otherwise it is 0.

[0062] gnb_high is the site height in meters.

[0063] down_angle is the sector downtilt angle, in degrees.

[0064] angle_cell is the cell direction angle, unit angle.

[0065] cell_location is the cell location.

[0066] cluster_center_location is the cluster center location.

[0067] The f1(out_door) function takes as input out_door and returns 1 if out_door is 1; if it is 0, it returns -10.

[0068] The function f2(gnb_high) takes gnb_high as input. If 10 < gnb_high < 60, it returns (gnb_high - 10) / 50.

[0069] The function f3(down_angle) takes down_angle as input. If 10 < down_angle < 60, it returns (gnb_high - 10) / 50; otherwise, it returns -10.

[0070] The function f4(angle_cell, cell_location, cluster_center_location) takes angle_cell, cell_location, and cluster_center_location as input. It calculates the angle angle_cell_cluster_center from the cell center to the cluster center using cell_location and cluster_center_location. If the absolute value angle_r of the angle between angle_cell and angle_cell_cluster_center is less than 60, it returns 1 - angle_r / 60; otherwise, it returns -10.

[0071] Construct polygon a based on the cell set y1 and the number of cells N1 that make up a. Use polygon a to construct the rectangle or square a that best fits and completely encloses the polygon as the core area a for frequency optimization first.

[0072] 3) Continue to run the clustering algorithm to cluster the area outside a again. Process the clustering results according to the scheme in 2). Construct polygon b_i and the number of cells N2 that make up b_i. Use b_i to construct the rectangle or square b1_i that best fits and completely encloses the polygon. If b1_i overlaps with a, delete the overlapping area in b1_i to form multiple non-core areas b2_i.

[0073] 4) Continue to run the clustering algorithm to cluster the area outside a and b_i again. Process the clustering results according to the scheme in 2). Construct polygon c_i and the number of cells N3 that make up c_i. Use c_i to construct the rectangle or square c1_i that best fits and completely encloses the polygon. If c1_i overlaps with a or b2_i, delete the overlapping area in c1_i to form multiple non-core areas c2_i.

[0074] 5) Perform rasterization on the generated polygons above: Calculate the square grids that can be divided for the areas corresponding to a, b2_i, and c2_i respectively according to area / corresponding number of cells.

[0075] 6) The grid in 5) is processed in a "two-color brick" mode: The grid in the core area a is processed in a two-color brick mode, and the issues and priority conditions that need to be considered during processing are: 1) At the same site, or the number of cells is greater than or equal to 3, there must be different frequencies; 2) Adjacent grids use different frequency bands, and diagonal grids use the same frequency band.

[0076] Optionally, Figure 3 An example diagram of a "two-color brick" is shown, Figure 3 As shown, "two-color bricks" refers to a frequency coverage scheme where adjacent grids have different frequencies and diagonal grids have the same frequency. The same color represents the same frequency band. As an optional segmentation, the frequency band can be divided into:

[0077] F1 frequency band: refers to the frequency range of 3300MHz to 3400MHz.

[0078] F2 frequency band: refers to the frequency range of 3400MHz to 3500MHz.

[0079] F3 frequency band: refers to the frequency range of 3500MHz to 3600MHz.

[0080] Among them, the F1 frequency band is dedicated to indoor cells, and the F2 and F3 frequency bands are dedicated to outdoor cells. The frequency bands mentioned in the method embodiments of the present application all use the F2 and F3 frequency bands.

[0081] As an optional implementation manner, allocation is performed based on the ratio of the number of dual-color grids and the ratio of cells in the F2 and F3 frequency bands, so that F2:F3=1:1.

[0082] Step S206, determine the first type of cell corresponding to the grid, and determine the corresponding frequency bands allocated to the first type of cells corresponding to multiple grids respectively based on the relative position relationship between the grids, wherein the frequency bands corresponding to two grids with a common edge are different, and the frequency bands corresponding to two grids with a common vertex but no common edge are the same.

[0083] Optionally, determining the first-class cell corresponding to the grid includes: determining the distance between each first-class cell and the grid; confirming whether the location information of the first-class cell meets the preset conditions in order from near to far, and determining the first first-class cell that meets the preset conditions as the first-class cell corresponding to the grid, wherein the location information includes at least one of the following: the location coordinates of the first-class cell, the distance, the direction angle of the first-class cell, and the angle between the line between the first-class cell and the grid and the preset baseline.

[0084] Optionally, determining the first type of cell corresponding to the grid includes:

[0085] Find the grid a_i where the center point of a is located and perform the following operations:

[0086] 1) Get the cell closest to a_i and check whether the following conditions (i.e., preset conditions) are met:

[0087] is_cover=f5(d_sort)*0.6+f6(angle_cell,cell_location,a_i_location)*0.4. If is_cover>0, the cell is regarded as the cell covering the grid. Otherwise, find the cell at the next level distance and repeat this step within the range of d_sort<2000 until a cell meeting the conditions is found. If no cell meets the conditions, the cell with the smallest d_sort is used as the covering cell.

[0088] in:

[0089] d_sort is the distance between the cell and a_i, in meters.

[0090] angle_cell is the cell direction angle, unit angle.

[0091] cell_location is the cell location.

[0092] a_i_location is the location of a_i.

[0093] f5(d_sort) takes input d_sort. If d_sort < 2000, it returns d_sort / 2000; otherwise, it returns -10.

[0094] f6(angle_cell,cell_location,a_i_location) takes angle_cell,cell_location,a_i_location as input and calculates the angle angle_cell_a_i with the cell as the center and the point a_i as the center. If the absolute value of the angle between angle_cell and a_i_location, angle_r, is less than 60, the function returns 1-angle_r / 60; otherwise, it returns -10.

[0095] 2) Starting from the center grid and spreading outward, the cells closest to the center of the grid are selected as coverage cells until all cells are filled into the grid.

[0096] Optionally, determining corresponding frequency bands allocated to first-category cells corresponding to a plurality of grids respectively according to the relative position relationship between the grids includes:

[0097] i. Perform two-color brick processing on the grids in core area a. Issues and priority conditions to be considered during processing: 1) For the same site, or if the number of cells is greater than or equal to 3, there must be different frequencies; 2) Adjacent grids use different frequencies, and diagonal grids use the same frequency.

[0098] ii. For non-core areas such as b2_i, two-color tiles are used. When planning the grid for b2_i, first obtain the frequency results of the five nearest planned cells from a. Then, plan the first grid for b2_i based on the principle of F2:F3 being as close to 1:1 as possible. It is important to note that the planning of each subsequent grid considers all five nearest planned grids and is performed according to the condition principle.

[0099] Optionally, the method embodiments of the present application support application in any scenario where multiple frequency points are used for mobile network coverage.

[0100] The present application embodiment provides a frequency band allocation method, such as Figure 4 As shown, the method includes the following steps:

[0101] (1) Import of basic data (engineering parameters and maps): Obtain basic engineering parameters (including latitude and longitude, direction angle, inclination, coverage type) and geospatial data layers of the area where network performance improvement is required.

[0102] Optionally, based on the area where network performance optimization is required (contiguous optimization is recommended), obtain cell engineering parameters, especially the cell latitude and longitude, (current) frequency, Azimuth (azimuth), and coverage type. The following table shows some cell engineering parameters for the area to be optimized:

[0103]

[0104] (2) Data preprocessing: The longitude and latitude of each cell are shifted by x meters along the azimuth direction (the default value x = 50, which can be adjusted appropriately according to the coverage scenario of the site).

[0105] Optionally, the outdoor cell is moved 50m in the original longitude and latitude according to the azimuth direction. The following table shows some pre-processed cell parameters for the area to be optimized:

[0106]

[0107] It should be noted that the reason for migrating the cell coverage direction by 50 meters is that: there are 3 cells in 1 base station, and the center point is not easy to fit into the small grid (that is, it is not easy to draw lines to distribute the grid). If it is migrated 50 meters in the azimuth direction (the specific value can be customized), the longitude and latitude of the center point of the cell will be inconsistent. You can simply follow the idea of ​​two-color bricks and put each cell into a grid.

[0108] (3.1) Using a clustering algorithm, automatically find the polygon a with the highest degree of cell clustering and the number of cells N1 that construct a. Use the polygon to construct a rectangle or square a that best fits and completely contains the polygon, which serves as the core area a for frequency optimization first.

[0109] Optionally,

[0110] (3.2) Continue running the clustering algorithm and cluster the area outside of a again. Use the clustering results to construct polygon b_i and the number of cells N2 that construct b_i. Use b_i to construct the rectangle or square b1_i that best fits and completely contains the polygon. If b1_i overlaps with a, delete the overlapping area in b1_i to form multiple non-core areas b2_i.

[0111] (3.3) Continue running the clustering algorithm and cluster the areas outside a and b_i again. Use the clustering results to construct polygon c_i and the number of cells N3 that construct c_i. Use c_i to construct the rectangle or square c1_i that best fits and completely contains the polygon. If c1_i overlaps with a or b2_i, delete the overlapping area in c1_i to form multiple non-core areas c2_i.

[0112] (4) Calculate the divisible square grids for the areas corresponding to a, b2_i, and c2_i according to the area / number of corresponding cells.

[0113] (5) Perform two-color brick processing on the grid of core area a. Issues and priority conditions to be considered during processing:

[0114] (5.1) If the number of cells is greater than or equal to 3, there must be different frequencies.

[0115] (5.2) Adjacent grids use different frequencies, while diagonal grids use the same frequency.

[0116] (5.3) Try to allocate according to the ratio of the number of two-color grids and the ratio of F2 and F3 frequency cells.

[0117] Optionally, clustering can be achieved using a clustering algorithm with the following initialization parameters: eps uses an epsilon neighborhood radius mode, a minimum cluster size of 5, and the algorithm for calculating distances between points is the 'ball_tree' algorithm using the 'haversine' distance metric. After clustering, the core area is automatically obtained as the starting area for the "two-color brick" frequency optimization:

[0118] Figure 5 A two-color brick design effect diagram is shown, such as Figure 5As shown, the polygon is rasterized according to the number of cells within the polygon range, and the "two-color brick" mode is used. At the same time, the condition is taken into consideration to achieve mobile network frequency optimization. The smaller the station distance, the smaller the grid, and vice versa.

[0119] (6) Find the grid a_i where the center point of a is located, and obtain the cell closest to a_i as the cell covering the grid.

[0120] (7) Starting from the center grid and spreading outward, the cells closest to the center of the grid are selected as the cells to be covered until all cells are filled into the grid.

[0121] (8) For the non-core area b2_i, two-color brick processing is performed. When planning the grid of b2_i:

[0122] (8.1) Obtain the frequency results of the five most recent cells after planning from a, and then plan the first grid of b2_i based on the principle that F2:F3 is as close to 1:1 as possible.

[0123] (8.2) The planning of each subsequent grid takes into account all the planned and nearest 5 grids and is planned according to the condition principle.

[0124] (9) The non-core area c2_i is treated with two-color bricks, and the planning principle is the same as b2_i, until the entire community in the area to be planned is re-planned.

[0125] Optionally, the method embodiment of the present application supports the combination of python+streamlit or other software and tool methods to realize the functions of geographical presentation of planning effects+planning result data export, so as to further improve the optimization efficiency.

[0126] Optionally, after the frequency band is allocated, compared with before the frequency band allocation, the perception indicators such as rate, bit error, delay, and packet loss are greatly improved, and the overall network capacity is significantly improved by nearly 20%. In addition, the core DPI and KPI (average traffic growth rate per cell, CQI quality rate, downlink rate, uplink bit error rate, downlink bit error rate, etc.) have all improved significantly, far exceeding other cities where the frequency band has not been reallocated. The following table shows the comparison of the DPI indicators of City 0 where the frequency band has been allocated and other cities:

[0127]

[0128] Through the above steps, it is possible to implement inter-frequency re-planning based only on engineering parameters, and combined with clustering algorithms, rasterization processing and other technologies, the accuracy and efficiency of inter-frequency re-planning are improved, and the network performance and capacity are truly and effectively improved. The method embodiment of the present application provides a mobile network frequency optimization process based on the "two-color brick" mode, which can effectively improve network quality and capacity. The method embodiment of the present application is aimed at outdoor cells, and is differentiated according to the coverage type. The "two-color brick" mode is used to optimize the frequency of cells in ordinary coverage scenarios, and the F3 frequency point is uniformly used for cells in fast-moving scenarios such as highways, high-speed railways, and subways. Clustering algorithms, rasterization processing and other technologies are used to improve the accuracy and efficiency of frequency optimization. Specifically, the method embodiment of the present application has the following advantages:

[0129] (1) The 3.3 frequency band is first used indoors. In conventional outdoor scenarios, 3.4 and 3.5 frequency bands are planned according to the "two-color brick" model for different frequency coverage. Separate frequency plans are set for fast-moving scenarios such as high-speed railways and main roads. Combined with reasonable network optimization parameters, this effectively improves network performance and capacity, and truly enhances the actual user experience.

[0130] (2) Based on the clustering algorithm, polygon construction, grading of core and non-core areas, and polygon rasterization are realized. Combined with the outward migration of the original azimuth direction of the cell's longitude and latitude, the full-area automated "two-color brick" mode planning can be quickly realized through coding, greatly improving the optimization efficiency.

[0131] (3) There is no need to purchase additional software and hardware. Only basic cell parameters are required. By combining the solution of the present invention and using a tool approach, the effect of zero cost increase and rapid output can be achieved.

[0132] The embodiment of the present application provides a frequency band allocation device, Figure 6 is a structural diagram of the device, such as Figure 6 As shown, the device includes: a first processing module 60, used to determine the first type of cell and the second type of cell in the target area, and determine that the frequency band allocated to the second type of cell is a preset frequency band, wherein the second type of cell is a cell covering a fast-moving scene, and the fast-moving scene includes at least one of the following: subway, highway, train; a second processing module 62, used to cluster the first type of cell, and determine a plurality of grids based on the clustering results; a third processing module 64, used to determine the first type of cell corresponding to the grid, and determine the corresponding frequency bands allocated to the first type of cells corresponding to the plurality of grids respectively based on the relative position relationship between the grids, wherein the frequency bands corresponding to two grids having a common edge are different, and the frequency bands corresponding to two grids having a common vertex but not a common edge are the same.

[0133] In some embodiments of the present application, the second processing module 62 performs clustering processing on the first type of cells and determines multiple grids based on the clustering results, including: iteratively clustering the first type of cells, and after each iteration, determining the area to be processed based on the target cell set in the clustering results, wherein the area to be processed is a polygonal area constructed based on the cells included in the target cell set, and the target cell set is the cell set with the largest number of first type cells included in the clustering results; after obtaining the area to be processed each time, determining the rectangle to be processed based on the area to be processed, wherein the rectangle to be processed covers the area to be processed, and the rectangle to be processed is the rectangle with the smallest area among the rectangles covering the area to be processed; and rasterizing the rectangle to be processed to obtain multiple grids.

[0134] In some embodiments of the present application, the second processing module 62 performs iterative clustering processing on the first type of cells, and after each iteration, determines the area to be processed according to the clustering result, including: a first step, determining an iteration termination condition, wherein the iteration termination condition includes at least one of the following: the number of iterations reaches a preset number of iterations, and the number of first type cells that are not assigned to the corresponding target cell set is less than a preset number; a second step, determining a set of cells to be clustered, wherein the set of cells to be clustered includes all first type cells that are not assigned to the corresponding target cell set; a third step, clustering the first type cells in the set of cells to be clustered to obtain a target cell set; a fourth step, determining the target cell set. In the fifth step, a first distance between the first type of cell in the target cell set and the cluster center of the target cell set is determined, and a first preset number of first sample cells are determined and extracted from the target cell set according to the first distance; in the fifth step, a second distance between the first type of cell outside the target cell set and the cluster center is determined, and a second preset number of second sample cells are determined according to the second distance; in the sixth step, a target sample cell is determined from the first sample cell and the second sample cell according to the preset screening condition, and the target sample cell is added to the target cell set; in the seventh step, an area to be processed is determined according to the target cell set; in the eighth step, whether an iteration termination condition is met, and if the iteration termination condition is not met, jumping to the second step.

[0135] In some embodiments of the present application, the second processing module 62 determines the second preset number of second sample cells based on the first distance, including: sorting the first type of cells in the target cell set in order of distance from far to near according to the first distance, and determining the first preset number of first type of cells after sorting as the first sample cells; determining the second preset number of second sample cells based on the second distance includes: sorting the first type of cells outside the target cell set in order of distance from near to far according to the second distance, and determining the first second preset number of first type cells after sorting as the second sample cells.

[0136] In some embodiments of the present application, the preset screening conditions include at least one of the following: cell coverage type, cell site height, cell sector downtilt angle, cell direction angle, cell location, and the angle between the line between the cell and the cluster center and the preset baseline.

[0137] In some embodiments of the present application, the second processing module 62 performs rasterization processing on the rectangle to be processed to obtain multiple grids, including: determining whether there is an overlapping area in the rectangle to be processed obtained in this iteration that overlaps with the rectangle to be processed obtained in the previous iteration; deleting the overlapping area in the rectangle to be processed obtained in this iteration, and rasterizing the rectangle to be processed with the overlapping area deleted.

[0138] In some embodiments of the present application, the third processing module 64 determines the first-class cell corresponding to the grid, including: determining the distance between each first-class cell and the grid; confirming whether the location information of the first-class cell meets the preset conditions in order from near to far, and determining the first first-class cell that meets the preset conditions as the first-class cell corresponding to the grid, wherein the location information includes at least one of the following: the location coordinates of the first-class cell, the distance, the direction angle of the first-class cell, and the angle between the line between the first-class cell and the grid and the preset baseline.

[0139] It should be noted that the various modules in the above-mentioned frequency band allocation device can be program modules (for example, a set of program instructions that implement a certain specific function) or hardware modules. For the latter, it can be expressed in the following forms, but is not limited to this: the expression form of each of the above-mentioned modules is a processor, or the functions of each of the above-mentioned modules are implemented by a processor.

[0140] An embodiment of the present application provides a non-volatile storage medium, in which a program is stored, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute the following frequency band allocation method: determining first-class cells and second-class cells in a target area, and determining that the frequency band allocated to the second-class cells is a preset frequency band, wherein the second-class cells are cells covering fast-moving scenarios, and the fast-moving scenarios include at least one of the following: subways, highways, and trains; clustering the first-class cells, and determining multiple grids based on the clustering results; determining the first-class cells corresponding to the grids, and determining the corresponding frequency bands allocated to the first-class cells corresponding to the multiple grids based on the relative position relationship between the grids, wherein the frequency bands corresponding to two grids with a common edge are different, and the frequency bands corresponding to two grids with a common vertex but no common edge are the same.

[0141] An embodiment of the present application provides an electronic device, comprising: a memory and a processor, the processor being configured to run a program stored in the memory, wherein the following frequency band allocation method is executed when the program is run: determining a first-class cell and a second-class cell in a target area, and determining that the frequency band allocated to the second-class cell is a preset frequency band, wherein the second-class cell is a cell covering a fast-moving scenario, and the fast-moving scenario includes at least one of the following: a subway, a highway, and a train; clustering the first-class cell, and determining a plurality of grids based on the clustering results; determining the first-class cell corresponding to the grid, and determining the corresponding frequency bands allocated to the first-class cells corresponding to the plurality of grids based on the relative positional relationship between the grids, wherein the frequency bands corresponding to two grids having a common edge are different, and the frequency bands corresponding to two grids having a common vertex but not a common edge are the same.

[0142] An embodiment of the present application provides a computer program product, including a computer program, which implements the following frequency band allocation method when executed by a processor: determining first-class cells and second-class cells in a target area, and determining that the frequency band allocated to the second-class cells is a preset frequency band, wherein the second-class cells are cells covering fast-moving scenarios, and the fast-moving scenarios include at least one of the following: subways, highways, and trains; clustering the first-class cells, and determining multiple grids based on the clustering results; determining the first-class cells corresponding to the grids, and determining the corresponding frequency bands allocated to the first-class cells corresponding to the multiple grids based on the relative position relationship between the grids, wherein the frequency bands corresponding to two grids with a common edge are different, and the frequency bands corresponding to two grids with a common vertex but no common edge are the same.

[0143] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0144] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0145] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0146] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0147] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the relevant technology or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0148] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A frequency band allocation method, characterized in that: include: Determining a first type of cell and a second type of cell in a target area, and determining that a frequency band allocated to the second type of cell is a preset frequency band, wherein the second type of cell is a cell covering a fast-moving scenario, and the fast-moving scenario includes at least one of the following: a subway, a highway, and a train; performing clustering processing on the first type of cells, and determining a plurality of grids according to the clustering results; Determine the first type of cell corresponding to the grid, and determine the corresponding frequency bands allocated to the first type of cells corresponding to the multiple grids respectively based on the relative position relationship between the grids, wherein the frequency bands corresponding to two grids with a common edge are different, and the frequency bands corresponding to two grids with a common vertex but no common edge are the same.

2. The frequency band allocation method according to claim 1, wherein: Clustering is performed on the first type of cells, and a plurality of grids are determined according to the clustering results, including: performing iterative clustering processing on the first type of cells, and after each iteration, determining a to-be-processed area based on a target cell set in the clustering result, wherein the to-be-processed area is a polygonal area constructed based on the cells included in the target cell set, and the target cell set is a cell set with the largest number of the first type of cells included in the clustering result; After obtaining the area to be processed each time, determining a rectangle to be processed according to the area to be processed, wherein the rectangle to be processed covers the area to be processed and is the rectangle with the smallest area among the rectangles covering the area to be processed; The rectangle to be processed is rasterized to obtain the multiple grids.

3. The frequency band allocation method according to claim 2, wherein: Perform iterative clustering processing on the first type of cells, and after each iteration, determine, based on the clustering results, that the area to be processed includes: The first step is to determine an iteration termination condition, wherein the iteration termination condition includes at least one of the following: the number of iterations reaches a preset number of iterations, and the number of the first type of cells that are not allocated to the corresponding target cell set is less than a preset number; The second step is to determine a set of cells to be clustered, wherein the set of cells to be clustered includes all cells of the first type that are not allocated to the corresponding target cell set; Step 3: clustering the first type of cells in the set of cells to be clustered to obtain the target cell set; The fourth step is to determine a first distance between the first type of cells in the target cell set and the cluster center of the target cell set, and determine and extract a first preset number of first sample cells from the target cell set based on the first distance; Step 5: determining a second distance between the first type of cells outside the target cell set and the cluster center, and determining a second preset number of second sample cells based on the second distance; Step 6: determining a target sample cell from the first sample cell and the second sample cell according to a preset screening condition, and adding the target sample cell to the target cell set; Step 7: determining the area to be processed based on the target cell set; In the eighth step, it is determined whether the iteration termination condition is satisfied, and if the iteration termination condition is not satisfied, the process jumps to the second step.

4. The frequency band allocation method according to claim 3, wherein: Determining a second preset number of second sample cells according to the first distance includes: sorting the first-category cells in the target cell set in descending order of distance according to the first distance, and determining the first preset number of the first-category cells after sorting as the first sample cells; Determining a second preset number of second sample cells according to the second distance includes: The first-category cells outside the target cell set are sorted in order of distance from near to far according to the second distance, and the second preset number of first-category cells after sorting are determined as the second sample cells.

5. The frequency band allocation method according to claim 3, wherein: The preset screening conditions include at least one of the following: cell coverage type, cell site height, cell sector downtilt angle, cell direction angle, cell location, and the angle between the line between the cell and the cluster center and a preset baseline.

6. The frequency band allocation method according to claim 2, wherein: The rectangle to be processed is subjected to rasterization processing to obtain the plurality of grids including: Determine whether the rectangle to be processed obtained in this iteration has an overlapping area with the rectangle to be processed obtained in the previous iteration; The overlapping area is deleted from the rectangle to be processed obtained in this iteration, and rasterization is performed on the rectangle to be processed after the overlapping area is deleted.

7. The frequency band allocation method according to claim 1, wherein: Determining the first type of cell corresponding to the grid includes: determining a distance between each of the first-type cells and the grid; Confirm whether the location information of the first-type cell meets the preset conditions in order from near to far of the distance, and determine that the first first-type cell that meets the preset conditions is the first-type cell corresponding to the grid, wherein the location information includes at least one of the following: the location coordinates of the first-type cell, the distance, the direction angle of the first-type cell, and the angle between the line between the first-type cell and the grid and a preset baseline.

8. A frequency band allocation device, characterized in that: include: a first processing module, configured to determine a first type of cell and a second type of cell in a target area, and determine that a frequency band allocated to the second type of cell is a preset frequency band, wherein the second type of cell is a cell covering a fast-moving scenario, and the fast-moving scenario includes at least one of the following: a subway, a highway, and a train; a second processing module, configured to perform clustering processing on the first type of cells and determine a plurality of grids according to the clustering result; The third processing module is used to determine the first type of cell corresponding to the grid, and determine the corresponding frequency bands allocated to the first type of cells corresponding to the multiple grids respectively based on the relative position relationship between the grids, wherein the frequency bands corresponding to two grids with a common edge are different, and the frequency bands corresponding to two grids with a common vertex but no common edge are the same.

9. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a program, wherein when the program is running, the device where the non-volatile storage medium is located is controlled to execute the frequency band allocation method according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: A memory and a processor, wherein the processor is configured to run a program stored in the memory, wherein the frequency band allocation method according to any one of claims 1 to 7 is executed when the program is run.

11. A computer program product, characterized in that The method comprises a computer program, which implements the frequency band allocation method according to any one of claims 1 to 7 when executed by a processor.

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