Frequency band allocation method and device, nonvolatile storage medium and electronic equipment

Abstract

The invention discloses a frequency band allocation method and device, a nonvolatile storage medium and electronic equipment. The method comprises the steps that a first type of cells and a second type of cells in a target area are determined, a frequency band allocated to the second type of cells is determined to be a preset frequency band, the second type of cells are cells covering a fast moving scene, and the fast moving scene comprises at least one of a subway, an expressway and a train; performing clustering processing on the first type of cells, and determining a plurality of grids according to a clustering result; and determining a first type of cells corresponding to the grids, and determining corresponding frequency bands allocated to the first type of cells corresponding to the plurality of grids according to the relative position relationship between the grids, the frequency bands corresponding to the two grids having the common edge being different, and the frequency bands corresponding to the two grids having the common vertex but not having the common edge being the same. According to the invention, the technical problems of low network performance and poor user experience caused by unreasonable frequency band allocation of the existing mobile network are solved.

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] In the optimization of 4G or 5G, or even future xG mobile network performance, network frequency band distribution analysis is a very important task for newly planned sites or existing sites, but it is often easily overlooked. In particular, for communications companies that are in the process of co-construction and sharing, multi-frequency coexistence, and have limited investment but want to benchmark network performance against industry leaders, it is crucial to be able to quickly analyze whether the frequency distribution is reasonable and provide a frequency optimization solution with minimal adjustment and maximum benefit.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present application provide a frequency band allocation method, device, 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 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 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 a to-be-processed area based on a target cell set in the clustering results, wherein the to-be-processed area is a polygonal area constructed based on cells included in the target cell set, and the target cell set is a cell set with the largest number of first type cells included in the clustering results; after obtaining the to-be-processed area each time, determining a to-be-processed rectangle based on the to-be-processed area, wherein the to-be-processed rectangle covers the to-be-processed area, and the to-be-processed rectangle is the rectangle with the smallest area among the rectangles covering the to-be-processed area; and rasterizing the to-be-processed rectangle to obtain multiple grids.

[0007] Optionally, performing iterative clustering processing on the first type of cells, and after each iteration, determining the area to be processed according to the clustering result includes: 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 the first type of cells that are not allocated 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 the first type of cells that are not allocated to the corresponding target cell set; a third step, performing clustering processing on the first type of cells in the set of cells to be clustered to obtain a target cell set; a fourth step, determining whether the first type of 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 according to 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 according to 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 according to 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 according to 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 the sorting as the first sample cells; determining the second preset number of second sample cells according to 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 of cells after the 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 an angle between a 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 cells meets preset conditions in order of distance 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 a 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 scene, and the fast-moving scene includes at least one of the following: subway, highway, train; a second processing module, used to cluster the first type of cell, and determine a plurality of 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 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.

[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, wherein when the program is running, 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, there is further provided an electronic device, 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, and when the computer program is executed by a processor, the frequency band allocation method is implemented.

[0016] In an embodiment of the present application, a first type of cell and a second type of cell in a target area are determined, and a frequency band allocated to the second type of cell is determined to be 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; the first type of cell is clustered, and a plurality of grids are determined based on the clustering results; the first type of cell corresponding to the grid is determined, and the corresponding frequency bands allocated to the first type of cells corresponding to the plurality of grids are determined based on the relative position relationship between the grids, wherein two grids having a common edge have different corresponding frequency bands, and two grids having a common vertex but not a common edge have the same corresponding frequency bands, and through data acquisition, data preprocessing, cell clustering, and "two-color brick" mode planning frequency band allocation, the purpose of accurately and efficiently allocating frequency bands 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 of 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 schematic diagram of a computer terminal provided according to an embodiment of the present application;

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

[0022] Figure 5 It 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 schematic 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 solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present 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 sequence. 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 an order 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 used in the fifth generation mobile communication network.

[0028] In related technologies, optimization of mobile network performance usually starts from RF (Radio Frequency) optimization, system parameter optimization, and terminal equipment upgrade. However, such technical solutions are usually only temporary solutions and do not address the root cause. They have the following disadvantages:

[0029] RF optimization solution: After the network is put into production operation, RF optimization is basically triggered by problem cells, complaints, etc., and is basically an on-site operation. The optimization field of view and efficiency are very limited, and there is a high probability that the risk of solving problem A will cause problem B.

[0030] System parameter optimization plan: mainly for the overall network performance, focusing on indicators such as system capacity, access success rate, call drop rate, etc. And the system parameters of network optimization often have checks and balances with each other, such as capacity and coverage, CQI (Channel Quality Indicator) rate and bit error rate, etc. Therefore, a lot of comparative analysis is often required, which is time-consuming and difficult to take into account user needs in different scenarios.

[0031] The upgrading 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 FIG. 1 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 (102a, 102b, ..., 102n are used to illustrate) 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 can 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 as shown, or with Figure 1 Different configurations are 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 circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuit acts 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 embodiment 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, that is, the above-mentioned frequency band allocation method is realized. 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 arranged 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 a combination thereof.

[0037] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used 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 comprises 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 scene, and the fast moving scene 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. The cells covering ordinary scenes are the first type cells, and the cells covering fast-moving scenes such as highways, high-speed railways, and subways are the second type cells. The target area is the area with the frequency band 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 also included:

[0043] (1) Data acquisition: Obtain basic engineering parameters (including longitude and latitude, 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 migrated 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, the cells with the top 3 signal strengths at the intersection of the covered road surface and other low-speed areas are determined through road testing and modified to the F2 frequency band.

[0046] Step S204, clustering the first type of cells, and determining a plurality of grids according to 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 the distance 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 a to-be-processed area based on a target cell set in the clustering results, wherein the to-be-processed area is a polygonal area constructed based on cells included in the target cell set, and the target cell set is a cell set with the largest number of first type cells included in the clustering results; after obtaining the to-be-processed area each time, determining a to-be-processed rectangle based on the to-be-processed area, wherein the to-be-processed rectangle covers the to-be-processed area, and the to-be-processed rectangle is the rectangle with the smallest area among the rectangles covering the to-be-processed area; and rasterizing the to-be-processed rectangle 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 according to 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 as the core area a for frequency optimization first.

[0051] Optionally, performing iterative clustering processing on the first type of cells, and after each iteration, determining the area to be processed according to the clustering result includes: 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 the first type of cells that are not allocated 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 the first type of cells that are not allocated to the corresponding target cell set; a third step, performing clustering processing on the first type of cells in the set of cells to be clustered to obtain a target cell set; a fourth step, determining whether the first type of 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 according to 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 according to 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 according to 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 according to 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 the sorting as the first sample cells; determining the second preset number of second sample cells according to 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 of cells after the 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 an angle between a 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 is performed on the first type of cells, and a plurality of grids are determined according to the clustering result, including:

[0056] 1) In the cell set y1 (i.e., the target cell set), select the 10% (i.e., the 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 sample cells of the 10 cells with the smallest distance from the cluster center as the second sample cells. The above cells are combined into the cell set y2 to be checked.

[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, and returns -10 if out_door is 0.

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

[0069] The function f3(down_angle) takes down_angle as the 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 the input. It calculates the angle angle_cell_cluster_center from the cell center to the cluster center through 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 the polygon to construct the rectangle or square a that best fits and completely contains the polygon as the core area a for the first frequency optimization.

[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 contains 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 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.

[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 the area / corresponding number of cells.

[0075] 6) The grid in 5) is processed in "two-color brick" mode: The grid in the core area a is processed in two-color brick mode, and the issues and priority conditions to be considered during processing are: 1) At the same site, or the number of cells is >= 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~3500MHz.

[0079] F3 frequency band: refers to the frequency range of 3500MHz~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, allocation is performed according to 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 cells meets preset conditions in order of distance 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 a 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 that meets 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) is the 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 inputs. It calculates the angle angle_cell_a_i pointing to a_i with the cell as the center through cell_location and a_i_location. If the absolute value of the angle between angle_cell and a_i_location angle_r is less than 60, it returns 1-angle_r / 60, otherwise it returns -10.

[0095] 2) Starting from the central 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-type cells corresponding to a plurality of grids respectively according to the relative position relationship between the grids includes:

[0097] i. The grids in the core area a are processed with two-color bricks, and the issues and priority conditions that need to be considered during the 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 frequencies, and diagonal grids use the same frequency.

[0098] ii. For non-core areas such as b2_i, two-color brick processing is performed. When planning the grid of b2_i: first obtain the frequency point results of the nearest 5 cells after planning from a, and then plan the first grid of b2_i according to the principle of F2:F3=1:1 as much as possible. It should be noted that the planning of each subsequent grid takes into account all the planned and nearest 5 grids and is planned according to the principle of condition.

[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 comprises the following steps:

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

[0102] Optionally, according to the area where network performance optimization is required (contiguous optimization is recommended), obtain the cell engineering parameters, especially the cell latitude and longitude, (current) frequency, Azimuth (azimuth), and coverage type. The following table shows some cell engineering parameters in 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 why the cell coverage direction is moved 50 meters is because: 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 moved 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 put each cell into a grid according to the idea of ​​two-color bricks.

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

[0109] Optionally,

[0110] (3.2) Continue to run the clustering algorithm, cluster the area outside a again, use the clustering results to construct the polygon b_i and the number of cells N2 that construct b_i, use b_i to construct the most fitting and complete rectangle or square b1_i, 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 to run the clustering algorithm, cluster the areas outside a and b_i again, use the clustering results to construct polygon c_i and the number of cells N3 to construct c_i, use c_i to construct the most fitting rectangle or square c1_i that 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 / corresponding number of cells.

[0113] (5) The grid in the core area a is processed with two-color bricks. Issues and priority conditions to be considered during the processing:

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

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

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

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

[0118] Figure 5 A two-color brick planning effect diagram is shown, such as Figure 5As shown, the polygon is rasterized according to the number of cells within the polygon, and the "two-color brick" mode is adopted while considering the condition to achieve mobile network frequency optimization. The smaller the station spacing, 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 central 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 nearest cells after planning from a, and then plan the first grid of b2_i according to 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 plans 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 functions such as geographical presentation of planning effects + export of planning result data, so as to further improve the optimization efficiency.

[0126] Optionally, after the frequency band is allocated, the rate, bit error, delay, packet loss and other perception indicators are greatly improved compared to before the frequency band is allocated, 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.) are all significantly improved, far exceeding other cities that have not reallocated frequency bands. The following table shows the comparison of DPI indicators between city 0 where frequency bands have 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. The 3.4 and 3.5 frequency bands are planned according to the "two-color brick" model for outdoor coverage in common scenarios. Separate frequency plans are set for fast-moving scenarios such as high-speed railways and trunk roads. Combined with reasonable network optimization parameters, this effectively improves network performance and capacity, and truly enhances the actual perceived experience of users.

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

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

[0132] The present application embodiment provides a frequency band allocation device, Figure 6 is a schematic diagram of the structure 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 having 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 according to 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 a 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: the first step, determining the 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 assigned to the corresponding target cell set is less than a preset number; the second step, determining the set of cells to be clustered, wherein the set of cells to be clustered includes all the first type of cells that are not assigned to the corresponding target cell set; the third step, clustering the first type of cells in the set of cells to be clustered to obtain the target cell set; the fourth step, determining the target cell set The first step is to determine the first distance between the first type of cell 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 according to the first distance; the fifth step is to determine the second distance between the first type of cell outside the target cell set and the cluster center, and determine a second preset number of second sample cells according to 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 according to 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.

[0135] In some embodiments of the present application, the second processing module 62 determines the second preset number of second sample cells according to 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 according to 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 of 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 a 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: determine a first type of cell and a second type of cell in a 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: a subway, a highway, and a train; cluster the first type of cell, and determine a plurality of grids based on 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 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 having a 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 used 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 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: 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 having 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 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 having a common edge are the same.

[0143] In the above embodiments of the present application, the description of each embodiment has its own emphasis. 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 schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, 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 separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on 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, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of 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, 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, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0148] The above is only a preferred implementation 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: 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 scene, and the fast moving scene 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 result; 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 according to 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, characterized in that: The first type of cells are clustered, and a plurality of grids are determined according to the clustering result, including: Iteratively clustering the first type of cells, and after each iteration, determining a to-be-processed area according to a target cell set in the clustering result, wherein the to-be-processed area is a polygonal area constructed according to 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 the area to be processed is obtained each time, a rectangle to be processed is determined according to 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; The rectangle to be processed is rasterized to obtain the multiple grids.

3. The frequency band allocation method according to claim 2, characterized in that: Iterative clustering is performed on the first type of cells, and after each iteration, the area to be processed is determined according to the clustering result to include: 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; The third step is to perform clustering processing on 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 according to 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 according to the second distance; Step 6: determining a target sample cell among the first sample cells and the second sample cells 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 according to 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.

4. The frequency band allocation method according to claim 3, characterized in that: Determining a second preset number of second sample cells according to the first distance includes: According to the first distance, the first type of cells in the target cell set are sorted in order of distance from far to near, and the first preset number of the first type of cells after sorting are determined as the first sample cells; Determining a second preset number of second sample cells according to the second distance includes: According to the second distance, the first-category cells outside the target cell set are sorted in order of distance from near to far, 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, characterized in that: The preset screening condition includes at least one of the following: cell coverage type, cell site height, cell sector downtilt angle, cell direction angle, cell location, and an angle between a line between the cell and the cluster center and a preset baseline.

6. The frequency band allocation method according to claim 2, characterized in that: The rectangle to be processed is subjected to rasterization processing, and the plurality of rasterizations obtained include: Determine whether the to-be-processed rectangle obtained in this iteration has an overlapping area with the to-be-processed rectangle 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, characterized in that: Determining the first type of cell corresponding to the grid includes: Determining the 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 of the distance from near to far, 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 is used to determine a first type of cell and a second type of cell in a 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: a subway, a highway, and a train; A second processing module, used for clustering the first type of cells and determining a plurality of grids according to the clustering result; The third processing module is used to determine the first-class cell corresponding to the grid, and determine the corresponding frequency bands allocated to the first-class cells corresponding to the multiple grids respectively according to 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 executed, 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 used 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 being executed by a processor.

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