Cell switching performance optimization method, device, electronic device and readable storage medium

Abstract

The present application discloses a method for optimizing cell switching performance, which belongs to the field of communication technology and is used to automatically determine the optimal cell switching chain in a road scene, thereby improving the cell switching performance in the road scene and improving the network quality. The method comprises: obtaining sampling point data of all cells on a test section; performing grid division on the sampling point data; determining target reference data based on the sampling point data, wherein the target reference data comprises beam interference of synchronization signal blocks SSB of adjacent cells of adjacent grids, throughput of each cell on its grid, and cell switching loss between adjacent grids; determining the optimal cell switching chain of the test section according to the target reference data and an optimal cell switching chain evaluation model, wherein the optimal cell switching chain evaluation model is constructed based on a local weighted regression algorithm.

Description

Technical Field

[0001] The present application belongs to the field of communication technology, and specifically relates to a method, device, electronic device and readable storage medium for optimizing cell switching performance. Background Art

[0002] With the rapid development of wireless communication technology, people have higher and higher requirements for network service quality in road trunk scenarios. In road trunk scenarios such as subways, high-speed railways, highways, urban main roads, and urban rapid bus elevated roads, terminals move fast and wireless network construction is complex. How to optimize cell switching performance has always been an important task for network optimization.

[0003] In related technologies, technicians usually conduct traversal tests on roads, use data playback tools to identify and analyze abnormal signaling events during the test, determine the rationality of switching between two cells, and finally optimize the network based on personal optimization experience. However, the above method is limited by the frequency and accuracy of road tests, heavily relies on manual experience and data processing methods, and can only analyze one by one to make judgments on the rationality of switching between two cells, but cannot optimize the cell switching of the entire road as a whole.

[0004] Therefore, how to optimize cell switching performance is a technical problem that needs to be solved urgently. Summary of the invention

[0005] The embodiments of the present application provide a method, device, electronic device and readable storage medium for optimizing cell switching performance, which can automatically determine the optimal cell switching chain in a road scene, thereby improving the cell switching performance in the road scene and improving the network quality.

[0006] In the first aspect, an embodiment of the present application provides a method for optimizing cell switching performance, the method comprising: obtaining sampling point data of all cells on a test section; dividing the sampling point data into grids; determining target reference data based on the sampling point data, the target reference data including beam interference of synchronization signal blocks SSB of adjacent cells of adjacent grids, the throughput of each cell on its grid, and cell switching loss between adjacent grids; determining the optimal cell switching chain of the test section based on the target reference data and an optimal cell switching chain evaluation model, wherein the optimal cell switching chain evaluation model is constructed based on a local weighted regression algorithm.

[0007] In the second aspect, an embodiment of the present application provides a device for optimizing cell switching performance, including: an acquisition module for acquiring sampling point data of all cells on a test section; a grid division module for performing grid division on the sampling point data; a first determination module for determining target reference data based on the sampling point data, the target reference data including beam interference of synchronization signal blocks SSB of adjacent cells of adjacent grids, the throughput of each cell on its grid, and cell switching loss between adjacent grids; a second determination module for determining the optimal cell switching chain of the test section based on the target reference data and an optimal cell switching chain evaluation model, wherein the optimal cell switching chain evaluation model is constructed based on a local weighted regression algorithm.

[0008] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method described in the first aspect.

[0009] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0010] In a fifth aspect, an embodiment of the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect.

[0011] In an embodiment of the present application, the sampling point data of all cells on the test section are obtained; the sampling point data are grid-divided; based on the sampling point data, the target reference data is determined, and the target reference data includes the beam interference of the synchronization signal block SSB of the adjacent cells of the adjacent grids, the throughput of each cell on the grid to which it belongs, and the cell switching loss between adjacent grids; according to the target reference data and the optimal cell switching chain evaluation model, the optimal cell switching chain of the test section is determined, wherein the optimal cell switching chain evaluation model is constructed based on a local weighted regression algorithm. In this way, the optimal cell switching chain in the road scene can be automatically determined, thereby improving the cell switching performance in the road scene and improving the network quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a flowchart of a method for optimizing cell switching performance provided by an embodiment of the present application;

[0013] Figure 2 is a schematic diagram of an optimal cell switching chain provided by an embodiment of the present application;

[0014] Figure 3 is a flowchart of a method for optimizing cell switching performance provided by another embodiment of the present application;

[0015] Figure 4 is a structural diagram of a cell switching performance optimization device according to an embodiment of the present application;

[0016] Figure 5 It is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are 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 are within the scope of protection of this application.

[0018] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0019] The cell switching performance optimization method provided in the embodiment of the present application is described in detail below through specific embodiments and application scenarios in conjunction with the accompanying drawings.

[0020] Figure 1 A schematic flow chart of a cell handover performance optimization method 100 provided by an embodiment of the present application is shown. The method can be executed by an electronic device, and the electronic device may include: a server and / or a terminal device. In other words, the method can be executed by software or hardware installed in the electronic device, and the method includes the following steps:

[0021] 110: Get the sampling point data of all cells on the test section.

[0022] Among them, all cells on the test section may include NR cells, LTE cells, and may also include NSA anchor LTE cells. The embodiment of the present application does not limit the type of cells on the test section.

[0023] The acquisition of the sampling point data is the first step of the cell handover performance optimization method, that is, the preparation of the data source. The sampling point data at least includes test data such as reference signal receiving power (RSRP) and handover delay.

[0024] The sampling point data can be obtained in a variety of ways, and the embodiments of the present application do not limit the method for obtaining the sampling point data. In one implementation, samples can be collected based on road testing to extract sampling point data for all cells on the test section. In another implementation, after raster positioning is completed using 5G MR OTT data, sampling points of virtual road test data (RSRP, reference signal received quality (RSRQ), signal-to-noise ratio, throughput) can be fitted to obtain the sampling point data for all cells.

[0025] 120: Perform grid division on the sampling point data.

[0026] It can be understood that the grid division of the sampling point data is based on the matching relationship between the positions of the sampling points and the road grid, and the sampling points and sampling point data falling into the road grid are grid marked and marked with grid number identification.

[0027] For example, the test section is first divided into grids according to the size of L*L square meters, where L is, for example, 10. The grids are numbered 1, 2, ..., n, ..., N in sequence, thereby dividing the test section into N grids. The sampling point data of all cells on the test section obtained in step 110 are then processed into grids, that is, according to the matching relationship between the longitude / latitude of the sampling point and the section grid, the sampling points and the sampling point data falling into the corresponding grid are marked with grid number labels.

[0028] 130: Determine target reference data based on the sampling point data, wherein the target reference data includes beam interference of synchronization signal blocks SSB of adjacent cells of adjacent grids, throughput of each cell on its grid, and cell switching loss between adjacent grids.

[0029] It can be understood that the target reference data is reference data used to determine the optimal cell switching chain of the test section.

[0030] In one implementation, the calculation formula for the SSB beam interference of the adjacent cells of the adjacent grid is:

[0031]

[0032] Where n is the grid number, i and j are the cell numbers, and the SSB beam interference of the adjacent cells of the adjacent grids is expressed as Indicates, a, b are coefficients, SSB_Rsrp cell_i 、SSB_Rsrp cell_j is the SSB RSRP of cell i and cell j.

[0033] In one implementation, the calculation formula for the throughput of each cell on the grid to which it belongs is:

[0034]

[0035] The throughput rate of each cell on the grid to which it belongs is expressed as Indicates that a and b are coefficients, CSI_Rsrp cell_i 、CSI_Rsrp cell_j is the channel state information CSI RSRP of cell i and cell j.

[0036] In one implementation, the cell switching loss between adjacent grids includes a 5GNR cell switching loss between adjacent grids and a 4G LTE cell switching loss between adjacent grids.

[0037] In one implementation, the calculation formula for the 5G NR cell switching loss between the adjacent grids and the 4G LTE cell switching loss between the adjacent grids is:

[0038]

[0039]

[0040] Among them, NR_HO_Delay and LTE_HO_Delay are the switching delays of 5G NR cells and 4G LTE cells.

[0041] 140: Determine the optimal cell switching chain of the test section according to the target reference data and the optimal cell switching chain evaluation model, wherein the optimal cell switching chain evaluation model is constructed based on a local weighted regression algorithm.

[0042] The local weighted regression algorithm is a non-parametric method for local regression analysis, also known as local scattered point smoothing estimation. This method mainly divides the samples into small intervals, performs polynomial fitting on the samples in the intervals, and repeats this process to obtain weighted regression curves in different intervals. Finally, the centers of these regression curves are connected together to synthesize a complete regression curve.

[0043] In one implementation, the optimal cell handover chain evaluation model is constructed based on a local weighted regression algorithm, and the optimal cell handover chain evaluation model can be represented by the following function:

[0044]

[0045] Wherein, N is the total number of grids on the test section, n is the grid number, i and j are the cell numbers, is the SSB beam interference of adjacent cells in adjacent grids, is the throughput rate of each cell on its grid, is the 5GNR cell switching loss between adjacent grids, It is the 4G LTE cell handover loss between adjacent grids.

[0046] According to the target reference data determined in step 130 and the optimal cell switching chain evaluation model constructed based on the local weighted regression algorithm, a target cell switching chain can be output, and the target cell switching chain is considered to be the optimal cell switching chain on the test section.

[0047] In one implementation, the optimal cell handover chain of the test section within the target length range is outputted according to the target reference data determined in step 130 and the optimal cell handover chain evaluation model constructed based on the local weighted regression algorithm. In one implementation, the target length is less than or equal to 20 kilometers.

[0048] Figure 2 FIG. 1 is a schematic diagram of an optimal cell switching chain provided by an embodiment of the present application. Figure 2 Taking the test section in the figure as an example, it can be seen that the forward direction of the test section is from left to right, and the optimal cell switching chain of the test section is determined to be: {(NR1, LTE1)-(NR2, LTE1)-(NR5, LTE2)-(NR7, LTE4)......}, which means that when the terminal passes through the test section from left to right, the cell switching according to {(NR1, LTE1)-(NR2, LTE1)-(NR5, LTE2)-(NR7, LTE4)......} is the optimal solution for cell switching.

[0049] The embodiment of the present application provides a method for optimizing cell switching performance, which obtains sampling point data of all cells on a test section; divides the sampling point data into grids; determines target reference data based on the sampling point data, wherein the target reference data includes beam interference of synchronization signal blocks SSB of adjacent cells of adjacent grids, throughput of each cell on its grid, and cell switching loss between adjacent grids; determines the optimal cell switching chain of the test section according to the target reference data and the optimal cell switching chain evaluation model, wherein the optimal cell switching chain evaluation model is constructed based on a local weighted regression algorithm. Thus, the optimal cell switching chain in the road scene can be automatically determined, and while ensuring continuous coverage, the number of unreasonable cell switching is effectively reduced, and switching problems such as ping-pong switching and frequent switching are improved, so that the terminal can stay in a high-speed cell for a longer time, effectively improving network quality and user experience.

[0050] Figure 3 A schematic flow chart of a cell handover performance optimization method 200 provided by an embodiment of the present application is shown. The method can be executed by an electronic device, and the electronic device may include: a server and / or a terminal device. In other words, the method can be executed by software or hardware installed in the electronic device. The method, based on any of the above embodiments, further includes the following steps:

[0051] 250: Based on the optimal cell switching chain, adjust the cell-specific offsets CIO of all cells on the test section, so that the terminal device performs cell switching along the optimal cell switching chain in the test section.

[0052] In one implementation, adjusting the cell-specific offset CIO of all cells on the test section based on the optimal cell switching chain includes: calculating a target CIO of each cell in the optimal cell switching chain according to the optimal cell switching chain.

[0053] For the LTE and NR cells in the optimal cell switching chain, the target CIO of each cell in the optimal cell switching chain is calculated according to the level of the serving cell and the level of the neighboring cell, and the following formula can be used:

[0054] Mn+CIO>Ms+Hyst+Offset

[0055] Among them, Mn is the neighboring cell level value, CIO is the cell-specific offset, Ms is the serving cell level value, Hyst is the switching amplitude hysteresis, and Offset is the switching offset.

[0056] Through the above formula, the optimal CIO of each cell in the optimal cell switching chain can be determined.

[0057] In addition to calculating the target CIO of each cell in the optimal cell switching chain, in order to ensure that the terminal performs cell switching along the optimal cell switching chain in the test section, the penalty CIO of each cell in the non-optimal cell switching chain can also be calculated. The target CIO and the penalty CIO are loaded to the corresponding cell to adjust the CIO of all cells on the test section.

[0058] The embodiment of the present application provides a method for optimizing cell switching performance, which obtains sampling point data of all cells on a test section; divides the sampling point data into grids; determines target reference data based on the sampling point data, wherein the target reference data includes beam interference of synchronization signal blocks SSB of adjacent cells of adjacent grids, throughput of each cell on its grid, and cell switching loss between adjacent grids; determines the optimal cell switching chain of the test section according to the target reference data and an optimal cell switching chain evaluation model, wherein the optimal cell switching chain evaluation model is constructed based on a local weighted regression algorithm. Thus, the optimal cell switching chain in a road scene can be automatically determined, thereby improving the cell switching performance in the road scene and improving the network quality.

[0059] An embodiment of the present application provides a method for optimizing cell switching performance, which adjusts the cell-specific offset CIO of all cells on the test section based on the optimal cell switching chain, thereby automatically calculating the adjustment parameters of the cell CIO, realizing the configuration of the cell switching parameters, and ensuring that the terminal device performs cell switching in the test section along the determined optimal cell switching chain.

[0060] Figure 4 Schematic diagram of the structure of the cell switching performance optimization device according to the embodiment of the present application. Figure 4 As shown, the cell switching performance optimization device 300 includes: an acquisition module 310, a grid division module 320, a first determination module 330, and a second determination module 340. The acquisition module 310 is used to acquire the sampling point data of all cells on the test section; the grid division module 320 is used to perform grid division on the sampling point data; the first determination module 330 is used to determine the target reference data based on the sampling point data, and the target reference data includes the beam interference of the synchronization signal block SSB of the adjacent cells of the adjacent grids, the throughput of each cell on the grid to which it belongs, and the cell switching loss between the adjacent grids; the second determination module 340 is used to determine the optimal cell switching chain of the test section according to the target reference data and the optimal cell switching chain evaluation model, wherein the optimal cell switching chain evaluation model is constructed based on the local weighted regression algorithm.

[0061] In one implementation, the optimal cell handover chain evaluation model is represented by the following function:

[0062]

[0063] Wherein, N is the total number of grids on the test section, n is the grid number, i and j are the cell numbers, is the SSB beam interference of adjacent cells in adjacent grids, is the throughput rate of each cell on its grid, is the 5GNR cell switching loss between adjacent grids, It is the 4G LTE cell handover loss between adjacent grids.

[0064] In one implementation, the first determination module calculates the SSB beam interference of the adjacent cells of the adjacent grid by the following formula:

[0065]

[0066] Among them, a and b are coefficients, SSB_Rsrp cell_i 、SSB_Rsrp cell_j is the SSB reference signal received power RSRP of cell i and cell j.

[0067] In one implementation, the first determining module calculates the throughput rate of each cell on the grid to which it belongs by using the following formula:

[0068]

[0069] Among them, a and b are coefficients, CSI_Rsrp cell_i 、CSI_Rsrp cell_j is the channel state information CSI reference signal received power RSRP of cell i and cell j.

[0070] In one implementation, the first determination module calculates the 5GNR cell switching loss between the adjacent grids and the 4G LTE cell switching loss between the adjacent grids by the following formula:

[0071]

[0072]

[0073] Among them, NR_HO_Delay and LTE_HO_Delay are the switching delays of 5G NR cells and 4G LTE cells.

[0074] In one implementation, the apparatus further includes a CIO adjustment module for adjusting the CIOs of all cells on the test section based on the optimal cell switching chain, so that the terminal device performs cell switching along the optimal cell switching chain in the test section.

[0075] In one implementation, the CIO adjustment module is specifically used to calculate the target CIO of each cell in the optimal cell switching chain and the penalty CIO of each cell in the non-optimal cell switching chain according to the optimal cell switching chain; load the target CIO and the penalty CIO to the corresponding cell to adjust the CIO of all cells on the test section.

[0076] The cell switching performance optimization device in the embodiment of the present application can be a device, or a component, integrated circuit, or chip in a terminal. The device can be a mobile electronic device or a non-mobile electronic device. Exemplarily, the mobile electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a wearable device, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook or a personal digital assistant (personal digital assistant, PDA), etc., and the non-mobile electronic device can be a server, a network attached storage (Network Attached Storage, NAS), a personal computer (personal computer, PC), a television (television, TV), a teller machine or a self-service machine, etc., which is not specifically limited in the embodiment of the present application.

[0077] The cell switching performance optimization device in the embodiment of the present application may be a device having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0078] The cell switching performance optimization device provided in the embodiment of the present application can implement each process in the cell switching performance optimization method provided in any of the above embodiments. To avoid repetition, it will not be repeated here.

[0079] Figure 5 A schematic diagram of the hardware structure of an electronic device for implementing an embodiment of the present application, the electronic device may be a terminal device or a server device, and the electronic device includes: an antenna 401, a radio frequency device 402, a baseband device 403, a network interface 404, a memory 405, and a processor 406, a program or instruction stored in the memory 405 and executable on the processor 406, and when the program or instruction is executed by the processor 406, the following is implemented:

[0080] Among them, the processor 406 is used to obtain sampling point data of all cells on the test section; divide the sampling point data into grids; determine target reference data based on the sampling point data, and the target reference data includes beam interference of synchronization signal blocks SSB of adjacent cells in adjacent grids, the throughput of each cell on its grid, and cell switching loss between adjacent grids; determine the optimal cell switching chain of the test section according to the target reference data and the optimal cell switching chain evaluation model, wherein the optimal cell switching chain evaluation model is constructed based on a local weighted regression algorithm.

[0081] In one implementation, the processor 406 is configured to adjust the cell-specific offsets CIO of all cells on the test section based on the optimal cell switching chain.

[0082] In one implementation, the processor 406 is used to calculate the target CIO of each cell in the optimal cell switching chain and the penalty CIO of each cell in the non-optimal cell switching chain according to the optimal cell switching chain; and load the target CIO and the penalty CIO to the corresponding cell to adjust the CIO of all cells on the test section.

[0083] According to the electronic device 400 of the embodiment of the present application, the process of the method 100-200 corresponding to the embodiment of the present application can be referred to, and the various units / modules in the electronic device 400 and the above-mentioned other operations and / or functions are respectively for implementing the corresponding processes in the method 100-200, and can achieve the same or equivalent technical effects. For the sake of brevity, they will not be repeated here.

[0084] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned cell switching performance optimization method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0085] The processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0086] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned 100-200 method embodiments, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0087] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0088] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0089] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0090] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A method for optimizing cell handover performance, characterized in that: The method comprises: Obtain the sampling point data of all cells on the test section; Performing grid division on the sampling point data; Based on the sampling point data, target reference data is determined, wherein the target reference data includes beam interference of synchronization signal blocks SSB of adjacent cells of adjacent grids, throughput of each cell on the grid to which it belongs, and cell switching loss between adjacent grids; Determining an optimal cell switching chain of the test section according to the target reference data and an optimal cell switching chain evaluation model, wherein the optimal cell switching chain evaluation model is constructed based on a local weighted regression algorithm; The optimal cell handover chain evaluation model is represented by the following function: *( ) Wherein, N is the total number of grids on the test section, n is the grid number, i and j are the cell numbers, is the SSB beam interference of adjacent cells in adjacent grids, is the throughput rate of each cell on its grid, is the 5G NR cell switching loss between adjacent grids, It is the 4G LTE cell handover loss between adjacent grids.

2. The method according to claim 1, characterized in that The SSB beam interference of the adjacent cells of the adjacent grid is calculated by the following formula: Among them, a and b are coefficients, , is the SSB reference signal received power RSRP of cell i and cell j.

3. The method according to claim 1, characterized in that The throughput of each cell on the grid to which it belongs is calculated by the following formula: Among them, a and b are coefficients, , is the channel state information CSI reference signal received power RSRP of cell i and cell j.

4. The method according to claim 1, characterized in that: The 5G NR cell switching loss between the adjacent grids and the 4G LTE cell switching loss between the adjacent grids are calculated by the following formula: in, , It is the switching delay between 5G NR cell and 4G LTE cell.

5. The method according to claim 1, characterized in that After determining the optimal cell switching chain of the test section, the method further includes: Based on the optimal cell switching chain, the cell-specific offsets CIO of all cells on the test section are adjusted so that the terminal equipment performs cell switching along the optimal cell switching chain in the test section.

6. The method according to claim 5, characterized in that The adjusting the CIOs of all cells on the test section based on the optimal cell switching chain includes: According to the optimal cell switching chain, calculating a target CIO of each cell in the optimal cell switching chain and a penalty CIO of each cell in a non-optimal cell switching chain; The target CIO and the penalty CIO are loaded into corresponding cells to adjust the CIOs of all cells on the test section.

7. A cell switching performance optimization device, characterized in that: include: An acquisition module is used to obtain the sampling point data of all cells on the test section; A grid division module, used for performing grid division on the sampling point data; A first determination module is used to determine target reference data based on the sampling point data, wherein the target reference data includes beam interference of synchronization signal blocks SSB of adjacent cells of adjacent grids, a throughput rate of each cell on its grid, and a cell switching loss between adjacent grids; A second determination module is used to determine the optimal cell switching chain of the test section according to the target reference data and the optimal cell switching chain evaluation model, wherein the optimal cell switching chain evaluation model is constructed based on a local weighted regression algorithm; The optimal cell handover chain evaluation model is represented by the following function: *( ) Wherein, N is the total number of grids on the test section, n is the grid number, i and j are the cell numbers, is the SSB beam interference of adjacent cells in adjacent grids, is the throughput rate of each cell on its grid, is the 5G NR cell switching loss between adjacent grids, It is the 4G LTE cell handover loss between adjacent grids.

8. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein when the program or instruction is executed by the processor, the steps of the cell switching performance optimization method as described in any one of claims 1 to 6 are implemented.

9. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the cell switching performance optimization method according to any one of claims 1 to 6 are implemented.

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