Terminal mobility performance improvement method, device, system, equipment, medium and product

Abstract

The invention discloses a method, a device, a system, equipment, a medium and a product for improving the mobility performance of a terminal. An RIS control server establishes a mapping relation among RIS equipment, a base station and a coverage area; the base station predicts the predicted position information and the movement scheme of the terminal in the future preset time according to the actual position information of the terminal and the mapping relation, generates movement scheme data and reports the movement scheme data to the RIS control server; and when the RIS control server determines a target RIS device to be occupied by the terminal in the future preset time according to the mobile scheme data, the RIS control server generates a pre-scheduling strategy for related RIS devices and related base stations and issues the pre-scheduling strategy to the related base stations and the related RIS devices, and the related RIS devices comprise the target RIS device. By adopting the method and the device, the base station and the RIS equipment are pre-scheduled by predicting the mobile scheme of the terminal, so that the processing time delay is reduced, and the mobile performance of the user terminal is effectively improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wireless, in particular to a terminal mobile performance improvement method, device, system, equipment, medium and product. BACKGROUND

[0002] RIS (Reconfigurable Intelligent Surface, Reconfigurable Intelligent Surface) is a two-dimensional implementation of electromagnetic metamaterial, which actively and intelligently controls the space electromagnetic wave in a programmable way to form an electromagnetic environment controllable in amplitude, phase, polarization and frequency. In the field of communication, RIS can be used to expand the signal coverage of difficult scenarios such as tunnel, dense urban area, low-altitude area, and improve the communication performance of users (especially high-speed mobile users) due to its advantages of low cost, low power consumption, low complexity and easy deployment.

[0003] Intelligent surface mainly reflects, transmits and provides a certain degree of signal enhancement capability for existing base station signals, and its effective coverage range has limitations. For scenarios where users move quickly, such as low-altitude economic zones and fast roads, the signal attenuation provided by the intelligent surface is too fast to affect the coverage quality. Therefore, it is necessary to optimize and improve the mobile performance of the RIS network.

[0004] The existing mobile performance improvement method of RIS network mainly increases the number of RIS device deployment, improves the overlapping coverage area of different RIS devices, and achieves the purpose of improving the mobile performance. However, increasing the deployment of hardware to improve the mobile performance will cause a substantial increase in cost. In addition, the existing method uses a passive wireless link establishment method of RIS, that is, when the user moves to the overlapping area of the RIS device, the link of the user through the RIS device to the serving cell is established. This method has a certain lag, which reduces the mobile performance of the user. SUMMARY

[0005] The purpose of the embodiments of the present application is to provide a terminal mobile performance improvement method, device, system, equipment, medium and product, which predicts the mobile scheme of the terminal, pre-schedules the base station and RIS device, thereby reducing the processing delay and effectively improving the mobile performance of the user terminal.

[0006] To achieve the above purpose, the embodiments of the present application provide a terminal mobile performance improvement method applied to an intelligent surface RIS control server, the method comprising: establishing a mapping relationship of RIS devices, base stations and coverage areas of RIS devices; The system receives mobile plan data of a terminal reported by a base station; wherein the mobile plan data includes the predicted location information and mobile plan of the terminal at a future preset time, and the predicted location information and the mobile plan are predicted by the base station based on the actual location information of the terminal and the mapping relationship. When the target RIS device of the terminal is determined based on the mobility scheme data, a pre-scheduling strategy is generated for the relevant RIS device and the relevant base station corresponding to the relevant RIS device; wherein, the relevant RIS device includes the target RIS device, and the target RIS device refers to the RIS device that the terminal will occupy in the future preset time. The pre-scheduling strategy is distributed to the relevant base stations and the relevant RIS devices.

[0007] As an improvement to the above scheme, when the target RIS device is inconsistent with the original RIS device currently occupied by the terminal, the relevant RIS device also includes the original RIS device.

[0008] As an improvement to the above scheme, establishing the mapping relationship between the RIS device, the base station, and the coverage area of ​​the RIS device includes: Obtain the base station corresponding to each RIS device; Obtain the engineering parameters for the coverage area of ​​each RIS device; Based on the engineering parameters, determine the three-dimensional coordinate information, main radiation direction, and coverage boundary of each RIS device; Based on the three-dimensional coordinate information, the main radiation direction, and the coverage boundary, calculate the coverage area information of each RIS device; Based on the base station and coverage area information corresponding to each RIS device, a mapping relationship is constructed between the RIS device, the base station, and the coverage area of ​​the RIS device.

[0009] As an improvement to the above scheme, the engineering parameters include longitude, latitude, altitude, azimuth, tilt angle, horizontal emission angle, vertical emission angle, horizontal beamwidth, vertical beamwidth, and maximum effective coverage distance. The main radiation direction includes the horizontal radiation direction and the vertical radiation direction.

[0010] As an improvement to the above solution, the moving solution includes: moving to the coverage area of ​​other RIS devices, continuing to maintain the currently occupied original RIS device, and moving out of the coverage area of ​​the original RIS device but unable to match a new RIS device.

[0011] As an improvement to the above solution, the mobile solution data also includes the actual location information of the terminal and the information of the original RIS device; When the mobility plan involves moving to the coverage area of ​​other RIS devices, the mobility plan data also includes information about the target RIS devices initially predicted by the base station.

[0012] As an improvement to the above scheme, when the target RIS device of the terminal is determined based on the mobility scheme data, generating a pre-scheduling strategy for the relevant RIS device and the relevant base station corresponding to the relevant RIS device includes: The mobile scheme data is input into a preset RIS device identification model for calculation, and the identification result output by the RIS device identification model is obtained; wherein, the identification result is that the terminal has a target RIS device and the corresponding target RIS device, or the terminal does not have a target RIS device; When the identification result indicates that the terminal has a target RIS device, a pre-scheduling strategy is generated for the relevant RIS device and the relevant base station corresponding to the relevant RIS device.

[0013] As an improvement to the above scheme, the RIS device identification model is a KNN model, which is used for: Calculate the distance between the predicted location information and the location information of each sample terminal in the preset database; The N nearest neighbor sample terminals of the terminal are selected based on the distance; where N≥1; Based on the information of the RIS device corresponding to the nearest neighbor sample terminal, candidate RIS devices are determined; Based on the coverage area of ​​the candidate RIS devices, determine whether the candidate RIS devices meet the coverage requirements for the terminal; If yes, the candidate RIS device is selected as the target RIS device, and the terminal is output as having a target RIS device; otherwise, the terminal is output as not having a target RIS device.

[0014] As an improvement to the above scheme, the pre-scheduling strategy for the target RIS device includes: resource scheduling duration, target location, and adjustment of the radiation angle of the sub-beam alignment and signal enhancement requirements based on the target location; the target location is the predicted location information of the terminal. The pre-scheduling strategy for the target base station includes: resource scheduling duration, information about the target RIS device, and the antenna weight parameters, beam parameters, power parameters, and RB resource reservation number of the serving cell corresponding to the target RIS device that need to be adjusted.

[0015] This invention also provides a method for improving terminal mobility performance, applied to a base station, the method comprising: Obtain the preset mapping relationship between RIS devices, base stations, and the coverage areas of RIS devices from the RIS control server; Based on the actual location information of the terminal and the mapping relationship, predict the predicted location information and movement plan of the terminal in the future preset time, and generate movement plan data; The mobility scheme data is reported to the RIS control server so that when the RIS control server determines the target RIS device of the terminal based on the mobility scheme data, it generates a pre-scheduling strategy for the relevant RIS device and the relevant base station corresponding to the relevant RIS device.

[0016] As an improvement to the above solution, the step of predicting the terminal's predicted location information and movement plan at a future preset time based on the terminal's actual location information and the mapping relationship, and generating movement plan data, includes: Obtain the relative position parameters between the terminal and the RIS device reported by the RIS device; Based on the three-dimensional coordinate information of the RIS device and the relative position parameters, the three-dimensional coordinate information of the terminal is converted and used as the actual position information; The moving speed of the terminal is calculated based on the actual location information of the terminal within a preset sampling time. Based on the actual location information and the moving speed, predict the predicted location information of the terminal at a future preset time. Based on the coverage area of ​​each RIS device in the mapping relationship, the mobile plan of the terminal within a preset time period is predicted.

[0017] As an improvement to the above solution, the method further includes: When the pre-scheduling policy is received from the RIS control server, the pre-scheduling policy is executed; wherein, when the base station is the target base station, the pre-scheduling policy includes: resource scheduling duration, information of the target RIS device, and antenna weight parameters, beam parameters, power parameters and RB resource reservation number of the serving cell corresponding to the target RIS device that need to be adjusted.

[0018] This invention also provides a terminal mobility performance enhancement device, applied to a RIS control server, the device comprising: The mapping relationship establishment module is used to establish the mapping relationship between RIS devices, base stations, and the coverage areas of RIS devices; A mobile plan data receiving module is used to receive mobile plan data of a terminal reported by a base station; wherein, the mobile plan data includes the predicted location information and mobile plan of the terminal at a preset future time, and the predicted location information and the mobile plan are predicted by the base station based on the actual location information of the terminal and the mapping relationship; A pre-scheduling strategy generation module is used to generate a pre-scheduling strategy for the relevant RIS devices and the relevant base stations corresponding to the relevant RIS devices when the target RIS device of the terminal is determined based on the mobility scheme data; wherein, the relevant RIS devices include the target RIS devices, and the target RIS devices refer to the RIS devices that the terminal will occupy in the future preset time. The pre-scheduling policy distribution module is used to distribute the pre-scheduling policy to the relevant base stations and the relevant RIS devices.

[0019] This invention also provides a terminal mobility performance enhancement device applied to a base station, the device comprising: The mapping relationship acquisition module is used to obtain the preset mapping relationship between RIS devices, base stations, and the coverage areas of RIS devices from the RIS control server; The mobile plan data generation module is used to predict the terminal's predicted location information and mobile plan at a future preset time based on the terminal's actual location information and the mapping relationship, and generate mobile plan data. The mobile scheme data reporting module is used to report the mobile scheme data to the RIS control server, so that when the RIS control server determines the target RIS device of the terminal based on the mobile scheme data, it generates a pre-scheduling strategy for the relevant RIS device and the relevant base station corresponding to the relevant RIS device.

[0020] This invention also provides a terminal mobility performance enhancement system, including a RIS device, a base station, and a RIS control server; The RIS device is used to obtain the actual location information of the terminal occupying its own signal and report it to the base station to which it belongs; and to execute the pre-scheduling strategy issued by the RIS control server. The base station is used to predict the terminal's predicted location information and movement plan at a future preset time based on the terminal's actual location information and the preset mapping relationship between the coverage areas of the RIS device, the base station, and the RIS device obtained from the RIS control server; generate movement plan data; and report the movement data plan to the RIS control server; and execute the pre-scheduling strategy issued by the RIS control server. The RIS control server is used to establish a mapping relationship between RIS devices, base stations, and the coverage areas of RIS devices. When the target RIS device of the terminal is determined based on the mobility scheme data, a pre-scheduling policy is generated for the relevant RIS devices and the relevant base stations corresponding to the relevant RIS devices, and the pre-scheduling policy is sent to the relevant base stations and the relevant RIS devices. The relevant RIS devices include the target RIS devices, which refer to the RIS devices that the terminal will occupy at the preset future time.

[0021] This invention also provides a terminal mobility performance enhancement device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the terminal mobility performance enhancement method as described in any of the above embodiments.

[0022] This invention also provides a computer-readable storage medium, which includes a stored computer program, wherein the computer program, when running, controls the device where the computer-readable storage medium is located to execute the terminal mobility performance improvement method as described in any of the above embodiments.

[0023] This invention also provides a computer program product, which includes a computer program or computer instructions. When the computer program or computer instructions are executed by a processor, they implement the terminal mobility performance improvement method as described in any of the above embodiments.

[0024] Compared with existing technologies, the terminal mobility performance enhancement method, apparatus, system, device, medium, and product disclosed in this invention predicts the terminal user's location information and movement plan at a predetermined time by the base station. The RIS control server then makes the final decision based on the predictive analysis results of the base station. When it is determined that the terminal will occupy a target RIS device at the predetermined time, a pre-scheduling strategy for the relevant RIS device and base station is generated. This embodiment of the invention pre-schedules relevant base stations and RIS devices during terminal movement, pre-scheduling beam resources to form coverage and establishing links from the target RIS device to the serving cell, thereby reducing processing latency and minimizing lag. Furthermore, this embodiment utilizes edge computing power on the base station side, placing a portion of the computing tasks at the forefront and using an edge-computing RIS control server for overall control, forming a two-layer processing mechanism that further reduces processing latency and effectively improves the mobility performance of user terminals, especially for high-speed mobile users. Attached Figure Description

[0025] Figure 1This is a flowchart illustrating a method for improving terminal mobility performance applied to a RIS control server, provided by an embodiment of the present invention. Figure 2 This is a flowchart illustrating a method for improving terminal mobility performance applied to a base station, as provided in an embodiment of the present invention. Figure 3 This is a schematic diagram of a terminal mobility performance enhancement system provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the preferred terminal mobility performance enhancement system in an embodiment of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0028] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0029] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0030] See Figure 1This is a flowchart illustrating a method for improving terminal mobility performance applied to a RIS control server according to an embodiment of the present invention. The embodiment of the present invention provides a method for improving terminal mobility performance applied to a smart metasurface RIS control server, the method comprising steps S11 to S14: S11. Establish the mapping relationship between the coverage areas of RIS devices, base stations, and RIS devices; S12. Receive the terminal's mobility plan data reported by the base station; wherein, the mobility plan data includes the terminal's predicted location information and mobility plan at a future preset time, the predicted location information and the mobility plan are predicted by the base station based on the terminal's actual location information and the mapping relationship, the terminal's actual location information is collected by the original RIS device currently occupied by the terminal and reported to the base station; S13. When the target RIS device of the terminal is determined based on the mobility scheme data, a pre-scheduling strategy is generated for the relevant RIS devices and the relevant base stations corresponding to the relevant RIS devices; wherein, the relevant RIS devices include the target RIS devices, and the target RIS devices refer to the RIS devices that the terminal will occupy in the future preset time. S14. The pre-scheduling strategy is sent to the relevant base stations and the relevant RIS devices.

[0031] It should be noted that this invention proposes an overall architecture for improving terminal mobility performance based on intelligent metasurface coverage. This architecture includes a RIS device, a base station, and a RIS control server. The RIS device consists of an antenna array composed of multiple RIS units. The RIS device employs a novel programmable subwavelength two-dimensional metamaterial and actively and intelligently controls electromagnetic waves through digital coding to achieve controllable reflection and transmission of 5G signals. It possesses multi-beam capability and can cover targets in different directions. The base station has certain edge computing capabilities and provides wireless networks to users. In existing networks, the intelligent metasurface RIS device is deployed to process the signal of a base station with a signal advantage. The RIS device and the base station are configured in a many-to-one or one-to-one relationship.

[0032] In this embodiment of the invention, the RIS control server obtains the basic parameter information of each RIS device, calculates the coverage area information of each RIS device, and obtains the correspondence between the RIS device and the base station, thereby obtaining and storing the mapping relationship of "RIS device-base station-coverage area".

[0033] The RIS device measures the actual location information of the terminal users occupying its signal in real time and reports it to the corresponding base station.

[0034] The edge computing module in the base station predicts the location information of the highly mobile terminal at a future preset time T based on the reported terminal location information, determines the user's possible movement plan, and then the edge computing module reports the analysis results and the data used to the RIS control server.

[0035] Preferably, the relocation scheme includes: moving to the coverage area of ​​another RIS device, continuing to maintain the currently occupied original RIS device, or moving out of the coverage area of ​​the original RIS device but unable to match a new RIS device.

[0036] Preferably, the mobility plan data also includes the actual location information of the terminal and the information of the original RIS device. When the mobility plan involves moving to the coverage area of ​​other RIS devices, the mobility plan data also includes the information of the target RIS device initially predicted by the base station. The base station reports the data used in edge computing analysis and the generated analysis results to the RIS control server, which helps to provide a certain data foundation for the RIS control server's decision-making and improves the accuracy of the RIS control server's decision-making.

[0037] The RIS control server, based on the reported mobility scheme data and combined with historical big data resources, performs modeling and final analysis and decision-making to predict the target RIS device that the terminal will occupy at the preset future time T. When the target RIS device is determined, a pre-scheduling strategy is generated and sent to the relevant base stations and relevant RIS devices, thereby controlling the relevant base stations and relevant RIS devices to implement the pre-scheduling strategy and adjust the working parameters of themselves and / or relevant serving cells to improve the terminal's mobility performance.

[0038] The relevant RIS device includes the target RIS device, and the relevant base station includes the target base station to which the target RIS device belongs. The target RIS device refers to the RIS device that the terminal will occupy at a predetermined future time T. The target RIS device can be a new RIS device or the original RIS device currently occupied by the terminal.

[0039] Preferably, when the target RIS device is different from the original RIS device currently occupied by the terminal, the related RIS device also includes the original RIS device, and the related base station also includes the original base station corresponding to the original RIS device.

[0040] Understandably, when the RIS control server determines that the terminal has no target RIS device, for example, when the terminal will move out of the coverage area of ​​all deployed RIS devices, the RIS control server will not generate a pre-scheduling strategy to avoid ineffective scheduling and resource consumption.

[0041] By employing the technical means of this invention, the base station predicts the terminal user's location information and movement plan for a predetermined time in the future. The RIS control server then makes the final decision based on the predictive analysis results of the base station. When it is determined that the terminal will occupy a target RIS device in the predetermined time, a pre-scheduling strategy for the relevant RIS device and base station is generated. This invention pre-schedules relevant base stations and RIS devices during terminal movement, pre-scheduling beam resources to form coverage and establishing links from the target RIS device to the serving cell, thereby reducing processing latency and minimizing lag. Furthermore, this invention utilizes edge computing power on the base station side, placing a portion of the computing tasks at the forefront and using an edge-computing RIS control server for overall control, forming a two-layer processing mechanism that further reduces processing latency and effectively improves the mobility performance of user terminals, especially for high-speed mobile users.

[0042] Compared to existing methods that improve mobility by deploying additional RIS devices, which significantly increases costs and is not conducive to practical applications, the embodiments of this invention do not require additional equipment, thus offering a cost advantage. Furthermore, unlike existing methods that use passive RIS link establishment (where a link is established only when the user moves to an overlapping area, resulting in latency and reduced mobility), the embodiments of this invention proactively establish RIS links by predicting mobility scheme data and pre-scheduling beam resources to form coverage, thereby reducing latency.

[0043] As a preferred embodiment, the present invention is further implemented based on the above embodiments. Step S11, namely establishing the mapping relationship between the RIS device, the base station, and the coverage area of ​​the RIS device, includes steps S111 to S115: S111, Obtain the base station corresponding to each RIS device; S112. Obtain the engineering parameters of the coverage area of ​​each RIS device; S113. Based on the engineering parameters, determine the three-dimensional coordinate information, main radiation direction, and coverage boundary of each RIS device; S114. Calculate the coverage area information of each RIS device based on the three-dimensional coordinate information, the main radiation direction, and the coverage boundary; S115. Based on the base station and coverage area information corresponding to each RIS device, construct a mapping relationship between the RIS device, the base station, and the coverage area of ​​the RIS device.

[0044] In this embodiment of the invention, the RIS control server first needs to interact with the RIS devices to obtain the current engineering parameters, thereby calculating the location information of the coverage area of ​​each RIS device. This information will be used to determine the target RIS device in subsequent mobility analysis.

[0045] Preferably, the engineering parameters include longitude, latitude, altitude, azimuth, tilt angle, horizontal emission angle, vertical emission angle, horizontal beamwidth, vertical beamwidth, and maximum effective coverage distance.

[0046] The engineering parameters are defined as follows: The longitude, latitude, and altitude of the intelligent metasurface RIS device.

[0047] The azimuth, tilt, horizontal emission angle, and vertical emission angle of the intelligent metasurface RIS device j.

[0048] The horizontal and vertical beamwidths of the intelligent metasurface RIS device j.

[0049] : The parameter for the farthest effective coverage distance of the intelligent metasurface device j.

[0050] After obtaining the aforementioned engineering parameters, the RIS device, according to... This determines the location of the intelligent metasurface device within a three-dimensional geographic coordinate system, i.e., its three-dimensional coordinate information. Then, based on... The main radiation direction of the intelligent metasurface device is determined, wherein the main radiation direction includes a horizontal radiation direction and a vertical radiation direction, wherein the horizontal main radiation direction is ( )%360 (reflection is positive in the clockwise direction and negative in the counterclockwise direction), perpendicular to the main radiation direction is (Reflection downwards is positive, upwards is negative). Then, according to... Determine the coverage boundary by extending the coverage area from the main radiation direction. The radiation range is horizontally equidistant from left to right. The width is the same in the vertical direction. The radiation distance is .

[0051] Furthermore, the correspondence between RIS devices and base stations is known information. The RIS control server obtains the mapping relationship of "RIS device-base station-RIS device coverage area" through the above calculation method. For example, RIS1 corresponds to base station 1, and the coverage area is a specified angle range with a radius of 200m centered on its coordinates. The above information is then synchronized to the edge computing modules of each base station for subsequent matching.

[0052] By employing the technical means of this invention, the coverage area of ​​each RIS device is calculated by real-time collection of engineering parameters of each RIS device configured in the scene. Combined with the pre-configured correspondence between RIS devices and base stations, a mapping relationship of "RIS device-base station-RIS device coverage area" is constructed and synchronized to each base station. This provides a data foundation for base stations to predict the location information and mobility scheme of terminals, thereby improving the accuracy of predicting location information and mobility scheme.

[0053] As a preferred embodiment, the present invention further implements the above embodiments. Step S13, that is, when the target RIS device of the terminal is determined according to the mobility scheme data, generating a pre-scheduling strategy for the relevant RIS device and the relevant base station corresponding to the relevant RIS device, includes steps S131 to S132: S131. Input the mobile scheme data into a preset RIS device identification model for calculation to obtain the identification result output by the RIS device identification model; wherein, the identification result is that the terminal has a target RIS device and the corresponding target RIS device, or the terminal does not have a target RIS device; S132. When the identification result indicates that the terminal has a target RIS device, a pre-scheduling strategy is generated for the relevant RIS device and the relevant base station corresponding to the relevant RIS device.

[0054] In this embodiment of the invention, the RIS control server continuously collects the terminal location data actually measured by the RIS device reported by the base station side and the corresponding occupied RIS device number, and constructs a RIS device coverage area identification model based on the data, which serves as the RIS device identification model.

[0055] The input to the RIS device identification model is the mobile scheme data, and the output is whether the terminal has a target RIS device, and if the terminal has a target RIS device, the information of the target RIS device.

[0056] The RIS control server obtains the output results of the RIS device identification model. When the RIS device identification model outputs information about the target RIS device, it generates a pre-scheduling strategy for the relevant RIS device and the relevant base station.

[0057] Preferably, the RIS device identification model is a KNN (K-Nearest Neighbors) model. This embodiment of the invention optimizes the traditional KNN distance measurement method to a distance calculation based on longitude, latitude, and altitude in three-dimensional Earth space (considering both planar distance and altitude difference), used to identify target RIS devices. When the predicted location information triple (latitude, longitude, and altitude) of the input terminal is used, the improved KNN model matches the k nearest historical location samples to determine the RIS device coverage area to which the user should belong in the future, providing a basis for pre-scheduling strategies.

[0058] Specifically, the RIS device identification model is used for: Calculate the distance between the predicted location information and the location information of each sample terminal in the preset database; The N nearest neighbor sample terminals of the terminal are selected based on the distance; where N≥1; Based on the information of the RIS device corresponding to the nearest neighbor sample terminal, candidate RIS devices are determined; Based on the coverage area of ​​the candidate RIS devices, determine whether the candidate RIS devices meet the coverage requirements for the terminal; If yes, the candidate RIS device is selected as the target RIS device, and the terminal is output as having a target RIS device; otherwise, the terminal is output as not having a target RIS device.

[0059] Preferably, determining the candidate RIS device based on the RIS device information corresponding to the nearest neighbor sample terminal includes: The RIS device with the largest number of corresponding RIS devices among the nearest neighbor sample terminals is selected as the candidate RIS device.

[0060] Preferably, the method for determining the coverage requirement is as follows: Calculate the average distance between the predicted location information and the location information of the nearest neighbor sample terminal corresponding to the candidate RIS device; The coverage distance threshold of the candidate RIS device is calculated based on the farthest effective coverage distance of the candidate RIS device and the preset distance adjustment coefficient. When the average distance is less than the coverage distance threshold, the candidate RIS device is determined to meet the coverage requirements for the terminal; otherwise, the coverage requirements are not met.

[0061] In this embodiment of the invention, a target RIS device identification model based on an improved KNN is first constructed. The distance metric in KNN is improved by modifying the distance metric based on the triplets of the terminal's location information. The distance metric is then modified to calculate point-to-point distance in three-dimensional Earth space based on longitude, latitude, and altitude. First, the distance between two points at the same altitude is calculated based on their latitude and longitude. Then, the altitude difference between the two points is calculated. Finally, the distance between the two points in three-dimensional Earth space is calculated. The distance metric formula is as follows: ;

[0062]

[0063] Specific identification process: Data preparation includes the actual measured terminal location of the RIS device and the RIS device serial number. The distance between points is calculated based on the improved distance metric formula described above. Nearest neighbors are found by selecting the k nearest neighbors to the sample to be classified (terminal predicted location information) based on the calculated distances. The classification decision is made by statistically analyzing the categories of these k nearest neighbors and using majority voting to determine the category of the sample to be classified.

[0064] Furthermore, an average distance judgment is added to the decision category. For example, if the system defaults to k being 5, and 3 out of 5 nearest neighbors belong to "RIS device X", then the decision is made that the terminal will move to the coverage area of ​​RIS device X. Further calculation is needed to determine the average distance between these 3 nearest neighbors and the predicted terminal user location. If this average distance exceeds the coverage distance threshold of the RIS device (e.g., the furthest effective coverage distance), then... Distance adjustment factor If the target RIS device cannot be stably covered, then the target RIS device will not be output.

[0065] In practical applications, for data reported by target RIS devices, the predicted location information triplet ( If the input RIS device identification model can output a target RIS device that is different from the original RIS device, a pre-scheduling instruction will be issued to the original RIS device, the target RIS device, and their corresponding base stations. If no target RIS device is output, or if the output is the same as the original RIS device, a pre-scheduling instruction will be issued to the original RIS device and its corresponding base station. For reported data without a target RIS device, a similar operation is performed: if a new target RIS device can be output, a pre-scheduling instruction will be issued to the original RIS device, the target RIS device, and their corresponding base stations; if no target RIS device is output, no further processing is performed to avoid resource waste.

[0066] Preferably, the pre-scheduling strategy for the relevant RIS devices includes resource scheduling duration and target location, and the pre-scheduling strategy for the relevant base stations includes resource scheduling duration and information about the corresponding RIS devices.

[0067] Optionally, the resource scheduling duration is T represents a future preset time, and k is an integer greater than or equal to 2. The information of the RIS device includes the RIS device number.

[0068] More preferably, the pre-scheduling strategy for the target RIS device includes: resource scheduling duration, target location, adjustment of the radiation angle of the sub-beam alignment and signal enhancement requirements based on the target location; the target location is the predicted location information of the terminal; and the signal enhancement requirements are whether to enable signal enhancement.

[0069] The pre-scheduling strategy for the target base station includes: resource scheduling duration, information about the target RIS device, and the antenna weight parameters, beam parameters, power parameters, and RB resource reservation number of the serving cell corresponding to the target RIS device that need to be adjusted.

[0070] Furthermore, for the target base station, after the base station-side edge computing module receives the pre-scheduling information sent by the RIS control server, it first parses the target RIS device number to determine the serving cell corresponding to the target RIS device; the corresponding serving cell appropriately improves the link coverage from the cell antenna to the RIS device antenna by adjusting the antenna weight parameters, beam parameters, and power parameters; and further implements RB resource reservation in the corresponding serving cell; the above operations continue for the resource scheduling duration in the pre-scheduling information.

[0071] After receiving the pre-scheduling information sent by the RIS control server, the target RIS device first calculates the radiation angle of the sub-beam alignment based on the target location and schedules coverage of that azimuth. If the pre-scheduling information includes enhancement requirements, the sub-beam signal is enhanced accordingly. The above operations continue for the duration of resource scheduling specified in the pre-scheduling information.

[0072] Taking a specific implementation as an example, assume a scenario deploying 3 RIS devices (RIS1, RIS2, RIS3), 3 base stations with edge computing capabilities (base station 1, base station 2, base station 3), and 1 RIS control server. A drone (user terminal) flies along a preset route at a speed of 120 km / h and needs to enhance signal coverage through the RIS devices. Assume base station 1 receives the terminal's actual location information (106.50°E, 29.539°N, 360m) from RIS1, predicts the terminal's location information for the next T=1s as (106.50°E, 29.545°N, 360m), the current RIS number (RIS1), and the target RIS number (RIS2), and reports this information as mobility scheme data to the RIS control server.

[0073] After receiving the data reported by base station 1, the RIS control server verifies the target RIS device corresponding to the predicted location by improving the KNN model.

[0074] Data preparation: Database D contains historical sample data (such as the location-RIS number mapping of past drone flights), and the samples to be classified are the predicted location information (106.50°E, 29.545°N, 360m). Distance Calculation: The distance between the sample to be classified and each sample terminal in the database is calculated using a three-dimensional spatial distance formula. For example, the distance between a sample point (106.50°E, 29.544°N, 360m) within the RIS2 coverage area of ​​the database and the sample to be classified is calculated as follows: same altitude distance (Calculated based on latitude and longitude difference), altitude difference Δh = 0m, final distance Select k=5 nearest neighbor sample terminals, of which 3 belong to RIS2, and the average distance between these 3 samples and the sample to be classified is 105m. Assuming that the farthest effective coverage distance of RIS2 is 200m, take the distance adjustment coefficient ε=0.8, and calculate the coverage distance threshold of RIS2 as 200m×ε=160m. The average distance is less than the coverage distance threshold, so the coverage requirement is met. Therefore, the target RIS device is confirmed to be RIS2.

[0075] Furthermore, the RIS control server issues pre-scheduling instructions to RIS1 (the original RIS device), RIS2 (the target RIS device), base station 1 (the original base station), and base station 2 (the target base station corresponding to RIS2). The instructions are as follows: Base station pre-scheduling information: resource scheduling duration RIS device number (base station 1 corresponds to RIS1, base station 2 corresponds to RIS2). RIS pre-scheduling information: resource scheduling duration 2s, target location (106.50°E, 29.545°N, 360m), enhancement requirements (enable signal enhancement).

[0076] Furthermore, the base station and RIS equipment implement a pre-scheduling strategy: Base Station 2: Adjust antenna weights and beam parameters to align the antenna main lobe with the direction of RIS2; increase the link power from the base station to RIS2, and reserve 10 RB resources (for drone access) for 2 seconds; Base Station 1: Maintain existing link parameters until the drone is fully switched to RIS2 to avoid signal interruption during the switchover process.

[0077] RIS2: Calculate the sub-beam radiation angle (88° horizontal, 2° vertical) based on the target location, and schedule the sub-beam to cover the azimuth; activate the signal enhancement function to increase the beam gain for 2 seconds; RIS1: Maintain existing beam coverage until the drone leaves its coverage area, ensuring a smooth handover transition.

[0078] Understandably, 1 second later, the drone enters the coverage area of ​​RIS2 according to the predicted trajectory. At this time, RIS2 has already completed beam scheduling and signal enhancement, and base station 2 has reserved resources. The drone does not need to wait for the link to be established and can directly access base station 2 through RIS2 to achieve seamless handover. After the handover is completed, RIS2 continues to measure the drone's position, and the edge computing module of base station 2 repeats the above prediction process. If the drone will subsequently move to RIS3, RIS3's pre-scheduling will be started in advance to continuously ensure signal coverage quality in high-speed mobile scenarios.

[0079] Using the technical means of this invention, the RIS control server determines the target RIS device of the terminal based on the improved KNN target RIS device identification model, thereby formulating a precise pre-scheduling strategy so that relevant base stations and RIS devices can perform targeted resource pre-scheduling according to the pre-scheduling strategy, effectively improving the mobility performance of the terminal.

[0080] See Figure 2 This is a flowchart illustrating a method for improving terminal mobility performance applied to a base station, provided by an embodiment of the present invention. The method includes steps S21 to S23: S21. Obtain the preset mapping relationship between the coverage areas of the RIS devices, base stations, and RIS devices from the RIS control server; S22. Based on the actual location information of the terminal and the mapping relationship, predict the predicted location information and movement plan of the terminal at a future preset time, and generate movement plan data; S23. The mobility scheme data is reported to the RIS control server so that when the RIS control server determines the target RIS device of the terminal based on the mobility scheme data, it generates a pre-scheduling strategy for the relevant RIS device and the relevant base station corresponding to the relevant RIS device.

[0081] In this embodiment of the invention, the RIS control server obtains the basic parameter information of each RIS device, calculates the coverage area information of each RIS device, and obtains the correspondence between the RIS device and the base station, thereby obtaining and storing the mapping relationship of "RIS device-base station-coverage area".

[0082] The RIS device measures the actual location information of the terminal users occupying its signal in real time and reports it to the corresponding base station.

[0083] The edge computing module in the base station predicts the location information of the highly mobile terminal at a future preset time T based on the reported terminal location information, determines the user's possible movement plan, and then the edge computing module reports the analysis results and the data used to the RIS control server.

[0084] Preferably, the relocation scheme includes: moving to the coverage area of ​​another RIS device, continuing to maintain the currently occupied original RIS device, or moving out of the coverage area of ​​the original RIS device but unable to match a new RIS device.

[0085] Preferably, the mobility plan data also includes the actual location information of the terminal and the information of the original RIS device. When the mobility plan involves moving to the coverage area of ​​other RIS devices, the mobility plan data also includes the information of the target RIS device initially predicted by the base station. The base station reports the data used in edge computing analysis and the generated analysis results to the RIS control server, which helps to provide a certain data foundation for the RIS control server's decision-making and improves the accuracy of the RIS control server's decision-making.

[0086] The RIS control server, based on the reported mobility scheme data and combined with historical big data resources, performs modeling and final analysis and decision-making to predict the target RIS device that the terminal will occupy at the preset future time T. When the target RIS device is determined, a pre-scheduling strategy is generated and sent to the relevant base stations and relevant RIS devices, thereby controlling the relevant base stations and relevant RIS devices to implement the pre-scheduling strategy and adjust the working parameters of themselves and / or relevant serving cells to improve the terminal's mobility performance.

[0087] The relevant RIS device includes the target RIS device, and the relevant base station includes the target base station to which the target RIS device belongs. The target RIS device refers to the RIS device that the terminal will occupy at a predetermined future time T. The target RIS device can be a new RIS device or the original RIS device currently occupied by the terminal.

[0088] Preferably, when the target RIS device is different from the original RIS device currently occupied by the terminal, the related RIS device also includes the original RIS device, and the related base station also includes the original base station corresponding to the original RIS device.

[0089] By employing the technical means of this invention, the base station predicts the terminal user's location information and movement plan for a predetermined time in the future. The RIS control server then makes the final decision based on the predictive analysis results of the base station. When it is determined that the terminal will occupy a target RIS device in the predetermined time, a pre-scheduling strategy for the relevant RIS device and base station is generated. This invention pre-schedules relevant base stations and RIS devices during terminal movement, pre-scheduling beam resources to form coverage and establishing links from the target RIS device to the serving cell, thereby reducing processing latency and minimizing lag. Furthermore, this invention utilizes edge computing power on the base station side, placing a portion of the computing tasks at the forefront and using an edge-computing RIS control server for overall control, forming a two-layer processing mechanism that further reduces processing latency and effectively improves the mobility performance of user terminals, especially for high-speed mobile users.

[0090] In a preferred embodiment, step S22, namely, predicting the terminal's predicted location information and movement plan at a preset time based on the terminal's actual location information and the mapping relationship, and generating movement plan data, includes steps S221 to S225: S221. Obtain the relative position parameters between the terminal and the RIS device reported by the RIS device; S222. Based on the three-dimensional coordinate information of the RIS device and the relative position parameters, the three-dimensional coordinate information of the terminal is converted and used as the actual position information; S223. Calculate the moving speed of the terminal based on the actual location information of the terminal within a preset sampling time. S224. Based on the actual location information and the moving speed, predict the predicted location information of the terminal at a future preset time. S225. Based on the coverage area of ​​each RIS device in the mapping relationship, predict the movement plan of the terminal within a preset time period in the future.

[0091] In this embodiment of the invention, the RIS device measures the location information of the terminal users occupying its signal in real time and reports it to the base station to which the RIS device belongs. Multiple RIS elements of the RIS device form an antenna array. When a user signal arrives at different RIS elements, there is a phase difference between the signals received by the antennas of the RIS elements at different locations. By calculating the phase difference, the horizontal and vertical angles of arrival of the signal are estimated. By calculating the round-trip delay of the signal from the RIS device to the terminal user and then from the terminal user to the RIS device, the time advance is obtained, and the following relative position parameters are obtained: : The horizontal angle of arrival of the antennas of the intelligent metasurface device j and the coverage terminal i; : The vertical angle of arrival of the antennas of the intelligent metasurface device j and the coverage terminal i; : The time lead between the intelligent metasurface device j and the coverage terminal i.

[0092] Furthermore, the base station edge computing module predicts the location of the terminal user over a future time period T based on the terminal user's actual location information. Firstly, it predicts the location based on the longitude, latitude, and altitude of the RIS device. Using [a reference point], the relative position parameters between the terminal and the RIS device are […]. ] transformed into [ The system uses time-series data of longitude, latitude, and altitude coordinates, and then calculates the terminal's moving speed based on the user's displacement distance and time. A location prediction model is then established for high-speed mobile users whose movement speed exceeds a threshold.

[0093] To improve edge computing efficiency and reduce latency, the system uses a model with low time complexity for modeling. Based on the laws of object motion, within a short time period, the trajectory generally does not exhibit particularly complex patterns. Therefore, cubic multinomial regression models are constructed for longitude, latitude, and altitude respectively for fitting and training. The triplet models are as follows:

[0094]

[0095]

[0096] Where v is a time point, , , and These are the longitude model coefficients, which are fitting parameters for the variation of longitude over time. , , and These are the latitude model coefficients, which are the fitting parameters for latitude changing over time. , , and The elevation model coefficients are fitting parameters for elevation changes over time.

[0097] Furthermore, based on the constructed location triplet model, the location vector of the terminal at a future preset time T is predicted. Further, based on the coverage area information of each RIS device in the "RIS device-base station-coverage area" mapping relationship, the RIS device that the terminal user will occupy in the future preset time T is determined.

[0098] Based on the RIS device that the terminal will occupy in the future at a preset time T, the possible movement options for the user are determined. These include moving to the coverage area of ​​another RIS device, continuing to occupy the current RIS device, or moving out of the coverage area of ​​the original RIS device but unable to find a new RIS device. The base station edge computing module reports the analysis results for moving to other RIS devices and moving out of the coverage area of ​​the original RIS device but unable to find a new RIS device. Specific information includes the measured actual location information of the terminal, the predicted location information (the number of the currently occupied original RIS device), and the predicted target RIS device number. When no RIS device can be matched, the predicted target RIS device number information is empty.

[0099] Taking a specific implementation as an example, suppose the scenario involves deploying 3 RIS devices (RIS1, RIS2, RIS3), 3 base stations with edge computing capabilities (base station 1, base station 2, base station 3), and 1 RIS control server. The drone (user terminal) flies along a preset route at a speed of 120km / h and needs to enhance signal coverage through the RIS devices.

[0100] During the flight of the UAV, it first enters the coverage area of ​​RIS1. RIS1 measures the UAV's position information in real time through its antenna array: by using the phase difference of the UAV signals received by different RIS units, it estimates the horizontal angle of arrival AoA=85° and the vertical angle of arrival ZoA=2°; by using the round-trip time difference of the signal, it obtains the time advance TA=3.3μs (corresponding to a straight-line distance of about 1000m between RIS1 and the UAV); RIS1 reports the relative position parameters (AoA=85°, ZoA=2°, TA=3.3μs) and its own number (RIS1) to the corresponding base station 1.

[0101] The edge computing module of base station 1 uses the coordinates of RIS1 (106.50°E, 29.53°N, 350m) as a reference point to convert the relative position parameters (AoA, ZoA, TA) into the absolute three-dimensional coordinates of the UAV. Specifically, based on TA, the straight-line distance is calculated to be 1000m. Combining AoA and ZoA, the current coordinates of the UAV are obtained as (106.50°E, 29.535°N, 360m). Simultaneously, base station 1 collects the UAV's position data every 0.1s, obtaining 5 sets of time-series data. Based on the latitude change (0.004°N) and time (0.4s) of the time-series data, the UAV's flight speed is calculated to be approximately 120km / h, exceeding the preset threshold of 80km / h, thus classifying it as a high-speed mobile user. Since the UAV flies at a constant speed along the latitude direction, with no change in longitude and altitude, the triplet model is simplified as follows: Longitude: lon = 106.50° (α3=α2=α1=0, α0=106.50°); Latitude: lat = 0.0025v³ + 0.005v² + 0.001v + 29.535 (v is the time point, unit: 0.1s); Altitude: alt = 360m (γ3=γ2=γ1=0, γ0=360m).

[0102] Base station 1 predicts its location in the future at T=1s (i.e., 10 time points later): Substituting v=10 into the triplet model, the predicted coordinates are obtained (106.50°E, 29.545°N, 360m). Querying the coverage areas of each RIS device in the mapping relationship reveals that these predicted coordinates belong to the coverage area of ​​RIS2. Therefore, the movement plan is determined as follows: the drone will move from RIS1 to RIS2.

[0103] Base station 1 reports mobility plan data to the RIS controller, including: current location (106.50°E, 29.539°N, 360m), predicted location (106.50°E, 29.545°N, 360m), current RIS number (RIS1), and target RIS number (RIS2).

[0104] Using the technical means of this invention, a location time series modeling method is adopted to construct cubic multinomial regression models for longitude, latitude, and altitude respectively for fitting training. This fully considers the actual scenario, reduces computational complexity, and ensures accuracy.

[0105] Preferably, after step S23, the method further includes step S24: S24. When the pre-scheduling policy is received from the RIS control server, the pre-scheduling policy is executed.

[0106] When the base station is the target base station, the pre-scheduling strategy includes: resource scheduling duration, information of the target RIS device, and the antenna weight parameters, beam parameters, power parameters, and RB resource reservation number of the serving cell corresponding to the target RIS device that need to be adjusted.

[0107] It should be noted that the terminal mobility performance improvement method applied to the base station provided in the embodiments of the present invention corresponds one-to-one with all the process steps of the terminal mobility performance improvement method applied to the RIS control server in the above embodiments. The working principle and beneficial effects of the two are the same, so they will not be described again.

[0108] This invention also provides a terminal mobility performance enhancement device, applied to a RIS control server, the device comprising: The mapping relationship establishment module is used to establish the mapping relationship between RIS devices, base stations, and the coverage areas of RIS devices; A mobile plan data receiving module is used to receive mobile plan data of a terminal reported by a base station; wherein, the mobile plan data includes the predicted location information and mobile plan of the terminal at a preset future time, and the predicted location information and the mobile plan are predicted by the base station based on the actual location information of the terminal and the mapping relationship; A pre-scheduling strategy generation module is used to generate a pre-scheduling strategy for the relevant RIS devices and the relevant base stations corresponding to the relevant RIS devices when the target RIS device of the terminal is determined based on the mobility scheme data; wherein, the relevant RIS devices include the target RIS devices, and the target RIS devices refer to the RIS devices that the terminal will occupy in the future preset time. The pre-scheduling policy distribution module is used to distribute the pre-scheduling policy to the relevant base stations and the relevant RIS devices.

[0109] It should be noted that the terminal mobility performance enhancement device for a RIS control server provided in this embodiment of the invention is used to execute all the process steps of the terminal mobility performance enhancement method for a RIS control server in the above embodiment. The working principles and beneficial effects of the two are one-to-one, so they will not be described again.

[0110] This invention also provides a terminal mobility performance enhancement device applied to a base station, the device comprising: The mapping relationship acquisition module is used to obtain the preset mapping relationship between RIS devices, base stations, and the coverage areas of RIS devices from the RIS control server; The mobile plan data generation module is used to predict the terminal's predicted location information and mobile plan at a future preset time based on the terminal's actual location information and the mapping relationship, and generate mobile plan data. The mobile scheme data reporting module is used to report the mobile scheme data to the RIS control server, so that when the RIS control server determines the target RIS device of the terminal based on the mobile scheme data, it generates a pre-scheduling strategy for the relevant RIS device and the relevant base station corresponding to the relevant RIS device.

[0111] It should be noted that the terminal mobility performance enhancement device for base stations provided in this embodiment of the invention is used to execute all the process steps of the terminal mobility performance enhancement method for base stations described in the above embodiment. The working principles and beneficial effects of the two are one-to-one, so they will not be described again.

[0112] See Figure 3 This is a schematic diagram of a terminal mobility performance enhancement system provided in an embodiment of the present invention. The embodiment of the present invention also provides a terminal mobility performance enhancement system 10, including a RIS device 11, a base station 12 and a RIS control server 13. The RIS device 11 is used to obtain the actual location information of the terminal occupying its own signal and report it to the base station to which it belongs; and to execute the pre-scheduling strategy issued by the RIS control server. The base station 12 is used to predict the terminal's predicted location information and movement plan in the future preset time based on the terminal's actual location information and the preset mapping relationship between the coverage areas of the RIS device, base station and RIS device obtained from the RIS control server, generate movement plan data, and report the movement data plan to the RIS control server; and execute the pre-scheduling strategy issued by the RIS control server. The RIS control server 13 is used to establish a mapping relationship between RIS devices, base stations, and the coverage areas of RIS devices. When the target RIS device of the terminal is determined according to the mobility scheme data, a pre-scheduling policy is generated for the relevant RIS devices and the relevant base stations corresponding to the relevant RIS devices, and the pre-scheduling policy is sent to the relevant base stations and the relevant RIS devices. The relevant RIS devices include the target RIS devices, which refer to the RIS devices that the terminal will occupy in the future preset time.

[0113] Preferably, see Figure 4 This is a schematic diagram of a preferred terminal mobility performance enhancement system in an embodiment of the present invention. The system 10 also includes an edge UPF (User Plane Function).

[0114] In this embodiment of the invention, the architecture of the terminal mobility performance enhancement system under intelligent metasurface coverage includes: a multi-beam RIS device, a base station device (a base station with certain edge computing capabilities), an edge UPF, and a RIS control server. The RIS device provides users with enhanced signal coverage and calculates and reports the location information of target users; the base station is responsible for providing edge computing power to achieve real-time inference and providing wireless networks for users; the edge UPF performs data routing and forwarding; and the RIS control server performs modeling and determines resource pre-scheduling strategies.

[0115] The RIS device employs a novel programmable subwavelength two-dimensional metamaterial, using digital coding to actively and intelligently control electromagnetic waves, achieving controllable reflection and transmission of 5G signals. It possesses multi-beam capability, enabling coverage of targets in different directions. It calculates the location parameters of end users and interacts with the serving base station to dynamically control link resources.

[0116] Base station equipment: Currently, base stations possess edge computing capabilities by adding computing power cards, etc. Base stations with inherent computing capabilities have been widely deployed in the network. The base station edge computing module mainly processes and calculates data, predicts future locations based on the location information of terminal users reported by the RIS device, determines the target RIS device for handover, controls the pre-allocation of link resources, and interacts with the RIS control server.

[0117] Edge UPF: Responsible for routing and forwarding service data, it directs user equipment service data to appropriate destinations according to policies, such as routing data from base station edge computing modules to the RIS control server. It identifies different service types and user data for policy-based traffic distribution and processing.

[0118] RIS Control Server: Interacts with base stations and base station edge computing modules, receives relevant service data, performs data processing, modeling and prediction, and formulates pre-scheduling strategies for base stations and RIS devices.

[0119] By employing the technical means of this invention, a terminal mobility performance enhancement system is constructed, comprising RIS devices, base stations, and a RIS control server. The base station predicts the terminal user's location and movement plan for a predetermined time in the future. The RIS control server makes the final decision based on the predictive analysis results of the base station. When it is determined that the terminal will occupy a target RIS device in the predetermined time, a pre-scheduling strategy for the relevant RIS device and base station is generated. This invention pre-schedules relevant base stations and RIS devices during terminal movement, pre-scheduling beam resources to form coverage and establishing links from the target RIS device to the serving cell, thereby reducing processing latency and minimizing lag. Furthermore, this invention utilizes edge computing power on the base station side, placing a portion of the computing tasks at the forefront and using the edge-computing RIS control server for overall control, forming a two-layer processing mechanism that further reduces processing latency and effectively improves the mobility performance of user terminals, especially for high-speed mobile users.

[0120] This invention also provides a terminal mobility performance enhancement device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the terminal mobility performance enhancement method as described in any of the above embodiments.

[0121] This invention also provides a computer-readable storage medium, which includes a stored computer program, wherein the computer program, when running, controls the device where the computer-readable storage medium is located to execute the terminal mobility performance improvement method as described in any of the above embodiments.

[0122] This invention also provides a computer program product, which includes a computer program or computer instructions. When the computer program or computer instructions are executed by a processor, they implement the terminal mobility performance improvement method as described in any of the above embodiments.

[0123] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0124] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for improving the mobility performance of a terminal, characterized in that, The method, applied to an intelligent metasurface RIS control server, includes: Establish a mapping relationship between the coverage areas of RIS devices, base stations, and RIS devices; The system receives mobile plan data of a terminal reported by a base station; wherein the mobile plan data includes the predicted location information and mobile plan of the terminal at a future preset time, and the predicted location information and the mobile plan are predicted by the base station based on the actual location information of the terminal and the mapping relationship. When the target RIS device of the terminal is determined based on the mobility scheme data, a pre-scheduling strategy is generated for the relevant RIS device and the relevant base station corresponding to the relevant RIS device; wherein, the relevant RIS device includes the target RIS device, and the target RIS device refers to the RIS device that the terminal will occupy in the future preset time. The pre-scheduling strategy is distributed to the relevant base stations and the relevant RIS devices.

2. The terminal mobility performance improvement method as described in claim 1, characterized in that, When the target RIS device is different from the original RIS device currently occupied by the terminal, the relevant RIS device also includes the original RIS device.

3. The terminal mobility performance improvement method as described in claim 1, characterized in that, The establishment of the mapping relationship between the RIS device, the base station, and the coverage area of ​​the RIS device includes: Obtain the base station corresponding to each RIS device; Obtain the engineering parameters for the coverage area of ​​each RIS device; Based on the engineering parameters, determine the three-dimensional coordinate information, main radiation direction, and coverage boundary of each RIS device; Based on the three-dimensional coordinate information, the main radiation direction, and the coverage boundary, calculate the coverage area information of each RIS device; Based on the base station and coverage area information corresponding to each RIS device, a mapping relationship is constructed between the RIS device, the base station, and the coverage area of ​​the RIS device.

4. The terminal mobility performance improvement method as described in claim 3, characterized in that, The engineering parameters include longitude, latitude, altitude, azimuth, tilt angle, horizontal emission angle, vertical emission angle, horizontal beamwidth, vertical beamwidth, and maximum effective coverage distance. The main radiation direction includes the horizontal radiation direction and the vertical radiation direction.

5. The terminal mobility performance improvement method as described in claim 1, characterized in that, The relocation schemes include: moving to the coverage area of ​​other RIS devices, continuing to maintain the currently occupied original RIS device, and moving out of the coverage area of ​​the original RIS device but unable to match a new RIS device.

6. The terminal mobility performance improvement method as described in claim 5, characterized in that, The mobile solution data also includes the actual location information of the terminal and the information of the original RIS device; When the mobility plan involves moving to the coverage area of ​​other RIS devices, the mobility plan data also includes information about the target RIS devices initially predicted by the base station.

7. The terminal mobility performance improvement method as described in claim 5 or 6, characterized in that, When the target RIS device of the terminal is determined based on the mobility scheme data, a pre-scheduling strategy is generated for the relevant RIS device and the relevant base station corresponding to the relevant RIS device, including: The mobile scheme data is input into a preset RIS device identification model for calculation, and the identification result output by the RIS device identification model is obtained; wherein, the identification result is that the terminal has a target RIS device and the corresponding target RIS device, or the terminal does not have a target RIS device; When the identification result indicates that the terminal has a target RIS device, a pre-scheduling strategy is generated for the relevant RIS device and the relevant base station corresponding to the relevant RIS device.

8. The terminal mobility performance improvement method as described in claim 7, characterized in that, The RIS device identification model is a KNN model, and the RIS device identification model is used for: Calculate the distance between the predicted location information and the location information of each sample terminal in the preset database; The N nearest neighbor sample terminals of the terminal are selected based on the distance; where N≥1; Based on the information of the RIS device corresponding to the nearest neighbor sample terminal, candidate RIS devices are determined; Based on the coverage area of ​​the candidate RIS devices, determine whether the candidate RIS devices meet the coverage requirements for the terminal; If yes, the candidate RIS device is selected as the target RIS device, and the terminal is output as having a target RIS device; otherwise, the terminal is output as not having a target RIS device.

9. The terminal mobility performance improvement method as described in claim 1, characterized in that, The pre-scheduling strategy for the target RIS device includes: resource scheduling duration, target location, and adjustment of the radiation angle of the sub-beam alignment and signal enhancement requirements based on the target location; the target location is the predicted location information of the terminal. The pre-scheduling strategy for the target base station includes: resource scheduling duration, information about the target RIS device, and the antenna weight parameters, beam parameters, power parameters, and RB resource reservation number of the serving cell corresponding to the target RIS device that need to be adjusted.

10. A method for improving the mobility performance of a terminal, characterized in that, Applied to a base station, the method includes: Obtain the preset mapping relationship between RIS devices, base stations, and the coverage areas of RIS devices from the RIS control server; Based on the actual location information of the terminal and the mapping relationship, predict the predicted location information and movement plan of the terminal in the future preset time, and generate movement plan data; The mobility scheme data is reported to the RIS control server so that when the RIS control server determines the target RIS device of the terminal based on the mobility scheme data, it generates a pre-scheduling strategy for the relevant RIS device and the relevant base station corresponding to the relevant RIS device.

11. The terminal mobility performance improvement method as described in claim 10, characterized in that, The step of predicting the terminal's predicted location information and movement plan at a future preset time based on the terminal's actual location information and the mapping relationship, and generating movement plan data, includes: Obtain the relative position parameters between the terminal and the RIS device reported by the RIS device; Based on the three-dimensional coordinate information of the RIS device and the relative position parameters, the three-dimensional coordinate information of the terminal is converted and used as the actual position information; The moving speed of the terminal is calculated based on the actual location information of the terminal within a preset sampling time. Based on the actual location information and the moving speed, predict the predicted location information of the terminal at a future preset time. Based on the coverage area of ​​each RIS device in the mapping relationship, the mobile plan of the terminal within a preset time period is predicted.

12. The terminal mobility performance improvement method as described in claim 10, characterized in that, The method further includes: When the pre-scheduling policy is received from the RIS control server, the pre-scheduling policy is executed; wherein, when the base station is the target base station, the pre-scheduling policy includes: resource scheduling duration, information of the target RIS device, and antenna weight parameters, beam parameters, power parameters and RB resource reservation number of the serving cell corresponding to the target RIS device that need to be adjusted.

13. A device for enhancing terminal mobility, characterized in that, The device, applied to a RIS control server, includes: The mapping relationship establishment module is used to establish the mapping relationship between RIS devices, base stations, and the coverage areas of RIS devices; A mobile plan data receiving module is used to receive mobile plan data of a terminal reported by a base station; wherein, the mobile plan data includes the predicted location information and mobile plan of the terminal at a preset future time, and the predicted location information and the mobile plan are predicted by the base station based on the actual location information of the terminal and the mapping relationship; A pre-scheduling strategy generation module is used to generate a pre-scheduling strategy for the relevant RIS devices and the relevant base stations corresponding to the relevant RIS devices when the target RIS device of the terminal is determined based on the mobility scheme data; wherein, the relevant RIS devices include the target RIS devices, and the target RIS devices refer to the RIS devices that the terminal will occupy in the future preset time. The pre-scheduling policy distribution module is used to distribute the pre-scheduling policy to the relevant base stations and the relevant RIS devices.

14. A device for enhancing terminal mobility, characterized in that, Applied to a base station, the device includes: The mapping relationship acquisition module is used to obtain the preset mapping relationship between RIS devices, base stations, and the coverage areas of RIS devices from the RIS control server; The mobile plan data generation module is used to predict the terminal's predicted location information and mobile plan at a future preset time based on the terminal's actual location information and the mapping relationship, and generate mobile plan data. The mobile scheme data reporting module is used to report the mobile scheme data to the RIS control server, so that when the RIS control server determines the target RIS device of the terminal based on the mobile scheme data, it generates a pre-scheduling strategy for the relevant RIS device and the relevant base station corresponding to the relevant RIS device.

15. A terminal mobility performance enhancement system, characterized in that, This includes RIS equipment, base stations, and RIS control servers; The RIS device is used to obtain the actual location information of the terminal occupying its own signal and report it to the base station to which it belongs; And, execute the pre-scheduling strategy issued by the RIS control server; The base station is used to predict the terminal's predicted location information and movement plan at a future preset time based on the terminal's actual location information and the preset mapping relationship between the coverage areas of the RIS device, the base station, and the RIS device obtained from the RIS control server, generate movement plan data, and report the movement data plan to the RIS control server. And, execute the pre-scheduling strategy issued by the RIS control server; The RIS control server is used to establish a mapping relationship between RIS devices, base stations, and the coverage areas of RIS devices. When the target RIS device of the terminal is determined based on the mobility scheme data, a pre-scheduling policy is generated for the relevant RIS devices and the relevant base stations corresponding to the relevant RIS devices, and the pre-scheduling policy is sent to the relevant base stations and the relevant RIS devices. The relevant RIS devices include the target RIS devices, which refer to the RIS devices that the terminal will occupy at the preset future time.

16. A device for enhancing terminal mobility performance, characterized in that, The device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the terminal mobility performance enhancement method as described in any one of claims 1 to 12.

17. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform the terminal mobility performance enhancement method as described in any one of claims 1 to 12.

18. A computer program product, characterized in that, The computer program product includes a computer program or computer instructions, which, when executed by a processor, implement the terminal mobility performance enhancement method as described in any one of claims 1 to 12.

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