5G base station intelligent reflector auxiliary beam enhancement method and system

Abstract

The invention discloses a 5G base station intelligent reflector auxiliary beam enhancement method and system, and relates to the field of wireless communication networks, and the method comprises the steps: determining a plurality of to-be-enhanced regions of a signal; calculating a direct incidence path and a reflection path from each to-be-enhanced area to the intelligent reflector array; determining signal loss values on the direct incidence path and the reflection path; determining priorities corresponding to the plurality of to-be-enhanced areas; when the signal power in the horizontal direction is higher than the signal power in the vertical direction by a preset power value, activating a horizontal polarization subunit in the dual-polarization reflection unit; when the signal power in the vertical direction is higher than the signal power in the horizontal direction by a preset power value, activating a vertical polarization subunit in the dual-polarization reflection unit; when the difference value between the signal power in the vertical direction and the signal power in the horizontal direction is smaller than a preset power value, the horizontal polarization subunit and the vertical polarization subunit are activated at the same time; and adjusting the phase of the activated polarization subunit. According to the invention, the stability and reliability of communication in the high-speed rail station are improved.

Description

Technical Field

[0001] The present application relates to the field of wireless communication networks, and in particular to a 5G base station intelligent reflector-assisted beam enhancement method and system. Background Art

[0002] With the rapid development and widespread adoption of 5G communication technology, base station network coverage quality has become a key factor affecting user experience. In complex urban electromagnetic environments, 5G signals are susceptible to significant penetration loss and numerous coverage blind spots due to factors such as building obstruction and multipath effects. This leads to degraded network performance and a poor user experience. Furthermore, base stations need to continuously transmit signals at high power, resulting in energy waste.

[0003] Static beamforming is a commonly used technique in related technologies. This technique creates directional beams by presetting fixed phase weights in the base station antenna array to enhance signal coverage in a specific area. By adjusting the phase parameters of the antenna array, this technique improves signal transmission quality, reduces signal penetration loss, and enhances network coverage.

[0004] However, in high-speed rail station applications, static beamforming technology generates multiple reflections and scattering during signal transmission due to the metal dome structure of the waiting hall and the significant time-varying passenger density. When a high-speed train arrives at the station, the rapid flow of passengers causes a dramatic change in the electromagnetic environment. This, combined with signal reflections from the metal structure, causes the preset beam direction to deviate from the actual requirements, increasing the time-varying nature of received signal power and reducing the reliability of the communication system. Summary of the Invention

[0005] The present application provides a 5G base station intelligent reflector-assisted beam enhancement method and system for improving the stability and reliability of communications within high-speed railway stations.

[0006] In the first aspect, the present application provides a 5G base station intelligent reflector-assisted beam enhancement method, which determines several areas to be enhanced where the signal strength is lower than a preset signal strength threshold based on the collected signal strength values ​​of each monitoring point in the high-speed railway station; Get real-time crowd density data in the waiting hall; Calculate the direct path and reflected path from each area to be enhanced to the smart reflector array, where the reflected path includes the path after the signal is reflected by the metal dome structure; Determine the signal loss values ​​on the direct path and the reflected path according to the received signal reflection intensity value and the preset signal transmission intensity value; Determine the priorities of several areas to be enhanced according to the positions of the crowd density data in the preset priority comparison table; The signal powers in the horizontal and vertical directions of the area to be enhanced are measured respectively; when the signal power in the horizontal direction is higher than the signal power in the vertical direction by a preset power value, the horizontal polarization subunit in the dual-polarization reflection unit is activated; when the signal power in the vertical direction is higher than the signal power in the horizontal direction by a preset power value, the vertical polarization subunit in the dual-polarization reflection unit is activated; when the difference between the signal power in the vertical direction and the signal power in the horizontal direction is less than a preset power value, the horizontal polarization subunit and the vertical polarization subunit are activated simultaneously; Adjust the phase of the activated polariton unit so that the signal of the 5G base station, after being reflected by the intelligent reflector array, will be different from all reflection paths with signal loss values ​​greater than the preset loss value, and will be aligned with each area to be enhanced according to priority.

[0007] By adopting the above technical solution, by obtaining real-time crowd density data in the waiting hall and combining it with signal strength monitoring data, areas requiring signal enhancement are identified, thus avoiding ineffective coverage of signal resources. Dual-polarization reflector units are used to respond to signals in the horizontal and vertical directions respectively, and the corresponding polarization sub-units are selectively activated according to the signal power difference, making the signal enhancement more directional and selective. By measuring the signal loss values ​​on the direct path and the reflected path, and combining the priority determined by the crowd density data, the system can avoid propagation paths with large signal losses and prioritize limited signal resources to areas with dense crowds and poor signal coverage, thereby improving the utilization efficiency of signal resources. At the same time, the reflection effect of the metal dome structure on the signal is taken into account, and the phase of the reflector unit is adjusted in real time through the FPGA controller, so that the system can establish a stable signal transmission channel in a complex indoor environment, improving the signal coverage quality within the high-speed rail station.

[0008] In conjunction with some embodiments of the first aspect, in some embodiments, determining, based on the collected signal strength values ​​of each monitoring point in the high-speed railway station, several areas to be enhanced whose signal strength is lower than a preset signal strength threshold specifically includes: The high-speed railway station is divided into several monitoring areas of equal area with each monitoring point in the station as the center; Collect the signal strength value of each monitoring point; The monitoring areas whose signal strength values ​​are lower than a preset signal strength threshold are determined as areas to be enhanced, and a plurality of areas to be enhanced are obtained.

[0009] By employing this technical solution, the high-speed rail station is divided into monitoring areas of equal size and signal strength values ​​are collected at each monitoring point, creating a uniform and complete signal strength distribution map. This grid-based monitoring method enables the system to accurately locate areas where signal strength falls below the threshold and create a map of signal coverage blind spots, avoiding ineffective projection of signal resources in areas with strong signal strength and improving the system's signal enhancement efficiency.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, calculating the direct path and the reflected path from each area to be enhanced to the smart reflective surface array specifically includes: Obtain the installation height, azimuth, and elevation of the intelligent reflector array, the three-dimensional coordinates of the monitoring points in the area to be enhanced, and the shape parameters of the metal dome structure of the waiting hall, including the curvature radius of the dome and the inclination angle of the reflector surface; Establish a three-dimensional coordinate system with the center of the waiting hall ground as the origin; Calculate the direct path vector from the smart reflector array to each monitoring point based on the installation height, azimuth, elevation angle and the three-dimensional coordinates of the monitoring point; According to the direct path vector and the shape parameters of the metal dome structure, the reflection path vector of the signal after being reflected by the metal dome structure and reaching each monitoring point is calculated using the geometric optics reflection law. Convert the direct path vector and the reflected path vector to the direct path and the reflected path.

[0011] By adopting this technical solution, a three-dimensional coordinate system with the center of the waiting hall floor as the origin was established. This, combined with the installation parameters of the smart reflector array and the structural parameters of the metal dome, enabled precise modeling of the signal propagation path. The law of geometric optics reflection was used to calculate the signal reflection path within the metal dome structure, accurately describing the multipath propagation characteristics in complex indoor environments. This provided precise directional guidance for phase adjustment of the smart reflector array, reduced energy loss during signal propagation, and improved signal transmission efficiency.

[0012] In conjunction with some embodiments of the first aspect, in some embodiments, after aligning the areas to be enhanced according to priority, the method further includes: Obtain the functional type of each area to be enhanced, including security check area, ticket purchase area and waiting area; Collect the MAC addresses of the terminal devices in each area to be enhanced at preset time intervals; Identify the type of application currently running on each terminal device based on the terminal device MAC address; When a payment application is detected, the signal latency requirement of the area to be enhanced is marked as high priority. When an audio and video application is detected, the signal bandwidth requirement of the area to be enhanced is marked as high priority. When an instant messaging application is detected, the signal stability requirement of the area to be enhanced is marked as high priority. Calculate the proportion of different signal feature requirements in each area to be enhanced; When the signal delay requirement is the highest, the vertical polarization subunit is activated to reduce the signal propagation path; When the signal bandwidth requirement is the highest, both the horizontally polarized sub-unit and the vertically polarized sub-unit are activated simultaneously to increase signal capacity. When the signal stability requirement is the highest, the horizontal polarization subunit is activated to enhance the anti-interference capability.

[0013] By adopting the above technical solution, the system can adaptively adjust the working mode of the polarization subunit according to the signal characteristic requirements of different types of applications. When the proportion of payment applications is high, the vertical polarization subunit is activated to reduce the propagation path. When the proportion of audio and video applications is high, the dual polarization units are activated at the same time to improve signal capacity. When the proportion of instant messaging applications is high, the horizontal polarization subunit is activated to enhance anti-interference capabilities. This signal optimization solution based on application characteristics enables the system to dynamically adjust signal characteristics according to the actual usage needs of users, optimizing the signal service quality while ensuring signal coverage, and improving the actual user experience.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, identifying the type of application currently running on each terminal device based on the terminal device MAC address specifically includes: Get the data packet type of each terminal device based on the MAC address; When the port number in the data packet type is a preset payment application port number, the corresponding terminal device is marked as running a payment application; When the port number in the data packet type is a preset audio and video application port number, the corresponding terminal device is marked as running the audio and video application; When the port number in the data packet type is a preset instant messaging application port number, the corresponding terminal device is marked as running the instant messaging application.

[0015] By adopting the above technical solution, by obtaining the data packet type of the terminal device based on the MAC address and marking the terminal device as running payment, audio and video or instant messaging applications according to the port number in the data packet, the system can accurately distinguish different types of applications, thereby judging the specific signal performance requirements of each terminal device and improving the efficiency of system resource utilization.

[0016] In conjunction with some embodiments of the first aspect, in some embodiments, after aligning the areas to be enhanced according to priority, the method further includes: Within a preset time period before the arrival or departure of a train, the signal strength detection interval for the area to be enhanced is reduced by a preset multiple; When it is determined that the signal strength change value of the area to be enhanced per unit time is greater than a preset change threshold, the activated polarimetric subunits of the smart reflective surface array are divided into a first group of polarimetric subunits and a second group of polarimetric subunits; Controlling the first group of polariton units to maintain signal coverage of the area to be enhanced; The reflection phases of the second group of polariton units are adjusted according to the direction of the signal strength change value, so that the signal coverage area is expanded in the direction of the signal strength change value.

[0017] By adopting the above technical solution, during the preset time period of train arrival or departure, the system responds to rapid changes in signal coverage requirements by reducing the signal strength detection interval and controlling the polarization subunits in groups. When it is detected that the signal strength change per unit time exceeds the threshold, the system divides the polarization subunits into two groups, one group maintains the original coverage, and the other group expands the coverage area according to the direction of the signal change. This group control mechanism enables the system to quickly respond to new signal requirements while maintaining signal stability in the original area. By increasing the signal detection frequency, the system can detect changing trends in signal coverage more promptly. At the same time, the group control strategy avoids the impact of the adjustment process on the original coverage area, improving the continuity and stability of signal coverage when passengers flow rapidly.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, adjusting the reflection phase of the second group of polarimetric subunits according to the direction of the signal strength change value specifically includes: Obtain a signal strength distribution map of the area to be enhanced; determining boundaries of areas with reduced signal strength in the signal strength distribution graph; Calculate the signal strength attenuation value at the area boundary; When it is determined that the attenuation value is greater than the preset attenuation threshold, the reflection phase of the second group of polariton units is adjusted so that the direction of the reflected signal is aligned with the region boundary.

[0019] By employing these technical solutions, the system accurately targets signal enhancements in areas requiring additional coverage. By setting a preset attenuation threshold as a trigger condition, it avoids over-response to slight signal fluctuations. The system adjusts phase based on actual measured signal distribution, rather than a fixed preset solution. This dynamic adjustment based on measured data improves signal reinforcement accuracy and enhances the system's energy efficiency.

[0020] In second aspect, an embodiment of the present application provides a 5G base station intelligent reflecting surface assisted beam enhancement system, which 5G base station intelligent reflecting surface assisted beam enhancement system includes: one or more processors and a memory; the memory is coupled to one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to enable the system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer-readable storage medium comprising instructions, which, when executed on a system, enables the system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer program product, which, when executed on a system, enables the system to execute the method described in any possible implementation manner in the first aspect.

[0023] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. The present application provides a 5G base station intelligent reflector-assisted beam enhancement method, which identifies areas requiring signal enhancement by acquiring real-time crowd density data in the waiting hall and combining it with signal strength monitoring data, thereby avoiding ineffective coverage of signal resources. A dual-polarization reflection unit is used to respond to signals in the horizontal and vertical directions respectively, and the corresponding polarization subunit is selectively activated according to the signal power difference, making the signal enhancement more directional and selective. By measuring the signal loss values ​​on the direct path and the reflected path, and combining the priority determined by the crowd density data, the system can avoid propagation paths with large signal losses, and prioritize limited signal resources to areas with dense crowds and poor signal coverage, thereby improving the utilization efficiency of signal resources. At the same time, the reflection effect of the metal dome structure on the signal is taken into account, and the phase of the reflection unit is adjusted in real time through the FPGA controller, so that the system can establish a stable signal transmission channel in a complex indoor environment, thereby improving the signal coverage quality in the high-speed rail station.

[0024] 2. This application provides a 5G base station intelligent reflector-assisted beam enhancement method. According to the signal characteristic requirements of different types of applications, the system can adaptively adjust the working mode of the polarization subunit. When the proportion of payment applications is high, the vertical polarization subunit is activated to reduce the propagation path. When the proportion of audio and video applications is high, the dual polarization units are activated at the same time to increase the signal capacity. When the proportion of instant messaging applications is high, the horizontal polarization subunit is activated to enhance the anti-interference capability. This signal optimization solution based on application characteristics enables the system to dynamically adjust the signal characteristics according to the actual usage needs of users, optimizes the signal service quality while ensuring signal coverage, and improves the actual user experience.

[0025] 3. The present application provides a 5G base station intelligent reflector assisted beam enhancement method, which responds to the rapid changes in signal coverage requirements by reducing the signal strength detection interval and controlling the polarization subunits in groups within a preset time period when the train arrives or departs. When it is detected that the signal strength change per unit time exceeds the threshold, the system divides the polarization subunits into two groups, one group maintains the original coverage, and the other group expands the coverage area according to the direction of the signal change. This group control mechanism enables the system to quickly respond to new signal requirements while maintaining the stability of the signal in the original area. By increasing the signal detection frequency, the system can detect the changing trend of signal coverage more promptly. At the same time, the group control strategy avoids the impact of the adjustment process on the original coverage area, and improves the continuity and stability of signal coverage when passengers flow rapidly. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is an embodiment of the present application Figure 1 This is a flow chart of a 5G base station intelligent reflector-assisted beam enhancement method in an embodiment of the present application.

[0027] Figure 2 This is a flow chart of a signal enhancement method based on application type identification in an embodiment of the present application.

[0028] Figure 3 This is a schematic diagram of the physical device structure of a 5G base station intelligent reflector assisted beam enhancement system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The terms used in the following examples of the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the specification and appended claims of this application, the singular expressions "a," "an," "said," "above," "the," and "this" are intended to include plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in this application refers to any or all possible combinations comprising one or more of the listed items.

[0030] In the following, the terms "first" and "second" are used for descriptive purposes only and should not be understood to imply or suggest relative importance or implicitly indicate the number of the technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of this application, unless otherwise specified, "plurality" means two or more.

[0031] The following uses an embodiment and combines Figure 1 , a 5G base station intelligent reflector assisted beam enhancement method in an embodiment of the present application is described: See also Figure 1 , which is a flow chart of a 5G base station intelligent reflector-assisted beam enhancement method in an embodiment of the present application.

[0032] S101, determining, based on the collected signal strength values ​​of each monitoring point in the high-speed railway station, several areas to be enhanced whose signal strength is lower than a preset signal strength threshold; The system determines several areas to be enhanced whose signal strength is lower than a preset signal strength threshold based on the collected signal strength values ​​of each monitoring point in the high-speed railway station. Specifically, the system includes: dividing the high-speed railway station into several monitoring areas of equal area with each monitoring point in the high-speed railway station as the center; collecting the signal strength value of each monitoring point; and determining the monitoring areas whose signal strength values ​​are lower than the preset signal strength threshold as areas to be enhanced, thereby obtaining several areas to be enhanced.

[0033] In this step, the system first establishes multiple monitoring points within the high-speed rail station and collects signal strength data at each point. The system then divides the station into several monitoring zones of equal size, each centered around a monitoring point. The system then compares the signal strength of each zone with a preset signal strength threshold and identifies zones with signal strength values ​​below the threshold as areas for enhancement.

[0034] Specifically, the system can implement this step in the following manner: First, multiple monitoring points are reasonably arranged in the high-speed rail station. The number and location of the monitoring points can be determined based on factors such as the area, structural characteristics, and signal coverage requirements of the high-speed rail station. Secondly, the system collects the signal strength value of each monitoring point through monitoring equipment, and the collection time interval can be set according to actual needs. Thirdly, the system divides the high-speed rail station into several monitoring areas according to the location of the monitoring points. The area of ​​each monitoring area is equal to ensure the balance of monitoring. Finally, the system compares the signal strength value of each monitoring area with the preset signal strength threshold, and determines the monitoring area with a signal strength value lower than the threshold as the area to be enhanced, thereby obtaining several areas to be enhanced.

[0035] S102, obtaining real-time crowd density data in the waiting hall; In this step, the system needs to obtain real-time crowd density data for the high-speed rail station waiting hall as a basis for subsequently prioritizing areas for enhancement. The system can obtain this data through the following methods: Crowd counting devices, such as infrared sensors and cameras, are installed at key areas such as the waiting hall entrances and exits, ticket sales areas, and waiting areas to count the number of people entering and leaving in real time. The system can also indirectly estimate the crowd density of the waiting hall using ticket sales data and train schedule information. By aggregating and analyzing data obtained from various channels, the system can generate real-time crowd density data for each area of ​​the waiting hall.

[0036] S103, calculating the direct path and the reflected path from each area to be enhanced to the smart reflective surface array; The system calculates the direct path and reflected path from each area to be enhanced to the smart reflective surface array, specifically including: obtaining the installation height, azimuth and elevation angles of the smart reflective surface array, the three-dimensional coordinates of the monitoring points in the area to be enhanced, and the shape parameters of the metal dome structure of the waiting hall, the shape parameters including the curvature radius of the dome and the inclination angle of the reflecting surface; establishing a three-dimensional coordinate system with the ground center of the waiting hall as the origin; calculating the direct path vector from the smart reflective surface array to each monitoring point based on the installation height, azimuth, elevation angle and the three-dimensional coordinates of the monitoring point; using the law of geometric optics reflection based on the direct path vector and the shape parameters of the metal dome structure, calculating the reflected path vector of the signal reaching each monitoring point after being reflected by the metal dome structure; and converting the direct path vector and the reflected path vector into a direct path and a reflected path.

[0037] The purpose of this step is to calculate the direct and reflected paths from the smart reflector array to each area to be enhanced, providing the necessary data support for subsequent signal enhancement control. This step requires comprehensive consideration of multiple factors, including the installation parameters of the smart reflector array, the location of the area to be enhanced, and the structural characteristics of the waiting hall. Accurate path information is obtained through methods such as geometric calculation and optical modeling.

[0038] During specific implementation, the system first needs to obtain the following key parameters: The installation height, azimuth, and elevation of the smart reflector array determine its position and orientation in three-dimensional space and are the basis for calculating direct and reflected paths.

[0039] The 3D coordinates of the monitoring points in the area to be enhanced. Each area to be enhanced has a corresponding monitoring point, and the coordinates of the monitoring point reflect the specific location of the area in the waiting hall.

[0040] The shape parameters of the metal dome structure of the waiting hall, including the dome's curvature radius and the inclination angle of the reflective surface, determine the geometric shape of the dome's reflective surface and are key to calculating the reflection path.

[0041] The system needs to use a variety of sensors and measurement equipment to collect key parameters of the intelligent reflective surface array, the area to be enhanced, and the waiting hall environment in real time. Specifically: The installation parameters of the intelligent reflector array can be obtained through built-in attitude sensors (such as accelerometers and gyroscopes) and positioning modules (such as GPS and BeiDou). These sensors can accurately measure the spatial position and orientation of the reflector array and upload the data to the control center in real time.

[0042] The coordinates of monitoring points in the areas to be enhanced can be obtained by deploying dedicated signal monitoring equipment in each area. These devices are equipped with high-precision GPS positioning modules and signal strength measurement circuits, which can measure the coordinates and received signal strength of the location in real time and report the data to the control center.

[0043] The structural parameters of the waiting hall can be acquired through 3D modeling using technologies such as laser scanning and photogrammetry. High-precision 3D scanning equipment can rapidly capture the waiting hall's spatial structural data. After computer processing, an accurate 3D model and key parameters (such as dome curvature and reflective surface inclination) are obtained.

[0044] After obtaining the above parameters, the system calculates the direct path and the reflected path according to the following steps: A three-dimensional coordinate system was established with the center of the waiting hall as the origin. A three-dimensional rectangular coordinate system was established with the center of the waiting hall as the origin, with the X and Y axes parallel to the long and wide sides of the waiting hall, respectively, and the Z axis perpendicular to the ground and pointing upward. This coordinate system unified the locations of the smart reflector array, monitoring points, and dome structure into a single spatial reference.

[0045] Calculate the direct path vector from the smart reflector array to each monitoring point. Based on the installation height, azimuth, and elevation of the smart reflector array, as well as the three-dimensional coordinates of the monitoring point, trigonometric functions and vector operations can be used to calculate the direct path vector from the center of the smart reflector array to each monitoring point. This vector starts at the center of the smart reflector array, ends at the monitoring point, and points in the direction of the smart reflector array toward the monitoring point.

[0046] Calculate the reflection path vector of the signal after it reflects off the metal dome structure and reaches each monitoring point. Using the direct path vector and the dome's shape parameters, and applying the law of reflection in geometric optics, we can calculate the location of the signal's reflection point on the dome's reflecting surface and the reflection path vector after it reaches the monitoring point. Specifically, consider the direct path vector as the incident ray and the dome's reflecting surface as the reflecting surface. By calculating the angle of incidence and the angle of reflection, and using trigonometric functions and vector operations, we can determine the reflection path vector.

[0047] Convert the direct and reflected path vectors into their corresponding direct and reflected paths. To facilitate subsequent analysis and application, the calculated path vectors must be converted into actual propagation paths. A path is typically represented by a series of coordinate points, which are connected sequentially in the order of signal propagation to form a continuous path curve. Interpolation algorithms and curve fitting techniques can be used to obtain a smooth and accurate path representation.

[0048] S104, determining signal loss values ​​on the direct path and the reflected path according to the received signal reflection intensity value and the preset signal transmission intensity value; The system first uses a receiving device to receive the signal reflected by the smart reflective surface array and measure the signal's reflection intensity. Simultaneously, the system also obtains a preset signal transmission intensity value, which is determined by parameters such as the 5G base station's transmit power and antenna gain and can be set in advance based on device parameters. After obtaining the signal reflection and transmission intensity values, the system calculates the difference between the two to determine the signal loss values ​​for the direct and reflected paths.

[0049] When calculating signal loss, the system needs to consider the following: First, because signal propagation is affected by factors such as free space loss, atmospheric absorption, and diffraction, the system needs to select an appropriate loss model based on parameters such as signal frequency and propagation distance. Second, the reflective characteristics of the smart reflector array also affect signal loss, requiring the system to model and calculate reflection loss based on parameters such as the smart reflector's material and structure.

[0050] S105: Determine the priorities of several areas to be enhanced according to the positions of the crowd density data in the preset priority comparison table; The purpose of this step is to determine the priority of each area to be enhanced based on the crowd density data of the waiting hall, so that the signal of each area can be enhanced according to the priority.

[0051] The system first needs to establish a preset priority table to map different crowd density ranges to corresponding priorities. For example, crowd density can be divided into three levels: high, medium, and low, corresponding to priorities 1, 2, and 3, respectively. The lower the priority number, the higher the priority.

[0052] When determining the priority of the areas to be enhanced, the system compares the crowd density data for each area to be enhanced with the priority comparison table, identifies the range of crowd density, and obtains the corresponding priority. If the crowd density of a certain area to be enhanced is high, then the priority of that area is 1, and so on. In this way, the system can assign a priority to each area to be enhanced, forming a priority list.

[0053] S106. Measure the signal power in the horizontal and vertical directions of the area to be enhanced respectively; when the signal power in the horizontal direction is higher than the signal power in the vertical direction by a preset power value, activate the horizontal polarizer in the dual-polarization reflection unit; when the signal power in the vertical direction is higher than the signal power in the horizontal direction by a preset power value, activate the vertical polarizer in the dual-polarization reflection unit; when the difference between the signal power in the vertical direction and the signal power in the horizontal direction is less than a preset power value, activate both the horizontal polarizer and the vertical polarizer. The main purpose of this step is to selectively activate the polarimetric subunits in the smart reflector array by measuring the signal power in the area to be enhanced, thereby achieving more refined signal enhancement control.

[0054] The system first requires deploying measurement equipment within each area to be enhanced, measuring both horizontal and vertical signal power. The resulting signal power data will serve as the basis for determining when to activate the polariton unit.

[0055] The system then compares the horizontal and vertical signal powers and calculates the difference. If the horizontal signal power exceeds the vertical power threshold by a preset value, the system activates the horizontal polarizers in the smart reflector array to reflect and enhance the signal. Similarly, if the vertical signal power exceeds the horizontal power threshold by a preset value, the system activates the vertical polarizers.

[0056] In some cases, the difference in signal power between the horizontal and vertical directions may be small and fall below the preset power threshold. In this case, the system will activate both the horizontal and vertical polarizers, allowing the smart reflector array to simultaneously enhance signals in both directions.

[0057] In actual applications, signal power measurements may contain errors due to factors such as environmental noise and device accuracy. To improve the reliability of the determination, the system can perform multiple measurements and average the results to reduce the impact of errors. Furthermore, the system can adaptively adjust the preset power threshold based on historical data and environmental factors to better adapt to different application scenarios.

[0058] S107. Adjust the phase of the activated polarimetric subunit so that the signal of the 5G base station, after being reflected by the smart reflector array, is different from all reflection paths with signal loss values ​​greater than a preset loss value, and is aligned with each area to be enhanced according to priority.

[0059] The purpose of this step is to achieve optimal signal enhancement by adjusting the phase of the activated polariton units in the smart reflector array so that the reflected signal avoids high-loss paths and is prioritized toward the area to be enhanced.

[0060] When adjusting the polariton unit phase, the system first needs to obtain the signal loss value of each reflection path calculated in step S104 and compare it with a preset loss threshold. For reflection paths with loss values ​​greater than the threshold, the system marks them as high-loss paths.

[0061] Next, the system prioritizes the areas to be enhanced and determines the order in which to enhance the signal. For the highest-priority area, the system adjusts the phase of the activated polarimetric subunits so that the 5G base station signal, after reflecting off the smart reflector array, avoids all high-loss paths and is directed as directly as possible toward that area. This is achieved by optimizing the reflection angle and polarization direction.

[0062] For lower-priority areas, the system needs to adjust the polarimetric phase to avoid high-loss paths while also taking into account the impact on higher-priority areas. Specifically, the system needs to ensure that while targeting lower-priority areas, it does not significantly degrade signal strength in higher-priority areas. This may require trade-offs between multiple areas to be enhanced.

[0063] In actual applications, due to environmental factors and device characteristics, the reflection characteristics of smart reflector arrays may deviate from theoretical models, resulting in suboptimal signal enhancement. To address this issue, the system can incorporate an adaptive optimization algorithm that dynamically adjusts the phase of the polariton units based on real-time monitoring of signal strength feedback in each area to be enhanced to achieve optimal signal enhancement. The system also regularly calibrates and calibrates the smart reflector array to ensure its performance meets design requirements.

[0064] In the above embodiment, by acquiring the waiting hall crowd density data in real time and combining it with the signal strength monitoring data, the area requiring signal enhancement is identified, thereby avoiding ineffective coverage of signal resources. A dual-polarization reflection unit is used to respond to signals in the horizontal and vertical directions respectively, and the corresponding polarization sub-unit is selectively activated according to the signal power difference, making the signal enhancement more directional and selective. By measuring the signal loss values ​​on the direct path and the reflected path, and combining the priority determined by the crowd density data, the system can avoid the propagation path with large signal loss, and give priority to projecting limited signal resources to areas with dense crowds and poor signal coverage, thereby improving the utilization efficiency of signal resources. At the same time, the reflection effect of the metal dome structure on the signal is taken into account, and the phase of the reflection unit is adjusted in real time through the FPGA controller, so that the system can establish a stable signal transmission channel in a complex indoor environment, thereby improving the signal coverage quality in the high-speed rail station.

[0065] In the above embodiment, the system achieves efficient allocation of signal resources through real-time monitoring and intelligent adjustment. However, in actual application scenarios, terminal devices in different areas may have different requirements for signal performance. For example, the ticket purchasing area may be more concerned with signal stability to ensure the security of the payment process, while the waiting area may require a larger signal bandwidth to meet passengers' entertainment needs such as watching videos. Therefore, in order to further improve the accuracy and practicality of signal enhancement, this application also provides a signal enhancement method based on application type identification. The following is combined with Figure 2 , a signal enhancement method based on application type identification in an embodiment of the present application is described: See also Figure 2 , which is a flow chart of a signal enhancement method based on application type identification in an embodiment of the present application.

[0066] S201, obtaining the function type of each area to be enhanced; The system obtains the functional type of each area to be enhanced, including security checkpoints, ticket purchase areas, and waiting areas. In this step, the system needs to obtain the specific functional type of each area to be enhanced within the high-speed rail station so that it can subsequently provide targeted signal enhancement strategies based on the characteristics of each area. Typically, the main functional areas within a high-speed rail station include security checkpoints, ticket purchase areas, and waiting areas.

[0067] The system can obtain the functional type of each area through the following methods: First, during the initial system deployment, staff manually enter the functional attributes of each area to form a static regional functional database; second, by connecting with the high-speed rail station's information management system, the functional identification of each area can be dynamically obtained. For example, an API interface can be used to query the service type of each area in real time. Different regional functions often correspond to different signal requirements. For example, the ticket purchase area is more concerned with signal security and low latency, while the waiting area requires high bandwidth and continuous coverage.

[0068] S202: Collect MAC addresses of terminal devices in each area to be enhanced at preset time intervals; After obtaining the functional type of each area, the system needs to further collect the MAC addresses of terminal devices in each area to identify the device's application type and service characteristics. The MAC address is a unique identifier for each network device and can be used to determine information such as the device's brand and model, and thus infer the device's application scenario.

[0069] The specific collection method is as follows: the system deploys a dedicated sniffing device in each area to be enhanced, passively monitors the wireless signals in the area, and extracts the MAC address information. Taking into account the mobility of the device, the system can periodically collect MAC addresses at preset time intervals (such as every 5 seconds) to form a dynamically updated device-area mapping relationship table. The collection time interval needs to be optimized based on the actual device density and mobility frequency, in order to capture the dynamic changes of the device as much as possible while avoiding the waste of resources caused by overly frequent sampling. At the same time, the collection of MAC addresses must strictly comply with relevant privacy protection regulations and perform necessary desensitization on the collected data.

[0070] S203, identifying the type of application currently running on each terminal device based on the terminal device MAC address; The system identifies the application type currently running on each terminal device based on the MAC address of the terminal device, specifically including: obtaining the data packet type of each terminal device based on the MAC address; when the port number in the data packet type is the preset payment application port number, the corresponding terminal device is marked as running a payment application; when the port number in the data packet type is the preset audio and video application port number, the corresponding terminal device is marked as running an audio and video application; when the port number in the data packet type is the preset instant messaging application port number, the corresponding terminal device is marked as running an instant messaging application.

[0071] After collecting the MAC addresses of devices in each area, the system needs to further identify the type of application currently running on each device to infer its network requirements. Different types of applications typically correspond to different network requirements. For example, payment applications are more concerned with security and latency, audio and video applications are more concerned with bandwidth and smoothness, and instant messaging applications are more concerned with connection stability.

[0072] The system can identify the device's application type in the following ways: The system obtains the data packet type of each terminal device based on the MAC address. Using DPI (Deep Packet Inspection) technology, the system can analyze the collected device data packets in real time and extract key application layer information, such as the URL of the HTTP request and the domain name of the DNS query.

[0073] The application type is determined based on the characteristic information in the data packet. For payment applications, the destination port number of their data packets is often a preset special value (such as 8080); for audio and video applications, the payload of their data packets often contains specific protocol headers (such as RTP and RTSP); and for instant messaging applications, the interaction patterns of their data packets often exhibit unique timing characteristics (such as heartbeat packets and login packets). The system can pre-establish a rule base that matches application type with data packet characteristics, quickly identifying application types by matching data packet characteristics.

[0074] The identification results are associated with the device's MAC address to generate a device-application type mapping table. The system can dynamically update this table to reflect changes in the device's application status in real time.

[0075] During the actual identification process, packet parsing and rule matching consume significant computing resources, potentially impacting the system's real-time performance. Therefore, the system can employ optimization strategies, such as using efficient pattern matching algorithms, setting a reasonable sampling rate, and introducing a multi-level identification mechanism. Furthermore, since MAC addresses are easily forged, identification results may be uncertain. Verification and supplementation with other methods, such as device fingerprinting and behavioral analysis, are necessary.

[0076] S204. When a payment application is detected, the signal delay requirement of the area to be enhanced is marked as a high priority; when an audio or video application is detected, the signal bandwidth requirement of the area to be enhanced is marked as a high priority; when an instant messaging application is detected, the signal stability requirement of the area to be enhanced is marked as a high priority; Based on the application types of devices in each area identified in S203, the system can further determine the signal enhancement focus of different areas. Since different application types have different signal requirements, the system needs to adjust the network optimization strategy of each area in a targeted manner.

[0077] Specifically, when a large number of payment applications are detected in an area, the system needs to prioritize signal latency requirements for that area. The payment process typically involves multiple interactive verifications, and timely responses must be guaranteed for each interaction. Failure to do so can easily lead to user anxiety and complaints. Therefore, the system prioritizes signal latency in the payment area, minimizing the round-trip time of signaling interactions by optimizing signal transmission paths and compressing protocol overhead.

[0078] When a large number of audio and video applications are detected in an area, the system needs to mark the signal bandwidth requirements of this area as high priority. Audio and video applications typically require high data transmission rates to ensure smooth playback of media content. Insufficient network bandwidth can easily lead to problems such as video freezes and audio distortion, seriously affecting the user experience. Therefore, the system must prioritize the bandwidth requirements of the audio and video area, maximizing available bandwidth resources by expanding channel capacity and compressing data redundancy.

[0079] When a large number of instant messaging applications are detected in an area, the system prioritizes signal stability in that area. Instant messaging applications place high demands on network continuity and reliability, ensuring real-time message transmission and synchronization. Network interruptions or excessive latency can lead to message loss or disorganization, impacting communication quality. Therefore, the system prioritizes signal stability in the instant messaging area, improving connection reliability through measures such as optimizing network topology and introducing redundant backups.

[0080] S205. Calculate the proportion of different signal feature requirements in each area to be enhanced; After determining the signal enhancement priorities for each area, the system needs to further quantify the relative weights of these priorities in order to develop a more refined signal optimization strategy. This requires statistically analyzing the distribution of different signal feature requirements within each area.

[0081] In specific implementation, the system can count the number of devices with priority requirements for different factors such as latency, bandwidth, and stability for each area to be enhanced, and calculate their proportion in the area. For example, the following formula can be used for calculation: Latency requirement ratio = Number of payment application devices / Total number of devices in the region Bandwidth requirement ratio = Number of devices using audio and video applications / Total number of devices in the area Stability requirement ratio = Number of devices using instant messaging apps / Total number of devices in the region These percentages reflect the differences in signal requirements within different areas, providing a reference for subsequent targeted optimization. For example, if the ticket purchase area has a higher latency requirement, while the waiting area has a higher bandwidth requirement, the system can adjust the network configuration of both areas accordingly, such as adding transmission paths in the ticket purchase area and expanding channel bandwidth in the waiting area.

[0082] S206. When the signal delay requirement accounts for the highest proportion, activate the vertical polarization sub-unit to reduce the signal propagation path; According to the proportion of different signal requirements in each area calculated by S205, the system can adjust the working mode of the intelligent reflective surface accordingly, optimize the spatial path of signal transmission, and thus improve network performance in a targeted manner.

[0083] When the system detects that latency requirements are highest in a certain area, it indicates that payment applications are the primary applications in that area and are most sensitive to signal latency. This requires shortening the signal propagation path as much as possible and reducing reflection and diffraction in space to reduce end-to-end transmission latency.

[0084] One possible optimization strategy is to activate the vertical polarization subunits in the smart reflector, allowing them to operate in a vertical polarization direction. Compared to horizontally polarized signals, vertically polarized signals are less affected by the ground and obstacles during spatial propagation, allowing them to reach the target area more directly. By adjusting the reflection angle and gain of the vertical polarization subunits, the system can create a nearly direct signal propagation path between the smart reflector and the terminal device, minimizing multiple signal reflections and thus minimizing propagation delay.

[0085] The specific activation method can be achieved through the following steps: Determine the geometric position relationship between the intelligent reflective surface and the target area based on the spatial mapping relationship calculated in S103, and calculate the ideal signal reflection angle; According to the signal wavelength and the structural parameters of the smart reflector, the optimal gain value of vertical polarization at this angle is calculated; Sending activation instructions to the control circuit of the smart reflector to adjust the reflection coefficient of each vertical polarization sub-unit to achieve maximum gain at the ideal angle; At the same time, it suppresses the operation of horizontal polarization sub-units, reducing unnecessary energy loss and interference; Continuously monitor signal quality and delay performance, and dynamically optimize vertical polarization reflection parameters based on feedback data.

[0086] S207. When the signal bandwidth requirement accounts for the highest proportion, activate the horizontal polarization sub-unit and the vertical polarization sub-unit simultaneously to increase the signal capacity; When the system detects that bandwidth requirements are highest in a certain area, it indicates that the primary applications in that area are audio and video, which have high requirements for signal transmission speed and capacity. Therefore, it is necessary to maximize the available channel bandwidth and increase the data transmission volume per unit time to meet the rate requirements of high-traffic applications.

[0087] One feasible optimization strategy is to simultaneously activate both the horizontally polarized and vertically polarized subunits in the smart reflector, allowing signals to operate simultaneously in two orthogonal polarization directions. This effectively introduces an additional spatial degree of freedom within the same channel, significantly increasing the channel's transmission capacity. Specifically, the horizontally and vertically polarized signals are spatially orthogonal and can be transmitted simultaneously without interfering with each other, thus achieving channel multiplexing and improving spectral efficiency.

[0088] S208. When the signal stability requirement accounts for the highest proportion, activate the horizontal polarization subunit to enhance the anti-interference capability.

[0089] When the system detects that the highest percentage of stability requirements is in a certain area, it indicates that the main applications in this area are instant messaging applications, which have high requirements for signal continuity and reliability. This requires enhancing the signal's ability to resist various interferences as much as possible, reducing the probability of signal interruptions and bit errors, and ensuring stable and smooth communication.

[0090] One feasible optimization strategy is to activate the horizontally polarized subunits in the smart reflector, ensuring that the signal operates in the horizontal polarization direction. Compared to vertically polarized signals, horizontally polarized signals are less affected by ground reflections and building obstructions during propagation, resulting in more stable channel conditions. This is because most interference sources (such as other communication systems and electromagnetic noise) are concentrated in the horizontal direction, and horizontally polarized signals can effectively avoid these interference sources. Furthermore, horizontally polarized signals have stronger penetration, allowing them to better bypass obstacles and reduce signal fading due to shadowing.

[0091] In the above embodiment, the system can adaptively adjust the operating mode of the polarization subunit based on the signal characteristics required by different types of applications. When payment applications account for a high proportion, the vertical polarization subunit is activated to reduce the propagation path. When audio and video applications account for a high proportion, the dual polarization subunit is simultaneously activated to increase signal capacity. When instant messaging applications account for a high proportion, the horizontal polarization subunit is activated to enhance anti-interference capabilities. This signal optimization solution based on application characteristics enables the system to dynamically adjust signal characteristics based on the actual user needs, optimizing the signal service quality while ensuring signal coverage, and improving the user's actual usage experience.

[0092] Furthermore, in another embodiment, after aligning the areas to be enhanced according to priority, the method further includes: reducing the signal strength detection time interval of the areas to be enhanced by a preset multiple within a preset time period before the arrival or departure of a train; When it is determined that the signal strength change value of the area to be enhanced per unit time is greater than a preset change threshold, the activated polarimetric subunits of the smart reflective surface array are divided into a first group of polarimetric subunits and a second group of polarimetric subunits; Controlling the first group of polariton units to maintain signal coverage of the area to be enhanced; Adjusting the reflection phase of the second group of polariton units according to the direction of the signal strength change value specifically includes: obtaining a signal strength distribution map of the area to be enhanced; determining the boundary of the area where the signal strength decreases in the signal strength distribution map; calculating the signal strength attenuation value at the area boundary; and when it is determined that the attenuation value is greater than a preset attenuation threshold, adjusting the reflection phase of the second group of polariton units so that the direction of the reflected signal is aligned with the area boundary, so that the signal coverage area expands in the direction of the signal strength change value.

[0093] The system first reduces the signal strength detection interval in the area to be enhanced by a preset multiple (e.g., halved) within a preset time period (e.g., 10 minutes before a train arrives or departs). This means the system monitors changes in signal quality in that area more frequently to promptly respond to passenger movement and gathering. By shortening the detection interval, the system can more accurately capture instantaneous changes in signal strength, providing a more granular basis for subsequent adjustments.

[0094] If the system detects through high-frequency detection that the signal strength change in the area to be enhanced exceeds a preset change threshold (such as 5dB) within a unit time (such as 1 minute), it will determine that there may be large-scale human movement in the area, resulting in a blind spot or weak coverage in the original signal. In this case, the system will divide the activated polarimetric subunits in the smart reflector array into two groups, namely Group 1 and Group 2.

[0095] The first set of polarimetric subunits maintains signal coverage in the area to be enhanced, ensuring that existing users' communications remain unaffected. These subunits maintain their original reflection phase and gain, continuing to provide stable signal service to the original coverage area.

[0096] The second set of polarization subunits is responsible for dynamically expanding the signal coverage area to adapt to changes in passenger gathering locations. The specific adjustment strategy is as follows: First, the system obtains a signal strength distribution map of the area to be enhanced, which can be obtained by interpolating the signal strengths of multiple monitoring points.

[0097] The system then finds the boundaries of areas where signal strength is significantly reduced in the signal strength distribution map, which reflects the approximate range of the passenger gathering area.

[0098] Next, the system calculates the signal strength attenuation value at the boundary of the area. The larger the attenuation value, the worse the coverage quality of the area and the higher the optimization intensity required.

[0099] When the attenuation value exceeds the preset attenuation threshold (such as 10dB), the system will activate the second set of polarization subunits and adjust their reflection phase so that the main direction of the reflected signal is aligned with the position of the area boundary.

[0100] By continuously iteratively optimizing the phase of the second set of polarization subunits, the system can dynamically extend the signal coverage area along the direction of personnel gathering until the attenuation value drops below the threshold or the physical coverage limit of the reflecting surface is reached.

[0101] In the above embodiment, during the preset time period of train arrival or departure, the system responds to rapid changes in signal coverage requirements by reducing the signal strength detection interval and controlling the polarization subunits in groups. When it is detected that the signal strength change per unit time exceeds a threshold, the system divides the polarization subunits into two groups, one group maintaining the original coverage and the other group expanding the coverage area based on the direction of the signal change. This group control mechanism enables the system to quickly respond to new signal requirements while maintaining signal stability in the original area. By increasing the signal detection frequency, the system can detect changing trends in signal coverage more promptly. At the same time, the group control strategy avoids the impact of the adjustment process on the original coverage area, thereby improving the continuity and stability of signal coverage when passengers flow rapidly.

[0102] The following describes the system in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of the physical device structure of a 5G base station intelligent reflector assisted beam enhancement system provided in an embodiment of the present application.

[0103] It should be noted that Figure 3 The structure of the system shown is only an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0104] like Figure 3 As shown, the system includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes, such as the methods described in the above embodiments, based on programs stored in a read-only memory (ROM) 302 or programs loaded from a storage unit 308 into a random access memory (RAM) 303. RAM 303 also stores various programs and data required for system operation. CPU 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to bus 304.

[0105] The following components are connected to the I / O interface 305: an input section 306 including a camera, infrared sensor, and the like; an output section 307 including a liquid crystal display (LCD) and speakers; a storage section 308 including a hard disk and the like; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. Removable media 311, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, is installed in the drive 310 as needed, so that computer programs read from the media can be installed in the storage section 308 as needed.

[0106] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for executing the methods illustrated in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 309 and / or installed from removable media 311. When executed by the central processing unit (CPU) 301, the computer program performs the various functions defined in the present invention.

[0107] It should be noted that the computer-readable medium described in the embodiments of the present invention may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium may include a data signal transmitted in baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal may take any of a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof.

[0108] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two boxes shown in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0109] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the system described in the above embodiments, or may exist independently and not incorporated into the system. The storage medium carries one or more computer programs, and when executed by a processor of a system, the system implements the methods provided in the above embodiments.

[0110] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0111] As used in the above embodiments, the term “when…” may be interpreted as “if…” or “after…” or “in response to determining…” or “in response to detecting…”, depending on the context. Similarly, the phrases “upon determining…” or “if (stated condition or event) is detected” may be interpreted as “if determining…” or “in response to determining…” or “upon detecting (stated condition or event)” or “in response to detecting (stated condition or event)”, depending on the context.

[0112] In the above embodiments, all or part of the embodiments can be implemented using software, hardware, firmware, or any combination thereof. When implemented using software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., a floppy disk, hard disk, tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive).

[0113] Those skilled in the art will appreciate that all or part of the process steps in the above-described method embodiments can be implemented by a computer program instructing the relevant hardware. The program can be stored in a computer-readable storage medium, and when executed, the program can include the process steps in the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM or random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A 5G base station intelligent reflector assisted beam enhancement method, characterized in that: The method is applied to a signal enhancement system, the signal enhancement system being arranged at a preset position, the signal enhancement system comprising an intelligent reflective array, the intelligent reflective array comprising a preset number of dual-polarization reflective units, each of the dual-polarization reflective units comprising a horizontal polarization subunit and a vertical polarization subunit, and each subunit being phase-adjusted by an FPGA controller. Determine, based on the collected signal strength values ​​of each monitoring point in the high-speed railway station, several areas to be enhanced where the signal strength is lower than a preset signal strength threshold; Get real-time crowd density data in the waiting hall; Calculating a direct path and a reflected path from each of the to-be-enhanced areas to the smart reflective surface array, wherein the reflected path includes a path after the signal is reflected by the metal dome structure; Determine the signal loss values ​​on the direct path and the reflected path according to the received signal reflection intensity value and the preset signal transmission intensity value; Determining the priorities of the plurality of areas to be enhanced according to the positions of the crowd density data in a preset priority comparison table; respectively measuring the signal power in the horizontal direction and the vertical direction in the area to be enhanced; when the signal power in the horizontal direction is higher than the signal power in the vertical direction by a preset power value, activating the horizontal polarization subunit in the dual-polarization reflection unit; when the signal power in the vertical direction is higher than the signal power in the horizontal direction by the preset power value, activating the vertical polarization subunit in the dual-polarization reflection unit; and when the difference between the signal power in the vertical direction and the signal power in the horizontal direction is less than the preset power value, activating the horizontal polarization subunit and the vertical polarization subunit at the same time; The phase of the activated polarization subunit is adjusted so that the signal of the 5G base station is different from the reflection path of all signal loss values ​​greater than the preset loss value after being reflected by the smart reflective surface array, and is aligned with each of the areas to be enhanced according to the priority.

2. The method according to claim 1, characterized in that The step of determining, based on the collected signal strength values ​​of each monitoring point in the high-speed railway station, a number of areas to be enhanced where the signal strength is lower than a preset signal strength threshold, specifically includes: Divide the high-speed railway station into several monitoring areas of equal area with each monitoring point in the high-speed railway station as the center; Collecting the signal strength value of each monitoring point; The monitoring areas where the signal strength values ​​are lower than a preset signal strength threshold are determined as areas to be enhanced, and a plurality of areas to be enhanced are obtained.

3. The method according to claim 1, characterized in that The calculating of the direct path and the reflected path from each of the to-be-enhanced areas to the smart reflective surface array specifically includes: Obtaining the installation height, azimuth and elevation angles of the intelligent reflective surface array, the three-dimensional coordinates of the monitoring points in the area to be enhanced, and the shape parameters of the metal dome structure of the waiting hall, wherein the shape parameters include the curvature radius of the dome and the inclination angle of the reflective surface; Establishing a three-dimensional coordinate system with the ground center of the waiting hall as the origin; Calculating a direct path vector from the smart reflective surface array to each of the monitoring points according to the installation height, the azimuth angle, the pitch angle, and the three-dimensional coordinates of the monitoring points; According to the direct path vector and the shape parameters of the metal dome structure, the reflection law of geometric optics is used to calculate the reflection path vector of the signal after being reflected by the metal dome structure and reaching each of the monitoring points; The direct path vector and the reflected path vector are converted into a direct path and a reflected path.

4. The method according to claim 1, wherein After aligning the to-be-enhanced areas according to the priorities, the method further includes: Acquire the function type of each area to be enhanced, where the function type includes a security inspection area, a ticket purchasing area, and a waiting area; Collecting MAC addresses of terminal devices in each of the areas to be enhanced at preset time intervals; Identify the type of application currently running on each terminal device based on the MAC address of the terminal device; When a payment application is detected, the signal delay requirement of the area to be enhanced is marked as a high priority; when an audio and video application is detected, the signal bandwidth requirement of the area to be enhanced is marked as a high priority; when an instant messaging application is detected, the signal stability requirement of the area to be enhanced is marked as a high priority; Calculating the proportions of different signal characteristic requirements in each of the areas to be enhanced; When the signal delay requirement accounts for the highest proportion, activating the vertical polarization subunit to reduce the signal propagation path; When the signal bandwidth requirement accounts for the highest proportion, activating the horizontal polarization subunit and the vertical polarization subunit simultaneously to increase signal capacity; When the signal stability requirement accounts for the highest proportion, the horizontal polarization subunit is activated to enhance the anti-interference capability.

5. The method according to claim 4, characterized in that The identifying the type of application currently running on each terminal device according to the terminal device MAC address specifically includes: Obtaining a data packet type of each terminal device based on the MAC address; When the port number in the data packet type is a preset payment application port number, marking the corresponding terminal device as running a payment application; When the port number in the data packet type is a preset audio and video application port number, the corresponding terminal device is marked as running the audio and video application; When the port number in the data packet type is a preset instant messaging application port number, the corresponding terminal device is marked as running an instant messaging application.

6. The method according to claim 1, characterized in that After aligning the to-be-enhanced areas according to the priorities, the method further includes: Within a preset time period before the arrival or departure of a train, the signal strength detection time interval of the area to be enhanced is reduced by a preset multiple; When it is determined that the signal strength change value of the area to be enhanced per unit time is greater than a preset change threshold, the activated polarimetric subunits of the smart reflective surface array are divided into a first group of polarimetric subunits and a second group of polarimetric subunits; Controlling the first group of polarimetric subunits to maintain signal coverage of the area to be enhanced; The reflection phases of the second group of polariton units are adjusted according to the direction of the signal strength change value, so that the signal coverage area is expanded in the direction of the signal strength change value.

7. The method according to claim 6, characterized in that The adjusting the reflection phases of the second group of polariton units according to the direction of the signal strength change value specifically includes: Acquire a signal strength distribution map of the area to be enhanced; determining, in the signal strength distribution map, a boundary of an area where signal strength decreases; Calculating a signal strength attenuation value at the boundary of the area; When it is determined that the attenuation value is greater than a preset attenuation threshold, the reflection phase of the second group of polariton units is adjusted so that the direction of the reflected signal is aligned with the region boundary.

8. A 5G base station intelligent reflector-assisted beam enhancement system, characterized in that: The system comprises: One or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to cause the system to execute the method according to any one of claims 1 to 7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instructions are executed on a system, the system is caused to perform the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is run on a system, the system is caused to perform the method according to any one of claims 1 to 7.

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