Multi-network signal switching control system and method based on big data

Abstract

The invention relates to the technical field of signal switching control, in particular to a multi-network signal switching control system and method based on big data, and the system comprises a user track prediction module, a network coverage analysis module, a signal load evaluation module, a signal switching decision module and a switching execution monitoring module. According to the invention, accurate prediction of a user moving track is provided by integrating user positioning and moving speed data, a potential network switching point is effectively predicted, and a system is allowed to dynamically adjust a network switching strategy by analyzing user behaviors in real time, so that the continuity and the stability of network services are improved, and the user experience is improved. The system can predict the future network demand before the user state is stable by calculating the trajectory trend change rate of the user, the prediction mode combines the current data and the historical trend, the prediction accuracy is improved, the signal switching opportunity and the target network selection are optimized by analyzing the signal coverage and the real-time load of each base station, and the user experience is improved. And data packet loss and time delay are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of signal switching control, and in particular to a multi-network signal switching control system and method based on big data. Background Art

[0002] Signal switching control technology involves how to manage and optimize the seamless switching of devices between different communication base stations or networks in wireless communication networks. This technology is essential to maintaining the continuity and stability of communications. Effective signal switching control can reduce call interruptions and data transmission delays, improve user experience, and provide users with more efficient and reliable communication services in the current multi-network environment (such as the integration of 4G, 5G and Wi-Fi).

[0003] Among them, the big data multi-network signal switching control system refers to a system that uses big data technology to optimize and control signal switching between multiple networks. The system automatically decides when and how to switch devices from one network to another by analyzing large amounts of data, such as user location, network conditions, traffic patterns, etc., to ensure optimal communication quality and service continuity. The main purpose of this system is to improve the stability and speed of data connections in smartphones, tablets and other mobile devices, especially when users cross different network coverage areas during movement, thereby optimizing users' online experience and improving the network efficiency of operating service providers.

[0004] When processing network switching during user mobility, existing technologies rely on static network selection criteria and signal quality assessments, which are difficult to adapt to changes in user needs and network status. As a result, network switching delays or incorrect network selection often occur in scenarios where users move at high speed or network conditions change frequently. For example, when users move across different network coverage areas, there is a lack of real-time analysis of user behavior and trajectory trends, which makes it impossible for the system to perform accurate network switching in a timely manner, resulting in connection loss or reduced service quality, affecting user experience, such as call interruptions and video playback freezes, while increasing the difficulty and cost of network management for operators. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a multi-network signal switching control system and method based on big data.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a multi-network signal switching control system based on big data, the system comprising: The user trajectory prediction module obtains the user device positioning information and moving speed data, analyzes the direction change rate and trajectory deviation amplitude, calculates the trajectory trend change rate, determines whether it is in a stable moving state, obtains potential network switching points, and obtains a trajectory deviation data set; The network coverage analysis module collects geographic location data of the target area based on the trajectory offset data set, extracts the base station signal coverage range, screens the base station nodes within the coverage range, calculates the multi-base station signal overlap index, and obtains the base station signal coverage index; The signal load evaluation module obtains the real-time channel occupancy rate of each base station in the coverage area based on the base station signal coverage index, analyzes the channel idle ratio, calculates the number of available channels, and obtains the channel idle ratio index; The signal switching decision module calls the channel idle ratio index, calculates the signal quality change according to the base station signal strength, sorts the number of available channels, and obtains the network switching priority; The switching execution monitoring module calls the network switching priority, executes the network switching operation, obtains the data packet loss rate and switching delay data during the switching, calculates the signal strength change trend, and obtains the signal stability analysis result.

[0007] The improvements of the present invention are that the trajectory offset data set includes position accuracy, speed accuracy, and trajectory continuity; the base station signal coverage index includes signal stability, the number of base stations, and the area coverage rate; the channel idle ratio index includes channel capacity, the number of idle channels, and the channel occupancy rate; the network switching priority includes signal strength score, network access priority, and channel selection sensitivity; the signal stability analysis result includes signal recovery speed, stability index, and connection quality evaluation result.

[0008] The present invention is improved in that the user trajectory prediction module comprises: The positioning data collection submodule obtains the user device positioning information and movement speed data, collects the device location points in multiple time periods, calculates the displacement increment in each time period, screens the displacement mutation points, and establishes a preliminary motion data set; The trajectory deviation analysis submodule calculates the direction change rate and trajectory deviation amplitude of the user in multiple time periods based on the preliminary motion data set, and analyzes the motion trajectory deviation trend using the formula: ; Calculate the trajectory deviation change , filter the data points with large offset amplitude and obtain the trajectory offset feature set, where, Representative Segment displacement increment, represents the i-th time increment, Represents the total number of time periods, It is The displacement rate of the segment, It is The displacement rate of the segment; The trajectory trend calculation submodule calculates the user trajectory trend change rate based on the trajectory deviation feature set to determine whether it is in a stable moving state. If the trajectory trend change rate is less than the trajectory deviation standard, the future moving trajectory is fitted, and the potential network switching point is obtained in combination with the device location information to obtain a trajectory deviation data set.

[0009] The present invention is improved in that the network coverage analysis module comprises: The geographic data acquisition submodule extracts the latitude and longitude, timestamp and movement trajectory offset information based on the trajectory offset data set, establishes the geographic coordinate distribution in the area, and performs spatial integration to obtain the geographic coordinate set of the target area; The base station signal screening submodule analyzes the signal coverage of each base station based on the target area geographic coordinate set, selects base stations with critical signal strength, and screens out base station nodes with weak signal quality to obtain a valid base station set; The multi-base station overlap analysis submodule calculates the coverage overlap of multiple base station signals in the same geographical area based on the effective base station set and base station coverage data, using the formula: ; Get base station signal coverage indicators ,in, Representative The signal coverage of each base station, Representative The signal coverage of each base station, Representative The area covered by the base station signal. Representative The area covered by the base station signal. Representative and The overlapping area of ​​the base station signal coverage range, is the total number of base stations in the valid base station set.

[0010] The present invention is improved in that the signal load evaluation module comprises: The channel occupancy calculation submodule collects real-time channel occupancy rate data based on the base station signal coverage index, calculates the total channel usage of each base station, and counts the channel occupancy of different base stations to obtain base station channel occupancy information; The target area signal screening submodule screens the base station data in the target area based on the base station channel occupancy information, excludes the base stations in the non-target area, and extracts the channel occupancy data of the base stations in the target area, performs normalization processing, and obtains the channel occupancy of the target area; The channel idle ratio analysis submodule calculates the channel idle ratios of multiple base stations based on the channel occupancy in the target area and analyzes the channel idle situation using the formula: ; Get the channel idle ratio index ,in, represents the maximum channel capacity of the base station, Representative base station The current channel occupancy of Representative The signal coverage of each base station, Represents the total number of base stations in the target area.

[0011] The present invention is improved in that the signal switching decision module comprises: The signal quality assessment submodule calls the channel idle ratio index, obtains the base station signal strength at the user's current location, calculates the signal strength attenuation from the current location to the target network, and adjusts the impact of the channel idle index using the formula: ; Get the signal quality change ,in, Represents the base station signal strength at the user’s current location. Represents the target network signal strength, Represents the idle ratio index of the target network channel, Represents the current base station channel idle ratio index, Represents the physical distance from the user's current location to the target network. Represents the theoretical signal coverage radius of the target network; The switching priority sorting submodule calls the signal quality variation, screens the target networks whose variation meets the switching standard, obtains the number of available channels and sorts them in descending order, then extracts the target networks at the top of the sorting column to obtain the network switching priority.

[0012] The present invention is improved in that the switching execution monitoring module includes: The switching execution control submodule calls the network switching priority, obtains the current network connection status and available network options, screens the available networks with critical priorities, executes the network switching operation, and records the changes in the network connection status during the switching process to obtain the network switching status data; The packet loss rate monitoring submodule monitors the packet loss during the switching process based on the network switching state data, calculates the packet loss rate, and compares the packet loss rate according to the network stability standard. If it exceeds the standard, the switching is terminated and rolled back to the original network connection. Otherwise, the packet loss rate and switching delay data are recorded to obtain the network switching stability data; The signal stability analysis submodule calculates the signal strength change trend based on the network switching stability data, using the formula: ; The signal stability analysis results are obtained, where Represents the signal stability, Representative The signal strength at the moment, represents the packet loss rate, represents the switching delay, Represents the total number of signal strength sampling points, Representative Signal strength at the moment.

[0013] A multi-network signal switching control method based on big data, the multi-network signal switching control method based on big data is executed based on the multi-network signal switching control system based on big data, comprising the following steps: S1: Obtain user device location information and moving speed data, analyze the direction change rate and trajectory deviation amplitude, calculate the user trajectory trend change rate, determine whether it is in a stable moving state, and obtain potential network switching points in combination with device location information to obtain a trajectory deviation data set; S2: Based on the trajectory deviation data set, the geographic location data of the user's target area is collected, the base station nodes within the signal coverage range are screened, and the multi-base station signal overlap index of the target area is calculated to obtain the base station signal coverage index; S3: Based on the base station signal coverage index, obtain the real-time channel occupancy rate of each base station in the coverage area, analyze the channel idle ratio of each base station, calculate the number of available channels, and obtain the channel idle ratio index; S4: Based on the channel idle ratio index and the signal strength of the base station to which the user is currently connected, the signal quality change from the user's current location to the target network is calculated, the target network whose change meets the switching criteria is selected, and the number of available channels is sorted to obtain the network switching priority; S5: Based on the network switching priority, perform a network switching operation to determine whether the loss rate exceeds the network stability standard. If so, terminate the switching and roll back to the original network connection. If the switching is successful, calculate the signal strength change trend after the switching to obtain the signal stability analysis result.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are: In the present invention, by integrating user positioning and movement speed data, an accurate prediction of user movement trajectory is provided, and potential network switching points are effectively foreseen. By real-time analysis of user behavior, the system is allowed to dynamically adjust the network switching strategy, thereby improving the continuity and stability of network services. By calculating the user's trajectory trend change rate, the system can predict future network needs before the user status stabilizes. This prediction method combines current data with historical trends to improve the accuracy of the prediction. By analyzing the signal coverage and real-time load of each base station, the signal switching timing and target network selection are optimized, and data packet loss and delay are reduced, thereby ensuring the smoothness and reliability of user experience in a multi-network environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A module diagram of a multi-network signal switching control system based on big data is proposed for the present invention; Figure 2 This is a flow chart of the user trajectory prediction module in the present invention; Figure 3 This is a flow chart of the network coverage analysis module in the present invention; Figure 4 is a flow chart of the signal load evaluation module in the present invention; Figure 5 It is a flow chart of the signal switching decision module in the present invention; Figure 6 This is a flow chart of the switching execution monitoring module in the present invention. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0017] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating positions or positional relationships, are based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0018] Example

[0019] See also Figure 1The present invention provides a technical solution: a multi-network signal switching control system based on big data comprises: The user trajectory prediction module obtains the user device positioning information and movement speed data, analyzes the direction change rate and trajectory deviation amplitude, screens the movement trajectory deviation values ​​of multiple time periods, calculates the user trajectory trend change rate, and determines whether it is in a stable movement state. If the trend change rate is less than the trajectory deviation standard, it fits the future movement trajectory and obtains the potential network switching point in combination with the device location information to obtain the trajectory deviation data set; The network coverage analysis module collects the geographic location data of the user's target area based on the trajectory offset data set, extracts the base station signal coverage range in the area, screens the base station nodes within the signal coverage range, and calculates the multi-base station signal overlap index in the target area to obtain the base station signal coverage index; The signal load evaluation module obtains the real-time channel occupancy rate of each base station in the coverage area based on the base station signal coverage index, filters the signal occupancy data of the target area, analyzes the channel idle ratio of each base station, calculates the number of available channels, and obtains the channel idle ratio index; The signal switching decision module calls the channel idle ratio index, calculates the signal quality change from the user's current location to the target network based on the signal strength of the base station currently connected to the user, selects the target network whose change meets the switching criteria, sorts the number of available channels, and then selects the target network with the highest ranking to obtain the network switching priority; The switching execution monitoring module calls the network switching priority, executes the network switching operation, obtains the packet loss rate and switching delay data during the switching, and determines whether the loss rate exceeds the network stability standard. If it exceeds, the switching is terminated and rolled back to the original network connection. If the switching is successful, the signal strength change trend after the switching is calculated to obtain the signal stability analysis result.

[0020] The trajectory deviation data set includes position accuracy, speed accuracy, and trajectory continuity. The base station signal coverage indicators include signal stability, number of base stations, and area coverage. The channel idle ratio index includes channel capacity, number of idle channels, and channel occupancy. The network switching priority includes signal strength score, network access priority, and channel selection sensitivity. The signal stability analysis results include signal recovery speed, stability index, and connection quality assessment results.

[0021] See also Figure 2 ,The user trajectory prediction module includes: The positioning data collection submodule obtains the user device positioning information and movement speed data, collects the device location points in multiple time periods, calculates the displacement increment in each time period, screens the displacement mutation points, and establishes a preliminary motion data set; The device can be a smart phone, a car GPS or a smart wearable device. The device continuously collects geographic location information and speed parameters through built-in sensors such as GPS modules and accelerometers. Each device reports its location in different time periods, and the timestamp data is used to calculate the displacement increment between adjacent time points, that is, ,in, Representative Geographic coordinate data of a time point, Representative The geographic coordinate data of a time point. Due to the error of GPS data, it is necessary to adjust the positioning data by comparing the average of multiple measurements. For example, the coordinates recorded by a device at 12:00:00 are (120.1, 30.2), and the coordinates recorded at 12:00:10 are (120.105, 30.205). The displacement increment within this time period is calculated as , get the moving speed ,in, The duration of this time period is 10 seconds, and the displacement mutation points are further screened out. If the speed change in adjacent time periods exceeds the set mutation threshold, such as the moving speed at a certain time point is greater than 10m / s, while the speed at the previous time point is only 2m / s, then this time point is identified as a mutation point. Finally, a preliminary motion data set is established, which includes the device position, speed, timestamp and other information of all time periods.

[0022] The trajectory deviation analysis submodule calculates the direction change rate and trajectory deviation amplitude of the user in multiple time periods based on the preliminary motion data set, and analyzes the motion trajectory deviation trend using the formula: ; Calculate the trajectory deviation change , filter the data points with large offset amplitude and obtain the trajectory offset feature set, where, Representative The displacement increment of the segment, that is, the user The change in position within a time period, represents the i-th time increment, i.e. the duration of the time period, Represents the total number of time periods, indicating the number of time periods into which the user's movement trajectory is divided. It is The displacement rate of a segment indicates the displacement change per unit time in this time period. It is The displacement rate of a segment indicates the displacement change per unit time in the previous time segment; If a user's trajectory is , , , in meters; ; ; , ; The displacement rate in the previous time period is: ; The current displacement rate is: ; Calculate the offset change: ; The result shows that the trajectory deviation in this time period is small and can be considered as a normal moving state.

[0023] The trajectory trend calculation submodule calculates the user trajectory trend change rate based on the trajectory deviation feature set to determine whether it is in a stable moving state. If the trajectory trend change rate is less than the trajectory deviation standard, the future moving trajectory is fitted and the potential network switching point is obtained in combination with the device location information to obtain the trajectory deviation data set. The direction change rate and trajectory deviation amplitude of multiple time periods are extracted, and the trajectory trend change rate is calculated. For each time period, the difference between the current direction change rate and the change rate of the previous time period is calculated, that is, , accumulate the data of all time periods and calculate the average value to obtain the overall trajectory trend change rate, set the trajectory deviation standard value, and compare the trajectory trend change rate with the deviation standard. If the change rate is lower than the standard, it is considered that the user is in a stable moving state. At this time, the trajectory is fitted by the least squares method, and the future trajectory path is fitted using the position information of the previous n time periods. In the fitting process, the position of the predicted trajectory point is calculated and combined with the network connection information of the device to determine the potential network switching point. For example, by analyzing the current base station signal strength, Wi-Fi signal switching status, and the network switching rules of historical trajectory points, the potential switching point is determined to obtain the trajectory deviation data set.

[0024] See also Figure 3 , the network coverage analysis module includes: The geographic data acquisition submodule extracts the latitude and longitude, timestamp and movement trajectory offset information based on the trajectory offset data set, establishes the geographic coordinate distribution in the area, and performs spatial integration to obtain the geographic coordinate set of the target area; First, the latitude and longitude, timestamp and movement trajectory offset information of the user's device are extracted. Specifically, the location coordinates of the device at different time points are obtained, and the spatial location information of each time point is recorded to form the user's movement trajectory. For the device data in a specific area, they are arranged in chronological order to analyze the displacement changes of the device at different times. For example, the longitude and latitude of a mobile phone changes from (30.5, 120.3) to (30.51, 120.31) within 1 minute. The movement trajectory offset information of the device is the displacement vector within this time period. After integrating the data of all devices, the geographic coordinate distribution of the target area can be established. For the spatial integration of data, a gridding method is used to divide the target area into multiple small area units, and the center point of each small area unit is used as a representative point. For example, a 5km×5km urban area can be divided into 100 500m×500m grids. The center point of each grid is used as the representative geographic coordinate point of the grid. The representative point data is integrated to form a target area geographic coordinate set.

[0025] The base station signal screening submodule analyzes the signal coverage of each base station based on the target area geographic coordinate set, selects base stations with critical signal strength, and screens out base station nodes with weak signal quality to obtain a valid base station set; Analyze the signal coverage of each base station, that is, use the parameters of the base station equipment such as transmission power, antenna gain, propagation path loss to calculate its signal coverage area. For example, for a base station with a transmission power of 20dBm, an antenna gain of 10dBi, and a path loss index of 3.5, assume that its signal strength attenuation model is ,in, is the received signal power, is the transmission power, is the antenna gain, The signal strength distribution of the base station at different distances is calculated for path loss, and its coverage radius is determined. For all base stations in the target area, their signal coverage range is analyzed in the same way, and the field strength distribution map in the target area is calculated. On this basis, base stations with critical signal strength are selected. For example, if the signal strength of a base station reaches up to -60dBm in the target area, the base station is selected as a valid base station. At the same time, for base stations with weak signal quality, for example, base stations with a maximum signal strength lower than -90dBm, they are eliminated from the calculation to obtain a set of valid base stations.

[0026] The multi-base station overlap analysis submodule calculates the coverage overlap of multiple base station signals in the same geographical area based on the effective base station set and base station coverage data, using the formula: ; Get base station signal coverage indicators ,in, Representative The signal coverage of each base station, Representative The signal coverage of each base station, Representative The area covered by the base station signal. Representative The area covered by the base station signal. Representative and The overlapping area of ​​the base station signal coverage range indicates the size of the shared range of the two base station signals in the same area. is the total number of base stations in the valid base station set; If there are 3 base stations in a certain area, the signal coverage areas are: Base station A: ; Base station B: ; Base station C: ; The overlapping area between base station A and base station B is: ; The overlapping area between base station A and base station C is: ; The overlapping area between base station B and base station C is: ; Calculate the overlap index of each base station: ; ; ; Add the overlap indexes of all base stations to get the base station signal coverage index: ; This result shows that the calculated It reflects the coverage degree of base station signals in the area. A larger value indicates that there are more overlapping areas in the base station coverage signals in the area, and a smaller value indicates that the base station signal coverage is more independent.

[0027] See also Figure 4 , the signal load evaluation module includes: The channel occupancy calculation submodule collects real-time channel occupancy data based on the base station signal coverage index, calculates the total channel usage of each base station, and counts the channel occupancy of different base stations to obtain the base station channel occupancy information; Obtain real-time channel occupancy data of all base stations, monitor channel usage, including the current number of occupied channels and the maximum number of available channels, and record occupancy changes in different time periods for trend analysis. Use timed data collection to record channel occupancy every 30 seconds. Assuming that the maximum number of available channels of a base station is 500, and at a certain moment, the number of occupied channels detected is 320, then the recorded data is (320 / 500=0.64), indicating that the channel occupancy rate of the base station is 64%. Perform statistics on different base stations and calculate their total channel usage. The total channel usage is calculated as the sum of the number of occupied channels of each base station. For example, There are three base stations in the area, and their channel occupancy numbers are 320, 280 and 350 respectively. The total channel usage is 320+280+350=950. Then the channel occupancy of different base stations is counted, and classified statistics are performed according to the preset occupancy rate ranges (0-30%, 30-60%, 60-90%, and above 90%). For example, if there are 10 base stations in a certain area, of which 2 have occupancy rates in the range of 0-30%, 3 in the range of 30-60%, 4 in the range of 60-90%, and 1 above 90%, the channel occupancy of the base stations is recorded separately for subsequent analysis to obtain the base station channel occupancy information.

[0028] The target area signal screening submodule screens the base station data in the target area based on the base station channel occupancy information, excludes the base stations in the non-target area, and extracts the channel occupancy data of the base stations in the target area, performs normalization processing, and obtains the channel occupancy of the target area; Set the boundary coordinates of the target area, and determine whether it is within the target area through the GPS positioning data of the base station. For example, if the target area is defined as a rectangular area with a coordinate range of (x1, y1) to (x2, y2), the GPS coordinates (xi, yi) of the base station need to satisfy x1≤xi≤x2 and y1≤yi≤y2 to be included in the target area. Exclude base stations that do not meet this condition, extract the channel occupancy data of the base stations in the target area, call the channel occupancy information of the base stations in the target area, and record the number of occupied channels and the maximum channel capacity. For example, the number of occupied channels of the five base stations in the target area are 200, 250, 280, 320, and 400, respectively, and the corresponding maximum channel capacities are 500, 500, 600, 600, and 700, respectively. The channel occupancy rates are 40%, 50%, 46.67%, 53.33%, and 57.14%, respectively. Normalize the data using the minimum-maximum normalization formula. ,in, is the original data, and are the minimum and maximum values ​​of the data set, respectively. For example, in the above channel occupancy data, the minimum value is 40% and the maximum value is 57.14%. After normalization, the normalized occupancy rates are , , , and , and obtain the channel occupancy of the target area.

[0029] The channel idle ratio analysis submodule calculates the channel idle ratios of multiple base stations based on the channel occupancy in the target area and analyzes the channel idle situation using the formula: ; Get the channel idle ratio index ,in, It stands for the maximum channel capacity of the base station, which refers to the maximum number of channels that each base station can support under ideal conditions. Representative base station The current channel occupancy of Representative The signal coverage of each base station, Represents the total number of base stations in the target area; The target area contains 4 base stations, whose maximum channel capacities are 500, 600, 700 and 800 respectively, the number of currently occupied channels is 250, 300, 400 and 500 respectively, and the coverage areas are 1.5, 1.8, 2.0 and 2.2 square kilometers respectively. Then calculate the channel idle ratio index of each base station: ; ; ; ; The result shows that the channel idle ratio index in the target area is 2.4455, which can be used to measure the overall channel idle situation in the target area. If the value is low (<1.5), it means that the channel idle ratio in the target area is low, the channel resources are tight, and it is necessary to increase base stations or optimize the scheduling strategy. If the value is high (>3.0), it means that the channel idle ratio in the target area is high, there is a waste of channel resources, and resource reallocation should be considered to improve channel utilization efficiency.

[0030] See also Figure 5 , the signal switching decision module includes: The signal quality assessment submodule calls the channel idle ratio index to obtain the base station signal strength at the user's current location, calculates the signal strength attenuation from the current location to the target network, and adjusts the impact of the channel idle index using the formula: ; Get the signal quality change ,in, Represents the base station signal strength at the user’s current location. Represents the target network signal strength, Represents the idle ratio index of the target network channel, Represents the current base station channel idle ratio index, Represents the physical distance from the user's current location to the target network. Represents the theoretical signal coverage radius of the target network; In the process of signal quality evaluation, the base station signal strength at the user's current location must first be obtained. This parameter can be measured by the wireless signal detection module of the mobile device and expressed in dBm (decibel milliwatt). Suppose the base station signal strength range is dBm (very weak) to dBm (extremely strong), for example, when the signal strength of the base station to which the user is currently connected is for When it is dBm, it means that the network signal quality at this location is relatively stable, and then you need to obtain the signal strength of the target network , which can be obtained through historical measurement data or neighboring cell measurement reports. If the target base station signal strength is dBm, the signal strength attenuation is ; If the channel idle ratio index of the base station is 0.6, the channel idle ratio index of the target network is 0.8, which means that the target network has more available channel resources. Then, the physical distance from the user to the target network is calculated. This parameter can be calculated by combining the user's location information with the base station coordinates. For example, the user is currently 200 meters away from the target base station, and the theoretical signal coverage radius of the target base station is is 1000 meters, then: ; Finally, substitute the above data to calculate the signal quality change: ; ; This value indicates that the signal quality of the target network is improved by 12.37 dB compared with the current network. The signal gain helps to evaluate whether to switch networks, and is further used to sort and select the best switching target to obtain the signal quality change.

[0031] The switching priority sorting submodule calls the signal quality change amount, selects the target network whose change amount meets the switching standard, obtains its available channel number and sorts it in descending order, then extracts the target network in the top column to obtain the network switching priority; Call the signal quality change and compare it with the switching standard value to determine whether it meets the switching conditions. Set the switching threshold to 10dB. When it is greater than 10dB, it means that the signal quality of the target network is significantly improved compared to the current base station, thus becoming a candidate network. In this example, dB, which meets the switching criteria, so the target network is included in the candidate list, and then the number of available channels of the target network is obtained. The number of available channels is updated regularly by the base station and reflects the number of currently available wireless resources. For example, if the number of available channels of target networks A, B, and C are A=12, B=8, and C=15 respectively, then they are sorted in descending order according to the number of available channels. , select the top-ranked target network according to the sorting order. If the system only selects the first two target networks as candidates, the results are C and A, that is, target network C takes precedence over A as the user's switching target, and the network switching priority is obtained.

[0032] See also Figure 6 , the switching execution monitoring module includes: The switching execution control submodule calls the network switching priority, obtains the current network connection status and available network options, screens the available networks with critical priorities, executes the network switching operation, and records the changes in the network connection status during the switching process to obtain the network switching status data; Get the current network connection status and available network options, and filter the available networks with key priorities. The screening process needs to consider multiple factors, including signal strength, bandwidth, network stability, and switching delay. The signal strength can be calculated by the received signal strength indication (RSSI). For example, if the RSSI of the WiFi signal currently connected to a device is -50dBm, and the RSSI of another available WiFi signal is -40dBm, the latter is better. The bandwidth can be measured by the speed test tool. For example, if the current network download speed is 50Mbps, and the download speed of another available network is 80Mbps, the latter is preferred. Combine the data, set the priority weight, and comprehensively calculate the comprehensive score of the available networks. The score calculation formula can be expressed as: ,in, Score the network priority, Represents the signal strength, represents bandwidth, represents the delay, , and are the corresponding weights respectively, if , , , if the network signal strength ,bandwidth , delay , then the priority score is calculated as ,According to the calculated priority score, the network with the highest score is selected for switching, and the network switching operation is performed. The network switching operation includes disconnecting the current network connection, connecting to the target network, verifying whether the network connection is successful, detecting whether the network connection status is stable, recording the changes in the network connection status during the switching process, and obtaining the network switching status data.

[0033] The packet loss rate monitoring submodule monitors the packet loss during the switching process based on the network switching status data, calculates the packet loss rate, and compares the packet loss rate according to the network stability standard. If it exceeds the standard, the switching is terminated and rolled back to the original network connection. Otherwise, the packet loss rate and switching delay data are recorded to obtain the network switching stability data; Monitor the packet loss during the switching process. The packet loss rate can be calculated by the number of packets sent and received. For example, if the device sends 1000 packets during the switching process and only successfully receives 950, the loss rate is calculated as follows: ,in, represents the packet loss rate, Represents the total number of packets sent. Represents the total number of successfully received data packets. Substituting the data into , the packet loss rate is compared according to the network stability standard. The stability standard requires that the packet loss rate does not exceed 2%. If the calculated result is greater than the threshold, the switch is terminated and rolled back to the original network connection. Otherwise, the packet loss rate and switching delay data are continued to be recorded. The switching delay refers to the time required from initiating network switching to successfully establishing a connection. The measurement method can be recorded through timestamps. For example, a device initiates network switching at 10:00:00 and completes the connection at 10:00:02. The switching delay is 2 seconds. Combined with the packet loss rate and switching delay data, the network switching stability data is obtained.

[0034] The signal stability analysis submodule calculates the signal strength change trend based on the network switching stability data using the formula: ; The signal stability analysis results are obtained, where Represents the signal stability. Representative The signal strength at the moment, represents the packet loss rate, represents the switching delay, Represents the total number of signal strength sampling points, Representative The signal strength at the moment, As the impact coefficient of packet loss rate and delay; The signal strength change trend can be calculated by measuring the signal strength fluctuation over a period of time. After the network is switched, the signal strengths collected by the device within 5 seconds are -40dBm, -42dBm, -41dBm, -43dBm and -44dBm respectively. Substitute the data into the calculation: ; Signal fluctuation mean: ; Packet loss rate , switching delay , calculate the stability: ; The result shows that the signal fluctuates greatly and the signal stability is poor. If the signal stability is less than a certain set threshold (for example, -1), the signal is judged to be unstable, otherwise the signal is stable.

[0035] A multi-network signal switching control method based on big data comprises the following steps: S1: Obtain user device location information and moving speed data, analyze the direction change rate and trajectory deviation amplitude, calculate the user trajectory trend change rate, determine whether it is in a stable moving state, and obtain potential network switching points in combination with device location information to obtain a trajectory deviation data set; S2: Based on the trajectory offset data set, the geographic location data of the user's target area is collected, the base station nodes within the signal coverage range are screened, and the multi-base station signal overlap index of the target area is calculated to obtain the base station signal coverage index; S3: Based on the base station signal coverage index, obtain the real-time channel occupancy rate of each base station in the coverage area, analyze the channel idle ratio of each base station, calculate its available channels, and obtain the channel idle ratio index; S4: Based on the channel idle ratio index and the signal strength of the base station to which the user is currently connected, the signal quality change from the user's current location to the target network is calculated, the target network whose change meets the switching criteria is selected, and the number of available channels is sorted to obtain the network switching priority; S5: Based on the network switching priority, perform the network switching operation to determine whether the loss rate exceeds the network stability standard. If it exceeds, terminate the switching and roll back to the original network connection. If the switching is successful, calculate the signal strength change trend after the switching to obtain the signal stability analysis result.

[0036] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A multi-network signal switching control system based on big data, characterized in that: The system comprises: The user trajectory prediction module obtains the user device positioning information and moving speed data, analyzes the direction change rate and trajectory deviation amplitude, calculates the trajectory trend change rate, determines whether it is in a stable moving state, obtains potential network switching points, and obtains a trajectory deviation data set; The network coverage analysis module collects geographic location data of the target area based on the trajectory offset data set, extracts the base station signal coverage range, screens the base station nodes within the coverage range, calculates the multi-base station signal overlap index, and obtains the base station signal coverage index; The signal load evaluation module obtains the real-time channel occupancy rate of each base station in the coverage area based on the base station signal coverage index, analyzes the channel idle ratio, calculates the number of available channels, and obtains the channel idle ratio index; The signal switching decision module calls the channel idle ratio index, calculates the signal quality change according to the base station signal strength, sorts the number of available channels, and obtains the network switching priority; The switching execution monitoring module calls the network switching priority, executes the network switching operation, obtains the data packet loss rate and switching delay data during the switching, calculates the signal strength change trend, and obtains the signal stability analysis result.

2. The multi-network signal switching control system based on big data according to claim 1 is characterized in that: The trajectory offset data set includes position accuracy, speed accuracy, and trajectory continuity; the base station signal coverage indicators include signal stability, number of base stations, and area coverage; the channel idle ratio index includes channel capacity, number of idle channels, and channel occupancy; the network switching priority includes signal strength score, network access priority, and channel selection sensitivity; the signal stability analysis results include signal recovery speed, stability index, and connection quality assessment results.

3. The multi-network signal switching control system based on big data according to claim 1 is characterized in that: The user trajectory prediction module includes: The positioning data collection submodule obtains the user device positioning information and movement speed data, collects the device location points in multiple time periods, calculates the displacement increment in each time period, screens the displacement mutation points, and establishes a preliminary motion data set; The trajectory deviation analysis submodule calculates the direction change rate and trajectory deviation amplitude of the user in multiple time periods based on the preliminary motion data set, and analyzes the motion trajectory deviation trend using the formula: ； Calculate the trajectory deviation change , filter the data points with large offset amplitude and obtain the trajectory offset feature set, where, Representative Segment displacement increment, represents the i-th time increment, Represents the total number of time periods, It is The displacement rate of the segment, It is The displacement rate of the segment; The trajectory trend calculation submodule calculates the user trajectory trend change rate based on the trajectory deviation feature set to determine whether it is in a stable moving state. If the trajectory trend change rate is less than the trajectory deviation standard, the future moving trajectory is fitted, and the potential network switching point is obtained in combination with the device location information to obtain a trajectory deviation data set.

4. The multi-network signal switching control system based on big data according to claim 1 is characterized in that: The network coverage analysis module includes: The geographic data acquisition submodule extracts the latitude and longitude, timestamp and movement trajectory offset information based on the trajectory offset data set, establishes the geographic coordinate distribution in the area, and performs spatial integration to obtain the geographic coordinate set of the target area; The base station signal screening submodule analyzes the signal coverage of each base station based on the target area geographic coordinate set, selects base stations with critical signal strength, and screens out base station nodes with weak signal quality to obtain a valid base station set; The multi-base station overlap analysis submodule calculates the coverage overlap of multiple base station signals in the same geographical area based on the effective base station set and base station coverage data, using the formula: ； Get base station signal coverage indicators ,in, Representative The signal coverage of each base station, Representative The signal coverage of each base station, Representative The area covered by the base station signal. Representative The area covered by the base station signal. Representative and The overlapping area of ​​the base station signal coverage range, is the total number of base stations in the valid base station set.

5. The multi-network signal switching control system based on big data according to claim 1 is characterized in that: The signal load evaluation module comprises: The channel occupancy calculation submodule collects real-time channel occupancy rate data based on the base station signal coverage index, calculates the total channel usage of each base station, and counts the channel occupancy of different base stations to obtain base station channel occupancy information; The target area signal screening submodule screens the base station data in the target area based on the base station channel occupancy information, excludes the base stations in the non-target area, and extracts the channel occupancy data of the base stations in the target area, performs normalization processing, and obtains the channel occupancy of the target area; The channel idle ratio analysis submodule calculates the channel idle ratios of multiple base stations based on the channel occupancy in the target area and analyzes the channel idle situation using the formula: ； Get the channel idle ratio index ,in, represents the maximum channel capacity of the base station, Representative base station The current channel occupancy of Representative The signal coverage of each base station, Represents the total number of base stations in the target area.

6. The multi-network signal switching control system based on big data according to claim 1 is characterized in that: The signal switching decision module includes: The signal quality assessment submodule calls the channel idle ratio index, obtains the base station signal strength at the user's current location, calculates the signal strength attenuation from the current location to the target network, and adjusts the impact of the channel idle index using the formula: ； Get the signal quality change ,in, Represents the base station signal strength at the user’s current location. Represents the target network signal strength, Represents the idle ratio index of the target network channel, Represents the current base station channel idle ratio index, Represents the physical distance from the user's current location to the target network. Represents the theoretical signal coverage radius of the target network; The switching priority sorting submodule calls the signal quality variation, screens the target networks whose variation meets the switching standard, obtains the number of available channels and sorts them in descending order, then extracts the target networks at the top of the sorting column to obtain the network switching priority.

7. The multi-network signal switching control system based on big data according to claim 1 is characterized in that: The switching execution monitoring module includes: The switching execution control submodule calls the network switching priority, obtains the current network connection status and available network options, screens the available networks with critical priorities, executes the network switching operation, and records the changes in the network connection status during the switching process to obtain the network switching status data; The packet loss rate monitoring submodule monitors the packet loss during the switching process based on the network switching state data, calculates the packet loss rate, and compares the packet loss rate according to the network stability standard. If it exceeds the standard, the switching is terminated and rolled back to the original network connection. Otherwise, the packet loss rate and switching delay data are recorded to obtain the network switching stability data; The signal stability analysis submodule calculates the signal strength change trend based on the network switching stability data, using the formula: ； The signal stability analysis results are obtained, where Represents the signal stability, Representative The signal strength at the moment, represents the packet loss rate, represents the switching delay, Represents the total number of signal strength sampling points, Representative Signal strength at the moment.

8. A multi-network signal switching control method based on big data, characterized in that: The multi-network signal switching control system based on big data according to any one of claims 1 to 7 comprises the following steps: S1: Obtain user device location information and moving speed data, analyze the direction change rate and trajectory deviation amplitude, calculate the user trajectory trend change rate, determine whether it is in a stable moving state, and obtain potential network switching points in combination with device location information to obtain a trajectory deviation data set; S2: Based on the trajectory deviation data set, the geographic location data of the user's target area is collected, the base station nodes within the signal coverage range are screened, and the multi-base station signal overlap index of the target area is calculated to obtain the base station signal coverage index; S3: Based on the base station signal coverage index, obtain the real-time channel occupancy rate of each base station in the coverage area, analyze the channel idle ratio of each base station, calculate the number of available channels, and obtain the channel idle ratio index; S4: Based on the channel idle ratio index and the signal strength of the base station to which the user is currently connected, the signal quality change from the user's current location to the target network is calculated, the target network whose change meets the switching criteria is selected, and the number of available channels is sorted to obtain the network switching priority; S5: Based on the network switching priority, perform a network switching operation to determine whether the loss rate exceeds the network stability standard. If so, terminate the switching and roll back to the original network connection. If the switching is successful, calculate the signal strength change trend after the switching to obtain the signal stability analysis result.

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