Communication transmission management method, system and storage medium for heterogeneous networks

Abstract

The present application relates to the field of data processing technology, and discloses a communication transmission management method, system and storage medium for heterogeneous networks. The method includes: processing the signal strength parameters and the data priority in the data classification configuration table to obtain a network resource allocation plan; real-time monitoring and processing of 4G / 5G cellular network base stations, WiFi hotspots and satellite communication nodes to obtain network switching control instructions; transmission quality monitoring and processing of engine parameters, navigation data, airborne equipment status data and environmental monitoring data to obtain a transmission quality parameter table; data mining and analysis of the network switching control instructions and the transmission quality parameter table to obtain transmission strategy optimization parameters including network resource optimization configuration. In a heterogeneous network environment, the present application realizes intelligent network switching and resource allocation based on data priority to ensure the transmission requirements of data of different priorities, while improving the efficiency of network resource utilization.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a communication transmission management method, system and storage medium for heterogeneous networks. Background Art

[0002] With the rapid development of civil aviation, aircraft flight data recorders play an increasingly important role in flight safety monitoring. Existing flight data recording technologies mainly rely on a single communication network for data transmission, such as 4G / 5G cellular networks, airport WiFi, or satellite communications. These communication methods have their own characteristics: cellular networks have a wide coverage range but unstable signals at high altitudes, WiFi has a high transmission rate but limited coverage, and satellite communications have high reliability but high costs. At present, the industry has begun to try to combine multiple communication networks to improve the reliability and efficiency of data transmission. Some flight data recording systems have begun to adopt dual-link or even multi-link transmission solutions.

[0003] However, the existing multi-network transmission scheme has obvious shortcomings. First, the switching of various communication networks lacks an intelligent decision-making mechanism, and is often switched based on a simple signal strength threshold, which fails to fully consider the actual needs of data transmission and the efficiency of network resource utilization. Second, different types of flight data have different transmission priorities and real-time requirements, but the existing system cannot dynamically adjust the transmission strategy according to the characteristics of the data. In addition, data loss or delay is prone to occur during the network switching process, affecting the reliability of data transmission. Summary of the invention

[0004] The present application provides a communication transmission management method, system and storage medium for heterogeneous networks, which are used to implement intelligent network switching and resource allocation based on data priority in a heterogeneous network environment to ensure the transmission requirements of data of different priorities while improving the efficiency of network resource utilization.

[0005] In the first aspect, the present application provides a communication transmission management method for a heterogeneous network, and the communication transmission management method for a heterogeneous network includes: performing feature collection and processing on 4G / 5G cellular network base station information, WiFi hotspot distribution information and satellite communication node orbit parameters to obtain a heterogeneous network node information database containing transmission delay, packet loss rate and signal strength parameters; performing hierarchical processing on engine parameters, navigation data, airborne equipment status data and environmental monitoring data based on the transmission delay and the packet loss rate to obtain a data hierarchical configuration table containing data priority levels; performing resource matching based on the signal strength parameters in the heterogeneous network node information database and the data priority levels in the data hierarchical configuration table. The invention relates to a method for performing heuristic algorithm processing on the 4G / 5G cellular network base station, the WiFi hotspot and the satellite communication node to obtain a network resource allocation plan including a network switching threshold; performing real-time monitoring processing on the 4G / 5G cellular network base station, the WiFi hotspot and the satellite communication node based on the network switching threshold to obtain a network switching control instruction including a network switching mode; performing transmission quality monitoring processing on the engine parameters, the navigation data, the airborne equipment status data and the environmental monitoring data based on the network switching mode to obtain a transmission quality parameter table including transmission control parameters; performing data mining analysis processing on the network switching control instruction and the transmission quality parameter table based on the resource matching to obtain transmission strategy optimization parameters including network resource optimization configuration.

[0006] In a second aspect, the present application provides a communication transmission management system for a heterogeneous network, the communication transmission management system for a heterogeneous network comprising:

[0007] The acquisition module is used to collect and process the characteristics of 4G / 5G cellular network base station information, WiFi hotspot distribution information and satellite communication node orbit parameters to obtain a heterogeneous network node information database containing transmission delay, packet loss rate and signal strength parameters;

[0008] A classification module, used for performing classification processing on engine parameters, navigation data, airborne equipment status data and environmental monitoring data based on the transmission delay and the packet loss rate to obtain a data classification configuration table including data priority levels;

[0009] A processing module, configured to perform a heuristic algorithm processing based on resource matching on the signal strength parameter in the heterogeneous network node information database and the data priority level in the data classification configuration table to obtain a network resource allocation scheme including a network switching threshold;

[0010] A switching module, configured to perform real-time monitoring and processing on the 4G / 5G cellular network base station, the WiFi hotspot, and the satellite communication node based on the network switching threshold, and obtain a network switching control instruction including a network switching mode;

[0011] A monitoring module, used for performing transmission quality monitoring processing on the engine parameters, the navigation data, the airborne device status data and the environmental monitoring data based on the network switching mode, and obtaining a transmission quality parameter table including transmission control parameters;

[0012] The analysis module is used to perform data mining analysis on the network switching control instruction and the transmission quality parameter table based on the resource matching to obtain transmission strategy optimization parameters including network resource optimization configuration.

[0013] In a third aspect, the present application provides a computer-readable storage medium, in which instructions are stored, and when the computer-readable storage medium is run on a computer, the computer executes the above-mentioned communication transmission management method for heterogeneous networks.

[0014] In the technical solution provided by the present application, by collecting and processing the characteristics of 4G / 5G cellular network base station information, WiFi hotspot distribution information and satellite communication node orbit parameters, the comprehensive perception and effective management of heterogeneous network resources are realized, ensuring the optimization of network resource utilization. On this basis, the engine parameters, navigation data, airborne equipment status data and environmental monitoring data are graded based on transmission delay and packet loss rate, and a scientific data priority mechanism is established to ensure the transmission quality of key data. By processing the signal strength parameters in the heterogeneous network node information database and the data priority level in the data classification configuration table based on resource matching, the dynamic optimization allocation of network resources is realized, and the resource utilization efficiency is improved. During the network switching process, the 4G / 5G cellular network base station, WiFi hotspot and satellite communication node are monitored and processed in real time based on the network switching threshold, ensuring the timeliness and accuracy of the network switching and reducing the data loss during the switching process. The transmission quality monitoring and processing of engine parameters, navigation data, airborne equipment status data and environmental monitoring data based on the network switching mode is carried out, realizing the real-time monitoring and dynamic adjustment of data transmission quality, and ensuring the reliability of data transmission. Finally, through data mining and analysis based on resource matching of network switching control instructions and transmission quality parameter tables, an adaptive network resource optimization mechanism was established to continuously improve the operating efficiency of the system. The overall solution significantly improves the communication transmission reliability in heterogeneous network environments through multi-level data processing and control strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0016] Figure 1 A schematic diagram of an embodiment of a communication transmission management method for a heterogeneous network in an embodiment of the present application;

[0017] Figure 2 This is a schematic diagram of an embodiment of a communication transmission management system for a heterogeneous network in an embodiment of the present application. DETAILED DESCRIPTION

[0018] The embodiments of the present application provide a communication transmission management method, system and storage medium for heterogeneous networks. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0019] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 , an embodiment of a communication transmission management method for a heterogeneous network in an embodiment of the present application includes:

[0020] Step S101, performing feature collection and processing on 4G / 5G cellular network base station information, WiFi hotspot distribution information and satellite communication node orbit parameters to obtain a heterogeneous network node information database including transmission delay, packet loss rate and signal strength parameters;

[0021] Step S102, performing hierarchical processing on engine parameters, navigation data, airborne equipment status data and environmental monitoring data based on transmission delay and packet loss rate to obtain a data hierarchical configuration table including data priority levels;

[0022] Step S103, performing a heuristic algorithm based on resource matching on the signal strength parameters in the heterogeneous network node information database and the data priority levels in the data classification configuration table to obtain a network resource allocation scheme including a network switching threshold;

[0023] Step S104: performing real-time monitoring and processing on 4G / 5G cellular network base stations, WiFi hotspots, and satellite communication nodes based on network switching thresholds to obtain a network switching control instruction including a network switching mode;

[0024] Step S105: Perform transmission quality monitoring processing based on the network switching mode on the engine parameters, navigation data, airborne equipment status data and environmental monitoring data to obtain a transmission quality parameter table including transmission control parameters;

[0025] Step S106: Perform data mining analysis based on resource matching on the network switching control instruction and the transmission quality parameter table to obtain transmission strategy optimization parameters including network resource optimization configuration.

[0026] It is understandable that the execution subject of the present application may be a communication transmission management system for a heterogeneous network, or a terminal or a server, which is not specifically limited here. The present application embodiment is described by taking a server as the execution subject as an example.

[0027] Specifically, a heterogeneous network node information database is established. By collecting features of 4G / 5G cellular network base station information, the location coordinates and coverage radius data of the base station are obtained. The base station information collection includes key parameters such as signal strength, network bandwidth, and real-time load. At the same time, the WiFi hotspot distribution information is collected to obtain data such as the geographical distribution of hotspots, signal coverage, and access capacity. The orbital parameters of satellite communication nodes are analyzed to record parameters such as the satellite's orbital altitude, inclination, and coverage. After feature extraction and data processing, these collected raw data form a heterogeneous network node information database containing transmission delay, packet loss rate, and signal strength parameters. After completing the network node information collection, the flight data needs to be graded. Flight data includes engine parameters (such as speed, temperature, pressure, etc.), navigation data (position, speed, attitude, etc.), airborne equipment status data (working mode, fault code, etc.), and environmental monitoring data (temperature, humidity, air pressure, etc.). These data are graded based on transmission delay and packet loss rate, with key engine parameters and navigation data that directly affect flight safety given the highest priority, airborne equipment status data given the second priority, and environmental monitoring data given the general priority, forming a data classification configuration table.

[0028] Next, a heuristic algorithm is used to perform resource matching processing on the signal strength parameters in the heterogeneous network node information database and the data priority in the data classification configuration table. The heuristic algorithm calculates the optimal resource allocation plan by evaluating the signal quality and data transmission requirements of the network nodes. The algorithm first establishes a network resource evaluation model, comprehensively considers factors such as network bandwidth and transmission delay, and then optimizes resource allocation according to data priority to generate a network resource allocation plan including a network switching threshold. Based on the generated network switching threshold, 4G / 5G cellular network base stations, WiFi hotspots, and satellite communication nodes are monitored in real time. The monitoring content includes indicators such as signal strength changes, network load status, and transmission quality. When the monitoring indicators reach the preset switching threshold, the network switching mechanism is triggered and a network switching control instruction is generated. The switching control instruction contains specific switching timing and switching mode to ensure the continuity of data transmission.

[0029] During the network switching process, the data transmission quality needs to be monitored in real time. According to the previously set network switching mode, the transmission quality of engine parameters, navigation data, airborne equipment status data and environmental monitoring data is monitored, including transmission rate, data integrity, transmission delay and other indicators. The monitoring results are recorded in the transmission quality parameter table as a basis for network resource optimization. Finally, data mining and analysis are performed on the network switching control instructions and the transmission quality parameter table. Through the analysis of historical data, the correlation between network switching mode and transmission quality is discovered, and the resource allocation strategy is optimized. The data mining process includes pattern recognition, correlation analysis, trend prediction, etc., and finally generates the transmission strategy optimization parameters for network resource optimization configuration.

[0030] For example, during the flight of an aircraft, the engine parameters are collected 10 times per second, the navigation data is collected 5 times per second, the equipment status data is collected 2 times per second, and the environmental data is collected 1 time per second. Through feature collection and processing, it is found that there are 3 4G base stations in the current area, with signal strengths of -75dBm, -82dBm, and -89dBm respectively, 2 WiFi hotspots with signal strengths of -65dBm and -72dBm, and satellite signal strength of -95dBm. Based on the transmission delay test, the average delay of the 4G network is 120ms, the WiFi delay is 80ms, and the satellite delay is 900ms; the packet loss rates are 1.2%, 0.8%, and 0.3% respectively. The system classifies key parameters such as engine speed and temperature as the highest priority, requiring the delay to not exceed 150ms, and navigation data as the second highest priority, with an allowable delay of 200ms. Through the heuristic algorithm, it is calculated that the network switching is triggered when the 4G signal strength is lower than -85dBm and the WiFi signal strength is higher than -70dBm. During the actual switching process, it was found that the transmission completeness rate of high-priority data remained above 99.5%, and the transmission delay was controlled within the expected range, proving that the solution can effectively ensure the data transmission quality in a heterogeneous network environment.

[0031] In the embodiment of the present application, by performing feature acquisition processing on 4G / 5G cellular network base station information, WiFi hotspot distribution information and satellite communication node orbit parameters, comprehensive perception and effective management of heterogeneous network resources are achieved, ensuring the optimization of network resource utilization. On this basis, engine parameters, navigation data, airborne equipment status data and environmental monitoring data are graded based on transmission delay and packet loss rate, and a scientific data priority mechanism is established to ensure the transmission quality of key data. By performing heuristic algorithm processing based on resource matching on the signal strength parameters in the heterogeneous network node information database and the data priority level in the data classification configuration table, dynamic optimization allocation of network resources is achieved, and resource utilization efficiency is improved. During the network switching process, 4G / 5G cellular network base stations, WiFi hotspots and satellite communication nodes are monitored and processed in real time based on the network switching threshold, ensuring the timeliness and accuracy of network switching and reducing data loss during the switching process. Transmission quality monitoring and processing based on the network switching mode are performed on engine parameters, navigation data, airborne equipment status data and environmental monitoring data, realizing real-time monitoring and dynamic adjustment of data transmission quality, and ensuring the reliability of data transmission. Finally, through data mining and analysis based on resource matching of network switching control instructions and transmission quality parameter tables, an adaptive network resource optimization mechanism was established to continuously improve the operating efficiency of the system. The overall solution significantly improves the reliability of communication transmission in heterogeneous network environments through multi-level data processing and control strategies.

[0032] In a specific embodiment, the process of executing step S101 may specifically include the following steps:

[0033] (1) Collect and process the location coordinates and coverage radius of 4G / 5G cellular network base station information to obtain the base station distribution matrix, and interpolate the signal attenuation factor in the base station distribution matrix to obtain the base station signal attenuation data;

[0034] (2) Collect and process the access capacity and channel bandwidth of WiFi hotspot distribution information to obtain the hotspot capacity matrix, and normalize the channel quality indicators in the hotspot capacity matrix to obtain the hotspot channel data;

[0035] (3) Analyze the orbital parameters of the satellite communication node to obtain the satellite coverage matrix, and compensate the signal beam data in the satellite coverage matrix to obtain satellite signal data;

[0036] (4) Perform feature extraction processing on base station signal attenuation data, hotspot channel data, and satellite signal data to obtain a signal feature set, and perform weighted fusion processing on the signal feature set to obtain transmission delay;

[0037] (5) Perform timing analysis on the transmission delay to obtain the packet loss probability distribution, and perform threshold segmentation on the packet loss probability distribution to obtain the packet loss rate;

[0038] (6) Perform channel quality assessment on base station signal attenuation data, hotspot channel data, and satellite signal data to obtain signal strength, and write the transmission delay, packet loss rate, and signal strength into the heterogeneous network node information database.

[0039] Specifically, the data of 4G / 5G cellular network base station information is collected and processed. The base station information includes location coordinates (longitude, latitude, altitude) and coverage radius, which are obtained through GPS positioning and field signal measurement. For each base station, its unique identification ID, working frequency band, transmission power and other parameters are recorded, and this information is organized into a base station distribution matrix. The base station distribution matrix is ​​a multidimensional array, and each row represents the complete information of a base station. The signal attenuation factor reflects the degree of signal loss during propagation. The signal attenuation factor in the base station distribution matrix is ​​interpolated, and the data between sampling points is estimated using the Kriging interpolation method to generate continuous signal attenuation distribution data. For the processing of WiFi hotspot distribution information, the two key parameters of access capacity and channel bandwidth are focused on. Access capacity refers to the maximum number of user connections supported by a single hotspot at the same time, and channel bandwidth represents the maximum rate of data transmission. These data are organized into a hotspot capacity matrix, and each element in the matrix contains information such as the location information, coverage range, number of current access users, and remaining bandwidth of the hotspot. The channel quality indicators in the hotspot capacity matrix are normalized, and indicators of different dimensions are unified to the [0,1] interval to facilitate subsequent comprehensive evaluation. The normalized data forms the hotspot channel data, which includes the standardized channel quality score.

[0040] The processing of satellite communication nodes focuses on orbital parameter analysis. Satellite orbital parameters include orbital altitude, inclination, period, etc. These parameters are used to calculate the real-time position and coverage of the satellite to form a satellite coverage matrix. The satellite coverage matrix describes the ground projection range and signal strength distribution of the satellite signal. The signal beam data in the satellite coverage matrix is ​​compensated to compensate for the influence of factors such as atmospheric attenuation and Doppler effect to obtain more accurate satellite signal data. The base station signal attenuation data, hotspot channel data and satellite signal data are feature extracted, and the principal component analysis method is used to extract key features to form a signal feature set. Feature extraction focuses on the trend of signal strength changes, spectral characteristics, spatial distribution characteristics, etc. The extracted features are weighted and fused, and weights are assigned according to the reliability and stability of different communication methods to calculate the comprehensive transmission delay index.

[0041] The transmission delay data is analyzed and processed in time series, and the time series analysis method is used to study the variation law of delay, including trend analysis, periodic analysis and mutation detection. The correlation between delay and packet loss is established through statistical analysis, and the packet loss probability distribution is generated. The OTSU algorithm is used to perform threshold segmentation on the packet loss probability distribution to determine the packet loss rate classification standard. Finally, the channel quality of the base station signal attenuation data, hotspot channel data and satellite signal data is evaluated, and the standardized signal strength index is calculated by comprehensively considering indicators such as signal strength, signal-to-noise ratio, bit error rate, etc. Key indicators such as transmission delay, packet loss rate and signal strength are written into the heterogeneous network node information database to provide data support for subsequent network selection and resource allocation.

[0042] For example, during a flight on a certain route, the 4G base station information along the way was collected, including the location coordinates of three base stations (base station A: 116.123°E, 39.456°N, 50m; base station B: 116.234°E, 39.567°N, 45m; base station C: 116.345°E, 39.678°N, 48m), with coverage radii of 1.2km, 1.5km, and 1.3km respectively. Through signal strength measurement, the signal attenuation factors were obtained to be 2.8dB / km, 3.1dB / km, and 2.9dB / km respectively. The Kriging interpolation method was used to spatially interpolate the signal attenuation and obtain a continuous signal attenuation distribution. At the same time, it was recorded that the access capacity of the two WiFi hotspots was 200 users and 150 users respectively, the channel bandwidth was 54Mbps and 36Mbps, the current number of access users was 120 and 85 respectively, and the channel quality indicators were obtained by normalization processing to be 0.85 and 0.78. The satellite communication node orbit altitude is 35786km, the inclination is 3.5°, and the signal strength after atmospheric attenuation compensation is -95dBm. Feature extraction and weighted fusion of these data are performed, and the average transmission delay is calculated to be: 125ms for 4G network, 85ms for WiFi network, and 890ms for satellite communication. After timing analysis and threshold segmentation, the packet loss rates of each network are 1.2%, 0.9%, and 0.3%, respectively. The final comprehensive evaluation signal strength indicators are 0.82, 0.88, and 0.95, respectively. These data are written into the heterogeneous network node information database to guide real-time network switching decisions.

[0043] In a specific embodiment, the process of executing step S102 may specifically include the following steps:

[0044] (1) Perform data sampling and processing on the engine parameters of speed, temperature, and pressure to obtain the engine state matrix, and perform importance analysis on the key indicators in the engine state matrix to obtain the engine data level;

[0045] (2) Perform data sampling and processing on the position, speed, and attitude of the navigation data to obtain the navigation state matrix, and perform threshold comparison on the deviation indicators in the navigation state matrix to obtain the navigation data level;

[0046] (3) Perform data analysis on the working mode and fault code of the airborne equipment status data to obtain the equipment status matrix, and classify the abnormal indicators in the equipment status matrix to obtain the equipment data level;

[0047] (4) Sampling and processing the temperature, humidity, and air pressure of the environmental monitoring data to obtain the environmental state matrix, and classifying the range of the change indicators in the environmental state matrix to obtain the environmental data level;

[0048] (5) Prioritize the engine data level, navigation data level, equipment data level, and environment data level based on the transmission delay to obtain a delay priority table, and perform correction processing on the delay priority table based on the packet loss rate to obtain the data priority level;

[0049] (6) Generate a data classification configuration table based on the data priority level and the corresponding relationship between engine parameters, navigation data, airborne equipment status data, and environmental monitoring data.

[0050] Specifically, the engine parameters are sampled and processed. The engine parameters include speed (RPM), temperature (turbine pre-temperature, exhaust temperature, etc.), and pressure (compressor pressure, fuel pressure, etc.). The sampling frequency is set to 10 times per second, and each sampling point records a complete set of engine parameters. These sampled data are organized into an engine state matrix, where each row of the matrix represents the sampled data at a time point, and the columns represent different parameter types. The key indicators in the engine state matrix are analyzed for importance and evaluated by setting safety thresholds. For example, speed fluctuations exceeding 5%, temperature exceeding the upper limit of the set value by 10%, and pressure below the normal value by 20% are all marked as high-importance indicators. After importance analysis, the engine data level is obtained, which is divided into three levels: emergency level, critical level, and general level. The sampling and processing of navigation data is the second key link. Navigation data contains aircraft position information (latitude and longitude, altitude), speed information (ground speed, airspeed, vertical speed) and attitude information (pitch angle, roll angle, heading angle). The sampling frequency is 5 times per second to form a navigation state matrix. The deviation indicators in the navigation status matrix are compared with thresholds, and the position deviation exceeding 100 meters, the speed deviation exceeding 10 knots, and the attitude angle deviation exceeding 2 degrees are identified as data that need special attention. The navigation data level is divided into real-time level, high priority level, and regular level according to the degree of deviation.

[0051] The processing of airborne equipment status data mainly focuses on working modes and fault codes. Working modes include normal, standby, fault and other states. Fault codes include various abnormal information found by equipment self-test. These data are parsed and processed to generate an equipment status matrix. The matrix records the operating status, fault level, duration and other information of each device. The abnormal indicators in the equipment status matrix are graded, and the equipment data level is divided into fault level, warning level and prompt level according to the severity of the fault and the impact on flight safety. The processing of environmental monitoring data includes sampling of parameters such as temperature, humidity and air pressure. The sampling frequency is once per second, recording the changes in the environment around the aircraft. These data constitute the environmental status matrix, which is used to monitor the changing trend of the flight environment. The change indicators in the environmental status matrix are range-graded. For example, the temperature change rate exceeds 5℃ / minute, and the air pressure change exceeds 5hPa / minute, which are marked as changes that need attention. According to the magnitude of the change, the environmental data level is divided into fast change level, medium change level and slow change level.

[0052] After obtaining the level division of various types of data, priority synthesis is required. First, the priority is initially divided based on the transmission delay. All engine data levels, navigation data levels, equipment data levels, and environmental data levels are sorted according to their sensitivity to delay, and a delay priority table is generated. Data with high delay sensitivity obtains higher priority, such as engine emergency data requiring a delay of no more than 100 milliseconds, and navigation real-time data requiring a delay of no more than 200 milliseconds. Then, the priority is corrected according to the packet loss rate, and the tolerance of different levels of data to packet loss is considered to generate the final data priority level. Finally, a corresponding relationship is established between the data priority level and the specific data type, and a data classification configuration table is generated. The configuration table records in detail the specific parameters, sampling requirements, priority level, transmission requirements, and other information of each type of data. This configuration table serves as an important basis for the allocation of heterogeneous network communication resources.

[0053] For example: During the flight of a commercial airliner, engine parameter sampling showed that the temperature of the engine No. 1 turbine reached 850°C (normal range 750-800°C), and the compressor pressure fluctuated (±5%), which was determined to be emergency data after importance analysis. Navigation data from the same period showed that the aircraft attitude fluctuated slightly, and the pitch angle changed by ±1.5 degrees, which was within the threshold range and was determined to be high priority data. Airborne equipment status monitoring found that the air conditioning system had a fault code E-235 (reduced cooling efficiency), which was assessed as a warning level based on the impact of the fault. Environmental monitoring data showed that the external temperature dropped by 8°C within 10 minutes, which was determined to be a rapid change level. Based on the delay requirements, the engine emergency level data requirement delay is set to 80ms, navigation high priority data 150ms, equipment warning level data 300ms, and environmental rapid change level data 500ms. Considering that the packet loss tolerance of engine data and navigation data is low (no more than 0.1%), while the tolerance of device status and environmental data is high (1% packet loss rate is acceptable), the engine temperature and pressure data are finally set as the highest priority in the data classification configuration table, the navigation attitude data is the second highest priority, and the device fault information and environmental change data are the regular priority. This hierarchical configuration ensures that when network resources are limited, critical data can be transmitted first.

[0054] In a specific embodiment, the process of executing step S103 may specifically include the following steps:

[0055] (1) Perform piecewise linearization on the signal strength parameters to obtain the network node signal sequence, and perform fluctuation analysis on the network node signal sequence to obtain the signal stability;

[0056] (2) Perform numerical quantization on the data priority to obtain a priority weight sequence, and normalize the priority weight sequence to obtain a data transmission weight;

[0057] (3) Perform correlation analysis on signal stability and data transmission weight to obtain a resource matching matrix, and then perform optimal matching processing on the resource matching matrix through a genetic algorithm to obtain a resource allocation sequence;

[0058] (4) Performing bandwidth allocation processing on the resource allocation sequence to obtain a bandwidth allocation table, and performing time slot scheduling processing on the bandwidth allocation table to obtain a resource allocation strategy;

[0059] (5) Calculate the network switching cost of the resource allocation strategy to obtain a switching cost matrix, and perform threshold extraction processing on the switching cost matrix to obtain a network switching threshold;

[0060] (6) Generate a network resource allocation plan based on the correspondence between the resource allocation strategy and the network switching threshold.

[0061] Specifically, the signal strength parameters are processed by piecewise linearization. The signal strength parameters include the strength values ​​of 4G / 5G base station signals, WiFi hotspot signals and satellite signals. The piecewise linearization process divides the continuous signal strength parameters into multiple linear intervals according to the preset segmentation points, and a linear function is used in each interval to describe the signal change characteristics. For example, the 4G signal strength of -75dBm to -85dBm is a linear interval, and -85dBm to -95dBm is another linear interval. After processing, a network node signal sequence is obtained, which contains the signal strength values ​​of each network node at different time points. The network node signal sequence is subjected to fluctuation analysis, and statistical indicators such as the standard deviation and coefficient of variation of the signal strength are calculated to evaluate the stability of the signal and obtain the signal stability. The data priority level is numerically quantified. The data priority level includes multiple levels such as the highest priority, high priority, medium priority and low priority. Each priority level is assigned a specific value through quantization, such as 1.0 for the highest priority, 0.8 for the high priority, 0.6 for the medium priority and 0.4 for the low priority. In this way, a priority weight sequence is obtained, and then the sequence is normalized so that the sum of all weight values ​​is 1, thereby obtaining a standardized data transmission weight.

[0062] The correlation analysis of signal stability and data transmission weight is performed. By calculating the correlation coefficient between the two, the matching degree between network signal quality and data transmission requirements is evaluated to form a resource matching matrix. Each element in the resource matching matrix represents the matching degree between a specific network node and a specific priority data. The genetic algorithm is used to optimize the resource matching matrix. The genetic algorithm continuously iterates to find the optimal resource allocation scheme through selection, crossover and mutation operations. The population size is set to 100, the number of iterations is 1000, the crossover probability is 0.8, and the mutation probability is 0.1. Finally, the resource allocation sequence is obtained. Bandwidth allocation processing is performed on the resource allocation sequence. According to the available bandwidth and data transmission requirements of each network node, the specific bandwidth value allocated to each data stream is calculated to generate a bandwidth allocation table. The bandwidth allocation table records the bandwidth allocation of each data stream in detail, including parameters such as the minimum guaranteed bandwidth and the maximum allowed bandwidth. The bandwidth allocation table is processed by time slot scheduling, the time axis is divided into time slots of fixed length, and transmission time slots are allocated to data of different priorities to form a complete resource allocation strategy.

[0063] Calculate the network switching cost for the resource allocation strategy. The switching cost includes multiple factors such as time overhead, energy consumption, and data cache. These factors are quantified to form a switching cost matrix. Perform threshold extraction processing on the switching cost matrix, set the critical conditions for switching triggering, and obtain the network switching threshold. The correspondence between the resource allocation strategy and the network switching threshold is organized into a complete network resource allocation plan.

[0064] For example, during the aircraft cruising process, the signal strength data of three network nodes are collected. The signal strength of the 4G base station fluctuates between -80dBm and -90dBm, and is divided into three intervals after piecewise linearization: [-80dBm, -85dBm], [-85dBm, -88dBm], and [-88dBm, -90dBm]. The calculated signal stability is 0.85. The signal strength of the WiFi hotspot is between -65dBm and -75dBm, and the signal stability is 0.92 after segmentation. The satellite signal strength is between -95dBm and -98dBm, and the signal stability is 0.95. At the same time, the onboard data is divided into four categories according to priority: engine key parameters are the highest priority (1.0), navigation data is high priority (0.8), equipment status is medium priority (0.6), and environmental data is low priority (0.4). After normalization, the data transmission weights are 0.36, 0.29, 0.21, and 0.14, respectively.

[0065] Through correlation analysis, the resource matching matrix is ​​calculated, among which the matching degree between WiFi hotspot and key engine parameters is the highest (0.95), the matching degree between 4G network and navigation data is 0.88, and the matching degrees between satellite communication and equipment status and environmental data are 0.82 and 0.78 respectively. After genetic algorithm optimization, the final resource allocation scheme is determined as follows: key engine parameters use WiFi network first, with a bandwidth of 20Mbps; navigation data uses 4G network, with a bandwidth of 15Mbps; equipment status and environmental data use satellite communication, with bandwidths of 5Mbps and 3Mbps respectively. Set network switching thresholds: when WiFi signal strength is lower than -72dBm and lasts for more than 3 seconds, switching is triggered; when 4G signal strength is lower than -87dBm and lasts for more than 5 seconds, switching is triggered; when satellite signal strength is lower than -97dBm and lasts for more than 10 seconds, switching is triggered. These parameters and thresholds are written into the network resource allocation scheme to guide real-time network switching and resource scheduling.

[0066] In a specific embodiment, the process of executing step S104 may specifically include the following steps:

[0067] (1) Sampling the real-time signal strength of the 4G / 5G cellular network base station to obtain a base station signal sequence, and comparing the base station signal sequence with the network switching threshold to obtain a base station switching trigger flag;

[0068] (2) Scanning and processing the real-time connection status of the WiFi hotspot to obtain a hotspot status sequence, and comparing the hotspot status sequence with the network switching threshold to obtain a hotspot switching trigger flag;

[0069] (3) Detecting and processing the real-time link quality of the satellite communication node to obtain a satellite link sequence, and comparing the satellite link sequence with the network switching threshold to obtain a satellite switching trigger flag;

[0070] (4) Perform state synthesis processing on the base station switching trigger flag, hotspot switching trigger flag and satellite switching trigger flag to obtain a switching state matrix, and perform pattern recognition processing on the switching state matrix to obtain a network switching mode, and generate a network switching control instruction according to the network switching mode.

[0071] Specifically, the real-time signal strength of the 4G / 5G cellular network base station is sampled and processed. The sampling frequency is set to 10 times per second, and parameters such as signal strength value (dBm), signal-to-noise ratio (dB), and bit error rate are recorded. The sampled data is arranged in chronological order to form a base station signal sequence. The base station signal sequence is compared with the network switching threshold. The comparison content includes whether the signal strength is lower than -85dBm, whether the signal-to-noise ratio is lower than 10dB, and whether the bit error rate exceeds Threshold indicators such as . When any indicator exceeds the threshold for a duration exceeding the preset 3 seconds, a base station switching trigger flag is generated. The flag value is 1 for switching and 0 for no switching. Scan the real-time connection status of WiFi hotspots. The scanning frequency is 5 times per second, and the parameters such as signal strength, channel congestion, and response time of the access point are recorded. These parameters are organized into a hotspot status sequence in chronological order. The hotspot status sequence is compared with the network switching threshold, focusing on threshold indicators such as whether the signal strength is lower than -70dBm, whether the channel congestion exceeds 80%, and whether the response time exceeds 100ms. When an abnormal state is detected to last for more than 2 seconds, a hotspot switching trigger flag is generated. Detect the real-time link quality of satellite communication nodes. The detection content includes parameters such as signal strength, carrier-to-noise ratio, and bit error rate. The detection frequency is 2 times per second. Organize the detection data into a satellite link sequence and record the changing trend of the link quality. Compare the satellite link sequence with the network switching threshold, focusing on whether the signal strength is lower than -95dBm, whether the carrier-to-noise ratio is lower than 8dB, and whether the bit error rate exceeds When the abnormal state lasts for more than 5 seconds, a satellite switching trigger flag is generated.

[0072] The obtained base station switching trigger flag, hotspot switching trigger flag and satellite switching trigger flag are subjected to state synthesis processing. The three trigger flags are combined into a switching state matrix, in which each row represents a time point and each column represents the switching state of a network. The switching state matrix is ​​subjected to pattern recognition processing to identify different network switching modes. The switching modes include: single network switching mode (only one network needs to be switched), dual network switching mode (two networks need to be switched at the same time), full network switching mode (three networks need to be switched), etc. According to the identified network switching mode, a specific network switching control instruction is generated.

[0073] For example, during the flight of an aircraft, the communication network status is monitored in real time. First, the 4G base station signal is sampled and 300 sampling points are obtained within 30 consecutive seconds. In the first 20 seconds, the signal strength is stable at about -82dBm, the signal-to-noise ratio is 12dB, and the bit error rate is maintained at However, starting from the 21st second, the signal strength dropped rapidly, and by the 24th second it dropped to -87dBm, the signal-to-noise ratio dropped to 9dB, and the bit error rate rose to , and this state lasted for 4 seconds. Since the preset -85dBm threshold and 3-second duration requirement were exceeded, a base station switching trigger mark 1 was generated. At the same time, WiFi hotspot status monitoring showed that a total of 150 sampling points were acquired within the 30 seconds. In the first 25 seconds, the signal strength remained at -68dBm, the channel congestion was about 60%, and the response time was stable at 80ms. Starting from the 26th second, the channel congestion suddenly rose to 85%, and the response time increased to 120ms, which lasted for 3 seconds. Since the congestion threshold of 80% and the response time threshold of 100ms were exceeded, and the duration exceeded 2 seconds, a hotspot switching trigger mark 1 was generated.

[0074] The satellite communication link collected 60 sample points in these 30 seconds, with the signal strength stable at -93dBm, the carrier-to-noise ratio at 10dB, and the bit error rate at The level of each indicator does not exceed the preset threshold, so the satellite switching trigger flag remains at 0. The three trigger flags are combined into a switching state matrix. The matrix shows that both the 4G network and the WiFi network need to be switched in the same time period, while the satellite communication remains stable. After pattern recognition, it is determined to be a dual network switching mode. According to this mode, a network switching control instruction is generated. The instruction content includes: transferring the 4G network data stream to an adjacent base station with a better signal; switching the WiFi hotspot to a backup access point with a lower congestion; and keeping the satellite communication link unchanged. This switching control instruction ensures that when the network status changes, data transmission can smoothly transition to a network channel with better performance.

[0075] In a specific embodiment, the process of executing step S105 may specifically include the following steps:

[0076] (1) Perform data integrity detection on the transmission process of engine parameters in the network switching mode to obtain the engine data integrity sequence, and perform statistical processing on the engine data integrity sequence to obtain the engine transmission quality value;

[0077] (2) Performing data delay detection on the transmission process of navigation data in the network switching mode to obtain a navigation data delay sequence, and performing statistical processing on the navigation data delay sequence to obtain a navigation transmission quality value;

[0078] (3) Perform data accuracy detection on the transmission process of the airborne equipment status data in the network switching mode to obtain the equipment data accuracy sequence, and perform statistical processing on the equipment data accuracy sequence to obtain the equipment transmission quality value;

[0079] (4) Perform data loss detection on the transmission process of environmental monitoring data in the network switching mode to obtain the environmental data loss sequence, and perform statistical processing on the environmental data loss sequence to obtain the environmental transmission quality value;

[0080] (5) Comprehensively process the engine transmission quality value, navigation transmission quality value, equipment transmission quality value and environment transmission quality value to obtain the transmission control parameters, and construct a transmission quality parameter table based on the transmission control parameters.

[0081] Specifically, the data integrity test is performed on the transmission process of the engine parameters in the network switching mode. The integrity test records the transmission status of each data packet by comparing the data packet sequence numbers of the sending and receiving ends. The engine parameters include key values ​​such as speed, temperature, and pressure, and the sampling frequency is 10 times per second. The receiving status is marked for each data packet: complete reception is recorded as 1, and data damage or loss is recorded as 0, forming an engine data integrity sequence. The sequence is statistically processed to calculate the complete reception rate of the data packet as the engine transmission quality value. The data delay test is performed on the transmission process of the navigation data in the network switching mode. The delay test calculates the time interval from sending to receiving by adding a timestamp to the data packet. The navigation data includes information such as position, speed, and attitude, and the sampling frequency is 5 times per second. The transmission delay value of each data packet is recorded to form a navigation data delay sequence. The delay sequence is statistically processed to calculate the average delay and delay jitter, and the navigation transmission quality value is obtained comprehensively.

[0082] The data accuracy of the airborne equipment status data is checked in the network switching mode. The accuracy check verifies the correctness of the data through the checksum mechanism. The equipment status data includes information such as the working mode and fault code, and the sampling frequency is 2 times per second. The data verification results are recorded, and the correct ones are recorded as 1 and the errors are recorded as 0 to form the equipment data accuracy sequence. The accuracy sequence is statistically processed, the data correct transmission rate is calculated, and the equipment transmission quality value is obtained. Data loss detection is performed on the environmental monitoring data in the network switching mode. The loss detection determines whether the data packet is lost through the continuous sequence number. The environmental monitoring data includes parameters such as temperature, humidity, and air pressure, and the sampling frequency is 1 per second. The data packet reception is recorded, and the received is recorded as 1 and the lost is recorded as 0 to form the environmental data loss sequence. The loss sequence is statistically processed, and the successful reception rate of the data packet is calculated to obtain the environmental transmission quality value.

[0083] Finally, the four transmission quality values ​​are processed comprehensively. Weights are assigned according to the importance of the data: engine data weight 0.4, navigation data weight 0.3, equipment status data weight 0.2, and environmental monitoring data weight 0.1. The comprehensive transmission quality index is obtained by weighted average calculation as the transmission control parameter. The transmission control parameters and their calculation basis are organized into a transmission quality parameter table. For example: During a network switching process, the transmission quality of various types of data is monitored. The engine parameters transmitted 100 data packets in 10 seconds, of which 97 were completely received and 3 data packets were damaged. The calculated data integrity was 97%. Statistics show that among the damaged data packets, 2 occurred within 1 second of the start of the switch and 1 occurred before the end of the switch, indicating that the switching process has a short-term impact on data integrity.

[0084] The navigation data transmitted 50 packets in the same period, and the transmission delay of each packet was recorded. The statistical results show that the average delay is 85ms, the maximum delay is 150ms at the switching moment, and the standard deviation of the delay is 25ms. According to the delay distribution characteristics, the navigation data transmission quality value is calculated to be 92%. The device status data transmitted 20 packets. Through checksum detection, it was found that 19 packets were correctly checked and 1 packet was wrong. The error packet appeared in the transition period of network switching, indicating that the data accuracy was less affected by the switch, and the calculated transmission quality value was 95%.

[0085] The environmental monitoring data transmitted 10 data packets. The sequence number continuity check showed that all data packets were successfully received without packet loss, and the transmission quality value was 100%. The transmission quality values ​​of the four types of data were combined and calculated according to the preset weights: 0.4×97% + 0.3×92% + 0.2×95% + 0.1×100% = 95.3%. This value was written into the transmission quality parameter table as a transmission control parameter to evaluate the overall transmission performance during the network switching process.

[0086] In a specific embodiment, the process of executing step S106 may specifically include the following steps:

[0087] (1) Performing timing analysis on the network switching mode in the network switching control instruction to obtain a switching mode sequence, and performing deep learning processing on the switching mode sequence to obtain a switching mode feature matrix;

[0088] (2) Perform multi-dimensional decomposition processing on the transmission control parameters in the transmission quality parameter table to obtain a transmission control tensor, and perform tensor decomposition processing on the transmission control tensor to obtain a transmission control feature sequence;

[0089] (3) Calculate the correlation degree of the switching mode feature matrix to obtain the mode correlation matrix, and then process the mode correlation matrix based on the neural network of resource matching to obtain the mode optimization rules;

[0090] (4) Performing time-frequency domain conversion on the transmission control feature sequence to obtain a feature spectrum diagram, and performing wavelet transform on the feature spectrum diagram to obtain the transmission feature rule;

[0091] (5) Perform rule fusion processing on the mode optimization rules and the transmission feature rules to obtain a fusion rule set, and perform adaptive processing on the fusion rule set based on reinforcement learning to obtain a candidate resource configuration solution;

[0092] (6) Verify the constraints of the candidate resource configuration schemes to obtain a network resource configuration scheme, and perform reliability evaluation on the network resource configuration scheme to obtain an optimized network resource configuration. Generate transmission strategy optimization parameters based on the optimized network resource configuration.

[0093] Specifically, the network switching mode in the network switching control instruction is subjected to timing analysis and processing. The switching modes include single network switching, dual network switching and full network switching. Each switching mode contains information such as specific switching time point, switching duration, network status before and after switching, etc. This information is arranged in chronological order to form a switching mode sequence. The sequence is processed by a deep learning model, and a three-layer convolutional neural network is used to extract timing features. The convolution kernel size of each layer is 3×3, the step size is 1, and the number of output channels is 64, 128, and 256, respectively. Finally, the switching mode feature matrix is ​​obtained. The transmission control parameters in the transmission quality parameter table are subjected to multi-dimensional decomposition processing. The transmission control parameters include multiple dimensions such as data integrity, transmission delay, data accuracy and packet loss rate. The Tucker decomposition method is used to decompose these parameters into transmission control tensors. The three dimensions of the tensor correspond to the data type, transmission characteristics and time series, respectively. The transmission control tensor is subjected to CP decomposition, and the high-dimensional tensor is decomposed into the sum of multiple rank-1 tensors to obtain the transmission control feature sequence.

[0094] The switching mode feature matrix is ​​processed by correlation calculation. The similarity, conversion probability and timing correlation between different switching modes are calculated to generate a mode correlation matrix. The matrix is ​​processed using a neural network based on resource matching. The network structure includes an input layer, two hidden layers and an output layer. The number of neurons in the hidden layer is 128 and 64 respectively. The ReLU activation function is used to train the network through the back propagation algorithm to obtain the mode optimization rules. The transmission control feature sequence is converted into time and frequency domains. The time domain features are converted to the frequency domain using the fast Fourier transform to generate a feature spectrum. The feature spectrum is subjected to wavelet transform, using the Daubechies wavelet basis, with a decomposition layer number of 4, to extract feature information at different scales and obtain the transmission feature rules.

[0095] The mode optimization rules and transmission feature rules are fused. The weighted average method is used to combine the two types of rules, and the weights are dynamically adjusted according to the reliability of the rules to form a fusion rule set. Adaptive processing based on reinforcement learning is used for the fusion rule set. The Deep Q-Network algorithm is used to set the state space, action space and reward function. Through repeated iterations of the optimization strategy, the candidate resource configuration scheme is obtained. The constraint conditions of the candidate resource configuration scheme are verified. The constraint conditions include bandwidth restrictions, delay requirements, energy consumption, etc., and the scheme is verified to meet all the constraint conditions to obtain the network resource configuration scheme. The reliability of the scheme is evaluated. The evaluation indicators include the stability, robustness and adaptability of the scheme, and finally the network resource optimization configuration and transmission strategy optimization parameters are generated.

[0096] For example, in the communication system of an aircraft, network switching data was recorded over a period of time. Time series analysis showed that 5 network switches occurred within 30 minutes, of which 3 were single network switches from 4G to WiFi, and 2 were dual network switches from 4G and WiFi to satellite communication at the same time. These switching records were processed through deep learning to extract features such as switching trigger conditions and switching duration to form a 256-dimensional feature vector. At the same time, the transmission quality parameters showed that when switching to a single network, the average data integrity was 98%, the transmission delay was 85ms, the accuracy was 99%, and the packet loss rate was 0.5%; when switching to a dual network, the average data integrity was 95%, the transmission delay was 150ms, the accuracy was 97%, and the packet loss rate was 1.2%. These multidimensional data are converted into feature sequences through tensor decomposition.

[0097] Correlation analysis found that when the aircraft altitude exceeds 8,000 meters, the probability of dual network switching increases to 80%, and the network performance after switching is more dependent on satellite communications. Based on this feature, the optimization rules learned by the neural network recommend pre-establishing a satellite communication backup link when flying at high altitudes. After time-frequency domain analysis and wavelet transform, it was found that the network performance showed obvious periodic changes before and after the switch, with the main frequency concentrated between 0.1Hz and 0.5Hz. This feature is used to predict the changing trend of network performance.

[0098] Through reinforcement learning, the system gradually optimized the resource allocation strategy: when flying at low altitude, 30% of the satellite communication bandwidth is reserved as a backup; when flying at medium and high altitudes, the satellite communication bandwidth share is increased to 50%; during the dual network switching process, it is ensured that there are at least two redundant transmission paths for key data. The final configuration scheme showed good adaptability in actual verification, and the data transmission interruption time caused by network switching was controlled within 100ms, meeting the reliability requirements of flight data transmission.

[0099] The above describes the communication transmission management method for heterogeneous networks in the embodiment of the present application. The following describes the communication transmission management system for heterogeneous networks in the embodiment of the present application. Figure 2 In one embodiment of the present application, a communication transmission management system for a heterogeneous network includes:

[0100] The acquisition module is used to collect and process the characteristics of 4G / 5G cellular network base station information, WiFi hotspot distribution information and satellite communication node orbit parameters to obtain a heterogeneous network node information database containing transmission delay, packet loss rate and signal strength parameters;

[0101] A classification module, used for performing classification processing on engine parameters, navigation data, airborne equipment status data and environmental monitoring data based on the transmission delay and the packet loss rate to obtain a data classification configuration table including data priority levels;

[0102] A processing module, configured to perform a heuristic algorithm processing based on resource matching on the signal strength parameter in the heterogeneous network node information database and the data priority level in the data classification configuration table to obtain a network resource allocation scheme including a network switching threshold;

[0103] A switching module, configured to perform real-time monitoring and processing on the 4G / 5G cellular network base station, the WiFi hotspot, and the satellite communication node based on the network switching threshold, and obtain a network switching control instruction including a network switching mode;

[0104] A monitoring module, used for performing transmission quality monitoring processing on the engine parameters, the navigation data, the airborne device status data and the environmental monitoring data based on the network switching mode, and obtaining a transmission quality parameter table including transmission control parameters;

[0105] The analysis module is used to perform data mining analysis on the network switching control instruction and the transmission quality parameter table based on the resource matching to obtain transmission strategy optimization parameters including network resource optimization configuration.

[0106] Through the cooperation of the above components, the comprehensive perception and effective management of heterogeneous network resources are realized by collecting and processing the characteristics of 4G / 5G cellular network base station information, WiFi hotspot distribution information and satellite communication node orbit parameters, ensuring the optimization of network resource utilization. On this basis, the engine parameters, navigation data, airborne equipment status data and environmental monitoring data are graded based on transmission delay and packet loss rate, and a scientific data priority mechanism is established to ensure the transmission quality of key data. By processing the signal strength parameters in the heterogeneous network node information database and the data priority level in the data classification configuration table based on resource matching heuristic algorithm, the dynamic optimization allocation of network resources is realized and the resource utilization efficiency is improved. During the network switching process, the 4G / 5G cellular network base station, WiFi hotspot and satellite communication node are monitored and processed in real time based on the network switching threshold, ensuring the timeliness and accuracy of network switching and reducing data loss during the switching process. The transmission quality monitoring and processing of engine parameters, navigation data, airborne equipment status data and environmental monitoring data based on the network switching mode realizes real-time monitoring and dynamic adjustment of data transmission quality and ensures the reliability of data transmission. Finally, through data mining and analysis based on resource matching of network switching control instructions and transmission quality parameter tables, an adaptive network resource optimization mechanism was established to continuously improve the operating efficiency of the system. The overall solution significantly improves the communication transmission reliability in heterogeneous network environments through multi-level data processing and control strategies.

[0107] The present application also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the communication transmission management method for heterogeneous networks.

[0108] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, systems and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0109] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A communication transmission management method for a heterogeneous network, characterized in that: The communication transmission management method for heterogeneous networks includes: Perform feature collection and processing on 4G / 5G cellular network base station information, WiFi hotspot distribution information, and satellite communication node orbit parameters to obtain a heterogeneous network node information database containing transmission delay, packet loss rate, and signal strength parameters; Performing hierarchical processing on engine parameters, navigation data, airborne equipment status data and environmental monitoring data based on the transmission delay and the packet loss rate to obtain a data hierarchical configuration table including data priority levels; The signal strength parameters in the heterogeneous network node information database and the data priority levels in the data classification configuration table are processed by a heuristic algorithm based on resource matching to obtain a network resource allocation scheme including a network switching threshold, including: performing piecewise linearization processing on the signal strength parameters to obtain a network node signal sequence, and performing fluctuation analysis processing on the network node signal sequence to obtain signal stability; performing numerical quantization processing on the data priority levels to obtain a priority weight sequence, and performing normalization processing on the priority weight sequence to obtain a data transmission weight; performing correlation analysis on the signal stability and the data transmission weight to obtain a resource matching matrix, and performing optimal matching processing on the resource matching matrix through a genetic algorithm to obtain a resource allocation sequence; performing bandwidth allocation processing on the resource allocation sequence to obtain a bandwidth allocation table, and performing time slot scheduling processing on the bandwidth allocation table to obtain a resource allocation strategy; performing network switching cost calculation on the resource allocation strategy to obtain a switching cost matrix, and performing threshold extraction processing on the switching cost matrix to obtain a network switching threshold; generating the network resource allocation scheme according to the corresponding relationship between the resource allocation strategy and the network switching threshold; Performing real-time monitoring and processing on the 4G / 5G cellular network base station, the WiFi hotspot, and the satellite communication node based on the network switching threshold to obtain a network switching control instruction including a network switching mode; Performing transmission quality monitoring processing based on the network switching mode on the engine parameters, the navigation data, the airborne device status data and the environmental monitoring data to obtain a transmission quality parameter table including transmission control parameters; The network switching control instruction and the transmission quality parameter table are subjected to data mining analysis based on the resource matching to obtain transmission strategy optimization parameters including network resource optimization configuration.

2. The communication transmission management method for heterogeneous networks according to claim 1, characterized in that: The feature collection and processing of 4G / 5G cellular network base station information, WiFi hotspot distribution information and satellite communication node orbit parameters is performed to obtain a heterogeneous network node information database containing transmission delay, packet loss rate and signal strength parameters, including: Performing data collection and processing on the location coordinates and coverage radius of the 4G / 5G cellular network base station information to obtain a base station distribution matrix, and performing interpolation processing on the signal attenuation factors in the base station distribution matrix to obtain base station signal attenuation data; Performing data collection and processing on the access capacity and channel bandwidth of the WiFi hotspot distribution information to obtain a hotspot capacity matrix, and performing normalization processing on the channel quality index in the hotspot capacity matrix to obtain hotspot channel data; Performing orbital parameter analysis on the satellite communication node orbital parameters to obtain a satellite coverage matrix, and performing compensation processing on the signal beam data in the satellite coverage matrix to obtain satellite signal data; Performing feature extraction processing on the base station signal attenuation data, the hotspot channel data and the satellite signal data to obtain a signal feature set, and performing weighted fusion processing on the signal feature set to obtain a transmission delay; Performing a timing analysis process on the transmission delay to obtain a packet loss probability distribution, and performing a threshold segmentation process on the packet loss probability distribution to obtain a packet loss rate; Channel quality assessment is performed on the base station signal attenuation data, the hotspot channel data and the satellite signal data to obtain signal strength, and the transmission delay, the packet loss rate and the signal strength are written into the heterogeneous network node information database.

3. The communication transmission management method for heterogeneous networks according to claim 1, characterized in that: The engine parameters, navigation data, airborne equipment status data and environmental monitoring data are subjected to hierarchical processing based on the transmission delay and the packet loss rate to obtain a data hierarchical configuration table containing data priority levels, including: Performing data sampling processing on the speed, temperature and pressure of the engine parameters to obtain an engine state matrix, and performing importance analysis on key indicators in the engine state matrix to obtain an engine data level; Performing data sampling processing on the position, speed and posture of the navigation data to obtain a navigation state matrix, and performing threshold comparison on the deviation index in the navigation state matrix to obtain a navigation data level; Performing data analysis on the working mode and fault code of the airborne equipment status data to obtain an equipment status matrix, and classifying the abnormal indicators in the equipment status matrix to obtain equipment data levels; Performing data sampling and processing on the temperature, humidity and air pressure of the environmental monitoring data to obtain an environmental state matrix, and performing range classification on the change indicators in the environmental state matrix to obtain an environmental data level; Performing priority synthesis based on the transmission delay on the engine data level, the navigation data level, the device data level and the environment data level to obtain a delay priority table, and performing correction processing on the delay priority table based on the packet loss rate to obtain a data priority level; The data classification configuration table is generated according to the correspondence between the data priority level and the engine parameters, the navigation data, the airborne equipment status data, and the environmental monitoring data.

4. The communication transmission management method for heterogeneous networks according to claim 1, characterized in that: The real-time monitoring and processing of the 4G / 5G cellular network base station, the WiFi hotspot, and the satellite communication node based on the network switching threshold to obtain a network switching control instruction including a network switching mode includes: Sampling the real-time signal strength of the 4G / 5G cellular network base station to obtain a base station signal sequence, and comparing the base station signal sequence with the network switching threshold to obtain a base station switching trigger flag; Scanning the real-time connection status of the WiFi hotspot to obtain a hotspot status sequence, and comparing the hotspot status sequence with the network switching threshold to obtain a hotspot switching trigger flag; Detecting the real-time link quality of the satellite communication node to obtain a satellite link sequence, and comparing the satellite link sequence with the network switching threshold to obtain a satellite switching trigger flag; The base station switching trigger flag, the hotspot switching trigger flag and the satellite switching trigger flag are subjected to state synthesis processing to obtain a switching state matrix, and the switching state matrix is ​​subjected to pattern recognition processing to obtain a network switching mode, and the network switching control instruction is generated according to the network switching mode.

5. The communication transmission management method for heterogeneous networks according to claim 1, characterized in that: The engine parameters, the navigation data, the airborne device status data and the environmental monitoring data are subjected to transmission quality monitoring processing based on the network switching mode to obtain a transmission quality parameter table containing transmission control parameters, including: Performing data integrity detection on the transmission process of the engine parameters in the network switching mode to obtain an engine data integrity sequence, and performing statistical processing on the engine data integrity sequence to obtain an engine transmission quality value; Performing data delay detection on a transmission process of the navigation data in the network switching mode to obtain a navigation data delay sequence, and performing statistical processing on the navigation data delay sequence to obtain a navigation transmission quality value; Performing data accuracy detection on the transmission process of the onboard device status data in the network switching mode to obtain a device data accuracy sequence, and performing statistical processing on the device data accuracy sequence to obtain a device transmission quality value; Performing data loss detection on the transmission process of the environmental monitoring data in the network switching mode to obtain an environmental data loss sequence, and performing statistical processing on the environmental data loss sequence to obtain an environmental transmission quality value; The engine transmission quality value, the navigation transmission quality value, the equipment transmission quality value and the environment transmission quality value are comprehensively processed to obtain transmission control parameters, and the transmission quality parameter table is constructed according to the transmission control parameters.

6. The communication transmission management method for heterogeneous networks according to claim 1, characterized in that: The performing of data mining analysis and processing on the network switching control instruction and the transmission quality parameter table based on the resource matching to obtain transmission strategy optimization parameters including network resource optimization configuration includes: Performing timing analysis processing on the network switching mode in the network switching control instruction to obtain a switching mode sequence, and performing deep learning processing on the switching mode sequence to obtain a switching mode feature matrix; Performing multi-dimensional decomposition processing on the transmission control parameters in the transmission quality parameter table to obtain a transmission control tensor, and performing tensor decomposition processing on the transmission control tensor to obtain a transmission control feature sequence; Performing correlation calculation processing on the switching mode feature matrix to obtain a mode correlation matrix, and performing neural network processing on the mode correlation matrix based on the resource matching to obtain a mode optimization rule; Performing time-frequency domain conversion processing on the transmission control feature sequence to obtain a feature spectrum diagram, and performing wavelet transform processing on the feature spectrum diagram to obtain a transmission feature rule; Performing rule fusion processing on the mode optimization rule and the transmission feature rule to obtain a fusion rule set, and performing adaptive processing based on reinforcement learning on the fusion rule set to obtain a candidate resource configuration solution; The candidate resource configuration scheme is subjected to constraint verification processing to obtain a network resource configuration scheme, and the network resource configuration scheme is subjected to reliability assessment processing to obtain an optimized network resource configuration, and the transmission strategy optimization parameters are generated according to the optimized network resource configuration.

7. A communication transmission management system for heterogeneous networks, used to implement the communication transmission management method for heterogeneous networks as described in any one of claims 1 to 6, characterized in that: The communication transmission management system for heterogeneous networks includes: The acquisition module is used to collect and process the characteristics of 4G / 5G cellular network base station information, WiFi hotspot distribution information and satellite communication node orbit parameters to obtain a heterogeneous network node information database containing transmission delay, packet loss rate and signal strength parameters; A classification module, used for performing classification processing on engine parameters, navigation data, airborne equipment status data and environmental monitoring data based on the transmission delay and the packet loss rate to obtain a data classification configuration table including data priority levels; A processing module, used for performing a heuristic algorithm processing based on resource matching on the signal strength parameters in the heterogeneous network node information database and the data priority levels in the data classification configuration table to obtain a network resource allocation scheme including a network switching threshold, including: performing piecewise linearization processing on the signal strength parameters to obtain a network node signal sequence, and performing fluctuation analysis processing on the network node signal sequence to obtain signal stability; performing numerical quantization processing on the data priority levels to obtain a priority weight sequence, and performing normalization processing on the priority weight sequence to obtain a data transmission weight; performing correlation analysis on the signal stability and the data transmission weight to obtain a resource matching matrix, and performing optimal matching processing on the resource matching matrix through a genetic algorithm to obtain a resource allocation sequence; performing bandwidth allocation processing on the resource allocation sequence to obtain a bandwidth allocation table, and performing time slot scheduling processing on the bandwidth allocation table to obtain a resource allocation strategy; performing network switching cost calculation on the resource allocation strategy to obtain a switching cost matrix, and performing threshold extraction processing on the switching cost matrix to obtain a network switching threshold; generating the network resource allocation scheme according to the corresponding relationship between the resource allocation strategy and the network switching threshold; A switching module, configured to perform real-time monitoring and processing on the 4G / 5G cellular network base station, the WiFi hotspot, and the satellite communication node based on the network switching threshold, and obtain a network switching control instruction including a network switching mode; A monitoring module, used for performing transmission quality monitoring processing on the engine parameters, the navigation data, the airborne device status data and the environmental monitoring data based on the network switching mode, and obtaining a transmission quality parameter table including transmission control parameters; The analysis module is used to perform data mining analysis on the network switching control instruction and the transmission quality parameter table based on the resource matching to obtain transmission strategy optimization parameters including network resource optimization configuration.

8. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the communication transmission management method for heterogeneous networks as described in any one of claims 1 to 6 is implemented.

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