Low earth orbit satellite mobile communication ground experiment method and system

Abstract

The application provides a low-orbit satellite mobile communication ground experiment method and system. According to the influence of different orbit heights and solar activity periods, a diversified orbit parameter set is planned to generate a virtual satellite network model; based on the virtual satellite network model, an optimal transmission path is calculated by using a path prediction algorithm, the characteristics of the transmitted signal are adjusted through real-time channel simulation technology, and a low-orbit satellite communication environment test scene is generated; based on the low-orbit satellite communication environment test scene, a self-adaptive performance evaluation algorithm is used to evaluate communication performance data, an energy efficiency optimization method is used to determine a power consumption mode, the relationship between battery consumption and communication quality is analyzed, and a performance evaluation report is generated; the power consumption data and the communication quality data are integrated, and after integration, the integrated data are converted into a practical solution, and a low-orbit satellite mobile communication ground experiment result is generated. The technical scheme provided by the application improves the comprehensiveness and practicality of the low-orbit satellite mobile communication ground experiment method.

Description

Technical Field

[0001] This application relates to the field of satellite mobile communication technology, and in particular to a ground experimental method and system for low-orbit satellite mobile communication. Background Technology

[0002] With the rapid development of low-Earth orbit (LEO) satellite communication systems, their applications in military, civilian, and commercial fields are becoming increasingly widespread. LEO satellite systems exhibit unique advantages, particularly in global coverage, rapid response, and high-bandwidth communication. However, the low orbital altitude of LEO satellites results in high orbital speeds and limited coverage areas, requiring a large constellation of satellites to achieve global coverage. Furthermore, the solar activity cycle significantly impacts satellite communications, increasing the complexity and uncertainty of the communication system. Therefore, planning diverse sets of orbital parameters and simulating the layout of virtual satellites based on these parameters to generate a virtual satellite network model has become a critical requirement for ensuring stable and reliable communication performance. This model is used to predict the location distribution of virtual satellites at different points in time and their connection methods with ground user terminals, providing a foundation for subsequent path prediction and channel simulation.

[0003] Existing experimental methods for low-Earth orbit (LEO) satellite mobile communication mainly rely on static orbital parameters and fixed satellite layout models. These methods perform simple path prediction using pre-defined orbital parameters and combine them with limited channel simulation techniques to evaluate communication performance. Existing schemes typically involve planning a fixed set of orbital parameters to generate a static satellite network model; using basic path prediction algorithms to calculate the transmission path between the user terminal and the satellite; adjusting the characteristics of the ground station's transmitted signals using simplified channel simulation techniques to generate a preliminary communication environment test scenario; and analyzing communication performance data based on static evaluation methods to generate a simple performance report.

[0004] While existing ground-based experimental methods for low-Earth orbit (LEO) satellite mobile communication can meet basic communication needs to some extent, they have significant shortcomings. These methods fail to fully consider the impact of different orbital altitudes and solar activity cycles on communication performance, resulting in a lack of comprehensiveness. Furthermore, due to the use of static orbital parameters and fixed satellite layout models, existing methods cannot adjust path prediction and channel simulation parameters in real time, making it difficult to cope with complex and dynamically changing environments. Finally, the lack of in-depth analysis of power consumption patterns of ground user terminals prevents an effective balance between battery consumption and communication quality, limiting the overall performance improvement of the system. Summary of the Invention

[0005] This application provides a ground experiment method and system for low-Earth orbit satellite mobile communication, which solves the problem of insufficient comprehensiveness in existing ground experiment methods for low-Earth orbit satellite mobile communication.

[0006] In a first aspect, embodiments of this application provide a ground-based experimental method for low-Earth orbit satellite mobile communication, including:

[0007] Based on the influence of different orbital altitudes and solar activity cycles, a diverse set of orbital parameters is planned, and the layout of virtual satellites is simulated according to the set of orbital parameters to generate a virtual satellite network model. The virtual satellite network model is used to predict the location distribution of virtual satellites at different points in time and their connection with ground user terminals.

[0008] Based on the virtual satellite network model, a path prediction algorithm is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point. According to the optimal transmission path, the transmission signal characteristics of the ground station are precisely adjusted through real-time channel simulation technology to generate a low-orbit satellite communication environment test scenario. The ground station is used to forward information to the ground user terminal through the virtual satellite.

[0009] Based on the aforementioned low-orbit satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to evaluate the communication performance data of the ground user terminal under different orbital parameter configurations, obtain performance evaluation results, and based on the performance evaluation results, combined with energy efficiency optimization methods, determine the power consumption mode of the ground user terminal, so as to analyze the relationship between the battery consumption and communication quality of the ground user terminal under different working states, and generate a performance evaluation report. The power consumption mode refers to the way and rate at which the ground user terminal consumes power under different working states.

[0010] The power consumption and communication quality data collected during the performance evaluation phase are integrated, and the integrated data is adjusted and verified based on the optimization suggestions proposed in the performance evaluation report, so as to transform the integrated data into a practical solution and generate the results of the low-orbit satellite mobile communication ground experiment.

[0011] Optionally, based on the virtual satellite network model, a path prediction algorithm is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point. Based on the optimal transmission path, real-time channel simulation technology is used to precisely adjust the transmission signal characteristics of the ground station to generate a low-Earth orbit satellite communication environment test scenario, including:

[0012] Based on the virtual satellite network model, the position and velocity vectors of the virtual satellites at each time point are calculated and processed to generate a dynamic satellite orbit information database.

[0013] Based on the dynamic satellite orbit information database, taking into account the curvature of the Earth and the refraction effect of the atmosphere, a path prediction algorithm is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point, so as to minimize the delay and attenuation in signal transmission and generate an optimized transmission path scheme.

[0014] Based on the optimized transmission path scheme, real-time channel simulation technology is used to precisely adjust the characteristics of the ground station's transmitted signal, and to simulate the effects of different weather conditions and multipath effects to generate signal characteristic parameter processing results.

[0015] Based on the processing results of the signal characteristic parameters, the actual communication performance data is compared with the expected results to optimize the simulation parameters and generate a test scenario for low-orbit satellite communication environment.

[0016] Optionally, based on the dynamic satellite orbit information database, and taking into account the Earth's curvature and atmospheric refraction effects, a path prediction algorithm is used to calculate the optimal transmission path between the user terminal's ground user terminal and the virtual satellite at each time point, in order to minimize signal transmission delay and attenuation, and generate an optimized transmission path scheme, including:

[0017] Based on the dynamic satellite orbit information database, the motion state of the virtual satellite at different points in time is simulated to generate a satellite motion state record.

[0018] Based on the satellite motion state record, taking into account the influence of the Earth's curvature and atmospheric refraction, a path prediction algorithm is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point, so as to minimize the delay and attenuation in signal transmission and generate a preliminary transmission path scheme.

[0019] Based on the preliminary transmission path scheme, the performance of different transmission paths is evaluated and compared, the transmission path parameters are optimized, and the transmission effect under different conditions is combined to generate an optimized transmission path scheme.

[0020] Optionally, based on the optimized transmission path scheme, real-time channel simulation technology is used to precisely adjust the characteristics of the ground station's transmitted signal, and to simulate the effects of different weather conditions and multipath effects, generating signal characteristic parameter processing results, including:

[0021] Based on the optimized transmission path scheme, the characteristics of the ground station's transmitted signal are analyzed in detail, the signal strength and phase changes are evaluated, and a set of signal characteristic parameters is generated.

[0022] Based on the aforementioned signal characteristic parameter set, real-time channel simulation technology is used to simulate the effects of different weather conditions and multipath effects, and to precisely adjust the transmission signal characteristics of the ground station to generate signal characteristic simulation results.

[0023] Based on the simulation results of the signal characteristics, the communication performance under each simulation scenario is comprehensively evaluated to generate the communication performance evaluation results of the simulation scenario.

[0024] Based on the communication performance evaluation results of the simulation scenario, the transmission power and coding strategy are adjusted to generate signal characteristic parameters.

[0025] Optionally, based on the low-Earth orbit satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to evaluate the communication performance data of the ground user terminal under different orbital parameter configurations, obtain performance evaluation results, and based on the performance evaluation results, combined with energy efficiency optimization methods, determine the power consumption mode of the ground user terminal, so as to analyze the relationship between battery consumption and communication quality of the ground user terminal under different operating states, and generate a performance evaluation report, including:

[0026] In the low-Earth orbit satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to dynamically monitor and evaluate the communication performance of ground user terminals under different orbital parameter configurations, and the performance evaluation results are obtained. Among them, the key indicators for evaluating communication performance include signal strength, bit error rate, data transmission rate, and latency. These key indicators are used to reflect the communication quality of ground user terminals under the influence of different orbital altitudes and solar activity cycles.

[0027] Based on the performance evaluation results and combined with energy efficiency optimization methods, the power consumption patterns of the ground user terminal under different operating states are determined, and the relationship between battery consumption and communication quality under different operating states is analyzed. Based on the analysis results, the performance and power consumption patterns of the ground user terminal under different operating states are summarized to generate a performance evaluation report, which includes performance evaluation results and optimization suggestions.

[0028] Optionally, in the low-Earth orbit satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to dynamically monitor and evaluate the communication performance of the ground user terminal under different orbital parameter configurations, and the performance evaluation results are obtained, including:

[0029] Based on the aforementioned low-orbit satellite communication environment test scenario, real-time acquisition and processing of communication data from ground user terminals under different orbital parameter configurations are performed to generate a structured communication performance dataset.

[0030] Based on the structured communication performance dataset, an adaptive performance evaluation algorithm is used to automatically adjust the evaluation criteria according to different orbital altitudes and solar activity cycles. The key communication performance indicators at each moment in the structured communication performance dataset are dynamically monitored and processed to generate real-time performance evaluation records.

[0031] Based on the real-time performance evaluation records, combined with multi-dimensional analysis methods, the differences in communication quality in the structured communication performance data under different orbital parameter configurations are identified, and intermediate performance evaluation results are generated.

[0032] Based on the intermediate results of the performance evaluation, multi-level analysis and processing are performed to identify the optimal and suboptimal orbital parameter configurations and generate performance evaluation results.

[0033] Optionally, the power consumption data and communication quality data collected during the integrated performance evaluation phase are adjusted and verified using the optimization suggestions proposed in the performance evaluation report to transform the integrated data into a practical solution and generate ground experimental results for low-Earth orbit satellite mobile communication, including:

[0034] Based on the performance evaluation report, the power consumption and communication quality data collected in all testing phases were systematically processed to generate a structured dataset. This step ensured the integrity and consistency of the data, providing a solid foundation for subsequent data integration and ensuring the standardization and accuracy of data management.

[0035] Based on the structured dataset and the optimization suggestions proposed in the performance evaluation report, power consumption data and communication quality data are compared and analyzed to identify differences and influencing factors under different operating conditions, generating a detailed comparative analysis report. This step reveals the specific effects of the optimization suggestions by comparing and analyzing performance under different configurations, and prepares the necessary input for further adjustments and verification.

[0036] Based on the detailed comparative analysis report, energy efficiency optimization methods were employed to adjust and verify the effectiveness of the integrated data. Through simulation verification of user terminal power consumption patterns and communication quality, it was ensured that the optimization measures could actually improve the overall system performance, generating a verified optimization scheme. This step not only verified the feasibility of the optimization suggestions but also provided a concrete implementation path for subsequent practical solutions, ensuring the actual effectiveness of the optimization measures.

[0037] Based on the verified optimization scheme, the integrated power consumption and communication quality data are transformed into practical solutions. Taking into account the overall system performance and potential improvement points, the final experimental results of low-Earth orbit satellite mobile communication are generated. This step not only summarizes the various indicators in the experiment but also proposes specific optimization schemes, providing a solid foundation for the further development of low-Earth orbit satellite mobile communication systems.

[0038] Optionally, based on the satellite motion state record, and taking into account the effects of Earth's curvature and atmospheric refraction, a path prediction algorithm is used to calculate the optimal transmission path between the user terminal ground user terminal and the virtual satellite at each time point, minimizing signal transmission delay and attenuation, and generating a preliminary transmission path scheme, including:

[0039] The satellite motion state record is processed for high-precision time synchronization, and a multi-layer atmospheric model is constructed to simulate atmospheric conditions at different altitudes and evaluate the dynamic impact of changes in the altitude of the ground user terminal on the signal propagation path in order to generate signal transmission delay.

[0040] The signal transmission delay can be calculated using the following formula:

[0041] ;

[0042] in, Signal transmission delay at each moment; The coefficient representing the influence of Earth's curvature; The atmospheric refraction coefficient; It is a function of the distance between the ground user terminal and the virtual satellite as a function of time; Let be the signal propagation constant; Angle conversion factor; This is a function of the angle between the line connecting the satellite and the ground user terminal and the ground plane as a function of time. This is a high correction factor; It is a high-impact factor; The height difference between the ground user terminal and the ground;

[0043] Based on the signal transmission delay, the delay and attenuation under different transmission paths are nonlinearly combined to form a comprehensive performance scoring function. By introducing weight coefficients to adjust the importance of each transmission path, a comprehensive performance evaluation value is generated.

[0044] The overall performance evaluation value is calculated using the following formula:

[0045] ;

[0046] in, The comprehensive performance evaluation value of all candidate transmission paths at each time point; These are the weighting coefficients for different candidate transmission paths; Signal transmission delay at each moment; For the first The signal attenuation level of each candidate transmission path at each time step; Indexes for candidate transmission paths, from 1 to... ; The number of candidate transmission paths; For dynamic adjustment coefficients; As a speed-affecting factor; The speed of movement of the ground user terminal;

[0047] Based on the comprehensive performance evaluation value, normalization is performed to ensure comparability between different transmission paths. An optimization algorithm is used to sort the paths to determine the optimal transmission path, and a preliminary transmission path scheme is generated based on the optimal transmission path.

[0048] Optionally, based on the structured communication performance dataset, an adaptive performance evaluation algorithm is used to automatically adjust the evaluation criteria according to different orbital altitudes and solar activity cycles. This dynamically monitors and processes key communication performance indicators at each moment in the structured communication performance dataset, generating real-time performance evaluation records, including:

[0049] Based on the structured communication performance data table, measurement errors are eliminated by filtering and denoising techniques, key performance indicators are extracted, normalization is performed, a multi-dimensional feature matrix is ​​constructed, and the indicators are integrated into an overall representation to generate a comprehensive performance index.

[0050] The overall performance index is calculated using the following formula:

[0051] ;

[0052] in, For a moment Comprehensive performance indicators; For performance weighting coefficients; For a moment Connection stability; For a moment The maximum value of the connection stability; This is the signal strength adjustment factor; Frequency conversion factor; For a moment Signal frequency stability; This is the quality correction factor; Quality influencing factors; For a moment The signal quality index;

[0053] Based on the comprehensive performance indicators, nonlinear transformation is performed to enhance the distinguishability, environmental impact factors are introduced, the evaluation criteria are adjusted to adapt to the real-time changing communication environment, and the evaluation criteria are further optimized by combining path reliability and delay index to generate an adaptive evaluation criterion.

[0054] The adaptive evaluation criterion is calculated using the following formula:

[0055] ;

[0056] in, For a moment Adaptive evaluation criteria; This is a comprehensive adjustment factor; This is the path weight factor; For the first The overall performance indicators of the path; This is an environmental correction factor; Environmental impact factors; For a moment Environmental change index; This is a reliability adjustment factor; For a moment No. The reliability index of the path; For a moment No. The delay index of the path; Indexes for candidate paths, from 1 to... ; The number of candidate paths;

[0057] Based on the adaptive evaluation criteria, a weighted average is applied to all path evaluation values ​​to highlight high-performing paths. Cluster analysis is used to identify path groups with similar performance characteristics, and real-time performance evaluation records are generated.

[0058] Secondly, embodiments of this application provide a low-orbit satellite mobile communication ground experimental system, comprising:

[0059] The planning module is used to plan diverse sets of orbital parameters, taking into account the influence of different orbital altitudes and solar activity cycles, and to generate a virtual satellite network model.

[0060] The calculation module is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point based on the virtual satellite network model and using a path prediction algorithm. Based on the optimal transmission path, the characteristics of the ground station's transmitted signal are precisely adjusted through real-time channel simulation technology to generate a low-orbit satellite communication environment test scenario.

[0061] The analysis module is used to evaluate the communication performance data of the ground user terminal under different orbital parameter configurations based on the low-orbit satellite communication environment test scenario and using an adaptive performance evaluation algorithm to obtain the performance evaluation results. Based on the performance evaluation results and combined with the energy efficiency optimization method, the power consumption mode of the ground user terminal is determined to analyze the relationship between the battery consumption and communication quality of the ground user terminal under different working conditions and generate a performance evaluation report.

[0062] The conversion module is used to integrate the power consumption data and communication quality data collected during the performance evaluation phase, and adjust and verify the integrated data according to the optimization suggestions proposed in the performance evaluation report, so as to transform the integrated data into a practical solution and generate the ground test results of low-orbit satellite mobile communication.

[0063] Thirdly, embodiments of this application provide a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement a ground experimental method for low-orbit satellite mobile communication as described in the first aspect.

[0064] Fourthly, embodiments of this application provide a computer storage medium storing a computer program, which, when executed by a computer, implements a ground experimental method for low-orbit satellite mobile communication as described in the first aspect.

[0065] In this embodiment, diverse orbital parameter sets are planned based on the influence of different orbital altitudes and solar activity cycles. The layout of virtual satellites is simulated according to these orbital parameter sets to generate a virtual satellite network model. This model predicts the location distribution of virtual satellites at different time points and their connection methods with ground user terminals. Based on the virtual satellite network model, a path prediction algorithm is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point. Based on this optimal transmission path, real-time channel simulation technology is used to precisely adjust the transmission signal characteristics of the ground station, generating a low-Earth orbit satellite communication environment test scenario. The ground station is used to forward information to the ground user terminal via the virtual satellite. In a satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to assess the communication performance data of ground user terminals under different orbital parameter configurations, obtaining performance evaluation results. Based on these results and combined with energy efficiency optimization methods, the power consumption mode of the ground user terminals is determined to analyze the relationship between battery consumption and communication quality under different operating states, generating a performance evaluation report. The power consumption mode refers to the power consumption method and rate of the ground user terminals under different operating states. The power consumption data and communication quality data collected during the performance evaluation phase are integrated, and the integrated data is adjusted and verified using optimization suggestions proposed in the performance evaluation report. This transforms the integrated data into a practical solution, generating low-Earth orbit satellite mobile communication ground experiment results. By planning diverse orbital parameter sets and simulating a virtual satellite network model, this method can accurately predict the location distribution of virtual satellites at different time points and their connection methods with ground user terminals. Combining path prediction algorithms and real-time channel simulation technology, the signal transmission path at each time point can be optimized, minimizing delay and attenuation, thereby significantly improving communication quality and reliability. Furthermore, based on adaptive performance evaluation algorithms and energy efficiency optimization methods, this approach can not only evaluate communication performance under different orbital parameter configurations, but also determine the power consumption patterns of ground user terminals, analyze the relationship between battery consumption and communication quality, and generate detailed performance evaluation reports. Finally, by integrating and validating the data, it is transformed into a practical solution, ensuring the practicality and operability of the experimental results.

[0066] Furthermore, by constructing a dynamic satellite orbit information database and comprehensively considering the Earth's curvature and atmospheric refraction effects, the calculation accuracy of the optimal transmission path was ensured. Real-time channel simulation technology was employed to simulate different weather conditions and multipath effects, making the signal characteristic parameters more closely resemble the actual communication environment. By comparing actual communication performance data with expected results, simulation parameters were continuously optimized, resulting in a more realistic and reliable low-Earth orbit satellite communication environment test scenario, providing a solid foundation for subsequent performance evaluation.

[0067] Furthermore, by dynamically monitoring and evaluating the communication performance of ground user terminals under different orbital parameter configurations, the accuracy and timeliness of the evaluation results were ensured. Key indicators (such as signal strength, bit error rate, data transmission rate, and latency) comprehensively reflect communication quality, especially under the influence of different orbital altitudes and solar activity cycles. Combined with energy efficiency optimization methods, the power consumption patterns of ground user terminals under different operating states were determined, and the relationship between battery consumption and communication quality was analyzed in depth. The generated performance evaluation report not only includes detailed evaluation results but also proposes specific optimization suggestions, providing a scientific basis for system optimization and improvement, and enhancing the overall performance and energy efficiency of the system.

[0068] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0069] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0070] Figure 1 A flowchart illustrating a ground-based experimental method for low-Earth orbit satellite mobile communication provided in this application embodiment;

[0071] Figure 2 A schematic diagram of the structure of a low-orbit satellite mobile communication ground experimental system provided in this application embodiment;

[0072] Figure 3 This is a schematic diagram of the structure of a computing device provided in an embodiment of this application. Detailed Implementation

[0073] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0074] In some of the processes described in the specification, claims, and accompanying drawings of this application, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 101, 102, etc., are merely used to distinguish different operations and do not themselves represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a chronological order, nor do they limit "first" and "second" to different types.

[0075] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0076] Figure 1 A flowchart of a ground experiment method for low-orbit satellite mobile communication is provided in this application embodiment, as shown below. Figure 1 As shown, the method includes:

[0077] 101. Based on the influence of different orbital altitudes and solar activity cycles, a diverse set of orbital parameters is planned, and the layout of virtual satellites is simulated based on the set of orbital parameters to generate a virtual satellite network model. The virtual satellite network model is used to predict the location distribution of virtual satellites at different points in time and their connection with ground user terminals.

[0078] In this step, the orbital parameter set includes a series of parameters used to describe the satellite's orbit, such as orbital altitude, inclination, right ascension of the ascending node, argument of perigee, and mean motion.

[0079] The virtual satellite network model is a simulation model generated based on the planned set of orbital parameters. It is used to predict the location distribution of virtual satellites at different points in time and their connection with ground user terminals. The model not only considers the motion characteristics of the satellites themselves, but also takes into account factors such as the curvature of the Earth and the refraction effect of the atmosphere to ensure the accuracy of the prediction results.

[0080] Location distribution refers to the specific coordinate information of virtual satellites at different points in time.

[0081] The connection method refers to the configuration of the communication link between the satellite and the ground user terminal, including the selection of signal transmission paths and frequency allocation.

[0082] In this embodiment, firstly, a diverse set of orbital parameters is planned based on different orbital altitudes and the influence of solar activity cycles; secondly, based on the orbital parameter set, simulation software is used to simulate the layout of virtual satellites and generate a virtual satellite network model; thirdly, the model is used to predict the location distribution of virtual satellites at different time points and their connection methods with ground user terminals; finally, these prediction results are used for subsequent path prediction and channel simulation analysis.

[0083] Suppose a low-Earth orbit satellite constellation system needs to cover multiple regions globally. To ensure communication quality and reliability, firstly, diverse sets of orbital parameters are planned based on different orbital altitudes (e.g., 500km, 700km, 1000km) and solar activity cycles (e.g., peak and quiet periods of sunspot activity). Secondly, based on these parameter sets, simulation software (e.g., STK or GMAT) is used to simulate the layout of virtual satellites, generating a detailed virtual satellite network model. Thirdly, this model is used to predict the hourly position distribution of virtual satellites and their connection methods with ground user terminals over the next week. Finally, these prediction results are used for subsequent path prediction and channel simulation analysis to ensure optimal configuration of the communication system.

[0084] 102. Based on the virtual satellite network model, a path prediction algorithm is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point. According to the optimal transmission path, the transmission signal characteristics of the ground station are precisely adjusted through real-time channel simulation technology to generate a low-orbit satellite communication environment test scenario. The ground station is used to forward information to the ground user terminal through the virtual satellite.

[0085] In this step, the path prediction algorithm is a technique for determining the best communication path. It calculates the optimal path that minimizes signal transmission delay and attenuation by analyzing the relative position, distance, and environmental conditions between the satellite and the ground user terminal.

[0086] The dynamic satellite orbit information database is a collection of data that stores the virtual satellite position and velocity vectors at each point in time, which is used for subsequent path prediction and channel simulation analysis.

[0087] Atmospheric refraction refers to the path deflection of electromagnetic waves as they propagate through the atmosphere due to changes in air density.

[0088] The optimal transmission path refers to the best path that minimizes signal transmission delay and attenuation between a ground user terminal and a virtual satellite at a given time and under given conditions.

[0089] Real-time channel simulation technology is a method for simulating channel characteristics in actual communication environments. By introducing factors such as multipath effects and weather conditions, it accurately adjusts the characteristics of ground station transmitted signals to ensure that the simulation results closely resemble the actual situation.

[0090] Transmitted signal characteristics include parameters such as signal frequency, power, and modulation method, which directly affect the signal propagation effect and reception quality.

[0091] Multipath effect refers to the phenomenon where signals travel through different paths to reach the receiver during propagation, resulting in signal superposition or mutual interference.

[0092] The signal characteristic parameter processing result refers to the transmitted signal characteristic parameters adjusted through real-time channel simulation technology, as well as the final signal characteristics obtained after simulating different weather conditions and multipath effects.

[0093] The low-Earth orbit satellite communication environment test scenario refers to the virtual environment generated through the above steps, used to evaluate and optimize the performance of low-Earth orbit satellite communication systems. This scenario includes all necessary simulation parameters and signal characteristics to ensure the accuracy and reliability of the test results.

[0094] In this embodiment, firstly, based on the virtual satellite network model, the position and velocity vectors of the virtual satellites at each time point are calculated and processed to generate a dynamic satellite orbit information database; secondly, combining the curvature of the Earth and the refraction effect of the atmosphere, a path prediction algorithm is used to calculate the optimal transmission path between the user terminal and the virtual satellite at each time point; thirdly, real-time channel simulation technology is used to precisely adjust the characteristics of the ground station's transmitted signal and simulate the effects of different weather conditions and multipath effects to generate signal characteristic parameter processing results; finally, the actual communication performance data is compared with the expected results to optimize the simulation parameters and generate a low-Earth orbit satellite communication environment test scenario.

[0095] For example, continuing the previous example, assuming a virtual satellite network model has been generated, path prediction will be performed based on this model. First, the position and velocity vectors of the virtual satellites at each time point are calculated to generate a dynamic satellite orbit information database. Second, combining the Earth's curvature and atmospheric refraction effects, a path prediction algorithm is used to calculate the optimal transmission path between the user terminal and the virtual satellite at each time point. Third, real-time channel simulation technology is used to precisely adjust the characteristics of the ground station's transmitted signals and simulate the effects of different weather conditions and multipath effects, generating signal characteristic parameter processing results. Finally, the simulation parameters are optimized by comparing actual communication performance data with expected results, generating a low-Earth orbit satellite communication environment test scenario to ensure the realism and reliability of the communication environment.

[0096] 103. Based on the aforementioned low-orbit satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to evaluate the communication performance data of the ground user terminal under different orbital parameter configurations, obtain performance evaluation results, and based on the performance evaluation results, combined with energy efficiency optimization methods, determine the power consumption mode of the ground user terminal, so as to analyze the relationship between the battery consumption and communication quality of the ground user terminal under different working states, and generate a performance evaluation report. The power consumption mode refers to the power consumption method and consumption rate of the ground user terminal under different working states.

[0097] In this step, the adaptive performance evaluation algorithm is an algorithm that can automatically adjust the evaluation criteria. It reflects the communication quality of ground user terminals under the influence of different orbital altitudes and solar activity cycles by dynamically monitoring and evaluating key communication performance indicators (such as signal strength, bit error rate, data transmission rate, and latency).

[0098] Key communication performance indicators include signal strength, bit error rate, data transmission rate, and latency, which are used to comprehensively reflect communication quality.

[0099] Energy efficiency optimization methods aim to find the most suitable power consumption mode to balance the relationship between battery consumption and communication quality, and extend the life of the device. Commonly used methods include dynamic voltage frequency adjustment (DVFS) and sleep mode switching.

[0100] Power consumption mode refers to the way and rate at which a ground user terminal consumes power under different working conditions. The power consumption mode of the terminal device will be different under different communication tasks and environmental conditions.

[0101] The performance evaluation report includes detailed evaluation results and optimization suggestions, summarizing the performance and power consumption patterns of ground user terminals under different operating conditions.

[0102] In this embodiment, firstly, in a low-Earth orbit satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to dynamically monitor and evaluate the communication performance of the ground user terminal under different orbital parameter configurations, and the performance evaluation results are obtained; secondly, based on the performance evaluation results, combined with energy efficiency optimization methods, the power consumption patterns of the ground user terminal under different working states are determined; thirdly, the relationship between battery consumption and communication quality under different working states is analyzed; finally, based on the analysis results, the performance and power consumption patterns of the ground user terminal under different working states are summarized, and a performance evaluation report is generated.

[0103] For example, continuing the previous example, assuming a low-Earth orbit satellite communication environment test scenario has been generated, we will next evaluate communication performance and determine power consumption patterns. First, in this test scenario, an adaptive performance evaluation algorithm is used to dynamically monitor and evaluate the communication performance of the ground user terminal under different orbital parameter configurations, obtaining performance evaluation results. Second, based on the performance evaluation results, combined with energy efficiency optimization methods, the power consumption patterns of the ground user terminal under different operating states are determined. Third, the relationship between battery consumption and communication quality under different operating states is analyzed. Finally, based on the analysis results, the performance and power consumption patterns of the ground user terminal under different operating states are summarized, a performance evaluation report is generated, and specific optimization suggestions are provided.

[0104] 104. Integrate the power consumption data and communication quality data collected during the performance evaluation phase, and adjust and verify the integrated data according to the optimization suggestions proposed in the performance evaluation report, so as to transform the integrated data into a practical solution and generate the ground test results of low-orbit satellite mobile communication.

[0105] In this step, power consumption data records the specific power consumption of the ground user terminal under different operating states, including power consumption rate, maximum power consumption value, etc.

[0106] Communication quality data reflects the communication performance of ground user terminals under different orbital parameter configurations, including key indicators such as signal strength, bit error rate, data transmission rate, and latency.

[0107] A practical solution refers to a specific implementation strategy derived from adjusting and verifying the integrated power consumption data and communication quality data based on the optimization suggestions proposed in the performance evaluation report.

[0108] The results of the ground experiments on low-Earth orbit satellite mobile communication refer to the final experimental results after integration and verification through the above steps. They cover the data and analysis conclusions of all testing phases, and these results provide a reliable reference for the practical application of low-Earth orbit satellite communication systems.

[0109] In this embodiment, firstly, power consumption data and communication quality data collected during the performance evaluation phase are integrated; secondly, the integrated data is adjusted and verified based on the optimization suggestions proposed in the performance evaluation report; thirdly, the integrated data is transformed into a practical solution; and finally, ground experimental results for low-orbit satellite mobile communication are generated to ensure the practicality and operability of the experimental results.

[0110] For example, continuing the previous example, assuming a performance evaluation report has already been generated, we will next integrate the data and generate experimental results. First, we will integrate the power consumption data and communication quality data collected during the performance evaluation phase; second, we will adjust and verify the integrated data based on the optimization suggestions proposed in the performance evaluation report; third, we will transform the integrated data into practical solutions; finally, we will generate ground experimental results for low-Earth orbit satellite mobile communication, ensuring the practicality and operability of the experimental results and providing a reliable reference for practical applications.

[0111] To address potential errors in path prediction and channel simulation, in some embodiments, step 102, which involves performing path prediction and generating a low-Earth orbit satellite communication environment test scenario based on a virtual satellite network model, includes: calculating the position and velocity vectors of the virtual satellite at each time point based on the virtual satellite network model to generate a dynamic satellite orbit information database; based on the dynamic satellite orbit information database, comprehensively considering the Earth's curvature and atmospheric refraction effects, using a path prediction algorithm to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point to minimize signal transmission delay and attenuation, generating an optimized transmission path scheme; based on the optimized transmission path scheme, employing real-time channel simulation technology to precisely adjust the characteristics of the ground station's transmitted signal and simulate the effects of different weather conditions and multipath effects, generating signal characteristic parameter processing results; and based on the signal characteristic parameter processing results, comparing actual communication performance data with expected results, optimizing simulation parameters, and generating a low-Earth orbit satellite communication environment test scenario.

[0112] In this embodiment, the dynamic satellite orbit information database is a dataset that stores the virtual satellite position and velocity vectors at each point in time, which is used for subsequent path prediction and channel simulation analysis.

[0113] Optimized transmission path schemes refer to the best path schemes calculated by path prediction algorithms that minimize signal transmission delay and attenuation. These schemes take into account not only physical distance but also environmental factors such as multipath effects and weather conditions.

[0114] The signal characteristic parameter processing results refer to the transmitted signal characteristic parameters adjusted through real-time channel simulation technology, as well as the final signal characteristics obtained after simulating different weather conditions and multipath effects. The results are used to verify and optimize communication environment test scenarios.

[0115] The optimal transmission path refers to the best path that minimizes signal transmission delay and attenuation between a ground user terminal and a virtual satellite at a given time and under given conditions. This path takes into account not only physical distance but also environmental factors such as multipath effects and weather conditions.

[0116] The signal characteristic parameter processing result refers to the transmitted signal characteristic parameters adjusted through real-time channel simulation technology, as well as the final signal characteristics obtained after simulating different weather conditions and multipath effects.

[0117] In this embodiment, firstly, based on the virtual satellite network model, the position and velocity vectors of the virtual satellites at each time point are calculated and processed to generate a dynamic satellite orbit information database. Secondly, using this information database and combining it with the Earth's curvature and atmospheric refraction effects, a path prediction algorithm is applied to calculate the optimal transmission path between the user terminal and the virtual satellite at each time point, in order to minimize delay and attenuation in signal transmission and generate an optimized transmission path scheme. Thirdly, based on the optimized transmission path scheme, real-time channel simulation technology is used to precisely adjust the characteristics of the ground station's transmitted signal and simulate the effects of different weather conditions and multipath effects to generate signal characteristic parameter processing results. Finally, the actual communication performance data is compared with the expected results to optimize the simulation parameters and generate a low-Earth orbit satellite communication environment test scenario.

[0118] Here is a specific example:

[0119] Assuming a low-Earth orbit (LEO) satellite constellation system needs to cover multiple regions globally, to ensure communication quality and reliability, we first calculate the position and velocity vectors of virtual satellites at each time point based on a virtual satellite network model, generating a dynamic satellite orbit information database. Second, using this database and considering the Earth's curvature and atmospheric refraction effects, we employ a path prediction algorithm to calculate the optimal transmission path between the user terminal and the virtual satellite at each time point, minimizing signal transmission delay and attenuation, thus generating an optimized transmission path scheme. Third, based on the optimized transmission path scheme, we use real-time channel simulation technology to precisely adjust the characteristics of the ground station's transmitted signals and simulate the effects of different weather conditions and multipath effects, generating signal characteristic parameter processing results. Finally, by comparing actual communication performance data with expected results, we optimize simulation parameters and generate a LEO satellite communication environment test scenario, ensuring the realism and reliability of the communication environment and providing a reliable reference for practical applications.

[0120] To address the signal transmission delay and attenuation issues in low-Earth orbit satellite communication, some embodiments include the path prediction and optimization scheme in step 102, which comprises: simulating the motion state of the virtual satellite at different time points based on the dynamic satellite orbit information database to generate satellite motion state records; based on the satellite motion state records, comprehensively considering the influence of Earth's curvature and atmospheric refraction effects, using a path prediction algorithm to calculate the optimal transmission path between the user terminal ground terminal and the virtual satellite at each time point to minimize signal transmission delay and attenuation, generating a preliminary transmission path scheme; and based on the preliminary transmission path scheme, evaluating and comparing the performance under different transmission paths, optimizing the transmission path parameters, and combining the transmission effects under different conditions to generate an optimized transmission path scheme.

[0121] In this embodiment, the dynamic satellite orbit information database is a collection of data that stores the virtual satellite position and velocity vector at each point in time. This database not only records the changes in the satellite's position, but also provides basic data support for real-time adjustment of the communication path.

[0122] Satellite motion status records refer to detailed records generated through simulation processing that describe the motion characteristics of virtual satellites at different points in time, including parameters such as position, velocity, and acceleration, which are used to accurately calculate communication paths.

[0123] The preliminary transmission path scheme refers to the transmission path generated based on initial calculations, which has not yet undergone performance evaluation and optimization.

[0124] Optimizing a transmission path scheme refers to generating the best transmission path scheme by comparing the performance of different transmission paths and combining the transmission effect under different conditions.

[0125] In this embodiment, firstly, based on the dynamic satellite orbit information database, the motion state of the virtual satellite at different time points is simulated to generate detailed satellite motion state records. Secondly, using these motion state records and considering the effects of Earth's curvature and atmospheric refraction, a path prediction algorithm is applied to calculate the optimal transmission path between the user terminal and the virtual satellite at each time point to minimize signal transmission delay and attenuation, generating a preliminary transmission path scheme. Thirdly, based on the preliminary transmission path scheme, the performance under different transmission paths is evaluated and compared, the transmission path parameters are optimized, and combined with the transmission effect under different conditions, an optimized transmission path scheme is generated. Finally, the optimized transmission path scheme is applied to the actual communication environment to ensure the efficient operation of the communication system.

[0126] Here is a specific example:

[0127] For example, suppose a low-Earth orbit satellite system is designed to provide reliable communication support for emergency rescue in remote areas. First, based on the dynamic satellite orbit information database, the motion state of the virtual satellite at different time points is simulated to generate detailed satellite motion state records. Second, using these motion state records and considering the effects of Earth's curvature and atmospheric refraction, a path prediction algorithm is applied to calculate the optimal transmission path between the user terminal and the virtual satellite at each time point, minimizing signal transmission delay and attenuation, thus generating a preliminary transmission path scheme. Third, based on the preliminary transmission path scheme, the performance of different transmission paths is evaluated and compared, the transmission path parameters are optimized, and the transmission effect under different conditions is considered to generate an optimized transmission path scheme. Finally, the optimized transmission path scheme is applied to a real communication environment to ensure that emergency rescue teams can maintain efficient communication connections even in complex terrain and extreme weather conditions, providing a solid guarantee for rescue operations.

[0128] To address the issue of signal characteristic adjustment and optimization in low-Earth orbit satellite communication, some embodiments include a real-time channel simulation and signal characteristic optimization scheme in step 102, comprising: based on the optimized transmission path scheme, performing a detailed analysis of the ground station's transmitted signal characteristics, evaluating signal strength and phase changes, and generating a signal characteristic parameter set; based on the signal characteristic parameter set, employing real-time channel simulation technology to simulate different weather conditions and multipath effects, precisely adjusting the ground station's transmitted signal characteristics, and generating signal characteristic simulation results; based on the signal characteristic simulation results, comprehensively evaluating the communication performance under each simulation scenario, and generating simulation scenario communication performance evaluation results; and based on the simulation scenario communication performance evaluation results, adjusting the transmission power and coding strategy to generate signal characteristic parameter processing results.

[0129] In this embodiment, optimizing the transmission path scheme refers to generating the best transmission path scheme by comparing the performance of different transmission paths and combining the transmission effect under different conditions.

[0130] Transmitted signal characteristics refer to various attributes of the signal transmitted by the ground station, such as frequency, power, and modulation method. These characteristics directly affect the signal propagation effect and reception quality.

[0131] The signal characteristic parameter set is a data set generated after detailed analysis of the characteristics of the transmitted signal, including parameters such as signal strength and phase change, which is used for subsequent channel simulation and adjustment processing.

[0132] The signal characteristic simulation results refer to the transmitted signal characteristic parameters adjusted by real-time channel simulation technology, as well as the final signal characteristics obtained after simulating different weather conditions and multipath effects.

[0133] The simulation scenario communication performance evaluation results are a comprehensive assessment of the communication performance under each simulation scenario, including key indicators such as bit error rate, data transmission rate, and latency, which are used to verify and optimize the communication system.

[0134] Encoding strategy refers to the method of encoding transmitted data to improve the reliability and efficiency of data transmission.

[0135] In this embodiment, firstly, based on the optimized transmission path scheme, the characteristics of the ground station's transmitted signal are analyzed in detail, signal strength and phase changes are evaluated, and a set of signal characteristic parameters is generated. Secondly, based on the set of signal characteristic parameters, real-time channel simulation technology is used to simulate different weather conditions and multipath effects, and the characteristics of the ground station's transmitted signal are precisely adjusted to generate signal characteristic simulation results. Thirdly, based on the signal characteristic simulation results, the communication performance under each simulation scenario is comprehensively evaluated to generate simulation scenario communication performance evaluation results. Finally, based on the simulation scenario communication performance evaluation results, the transmission power and coding strategy are adjusted to generate signal characteristic parameter processing results, ensuring the optimal performance of the communication system.

[0136] Here is a specific example:

[0137] For example, suppose a low-Earth orbit satellite system is designed to provide stable communication support for a polar research team. First, based on the optimized transmission path scheme, the characteristics of the ground station's transmitted signal are analyzed in detail, evaluating signal strength and phase changes to generate a set of signal characteristic parameters. Second, based on this set of parameters, real-time channel simulation technology is used to simulate different weather conditions (such as polar cold and blizzards) and the effects of multipath propagation, precisely adjusting the ground station's transmitted signal characteristics to generate simulation results. Third, based on these simulation results, the communication performance under each simulation scenario is comprehensively evaluated to generate simulation scenario communication performance evaluation results. Finally, based on these simulation scenario communication performance evaluation results, the transmission power and coding strategy are adjusted to generate signal characteristic parameter processing results, ensuring that the polar research team can maintain reliable communication connections even under extreme environmental conditions, guaranteeing the smooth progress of scientific research tasks.

[0138] To address the challenges of communication performance evaluation and energy efficiency optimization under different orbital parameter configurations in low-Earth orbit (LEO) satellite communication, some embodiments include an adaptive performance evaluation and power consumption mode determination scheme in step 103. This scheme comprises: in the LEO satellite communication environment test scenario, using an adaptive performance evaluation algorithm to dynamically monitor and evaluate the communication performance of a ground user terminal under different orbital parameter configurations, obtaining performance evaluation results; where key indicators for evaluating communication performance include signal strength, bit error rate, data transmission rate, and latency, these key indicators reflecting the communication quality of the ground user terminal under the influence of different orbital altitudes and solar activity cycles; based on the performance evaluation results, combined with energy efficiency optimization methods, determining the power consumption mode of the ground user terminal under different operating states, and analyzing the relationship between battery consumption and communication quality under different operating states; based on the analysis results, summarizing the performance and power consumption modes of the ground user terminal under different operating states to generate a performance evaluation report, which includes performance evaluation results and optimization suggestions.

[0139] In this embodiment, the performance evaluation result refers to the specific conclusion drawn after dynamically monitoring and evaluating the communication performance of the ground user terminal under different orbital parameter configurations through an adaptive performance evaluation algorithm.

[0140] Power consumption mode refers to the way and rate at which a ground user terminal consumes power under different working conditions. The power consumption mode of the terminal device will be different under different communication tasks and environmental conditions.

[0141] Battery consumption refers to the amount of electricity consumed by a ground user terminal during operation, usually expressed in milliampere-hours (mAh).

[0142] The performance evaluation report contains detailed evaluation results and optimization suggestions, summarizing the performance and power consumption patterns of ground user terminals under different operating conditions, providing a scientific basis for system optimization and improvement.

[0143] In this embodiment, firstly, in the low-Earth orbit satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to dynamically monitor and evaluate the communication performance of the ground user terminal under different orbital parameter configurations, obtaining performance evaluation results. Key indicators for evaluating communication performance include signal strength, bit error rate, data transmission rate, and latency. These key indicators reflect the communication quality of the ground user terminal under different orbital altitudes and the influence of solar activity cycles. Secondly, based on the performance evaluation results and combined with energy efficiency optimization methods, the power consumption patterns of the ground user terminal under different operating states are determined, and the relationship between battery consumption and communication quality under different operating states is analyzed. Thirdly, based on the analysis results, the performance characteristics and power consumption patterns of the ground user terminal under different operating states are summarized. Finally, a performance evaluation report is generated, which not only includes the performance evaluation results but also proposes specific optimization suggestions, providing guidance for practical applications.

[0144] For example, suppose a low-Earth orbit (LEO) satellite system aims to provide real-time communication support for aircraft of airlines worldwide. First, in the LEO satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to dynamically monitor and evaluate the communication performance of ground user terminals (i.e., communication equipment on aircraft) under different orbital parameter configurations, obtaining performance evaluation results. Key indicators for evaluating communication performance include signal strength, bit error rate, data transmission rate, and latency. These key indicators reflect the communication quality of ground user terminals under different orbital altitudes and the influence of solar activity cycles. Second, based on the performance evaluation results and combined with energy efficiency optimization methods, the power consumption patterns of ground user terminals under different operating states are determined, and the relationship between battery consumption and communication quality under different operating states is analyzed. Third, based on the analysis results, the performance and power consumption patterns of ground user terminals under different operating states are summarized. Finally, a performance evaluation report is generated. This report not only includes the performance evaluation results but also proposes specific optimization suggestions to ensure that airline aircraft can maintain efficient and stable communication connections globally, improving flight safety and service quality.

[0145] To address the issue of dynamic monitoring and evaluation of communication performance under different orbital parameter configurations in low-Earth orbit (LEO) satellite communication, some embodiments include the adaptive performance evaluation scheme in step 103, which comprises: real-time acquisition and processing of communication data from ground user terminals under different orbital parameter configurations based on the LEO satellite communication environment test scenario, generating a structured communication performance dataset; based on the structured communication performance dataset, using an adaptive performance evaluation algorithm to automatically adjust the evaluation criteria according to different orbital altitudes and solar activity cycles, dynamically monitoring and processing key communication performance indicators at each moment in the structured communication performance dataset, generating real-time performance evaluation records; based on the real-time performance evaluation records, combined with multi-dimensional analysis methods, identifying communication quality differences in the structured communication performance dataset under different orbital parameter configurations, generating intermediate performance evaluation results; and based on the intermediate performance evaluation results, performing multi-level analysis and processing to identify the optimal and suboptimal orbital parameter configurations, generating performance evaluation results.

[0146] In this embodiment, the structured communication performance dataset is a collection of data generated by real-time acquisition and processing of communication data from ground user terminals under different orbital parameter configurations. This data is organized and standardized to facilitate subsequent analysis.

[0147] Real-time performance evaluation records are detailed records generated by dynamically monitoring and processing key communication performance indicators at each moment in a structured communication performance dataset. These records are used to track the real-time performance of the communication system.

[0148] Multidimensional analysis refers to the technique of comprehensively analyzing communication performance data from multiple perspectives (such as time, space, environmental conditions, etc.) in order to identify differences in communication quality under different orbital parameter configurations.

[0149] Intermediate performance evaluation results are preliminary evaluation conclusions generated based on real-time performance evaluation records and multi-dimensional analysis methods, which are used for further multi-level analysis.

[0150] The performance evaluation results are the final conclusions drawn from in-depth analysis of the intermediate performance evaluation results, identifying the optimal and suboptimal orbital parameter configurations and providing guidance for practical applications.

[0151] Here is a specific example:

[0152] For example, suppose a low-Earth orbit (LEO) satellite system aims to provide stable communication support for ships navigating the globe. First, based on the LEO satellite communication environment test scenario, real-time data collection and processing of communication data from ground user terminals (i.e., shipborne communication equipment) under different orbital parameter configurations is performed to generate a structured communication performance dataset. Second, based on this structured communication performance dataset, an adaptive performance evaluation algorithm is used to automatically adjust the evaluation criteria according to different orbital altitudes and solar activity cycles, dynamically monitoring key communication performance indicators at each moment in the structured communication performance dataset to generate real-time performance evaluation records. Third, based on these real-time performance evaluation records, combined with multi-dimensional analysis methods, the differences in communication quality within the structured communication performance dataset under different orbital parameter configurations are identified, generating intermediate performance evaluation results. Finally, based on these intermediate performance evaluation results, multi-level analysis is performed to identify the optimal and suboptimal orbital parameter configurations, generating performance evaluation results to ensure that ships navigating the globe can maintain efficient and stable communication connections, improving navigation safety and service quality.

[0153] In this embodiment, firstly, based on the low-Earth orbit satellite communication environment test scenario, real-time acquisition and processing of communication data from ground user terminals under different orbital parameter configurations are performed to generate a structured communication performance dataset. Secondly, based on the structured communication performance dataset, an adaptive performance evaluation algorithm is used to automatically adjust the evaluation criteria according to different orbital altitudes and solar activity cycles, dynamically monitoring and processing key communication performance indicators at each moment in the structured communication performance dataset to generate real-time performance evaluation records. Thirdly, based on the real-time performance evaluation records, combined with multi-dimensional analysis methods, the differences in communication quality in the structured communication performance dataset under different orbital parameter configurations are identified, generating intermediate performance evaluation results. Finally, based on the intermediate performance evaluation results, multi-level analysis and processing are performed to identify the optimal and suboptimal orbital parameter configurations, generating performance evaluation results to ensure the optimal configuration of the communication system.

[0154] To address the optimization issues of power consumption and communication quality in low-Earth orbit satellite mobile communication systems, some embodiments include the data integration and practical solution generation scheme described in step 104, which includes: Based on the performance evaluation report, systematically organizing and processing the power consumption and communication quality data collected during all testing phases to generate a structured dataset. This step ensures data integrity and consistency, providing a solid foundation for subsequent data integration and ensuring the standardization and accuracy of data management; Based on the structured dataset, and in conjunction with the optimization suggestions proposed in the performance evaluation report, comparing and analyzing the power consumption and communication quality data to identify differences under different operating states and their influencing factors, generating a detailed comparative analysis report; This step, through comparative analysis of performance under different configurations, reveals the specific effects of the optimization suggestions and prepares the necessary input for the next step of adjustment and verification; Based on the detailed comparative analysis report, using energy efficiency optimization methods, adjusting and verifying the effectiveness of the integrated data. By simulating and verifying the power consumption patterns and communication quality of user terminals, this step ensures that the optimization measures can actually improve the overall system performance, generating a verified optimization scheme. This step not only verifies the feasibility of the optimization suggestions but also provides a specific implementation path for subsequent practical solutions, ensuring the actual effectiveness of the optimization measures. Based on the verified optimization scheme, the integrated power consumption and communication quality data are transformed into practical solutions. Taking into account the overall system performance and potential improvement points, the final results of the low-Earth orbit satellite mobile communication ground experiment are generated. This step not only summarizes the various indicators in the experiment but also proposes specific optimization schemes, providing a solid foundation for the further development of low-Earth orbit satellite mobile communication systems.

[0155] In this embodiment, the structured dataset refers to the data set generated after systematically organizing and processing the power consumption data and communication quality data collected in all testing phases. This ensures the integrity and consistency of the data and provides a solid foundation for subsequent data integration.

[0156] The comparative analysis report is a document generated by conducting a detailed comparative analysis of power consumption and communication quality data under different operating conditions, revealing the performance differences under different configurations and their influencing factors.

[0157] Validated optimization schemes refer to optimization measures that have been verified and confirmed to be effective through simulation, ensuring that these measures can improve the overall performance of the system in practical applications.

[0158] Practical solutions transform validated optimization schemes into concrete and actionable improvement measures. They comprehensively consider the overall performance and potential areas for improvement of the system, and are ultimately applied to the actual system to enhance its performance and reliability.

[0159] In this embodiment, firstly, based on the performance evaluation report, the power consumption data and communication quality data collected in all testing phases are systematically organized and processed to generate a structured dataset. This step ensures the integrity and consistency of the data, providing a solid foundation for subsequent data integration. Secondly, based on the structured dataset and in conjunction with the optimization suggestions proposed in the performance evaluation report, the power consumption data and communication quality data are compared and analyzed to identify the differences and influencing factors under different operating states, generating a detailed comparative analysis report. This step, by comparing and analyzing the performance under different configurations, reveals the specific effects of the optimization suggestions and prepares the necessary foundation for the next step of adjustment and verification. The required input is then obtained. Next, based on the detailed comparative analysis report, an energy efficiency optimization method is used to adjust and verify the effectiveness of the integrated data. Through simulation verification of the power consumption mode and communication quality of user terminals, it is ensured that the optimization measures can actually improve the overall performance of the system, generating a verified optimization scheme. Finally, based on the verified optimization scheme, the integrated power consumption data and communication quality data are transformed into a practical solution. Taking into account the overall performance of the system and potential improvement points, the final results of the low-Earth orbit satellite mobile communication ground experiment are generated. This not only summarizes the various indicators in the experiment but also proposes specific optimization schemes, providing a solid foundation for the further development of low-Earth orbit satellite mobile communication systems.

[0160] For example, suppose a low-Earth orbit satellite system aims to provide reliable communication support for emergency medical care in remote areas worldwide. First, based on the performance evaluation report, power consumption and communication quality data collected during all testing phases are systematically processed to generate a structured dataset. This step ensures data integrity and consistency, providing a solid foundation for subsequent data integration. Second, based on the structured dataset and the optimization suggestions proposed in the performance evaluation report, power consumption and communication quality data are compared and analyzed to identify differences under different operating conditions and their influencing factors, generating a detailed comparative analysis report. This step, by comparing and analyzing performance under different configurations, reveals the specific effects of the optimization suggestions and prepares the necessary input for further adjustments and verification. Third, based on the detailed... The comparative analysis report employs energy efficiency optimization methods to adjust and verify the effectiveness of the integrated data. Through simulation verification of user terminal power consumption patterns and communication quality, it ensures that the optimization measures can effectively improve the overall system performance, generating a verified optimization scheme. Finally, based on the verified optimization scheme, the integrated power consumption and communication quality data are transformed into practical solutions. Taking into account the overall system performance and potential improvement points, the final results of the low-Earth orbit satellite mobile communication ground experiment are generated. This not only summarizes the various indicators in the experiment but also proposes specific optimization schemes to ensure that medical emergency teams in remote areas can maintain efficient and stable communication connections globally, improving emergency response speed and service quality.

[0161] This application considers that, in order to solve the problems of signal transmission delay and attenuation in low-Earth orbit satellite communication, existing technologies face the challenge of not being able to accurately predict and optimize signal transmission paths, leading to unstable communication quality in complex environments. Therefore, the present invention proposes this alternative solution to solve the above-mentioned technical problems and ensure the efficient operation of the communication system. This solution includes:

[0162] Based on the satellite motion records, and taking into account the effects of Earth's curvature and atmospheric refraction, a path prediction algorithm is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point, minimizing signal transmission delay and attenuation, and generating a preliminary transmission path scheme, including:

[0163] The satellite motion state record is processed for high-precision time synchronization, and a multi-layer atmospheric model is constructed to simulate atmospheric conditions at different altitudes and evaluate the dynamic impact of changes in the altitude of the ground user terminal on the signal propagation path in order to generate signal transmission delay.

[0164] The signal transmission delay can be calculated using the following formula:

[0165] ;

[0166] in, Signal transmission delay at each moment; The coefficient representing the influence of Earth's curvature; The atmospheric refraction coefficient; It is a function of the distance between the ground user terminal and the virtual satellite as a function of time; Let be the signal propagation constant; Angle conversion factor; This is a function of the angle between the line connecting the satellite and the ground user terminal and the ground plane as a function of time. This is a high correction factor; It is a high-impact factor; The height difference between the ground user terminal and the ground;

[0167] Based on the signal transmission delay, the delay and attenuation under different transmission paths are nonlinearly combined to form a comprehensive performance scoring function. By introducing weight coefficients to adjust the importance of each transmission path, a comprehensive performance evaluation value is generated.

[0168] The overall performance evaluation value is calculated using the following formula:

[0169] ;

[0170] in, The comprehensive performance evaluation value of all candidate transmission paths at each time point; These are the weighting coefficients for different candidate transmission paths; Signal transmission delay at each moment; For the first The signal attenuation level of each candidate transmission path at each time step; Indexes for candidate transmission paths, from 1 to... ; The number of candidate transmission paths; For dynamic adjustment coefficients; As a speed-affecting factor; The speed of movement of the ground user terminal;

[0171] Based on the comprehensive performance evaluation value, normalization is performed to ensure comparability between different transmission paths. An optimization algorithm is used to sort the paths to determine the optimal transmission path, and a preliminary transmission path scheme is generated based on the optimal transmission path.

[0172] This method aims to more accurately predict and optimize signal transmission paths in low-Earth orbit satellite communications, taking into account factors such as Earth's curvature, atmospheric refraction, and altitude variations of ground user terminals. By introducing mathematical models and optimization algorithms, delays and attenuation in signal transmission can be minimized, thereby improving communication quality and reliability.

[0173] The effect of Earth's curvature in signal transmission delay Considering the influence of the Earth's curvature on the signal propagation path, this sub-item uses an exponential decay function to describe the effect that gradually weakens with increasing distance; Angular influence term. Considering the impact of changes in the angle between the line connecting the satellite and the ground user terminal and the ground plane on the signal propagation path, this sub-item uses a sine function to describe the periodic effect caused by the angle change; Altitude Correction Item Considering the impact of the altitude difference between the ground user terminal and the ground on the signal propagation path, this sub-item uses the logistic function to describe the nonlinear effect caused by altitude changes.

[0174] Among them, the Earth curvature influence coefficient and atmospheric refraction coefficient The signal propagation constant can be obtained from literature or empirical data. and angle conversion factor The high correction factor can be obtained through experimental measurement or simulation. and high impact factor The distance between the ground user terminal and the virtual satellite can be obtained from historical data statistics. Angle and height difference It can be detected in real time through satellite navigation systems or sensors;

[0175] In the comprehensive performance evaluation value, the delay attenuation combination item : Delaying signal transmission under different candidate transmission paths and degree of attenuation A nonlinear combination is performed to form a comprehensive performance scoring function; weight standardization term Standardizing the weighting coefficients ensures comparability between different transmission paths; speed correction term. Considering the impact of the ground user terminal's movement speed on the signal propagation path, this sub-item uses an exponential function to describe the effect of speed changes;

[0176] Among them, the weight coefficients of different candidate transmission paths The signal transmission delay can be set based on experience in actual application scenarios. The degree of attenuation is calculated from the first formula. The dynamic adjustment coefficient can be obtained through channel model simulation or experimental measurement. and speed influence factor The movement speed of the ground user terminal can be obtained from historical data statistics. It can be monitored in real time through positioning systems such as GPS;

[0177] Suppose a low-Earth orbit satellite system is designed to provide stable communication support for global agricultural monitoring;

[0178] Assuming the influence coefficient of Earth's curvature Atmospheric refraction coefficient Signal propagation constant Angle conversion factor (i.e., convert each degree to radians); height correction factor High impact factor Distance between ground user terminal and virtual satellite included angle Height difference ;

[0179] ;

[0180] Assuming weight coefficients for different candidate transmission paths The attenuation level of the first candidate transmission path The attenuation level of the second candidate transmission path Dynamic adjustment coefficient Speed ​​Influence Factor ; speed of movement of ground user terminals ;

[0181] ;

[0182] Assuming a threshold of 0.9 is set, the calculated result of 0.98, which is greater than this threshold, indicates that the transmission path has high effectiveness and stability, ensuring that data is not affected by excessive delay or attenuation during transmission. This is because a high overall performance evaluation value reflects that the optimized transmission path can effectively guarantee communication quality under current environmental conditions without affecting transmission efficiency. Through the above steps, the stability and reliability of environmental monitoring data transmission are ensured, the accuracy and timeliness of monitoring actions are improved, and the response speed and service quality of the entire environmental monitoring system are enhanced.

[0183] This application considers that, in order to address the problem of dynamically monitoring and evaluating communication performance under different orbital altitudes and solar activity cycles in low-Earth orbit satellite communication, existing technologies suffer from the inability to adjust evaluation criteria in real time to adapt to changing communication environments, leading to unstable communication quality in complex environments. Therefore, the present invention proposes this alternative solution to solve the aforementioned technical problems and ensure the efficient operation of the communication system. This solution includes:

[0184] Based on the structured communication performance dataset, an adaptive performance evaluation algorithm is used to automatically adjust the evaluation criteria according to different orbital altitudes and solar activity cycles. This dynamically monitors and processes key communication performance indicators at each moment in the structured communication performance dataset, generating real-time performance evaluation records, including:

[0185] Based on the structured communication performance data table, measurement errors are eliminated by filtering and denoising techniques, key performance indicators are extracted, normalization is performed, a multi-dimensional feature matrix is ​​constructed, and the indicators are integrated into an overall representation to generate a comprehensive performance index.

[0186] The overall performance index is calculated using the following formula:

[0187] ;

[0188] in, For a moment Comprehensive performance indicators; For performance weighting coefficients; For a moment Connection stability; For a moment The maximum value of the connection stability; This is the signal strength adjustment factor; Frequency conversion factor; For a moment Signal frequency stability; This is the quality correction factor; Quality influencing factors; For a moment The signal quality index;

[0189] Based on the comprehensive performance indicators, nonlinear transformation is performed to enhance the distinguishability, environmental impact factors are introduced, the evaluation criteria are adjusted to adapt to the real-time changing communication environment, and the evaluation criteria are further optimized by combining path reliability and delay index to generate an adaptive evaluation criterion.

[0190] The adaptive evaluation criterion is calculated using the following formula:

[0191] ;

[0192] in, For a moment Adaptive evaluation criteria; This is a comprehensive adjustment factor; This is the path weight factor; For the first The overall performance indicators of the path; This is an environmental correction factor; Environmental impact factors; For a moment Environmental change index; This is a reliability adjustment factor; For a moment No. The reliability index of the path; For a moment No. The delay exponent of the candidate path; j is the index of the candidate path, from 1 to... ; The number of candidate paths;

[0193] Based on the adaptive evaluation criteria, a weighted average is applied to all path evaluation values ​​to highlight high-performing paths. Cluster analysis is used to identify path groups with similar performance characteristics, and real-time performance evaluation records are generated.

[0194] This method aims to more accurately evaluate and optimize performance metrics in low-Earth orbit satellite communications. It requires considering the impact of different orbital altitudes and solar activity cycles, and adjusting evaluation criteria in real time to adapt to changing communication environments. By introducing mathematical models and adaptive algorithms, the discriminative power can be enhanced and the evaluation criteria optimized, thereby improving communication quality and reliability.

[0195] In the comprehensive performance indicators, the connection stability attenuation item Considering the impact of connection stability on communication performance, this sub-item uses a cubic power function to describe the gradually weakening effect as connection stability decreases; signal frequency stability term. Considering the impact of signal frequency stability on communication performance, this sub-item uses a cosine function to describe the periodic effects of frequency variations; Signal quality index term Considering the impact of signal quality index on communication performance, this sub-item uses an exponential decay function to describe the nonlinear effects of quality changes.

[0196] Among them, performance weight coefficient Signal strength adjustment coefficient Quality correction factor It can be configured based on experience in actual application scenarios; connection stability. and maximum connection stability Frequency conversion factor can be obtained by monitoring the communication link status in real time. It can be determined based on the signal's spectral characteristics; signal frequency stability Quality Influence Factor; can be measured using frequency domain analysis tools. Signal quality index can be obtained from historical data statistics. It can be obtained through channel model simulation or experimental measurement;

[0197] In adaptive evaluation criteria, the path comprehensive performance item The comprehensive performance indicators of each path are subjected to nonlinear transformation to enhance discriminative power; environmental change index term. Considering the impact of environmental changes on communication performance, this sub-item uses a logarithmic function to describe the effects of environmental changes; Path reliability and delay index term. Further optimize the evaluation criteria by combining path reliability and latency index;

[0198] Among them, the comprehensive adjustment coefficient Environmental correction factor Reliability adjustment factor Path weight factor can be set based on experience in actual application scenarios. It can be set according to path importance; comprehensive performance indicators Environmental impact factors are calculated from the first formula. The environmental change index can be obtained based on historical data. Reliability index can be obtained through real-time monitoring using environmental monitoring equipment. and delay index It can be obtained through channel model simulation or experimental measurement;

[0199] Assume a low-Earth orbit satellite system designed to provide stable communication support for global environmental monitoring; assume performance weighting coefficients... Connection stability Maximum connection stability Signal strength adjustment factor Frequency conversion factor Signal frequency stability at time t Quality correction factor Quality Influence Factors Signal quality index at time t ;

[0200] ;

[0201] Assuming a comprehensive adjustment coefficient Path weight factor Environmental correction factor Environmental impact factors Environmental change index at time t Reliability adjustment factor Reliability index of the j-th path at time t The delay exponent of the j-th path at time t Number of candidate paths ;

[0202] ;

[0203] Assuming a threshold of 0.8, the calculated result of 0.85 is greater than this threshold, indicating that the transmission path has a high adaptive evaluation standard, ensuring communication quality and reliability under different orbital altitudes and solar activity cycles. This is because a high adaptive evaluation standard reflects that the optimized evaluation standard can effectively adapt to the real-time changing communication environment, while highlighting the superior performance of the path. Through the above steps, the stability and reliability of environmental monitoring data transmission are ensured, the accuracy and timeliness of monitoring actions are improved, and the response speed and service quality of the entire environmental monitoring system are enhanced.

[0204] Figure 2 This application provides a schematic diagram of the structure of a low-orbit satellite mobile communication ground experimental system, as shown in the embodiment of the present application. Figure 2 As shown, the device includes:

[0205] Planning module 21 is used to plan a diverse set of orbital parameters, taking into account the influence of different orbital altitudes and solar activity cycles, and to generate a virtual satellite network model.

[0206] The calculation module 22 is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point based on the virtual satellite network model and using a path prediction algorithm. Based on the optimal transmission path, the characteristics of the ground station's transmitted signal are precisely adjusted through real-time channel simulation technology to generate a low-orbit satellite communication environment test scenario.

[0207] Analysis module 23 is used to evaluate the communication performance data of the ground user terminal under different orbit parameter configurations based on the low-orbit satellite communication environment test scenario using an adaptive performance evaluation algorithm, obtain performance evaluation results, and determine the power consumption mode of the ground user terminal based on the performance evaluation results and combined with energy efficiency optimization methods, so as to analyze the relationship between the battery consumption and communication quality of the ground user terminal under different working conditions and generate a performance evaluation report.

[0208] The conversion module 24 is used to integrate the power consumption data and communication quality data collected during the performance evaluation phase, and adjust and verify the integrated data according to the optimization suggestions proposed in the performance evaluation report, so as to transform the integrated data into a practical solution and generate the ground test results of low-orbit satellite mobile communication.

[0209] Figure 2 The aforementioned low-orbit satellite mobile communication ground experimental system can perform... Figure 1 The implementation principle and technical effects of the low-Earth orbit satellite mobile communication ground experiment method described in the illustrated embodiment will not be repeated here. The specific methods by which each module and unit of the low-Earth orbit satellite mobile communication ground experiment system performs operations have been described in detail in the embodiments related to this method, and will not be elaborated upon here.

[0210] In one possible design, Figure 2 The low-Earth orbit satellite mobile communication ground experimental system of the embodiment shown can be implemented as a computing device, such as... Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0211] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are invoked and executed by the processing component 32.

[0212] The processing component 32 is used to: plan diverse sets of orbital parameters based on different orbital altitudes and the influence of solar activity cycles, and simulate the layout of virtual satellites based on the orbital parameter sets to generate a virtual satellite network model. This virtual satellite network model is used to predict the location distribution of virtual satellites at different time points and their connection methods with ground user terminals. Based on the virtual satellite network model, a path prediction algorithm is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point. Based on the optimal transmission path, real-time channel simulation technology is used to precisely adjust the transmission signal characteristics of the ground station to generate a low-Earth orbit satellite communication environment test scenario. The ground station is used to forward information to the ground user terminal via the virtual satellite. In a low-Earth orbit (LEO) satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to assess the communication performance data of ground user terminals under different orbital parameter configurations, obtaining performance evaluation results. Based on these results and combined with energy efficiency optimization methods, the power consumption mode of the ground user terminal is determined to analyze the relationship between battery consumption and communication quality under different operating conditions, generating a performance evaluation report. The power consumption mode refers to the way and rate at which the ground user terminal consumes power under different operating conditions. The power consumption data and communication quality data collected during the performance evaluation phase are integrated, and the integrated data is adjusted and verified using the optimization suggestions proposed in the performance evaluation report. This results in the transformation of the integrated data into a practical solution and the generation of LEO satellite mobile communication ground experimental results.

[0213] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above-described method. Alternatively, the processing component may be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described method.

[0214] Storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0215] Of course, computing devices may also include other components, such as input / output interfaces, display components, communication components, etc.

[0216] Input / output interfaces provide interfaces between processing components and peripheral interface modules, which can be output devices, input devices, etc.

[0217] The communication components are configured to facilitate wired or wireless communication between computing devices and other devices.

[0218] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform. In this case, the computing device can refer to a cloud server, and the aforementioned processing components, storage components, etc., can be basic server resources rented or purchased from the cloud computing platform.

[0219] This application also provides a computer storage medium storing a computer program, which, when executed by a computer, can perform the above-described functions. Figure 1 The illustrated embodiment is a ground-based experimental method for low-orbit satellite mobile communication.

[0220] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0221] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0222] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0223] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A ground-based experimental method for low-Earth orbit satellite mobile communication, characterized in that, include: Based on the influence of different orbital altitudes and solar activity cycles, a diverse set of orbital parameters is planned, and the layout of virtual satellites is simulated according to the set of orbital parameters to generate a virtual satellite network model. The virtual satellite network model is used to predict the location distribution of virtual satellites at different points in time and their connection with ground user terminals. Based on the virtual satellite network model, a path prediction algorithm is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point. According to the optimal transmission path, the transmission signal characteristics of the ground station are precisely adjusted through real-time channel simulation technology to generate a low-orbit satellite communication environment test scenario. The ground station is used to forward information to the ground user terminal through the virtual satellite. Based on the aforementioned low-orbit satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to evaluate the communication performance data of the ground user terminal under different orbital parameter configurations, obtain performance evaluation results, and based on the performance evaluation results, combined with energy efficiency optimization methods, determine the power consumption mode of the ground user terminal, so as to analyze the relationship between the battery consumption and communication quality of the ground user terminal under different working states, and generate a performance evaluation report. The power consumption mode refers to the way and rate at which the ground user terminal consumes power under different working states. The power consumption data and communication quality data collected during the performance evaluation phase are integrated, and the integrated data is adjusted and verified according to the optimization suggestions proposed in the performance evaluation report, so as to transform the integrated data into a practical solution and generate the ground test results of low-orbit satellite mobile communication. Based on the virtual satellite network model, a path prediction algorithm is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point. According to the optimal transmission path, real-time channel simulation technology is used to precisely adjust the transmission signal characteristics of the ground station, generating a low-Earth orbit satellite communication environment test scenario, including: Based on the virtual satellite network model, the position and velocity vectors of the virtual satellites at each time point are calculated and processed to generate a dynamic satellite orbit information database. Based on the dynamic satellite orbit information database, the motion state of the virtual satellite at different points in time is simulated to generate a satellite motion state record. The satellite motion state record is processed for high-precision time synchronization, and a multi-layer atmospheric model is constructed to simulate atmospheric conditions at different altitudes and evaluate the dynamic impact of changes in the altitude of the ground user terminal on the signal propagation path in order to generate signal transmission delay. The signal transmission delay can be calculated using the following formula: ； in, Signal transmission delay at each moment; The coefficient representing the influence of Earth's curvature; The atmospheric refraction coefficient; It is a function of the distance between the ground user terminal and the virtual satellite as a function of time; Let be the signal propagation constant; Angle conversion factor; This is a function of the angle between the line connecting the satellite and the ground user terminal and the ground plane as a function of time. This is a high correction factor; It is a high-impact factor; The height difference between the ground user terminal and the ground; Based on the signal transmission delay, the delay and attenuation under different transmission paths are nonlinearly combined to form a comprehensive performance scoring function. By introducing weight coefficients to adjust the importance of each transmission path, a comprehensive performance evaluation value is generated. The overall performance evaluation value is calculated using the following formula: ; in, The comprehensive performance evaluation value of all candidate transmission paths at each time point; These are the weighting coefficients for different candidate transmission paths; Signal transmission delay at each moment; For the first The signal attenuation level of each candidate transmission path at each time step; Indexes for candidate transmission paths, from 1 to... ; The number of candidate transmission paths; For dynamic adjustment coefficients; As a speed-affecting factor; The speed of movement of the ground user terminal; Based on the comprehensive performance evaluation value, normalization is performed to ensure comparability between different transmission paths. An optimization algorithm is used to sort the paths to determine the optimal transmission path, and a preliminary transmission path scheme is generated based on the optimal transmission path. Based on the preliminary transmission path scheme, the performance of different transmission paths is evaluated and compared, the transmission path parameters are optimized, and the transmission effect under different conditions is combined to generate an optimized transmission path scheme. Based on the optimized transmission path scheme, real-time channel simulation technology is used to precisely adjust the characteristics of the ground station's transmitted signal, and to simulate the effects of different weather conditions and multipath effects to generate signal characteristic parameter processing results. Based on the signal characteristic parameter processing results, the actual communication performance data is compared with the expected results to optimize the simulation parameters and generate a low-orbit satellite communication environment test scenario.

2. The method according to claim 1, characterized in that, Based on the optimized transmission path scheme, real-time channel simulation technology is used to precisely adjust the characteristics of the ground station's transmitted signal, and to simulate the effects of different weather conditions and multipath effects, generating signal characteristic parameter processing results, including: Based on the optimized transmission path scheme, the characteristics of the ground station's transmitted signal are analyzed in detail, the signal strength and phase changes are evaluated, and a set of signal characteristic parameters is generated. Based on the aforementioned signal characteristic parameter set, real-time channel simulation technology is used to simulate the effects of different weather conditions and multipath effects, and to precisely adjust the transmission signal characteristics of the ground station to generate signal characteristic simulation results. Based on the simulation results of the signal characteristics, the communication performance under each simulation scenario is comprehensively evaluated to generate the communication performance evaluation results of the simulation scenario. Based on the communication performance evaluation results of the simulation scenario, the transmission power and coding strategy are adjusted to generate signal characteristic parameters.

3. The method according to claim 1, characterized in that, The test scenario based on the low-Earth orbit satellite communication environment employs an adaptive performance evaluation algorithm to assess the communication performance data of the ground user terminal under different orbital parameter configurations, obtaining performance evaluation results. Based on these performance evaluation results and combined with energy efficiency optimization methods, the power consumption mode of the ground user terminal is determined to analyze the relationship between battery consumption and communication quality under different operating conditions, generating a performance evaluation report, including: In the low-Earth orbit satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to dynamically monitor and evaluate the communication performance of ground user terminals under different orbital parameter configurations, and the performance evaluation results are obtained. Among them, the key indicators for evaluating communication performance include signal strength, bit error rate, data transmission rate, and latency. These key indicators are used to reflect the communication quality of ground user terminals under the influence of different orbital altitudes and solar activity cycles. Based on the performance evaluation results and combined with energy efficiency optimization methods, the power consumption patterns of the ground user terminal under different operating states are determined, and the relationship between battery consumption and communication quality under different operating states is analyzed. Based on the analysis results, the performance and power consumption patterns of the ground user terminal under different operating states are summarized to generate a performance evaluation report, which includes performance evaluation results and optimization suggestions.

4. The method according to claim 3, characterized in that, In the aforementioned low-Earth orbit satellite communication environment test scenario, an adaptive performance evaluation algorithm is used to dynamically monitor and evaluate the communication performance of ground user terminals under different orbital parameter configurations, obtaining performance evaluation results, including: Based on the aforementioned low-orbit satellite communication environment test scenario, real-time acquisition and processing of communication data from ground user terminals under different orbital parameter configurations are performed to generate a structured communication performance dataset. Based on the structured communication performance dataset, an adaptive performance evaluation algorithm is used to automatically adjust the evaluation criteria according to different orbital altitudes and solar activity cycles. The key communication performance indicators at each moment in the structured communication performance dataset are dynamically monitored and processed to generate real-time performance evaluation records. Based on the real-time performance evaluation records, combined with multi-dimensional analysis methods, the differences in communication quality in the structured communication performance data under different orbit parameter configurations are identified, and intermediate performance evaluation results are generated. Based on the intermediate results of the performance evaluation, multi-level analysis and processing are performed to identify the optimal and suboptimal orbital parameter configurations and generate performance evaluation results.

5. The method according to claim 4, characterized in that, The power consumption and communication quality data collected during the integrated performance evaluation phase are adjusted and verified using optimization suggestions proposed in the performance evaluation report. This process transforms the integrated data into a practical solution and generates ground-based experimental results for low-Earth orbit satellite mobile communication, including: Based on the performance evaluation report, the power consumption data and communication quality data collected in all testing phases are systematically organized and processed to generate a structured dataset. This step ensures the integrity and consistency of the data, provides a solid foundation for subsequent data integration, and ensures the standardization and accuracy of data management. Based on the structured dataset and the optimization suggestions proposed in the performance evaluation report, the power consumption data and communication quality data are compared and analyzed to identify the differences and influencing factors under different working conditions, and a detailed comparative analysis report is generated. This step reveals the specific effects of the optimization suggestions by comparing and analyzing the performance under different configurations, and prepares the necessary input for the next step of adjustment and verification. Based on the detailed comparative analysis report, an energy efficiency optimization method was adopted to adjust and verify the effectiveness of the integrated data. By simulating and verifying the power consumption mode and communication quality of user terminals, it was ensured that the optimization measures could actually improve the overall performance of the system, and a verified optimization scheme was generated. This step not only verified the feasibility of the optimization suggestions, but also provided a specific implementation path for subsequent practical solutions, ensuring the actual effect of the optimization measures. Based on the verified optimization scheme, the integrated power consumption data and communication quality data are transformed into practical solutions. Taking into account the overall performance of the system and potential improvement points, the final results of the low-Earth orbit satellite mobile communication ground experiment are generated. This step not only summarizes the various indicators in the experiment, but also proposes specific optimization schemes, providing a solid foundation for the further development of low-Earth orbit satellite mobile communication systems. Based on the structured communication performance dataset, an adaptive performance evaluation algorithm is used to automatically adjust the evaluation criteria according to different orbital altitudes and solar activity cycles. This dynamically monitors and processes key communication performance indicators at each moment in the structured communication performance dataset, generating real-time performance evaluation records, including: Based on the structured communication performance dataset, measurement errors are eliminated through filtering and denoising techniques, key performance indicators are extracted, normalization is performed, a multi-dimensional feature matrix is ​​constructed, and the indicators are integrated into an overall representation to generate a comprehensive performance index. The overall performance index is calculated using the following formula: ； in, For each moment, it represents a comprehensive performance indicator; For performance weighting coefficients; For a moment Connection stability; For a moment The maximum value of the connection stability; This is the signal strength adjustment factor; Frequency conversion factor; For a moment Signal frequency stability; This is the quality correction factor; Quality influencing factors; For a moment The signal quality index; Based on the comprehensive performance indicators, nonlinear transformation is performed to enhance the distinguishability, environmental impact factors are introduced, the evaluation criteria are adjusted to adapt to the real-time changing communication environment, and the evaluation criteria are further optimized by combining path reliability and delay index to generate an adaptive evaluation criterion. The adaptive evaluation criterion is calculated using the following formula: ； in, For a moment Adaptive evaluation criteria; This is a comprehensive adjustment factor; This is the path weight factor; For the first The overall performance indicators of the path; This is an environmental correction factor; Environmental impact factors; For a moment Environmental change index; This is a reliability adjustment factor; For a moment No. The reliability index of the path; For a moment No. The delay index of the path; Indexes for candidate paths, from 1 to... ; The number of candidate paths; Based on the adaptive evaluation criteria, a weighted average is applied to all path evaluation values ​​to highlight high-performing paths. Cluster analysis is used to identify path groups with similar performance characteristics, and real-time performance evaluation records are generated.

6. A ground experimental system for low-Earth orbit satellite mobile communication, used to execute the ground experimental method for low-Earth orbit satellite mobile communication as described in any one of claims 1 to 5, characterized in that, include: The planning module is used to plan diverse sets of orbital parameters, taking into account the influence of different orbital altitudes and solar activity cycles, and to generate a virtual satellite network model. The calculation module is used to calculate the optimal transmission path between the ground user terminal and the virtual satellite at each time point based on the virtual satellite network model and using a path prediction algorithm. Based on the optimal transmission path, the characteristics of the ground station's transmitted signal are precisely adjusted through real-time channel simulation technology to generate a low-orbit satellite communication environment test scenario. The analysis module is used to evaluate the communication performance data of the ground user terminal under different orbital parameter configurations based on the low-orbit satellite communication environment test scenario and using an adaptive performance evaluation algorithm to obtain the performance evaluation results. Based on the performance evaluation results and combined with the energy efficiency optimization method, the power consumption mode of the ground user terminal is determined to analyze the relationship between the battery consumption and communication quality of the ground user terminal under different working conditions and generate a performance evaluation report. The conversion module is used to integrate the power consumption data and communication quality data collected during the performance evaluation phase, and adjust and verify the integrated data according to the optimization suggestions proposed in the performance evaluation report, so as to transform the integrated data into a practical solution and generate the ground test results of low-orbit satellite mobile communication.

7. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement a ground experimental method for low-orbit satellite mobile communication as described in any one of claims 1 to 5.

8. A computer storage medium, characterized in that, The device contains a computer program that, when executed by a computer, implements a ground-based experimental method for low-orbit satellite mobile communication as described in any one of claims 1 to 5.

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