Communication link simulation method and simulation system for low-orbit satellite constellation

Abstract

The invention provides a communication link simulation method and simulation system for a low-orbit satellite constellation. The method provided by the invention comprises the following steps: a local control device transmits a simulation scene and a static network topology to each computing node in an initialization stage; the local control equipment generates and issues a simulation task according to a task demand in a simulation stage; when the control node receives the simulation task, determining a target computing node for executing the simulation task, and issuing the simulation task to the target computing node; the target computing node performs link performance simulation according to a pre-constructed natural electromagnetic environment description model, an inter-satellite electromagnetic interference description model and a man-made electromagnetic interference description model, and reports a simulation result to the control node; and the control node receives and stores the simulation result and transmits the simulation result to the local control equipment. The communication link simulation method and simulation system for the low-orbit satellite constellation provided by the invention are used for accurately and reliably carrying out communication link simulation.

Description

Technical Field

[0001] The present application relates to the field of satellite communication technology, and in particular to a communication link simulation method and simulation system for low-orbit satellite constellations. Background Art

[0002] With the rapid development of satellite communication technology, low-orbit satellite constellations, as a key component of the next-generation communication network, offer advantages such as wide coverage, low latency, and high capacity, making them a crucial infrastructure for future global communications. To effectively verify and optimize the performance of low-orbit satellite constellations, communication link simulation technology is particularly important.

[0003] Existing communication link simulation technology generates simulation scenarios by constructing descriptive models. However, its accuracy and reliability cannot meet the requirements when facing interference from complex electromagnetic environments. In particular, existing methods often fail to fully consider the impact of the electromagnetic environment on communication quality or only perform simple analysis, resulting in large deviations between simulation results and actual operation. Summary of the Invention

[0004] In view of this, the present application provides a communication link simulation method and system for low-orbit satellite constellations, which are used to accurately and reliably simulate communication links.

[0005] Specifically, this application is implemented through the following technical solutions:

[0006] In a first aspect, the present application provides a communication link simulation method for a low-orbit satellite constellation. The method is applied to a simulation system, wherein the simulation system includes a local control device, a control node, and multiple computing nodes. The method includes:

[0007] During the initialization phase, the local control device transmits the simulation scenario and the static network topology of the low-orbit satellite constellation to each computing node through the control node;

[0008] During the simulation phase, the local control device generates simulation tasks according to task requirements and sends the simulation tasks to the control node;

[0009] When receiving a simulation task, the control node determines the target computing node for executing the simulation task and sends the simulation task to the target computing node;

[0010] Upon receiving a simulation task, the target computing node simulates link performance based on pre-built natural electromagnetic environment description models, inter-satellite electromagnetic interference description models, and man-made electromagnetic interference description models, and reports the simulation results to the control node. The natural electromagnetic environment description model is used to describe the impact of precipitation rate, cloud water content, oxygen absorption coefficient, and water vapor absorption coefficient on link performance. The inter-satellite interference description model is used to simulate interference between satellites and evaluate the impact of inter-satellite interference on link performance. The man-made electromagnetic interference description model is used to simulate electromagnetic interference generated by various man-made sources and evaluate the impact of such electromagnetic interference on link performance.

[0011] The control node receives and stores the simulation results and transmits the simulation results to the local control device.

[0012] A second aspect of the present application provides a simulation system, comprising a local control device, a control node, and a plurality of computing nodes; wherein:

[0013] Local control device, used to transmit the simulation scenario and the static network topology of the low-orbit satellite constellation to each computing node through the control node during the initialization phase;

[0014] The local control device is also used to generate simulation tasks according to task requirements during the simulation phase and send the simulation tasks to the control node;

[0015] The control node is used to determine the target computing node for executing the simulation task when receiving the simulation task, and send the simulation task to the target computing node;

[0016] The target computing node is configured to, upon receiving a simulation task, simulate link performance based on a pre-built natural electromagnetic environment description model, an inter-satellite electromagnetic interference description model, and an artificial electromagnetic interference description model, and report the simulation results to the control node; wherein the natural electromagnetic environment description model is used to describe the impact of precipitation rate, cloud water content, oxygen absorption coefficient, and water vapor absorption coefficient on link performance; the inter-satellite interference description model is used to simulate interference between satellites and evaluate the impact of inter-satellite interference on link performance; and the artificial electromagnetic interference description model is used to simulate electromagnetic interference generated by various artificial sources and evaluate the impact of such electromagnetic interference on link performance;

[0017] The control node is also used to receive and store simulation results, and transmit the simulation results to the local control device.

[0018] The communication link simulation method and simulation system for low-orbit satellite constellations provided in this application integrate multiple interference models such as natural electromagnetic environment, inter-satellite electromagnetic interference, and man-made electromagnetic interference, providing the simulation system with unprecedented comprehensiveness and complexity. Compared with traditional low-orbit satellite communication simulation technology that only considers each interference item separately, it is difficult to fully reflect the complex interactions in the real communication environment. This method organically combines these factors by constructing a natural electromagnetic environment description model, an inter-satellite electromagnetic interference description model, and an man-made electromagnetic interference description model, thereby better understanding and predicting possible communication problems in low-orbit satellite constellations and improving the accuracy and reliability of link performance simulation. In addition, the method uses a distributed simulation architecture of local control devices, control nodes, and multiple computing nodes. Through this structure, simulation tasks can be dynamically allocated according to task requirements and node capabilities, ensuring the flexibility of the simulation process. Furthermore, as the scale of low-orbit satellite constellations expands and the complexity of simulation tasks increases, the simulation system can expand simulation capabilities by adding computing nodes to adapt to simulation tasks of different scales and complexities.

[0019] Furthermore, the method provided in this application addresses the problem of inaccurate simulation caused by changes in local network topology due to link disconnection and re-establishment before and after the intersection of satellite orbits. Dynamic simulation of satellite network topology is achieved through time slice management, which can ensure the precise synchronization of topology changes during the simulation process and improve the timeliness and accuracy of the simulation results.

[0020] Furthermore, the method provided by this application not only builds a complete system for comparing performance data between interference-free and interference-affected links, but also identifies interference types through spectrum analysis and establishes a mapping relationship between interference characteristics and link performance impacts. This approach improves the ability to quantitatively assess electromagnetic interference and provides more targeted anti-interference optimization strategies for low-orbit satellite communication systems.

[0021] Furthermore, the method provided in this application can maintain real-time updating of simulation data during satellite orbit changes to address the unpredictability of satellite topology changes during human-in-loop simulation, ensure the dynamic adaptability and real-time performance of the simulation process, and ensure that the simulation system can continue to operate stably under changing satellite topology and link conditions.

[0022] In addition, through efficient link information matching, data synchronization and distributed processing mechanisms, the dynamic simulation of low-orbit satellite link performance is ensured to be accurately synchronized between various computing nodes, effectively reducing the time delay, data inconsistency and error accumulation in the simulation process, and improving the synchronization accuracy and calculation accuracy of the entire simulation system, ultimately helping to better simulate the performance of low-orbit satellite constellation links in actual environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1Flowchart of Example 1 of the communication link simulation method for low-orbit satellite constellations provided by this application;

[0024] Figure 2 A schematic diagram of a simulation system shown as an exemplary embodiment of the present application;

[0025] Figure 3 This is a flowchart of Example 2 of the communication link simulation method for low-orbit satellite constellations provided in this application. DETAILED DESCRIPTION

[0026] Exemplary embodiments are described in detail herein, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different drawings represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with this application.

[0027] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms "a," "the," and "the" used in this application are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0028] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0029] Specific embodiments are given below to introduce the technical solutions of the present application in detail.

[0030] Figure 1 This is a flow chart of the first embodiment of the communication link simulation method for low-orbit satellite constellations provided by this application. Figure 1 The method provided in this embodiment is applied to a simulation system, wherein the simulation system includes a local control device, a control node, and multiple computing nodes; the method may include:

[0031] S101. During the initialization phase, the local control device transmits the simulation scenario and the static network topology of the low-orbit satellite constellation to each computing node through the control node.

[0032] Before introducing the method provided by this implementation, the following is a brief introduction to the simulation system. Figure 2 This is a schematic diagram of a simulation system shown in an exemplary embodiment of the present application. Figure 2 , the simulation system includes a local control device, a control node and multiple computing nodes.

[0033] Specifically, the local control device is the core control unit of the simulation system, responsible for initializing the entire simulation process, allocating tasks, and collecting results. For example, it is primarily responsible for managing the simulation scenario of a low-orbit satellite constellation, including static topology initialization and construction, dynamic simulation control, and scenario parsing and saving data to the control node database.

[0034] In specific implementation, the local control device can be a high-performance computer or server with powerful computing and storage capabilities.

[0035] Furthermore, the control node is the core of the simulation system. It receives commands from the local control device and forwards them to the various compute nodes. It also collects simulation results from the compute nodes and returns them to the local control device. In other words, the control node acts as a bridge and coordinator. In other words, the control node is the connection channel between simulation scenarios and simulation scenarios, receiving and transmitting data, controlling simulation operations by issuing commands, and storing relevant data in a database.

[0036] Furthermore, the computing node is a device that performs actual simulation calculations and performs link performance simulation according to the instructions of the control node.

[0037] The method provided in this embodiment is introduced below.

[0038] Specifically, before the simulation begins, the simulation scenario and the static network topology of the low-orbit satellite constellation need to be initialized and distributed to multiple computing nodes to ensure a consistent data foundation for the simulation system. The simulation scenario is the specific communication environment simulated by the simulation system, including the layout of the low-orbit satellite constellation, communication links between satellites, and the location of ground stations. Furthermore, the static network topology of the low-orbit satellite constellation is used to describe the network structure of the low-orbit satellite constellation during the initialization phase. It can include the number, location, orbits, and connectivity of satellites.

[0039] As described above, during the initialization phase, the local control device transmits the simulation scenario and static network topology to each computing node through the control node. The control node acts as a transfer station, receiving data packets from the local control device and distributing these data packets to each computing node according to the network architecture.

[0040] It is understandable that after receiving this information, the computing node configures its own simulation environment according to the information and prepares for subsequent link performance simulation.

[0041] S102: The local control device generates a simulation task according to task requirements during the simulation phase, and sends the simulation task to the control node.

[0042] Specifically, the simulation phase is the phase in which the simulation system is running. At this time, the simulation system has completed the initialization settings, and the simulation system will perform actual simulation operations according to the preset task requirements.

[0043] It should be noted that the task requirements include specific goals or scenarios for simulation and verification, which are set by users or system administrators based on actual needs before simulation.

[0044] In specific implementations, for example, in one embodiment, the task requirement is to evaluate the performance of a communication link under different electromagnetic interference conditions. In another embodiment, the task requirement is to test the impact of network topology changes on communication quality.

[0045] Furthermore, the local control device generates a specific simulation task based on the preset task requirements. In specific implementations, a simulation task can be generated that contains multiple subtasks (each simulation task includes specific parameter settings) to ensure that the simulation can fully and accurately simulate the required communication environment and link performance.

[0046] Furthermore, after generating the simulation task, the local control device will encapsulate the simulation task into a data packet and send it to the control node through the network. After confirming that the data packet is correct, the control node will allocate the simulation task to the computing node efficiently and fairly based on the nature and requirements of the simulation task, combined with the routing selection algorithm and load balancing algorithm.

[0047] S103 . When receiving the simulation task, the control node determines a target computing node for executing the simulation task, and sends the simulation task to the target computing node.

[0048] Specifically, different computing nodes have different computing capabilities and resources. The control node needs to select one or more suitable computing nodes to perform the task based on the task requirements and the system resource status. For the sake of convenience, the selected computing nodes are recorded as target computing nodes.

[0049] In specific implementation, when the control node receives a simulation task from the local control device, it determines the corresponding target computing node to execute the simulation task based on the system's resource status and task requirements. Furthermore, after determining the target computing node, the control node will send the simulation task to the target computing node. After receiving the simulation task, the target computing node will perform the corresponding simulation operation according to the simulation instructions in the simulation task.

[0050] A specific embodiment is given below to describe in detail the process of determining the target computing node. Optionally, in one possible implementation, determining the target computing node for executing the simulation task includes:

[0051] (1) Obtaining status information of each computing node; wherein the status information includes CPU utilization, memory occupancy, network traffic, and number of tasks.

[0052] In specific implementation, the simulation system can obtain the status information of each computing node through monitoring tools or the computing node's own management system. This status information includes CPU utilization, memory usage, network traffic, and the number of tasks. For example, the status information of a computing node can be expressed as:

[0053] S i =(CPU i ,RAM i ,Net i ,Task i );

[0054] (2) For each computing node, based on a preset reward function and the state information of the computing node, determine the reward value of the computing node for executing the simulation task.

[0055] Specifically, the reward function is a mathematical function used to evaluate the effectiveness of a computing node in executing a simulation task, and the reward value can be calculated based on the status information of the computing node.

[0056] Referring to the previous description, it can be understood that the reward value is a numerical value calculated by the reward function, which is used to measure the effectiveness of the computing node in performing the simulation task. In other words, the higher the reward value, the better the efficiency or effect of the node in performing the task.

[0057] The preset reward function is set according to actual needs and is not limited in this embodiment. For example, in one embodiment, the preset reward function is:

[0058] R i =-(w1·CPU i +w2·RAM i +w3·Task i +w4·Net i );

[0059] In specific implementation, for each computing node, a preset reward function is used, combined with the node's status information, to calculate a reward value that reflects the node's processing capacity, resource utilization efficiency, and current load conditions.

[0060] (3) Determine the target computing node based on the reward value of each computing node executing the simulation task.

[0061] In specific implementation, the reward values ​​of all computing nodes can be compared, and the node with the highest reward value can be selected as the target computing node. The target computing node has the highest efficiency and effect when executing the simulation task.

[0062] It can be understood that by collecting status information such as the CPU utilization, memory occupancy, network traffic and number of tasks of the computing nodes, and using the preset reward function to evaluate the efficiency and effectiveness of each node in executing the simulation task, the node with the highest reward value is finally selected as the target computing node to execute the task, thereby optimizing resource allocation, effectively achieving load balancing, optimizing resource allocation, avoiding the situation where some nodes are overloaded while other nodes are idle, and improving the efficiency of the entire simulation system.

[0063] S104. When receiving the simulation task, the target computing node performs link performance simulation according to the pre-built natural electromagnetic environment description model, inter-satellite electromagnetic interference description model and artificial electromagnetic interference description model, and reports the simulation results to the control node.

[0064] It should be noted that the natural electromagnetic environment description model is used to describe the impact of precipitation rate, cloud water content, oxygen absorption coefficient, and water vapor absorption coefficient on link performance; the inter-satellite interference description model is used to simulate interference between satellites and evaluate the impact of interference between satellites on link performance; the man-made electromagnetic interference description model is used to simulate electromagnetic interference generated by various man-made sources and evaluate the impact of such electromagnetic interference on link performance.

[0065] Specifically, the natural electromagnetic environment description model is used to describe the impact of various factors in the natural environment on the performance of satellite communication links.

[0066] In specific implementation, the natural electromagnetic environment description model can characterize the attenuation or interference caused by precipitation rate, cloud water content, oxygen absorption coefficient, water vapor absorption coefficient, etc. on the propagation of radio waves.

[0067] Optionally, in a possible implementation, the process of constructing the pre-built natural electromagnetic environment description model includes:

[0068] Constructing rain attenuation models, cloud attenuation models, and atmospheric attenuation models; wherein the rain attenuation model is used to describe the effects of precipitation rate, frequency, and propagation path length on signal power loss; the cloud attenuation model is used to describe the effects of cloud water content, frequency, and propagation path length on signal power loss; and the atmospheric attenuation model is used to describe the effects of oxygen absorption coefficient, water vapor absorption coefficient, frequency, and propagation path length on signal power loss;

[0069] The natural electromagnetic environment description model is constructed according to the rain attenuation model, the cloud and fog attenuation model, and the atmospheric attenuation model.

[0070] In the specific implementation, we first construct rain attenuation models, cloud and fog attenuation models, and atmospheric attenuation models respectively. These models consider the effects of factors such as precipitation rate, cloud water content, oxygen absorption coefficient, and water vapor absorption coefficient on signal power loss. Then, using these models as a basis, by integrating their parameters and characteristics, we construct a natural electromagnetic environment description model that can comprehensively describe the impact of the natural electromagnetic environment on signal transmission. In this way, we can accurately simulate various attenuation factors in the natural environment, providing an accurate electromagnetic environment foundation for the simulation of low-orbit satellite constellation communication links.

[0071] For example, in one embodiment, the constructed natural electromagnetic environment description model is:

[0072] P loss =f(precipitation rate, cloud water content, oxygen absorption, water vapor absorption);

[0073] Furthermore, an intersatellite electromagnetic interference description model can be constructed through signal link modeling, interference type definition and interference calculation.

[0074] In specific implementation, we can first establish the basic communication network framework, then set the interference mode, parameters and source, and finally calculate the impact of the interference signal on the link, including the signal-to-interference ratio (SIR) and bit error rate (BER).

[0075] Furthermore, artificial electromagnetic interference primarily refers to noise amplitude modulation (AM) and frequency modulation (FM) interference on satellite-to-ground communication downlinks from airborne platforms such as drones. To implement this, the airborne platform can be modeled first. Then, based on the mathematical model of AM / FM interference, the interference signal can be constructed, and its impact on the downlink can be calculated.

[0076] It should be noted that each computing node performs link performance simulation based on its pre-established electromagnetic interference description model. A specific embodiment is given below to introduce the link performance simulation process in detail.

[0077] Optionally, in a possible implementation, the specific process of link performance simulation may include:

[0078] (1) Extract the receiver name and transmitter name from the input link data and assign unique identification information to the link consisting of a receiver and a transmitter.

[0079] Specifically, a receiver is a device or system that receives satellite signals in a satellite communication link, and a receiver name is a text label or identifier used to uniquely identify the receiver. A transmitter is a device or system that sends satellite signals in a satellite communication link, and a transmitter name is a text label or identifier used to uniquely identify the transmitter.

[0080] In specific implementations, the receiver name and transmitter name are obtained from the link metadata, and a unique identification information is assigned to each link consisting of a receiver and a transmitter. For example, in one embodiment, a unique string or numeric code generated based on the receiver name A, transmitter name B, link type, communication frequency, etc. is used as the identification information between links A and B.

[0081] (2) For each link, obtain the performance data of the link before and after the interference, and determine whether the link has performance degradation based on the performance data before and after the interference.

[0082] Specifically, for each link, performance data before and after interference is obtained (performance data may include signal power, signal-to-noise ratio, bit error rate). These data may be obtained through real-time simulation.

[0083] Furthermore, the performance data of each link before and after the interference is compared, and a predetermined threshold is used to determine whether the link has experienced performance degradation. For example, in one embodiment, performance degradation of link AB is determined when the signal power of link AB decreases by more than 30%. In another embodiment, performance degradation of link CD is determined when the bit error rate of link CD increases by 10%.

[0084] (3) When the link has performance degradation, the link is determined to be an interfered link, and the performance data of the link is saved as the final output result.

[0085] Specifically, when a link has performance degradation, it is called an interfered link. The performance degradation of the interfered link is caused by various electromagnetic interferences.

[0086] In specific implementation, for example, in one embodiment, when it is determined that the performance of link AB has degraded, link AB is determined as an interfered link, and its performance data (which may be data before and after interference) is saved as the final output result.

[0087] It is understandable that assigning a unique identification information to each link consisting of a specific receiver and transmitter not only facilitates the tracking and management of the link, but also facilitates subsequent data processing and result output. By comparing the link performance data before and after interference, the interfered links with degraded performance can be accurately identified, thereby effectively screening out the interfered communication links and providing accurate data support for subsequent interference analysis and link optimization.

[0088] Furthermore, in a possible implementation, the specific process of link performance simulation may further include:

[0089] (1) Based on the static network topology of the low-orbit satellite constellation, the original link performance data in the absence of interference is calculated.

[0090] Specifically, the orbital parameters of the low-orbit satellite constellation (such as orbital altitude, inclination, number of satellites, and inter-satellite links) can be obtained, and then the satellite position at a certain moment can be calculated based on orbital dynamics to establish a static network topology.

[0091] Furthermore, based on the static network topology, link performance data such as free space path loss, signal-to-noise ratio, and bit error rate can be calculated. For the sake of convenience, the low-orbit satellite constellation link performance data obtained through simulation without artificial electromagnetic interference is recorded as the original link performance data.

[0092] In the specific implementation, based on the static network topology of the low-orbit satellite constellation, a simulation model is used to calculate the original link performance data of each communication link in the absence of artificial electromagnetic interference.

[0093] (2) Generate an artificial interference signal in a simulation environment according to the artificial electromagnetic interference description model.

[0094] Specifically, the artificial interference signal is used to simulate the artificial electromagnetic interference that may be encountered in practice, so as to evaluate its impact on the performance of the communication link of the low-orbit satellite constellation.

[0095] In specific implementation, a simulated artificial interference signal is generated in a simulation environment according to the artificial electromagnetic interference description model.

[0096] (3) Based on the original link performance data and the interference signal, calculate the interference link performance data under the interference condition.

[0097] Specifically, the interference link performance data is the communication link performance data recalculated after adding an artificial interference signal in a simulation environment, which reflects the communication quality and reliability of the link in the presence of artificial electromagnetic interference.

[0098] In specific implementation, after adding artificial interference signals in the simulation environment, the performance data of each communication link is recalculated.

[0099] (4) Draw a spectrum diagram of the artificial interference signal and identify the interference type based on the spectrum diagram.

[0100] Specifically, the spectrum diagram of the artificial interference signal is used to show the power distribution of the signal at different frequencies, which can identify and analyze the frequency characteristics of the interference signal.

[0101] Furthermore, the type of the interference signal is identified based on the spectrum diagram and other features of the interference signal.

[0102] In specific implementation, the interference types may include noise amplitude modulation interference, noise frequency modulation interference, narrowband interference, broadband interference, etc.

[0103] (5) Establishing a correspondence between the interference type and the interference link performance data.

[0104] Specifically, based on the spectrum diagram and other characteristics of the artificial interference signal, the type of the interference signal is identified, and a correspondence is established between the identified interference type and the corresponding interference link performance data.

[0105] It can be understood that by calculating the original link performance data in the non-interference situation, a benchmark for the link in an ideal state is established. Furthermore, by combining the artificial electromagnetic interference description model, an artificial interference signal is generated in the simulation environment, making the interference scenario closer to the real environment, improving the reliability of the simulation results, and by comparing the original link performance data and the link performance data after interference, the impact of different interference signals on link performance can be quantitatively evaluated, providing a basis for anti-interference optimization. Furthermore, by drawing a spectrum diagram of the interference signal and identifying the interference type based on the spectrum characteristics, and establishing a corresponding relationship between the interference type and the interference link performance data, in summary, the above method can not only build a complete comparison system for non-interference and interfered link performance data, but also identify the interference type through spectrum analysis and establish a mapping relationship between interference characteristics and link performance impact. This method improves the quantitative evaluation capability of electromagnetic interference and provides a more targeted anti-interference optimization strategy for low-orbit satellite communication systems.

[0106] Optionally, in a possible implementation, the link performance simulation process may further include:

[0107] (1) Divide the simulation process into multiple time slices.

[0108] Specifically, time slices are used to more finely control the passage of time and state changes during the simulation process.

[0109] In specific implementation, the entire simulation process is divided into a series of time periods of equal length, and each time period is a time slice.

[0110] (2) In the current time slice, the network topology of the low-orbit satellite constellation is updated according to the satellite positions in the current time slice, and the network topology of the low-orbit satellite constellation in the next time slice is predicted.

[0111] In specific implementation, the relative positions and visibility conditions between satellites can be calculated to determine which satellites can establish communication links, and the network topology can be updated based on the established communication links.

[0112] Furthermore, after updating the network topology of the current time slice, the change of satellite position in the next time slice is predicted based on the motion law and orbital parameters of the satellite, and the network topology of the low-orbit satellite constellation in the next time slice is predicted accordingly.

[0113] (3) Calculate link performance data based on the updated network topology.

[0114] In specific implementation, based on the updated network topology, the communication link model is used to calculate the performance data of each link.

[0115] It can be understood that simulation updates are performed based on dynamic network topology and time slice division. As the satellite orbit changes, the simulated network topology can be adjusted in real time, ensuring the accurate calculation of link performance data in a dynamically changing environment and improving the timeliness and accuracy of the simulation results.

[0116] It should be noted that the method provided in this embodiment addresses the problem of inaccurate simulation caused by changes in local network topology due to link disconnection and re-establishment before and after the satellite's orbit intersects. Dynamic simulation of satellite network topology is achieved through time slice management, which can ensure the precise synchronization of topology changes during the simulation process and improve the timeliness and accuracy of the simulation results.

[0117] Optionally, to address the issue of unpredictable dynamic changes in satellite topology during loop simulation, the link performance simulation process of the method provided in this embodiment may further include:

[0118] (1) The control node selects a computing node as an access terminal and sends a track change instruction to the access terminal, instructing the access terminal to forward the track change instruction to the local control device after receiving the track change instruction.

[0119] Specifically, an access point is a computing node selected to receive orbit change commands and forward them to the local control device. The access point serves as a relay for this information. An orbit change command instructs a satellite to change its orbit. This command can include key parameters such as the time, direction, and speed of the change.

[0120] In a specific implementation, in one possible implementation method, a computing node with high computing power and stable connection can be selected as the access end.

[0121] (2) After receiving the orbit change instruction, the local control device finds the target satellite that needs to be adjusted according to the current orbital position of the satellite and the orbit change instruction, and adjusts the orbit parameters of the target satellite based on the orbit change information indicated by the orbit change instruction.

[0122] In specific implementation, the local control device is specifically used to calculate orbit adjustments, that is, to determine the target satellite and adjust the orbit parameters; among them, the orbit parameters are a set of numerical values ​​that describe the orbital state of the satellite, and the orbit parameters may include orbital altitude, inclination, eccentricity, etc.

[0123] It should be noted that the core of orbit adjustment is to solve the orbital dynamics equations to ensure that the orbital parameters after the orbit change meet the command requirements. The calculation method usually adopts the numerical integration of the Cauchy problem and uses the Runge-Kutta method or Cowell's formula to calculate the orbit propagation.

[0124] In specific implementations, when the orbit change instruction specifies a satellite to be moved, the specified satellite is directly used as the target satellite. If the orbit change instruction does not specify a target satellite, the real-time orbit data of each satellite can be obtained to calculate the orbit change cost of each satellite to the target orbit. Based on the orbit change costs of each satellite, the satellite with the lowest cost is selected as the target satellite.

[0125] Specifically, the orbit change instruction includes the target orbit parameters. When adjusting the orbit parameters of the target satellite, the Hohmann transfer or double-pulse orbit change strategy can be used to calculate the propulsion force required for the orbit change, and finally the orbit parameters are updated according to the calculation results.

[0126] (3) The local control device recalculates and updates the link performance data based on the adjusted orbit parameters, and sends the updated link performance data to the control node.

[0127] Specifically, after adjusting the satellite's orbital parameters, the local control device needs to recalculate the link performance data to reflect the communication quality between satellites under the new orbital state. After the calculation is completed, the updated data will be sent to the control node.

[0128] In specific implementation, the geometric relationship between the satellite and the ground station can be calculated, and link performance data such as signal path loss and communication delay can be calculated.

[0129] (4) The control node issues instructions to the computing nodes affected by the track change instruction based on the updated link performance data; the instructions include: reloading link performance data, pausing simulation, and continuing simulation.

[0130] It should be noted that after the orbit change, it is necessary to ensure that the simulation status of the computing node is synchronized with the latest orbit and link data, and the control node needs to issue instructions to allow the computing node to make corresponding adjustments.

[0131] Specifically, the control node needs to determine which compute nodes are dependent on the orbit-changing satellite and are affected by the orbit-changing instruction. Furthermore, it issues instructions to all affected compute nodes. Its core task is to identify the affected compute nodes and then issue appropriate instructions to ensure consistency across the simulation system.

[0132] In practice, when the orbital parameters of a satellite are updated, they will affect the computing nodes that rely on the satellite. The following are the main types of computing nodes affected and their screening methods:

[0133] (1) The directly affected computing nodes that directly process the orbit-changing satellite data are determined by querying the ground station / relay station mapping table;

[0134] (2) Affected link calculation nodes. Specifically, orbit change will affect the interstellar communication link, resulting in changes in link delay, adjustment of communication nodes, and changes in relay paths. At this time, the satellite link status before and after the orbit change can be obtained, the delay and throughput changes can be calculated, and the available communication links between satellites can be recalculated to determine whether the link routing needs to be adjusted.

[0135] Furthermore, the instructions issued include: reloading link performance data, pausing simulation, and continuing simulation, which are not limited in this embodiment. In specific implementation, a pause simulation instruction can be issued when the computing node receives new orbital parameters and link data to prevent the simulation from continuing when the data is updated. Or a reload link performance data instruction can be issued to instruct the computing node to load the newly calculated link data to ensure that the latest satellite orbit parameters and topology changes are taken into account during the simulation. Or a continue simulation instruction can be issued to instruct the computing node to restart the simulation process and continue to perform other operations (such as link optimization, path calculation, scheduling strategy, etc.).

[0136] It can be understood that the method provided in this embodiment addresses the unpredictability of satellite topology changes during loop simulation. Through the above operations, simulation data can be kept updated in real time during satellite orbit changes. This ensures the dynamic adaptability and real-time performance of the simulation process, and ensures that the simulation system can continue to operate stably under changing satellite topology and link conditions.

[0137] In other words, during satellite orbit changes, changes in satellite orbits can affect inter-satellite links and topology. Real-time updates to simulation data ensure the stability and accuracy of the simulation process. This ensures that the simulation system can respond quickly and maintain real-time performance when satellite topology changes occur, avoiding simulation errors or failures caused by data delays or inconsistencies. This approach ensures that the simulation system can automatically adjust and maintain efficient and stable simulation operations in complex dynamic environments, especially in highly dynamic scenarios such as satellite orbit changes.

[0138] S105: The control node receives and stores the simulation result, and transmits the simulation result to the local control device.

[0139] Specifically, the local control device can process and analyze the simulation results. The local control device can be an interface for interacting with the user, and the user can view and analyze the simulation results through the local control device.

[0140] In specific implementation, after receiving the simulation results, the control node will store them in the internal database or file system. After completing the storage of the simulation data, the control node can package the simulation results into a suitable data format and send them to the local control device through the network. Finally, the local control device will receive the simulation results from the control node and present them to the user so that the detailed information of the simulation results can be viewed through the interface of the local control device and the simulation experiment can be evaluated and analyzed.

[0141] It should be noted that the architecture design of the simulation system is aimed at achieving high-fidelity and real-time dynamic simulation of the communication link. It is divided into five layers from bottom to top, namely:

[0142] a) Physical layer

[0143] Provides physical equipment for the system and manages and maintains it, allowing the system to scale up or down by adding or reducing resources.

[0144] b) Device layer

[0145] Build software devices on top of the physical layer.

[0146] c) Data Layer

[0147] All data during the storage system operation (simulation scenarios, exported data, simulation scenario data, etc.) are stored in the database.

[0148] d) Service layer

[0149] The functions and interfaces of the data layer and the device layer are further encapsulated and divided into simulation scenario management service, simulation scenario management service and simulation process management service, which are responsible for simulation scenarios, creation and management of simulation scenarios and specific management of simulation processes respectively.

[0150] e) User Layer

[0151] The three services facing the service layer provide three user interfaces (simulation scenario management user interface, simulation scenario management user interface and simulation process management user interface), and control the system operation through different user interfaces.

[0152] In addition, its key technical implementations mainly include:

[0153] a) Diversified user interaction interface technologies

[0154] Diversified user interaction interface technology is one of the key technologies of simulation systems, mainly including three interaction methods: visual interaction, programmatic interaction, and API interface interaction.

[0155] (1) Visual interaction

[0156] Through the visual interface, the simulation scene can be controlled and analyzed, the simulation can be controlled, and the visual data can be updated at the same time.

[0157] ii. Programmatic Interaction

[0158] Directly integrate all functions of each service, manage simulation scenarios through simulation scenario management service, manage simulation scenarios through simulation scenario management service, manage simulation processes through simulation process management service, and display the data generated in the process in the form of direct printing or log records through the program.

[0159] iii.API interface interaction

[0160] Start a web service to receive various requests during the simulation process, including simulation scenarios, simulation scenarios, and simulation process management. You need to design an API request interface, interact through request lines and request bodies, and display operation results in the form of return bodies.

[0161] It is understandable that since the link performance of low-orbit satellites changes dynamically and rapidly, the distributed simulation system can obtain and update link performance data in real time to ensure that the simulation accuracy is adjusted in time with changes in actual conditions.

[0162] The communication link simulation method for low-orbit satellite constellations provided in this embodiment integrates multiple interference models, including the natural electromagnetic environment, intersatellite electromagnetic interference, and man-made electromagnetic interference. This provides unprecedented comprehensiveness and complexity for the simulation system. Compared to traditional low-orbit satellite communication simulation technologies that only consider individual interference factors individually and fail to fully reflect the complex interactions in real communication environments, this method organically combines these factors by constructing models describing the natural electromagnetic environment, intersatellite electromagnetic interference, and man-made electromagnetic interference. This allows for a better understanding and foreseeability of communication issues that may arise in low-orbit satellite constellations, thereby improving the accuracy and reliability of link performance simulation. Furthermore, this method utilizes a distributed simulation architecture consisting of local control devices, control nodes, and multiple computing nodes. This structure allows simulation tasks to be dynamically allocated based on task requirements and node capabilities, ensuring flexibility in the simulation process. Furthermore, as the scale of low-orbit satellite constellations expands and the complexity of simulation tasks increases, the simulation system can expand its simulation capabilities by adding computing nodes to accommodate simulation tasks of varying scale and complexity.

[0163] Figure 3 This is a flow chart of the second embodiment of the communication link simulation method for low-orbit satellite constellations provided by this application. Figure 3 , based on the above embodiment, the method further includes:

[0164] S301. After receiving a simulation information initialization command sent by a control node, the computing node obtains node information and link information from the control node.

[0165] Specifically, the simulation information initialization command is an instruction sent by the control node to the computing node, and is used to initialize the information and data required for the simulation process.

[0166] Furthermore, node information is used to describe the properties, status, and other information of each computing node in the simulation system. Node information is the basis for identifying and managing itself and interacting with other computing nodes.

[0167] Furthermore, the link information is used to describe information about the communication links between computing nodes in the simulation system. For example, in one embodiment, the link information may include the starting node, the ending node, and the link performance parameters.

[0168] In specific implementation, the computing node receives the simulation information initialization command from the control node. The initialization command marks the beginning of the simulation process and contains the basic information and data required for the simulation.

[0169] S302: The computing node traverses the link information and the node information, and determines whether the link start node name in the link information is consistent with the computing node name indicated by the node information.

[0170] Specifically, the computing node traverses the link information and the node information, compares the link start node name in the link information with the computing node name indicated in the node information to see if they are consistent, and ensures that the start node in the link information corresponds to the computing node.

[0171] S303: When the link start node name in the link information is consistent with the computing node name indicated by the node information, the computing node creates a folder and downloads the link performance data to the folder.

[0172] Specifically, link performance data is used to describe the performance of a communication link.

[0173] Furthermore, the specific data type included in the link performance data is determined according to actual needs and is not limited in this embodiment. In specific implementation, for example, in one embodiment, the link performance data includes signal strength, bit error rate, throughput, etc.

[0174] Furthermore, if the link start node name is the same as the computing node name, the computing node will create a folder and download the link performance data from the control node to the folder. This folder will serve as a temporary storage container for storing link performance data related to the current computing node.

[0175] S304: The computing node traverses the node information and loads the folder into each computing node indicated by the node information.

[0176] In the specific implementation, the computing node traverses the node information and loads the previously created folder containing the link performance data into each computing node indicated by the node information, ensuring that each relevant computing node can access the link performance data related to itself, providing support for subsequent calculation and simulation processes.

[0177] It's important to note that each compute node obtains relevant link information based on its role and matches it with the link's starting node name, ensuring that only link data relevant to that node is downloaded and processed. This ensures more accurate data synchronization and avoids synchronization errors caused by interference from irrelevant data between different compute nodes. Furthermore, each node processes only link performance data relevant to itself, reducing unnecessary communication delays and the risk of data inconsistencies. This allows for more coordinated data updates and sharing across nodes during the simulation process, thereby ensuring the temporal consistency and accuracy of the simulation results.

[0178] In summary, through efficient link information matching, data synchronization, and distributed processing mechanisms, the dynamic simulation of low-orbit satellite link performance is accurately synchronized between computing nodes, effectively reducing delays, data inconsistencies, and error accumulation during the simulation process, improving the synchronization and calculation accuracy of the entire simulation system, and ultimately helping to better simulate the performance of low-orbit satellite constellation links in actual environments.

[0179] Optionally, in a possible implementation, the method further includes:

[0180] (1) The control node monitors the status information of each computing node in real time.

[0181] Specifically, the status information is used to describe the current operating status of the computing node. For example, in one embodiment, the status information may include CPU usage, memory occupancy, disk I / O, network bandwidth, etc.

[0182] In specific implementation, the control node continuously collects status information from each computing node, including CPU usage, memory occupancy, etc., to understand their real-time operating status.

[0183] (2) The control node calculates the load score used to characterize the load situation based on the status information of each computing node.

[0184] Specifically, based on the collected status information, the control node calculates a load score for each computing node. The load score reflects the busyness of the node or the utilization of its processing capacity. A higher score indicates a heavier load.

[0185] In specific implementation, for example, in one embodiment, each type of status information can be normalized to obtain a normalized value, and then a comprehensive score is calculated based on the normalized value of each status information and the weight corresponding to each status information, and the comprehensive score is determined as the load score.

[0186] (3) For the highest computing node with the highest load score, when the task executed on the highest computing node is an interruptible task, the control node suspends the task executed on the highest computing node and transmits the computing status data of the task to the lowest computing node with the lowest load score, so as to instruct the lowest computing node to continue executing the task after successfully receiving the computing status data.

[0187] Specifically, the highest computing node is the node with the highest load score among all the computing nodes currently monitored. The highest computing node currently carries the most tasks or workloads; the lowest computing node is the node with the lowest load score among all the computing nodes currently monitored. The lowest computing node is currently relatively idle and capable of accepting and executing new tasks.

[0188] Furthermore, an interruptible task is a task that can be paused and resumed later. An interruptible task will not lose data or state due to a short interruption.

[0189] In specific implementation, if the task being executed on the highest computing node is an interruptible task, the control node will pause the task and transmit the computing status data of the suspended task to the lowest computing node with the lowest load score. After successfully receiving the computing status data, the lowest computing node will continue to execute the suspended task based on this data. In this way, the task can continue to run on the node with lower load, thereby achieving load balancing and resource optimization.

[0190] The method provided in this embodiment dynamically identifies the computing node with the highest load by monitoring the status information of the computing nodes in real time and calculating the load score. When an interruptible task is running on the node, the task is migrated to the node with the lowest load for continued execution. This can effectively optimize the system load and enable tasks to be dynamically migrated according to the node status, thereby improving the overall performance and response speed of the system.

[0191] Corresponding to the aforementioned embodiment of a communication link simulation method for a low-orbit satellite constellation, the present application also provides an embodiment of a simulation system. The simulation system provided by the present application is introduced below:

[0192] Please continue to refer to Figure 2 The simulation system provided in this embodiment includes a local control device, a control node, and multiple computing nodes; wherein:

[0193] Local control device, used to transmit the simulation scenario and the static network topology of the low-orbit satellite constellation to each computing node through the control node during the initialization phase;

[0194] The local control device is also used to generate simulation tasks according to task requirements during the simulation phase and send the simulation tasks to the control node;

[0195] The control node is used to determine the target computing node for executing the simulation task when receiving the simulation task, and send the simulation task to the target computing node;

[0196] The target computing node is configured to, upon receiving a simulation task, simulate link performance based on a pre-built natural electromagnetic environment description model, an inter-satellite electromagnetic interference description model, and an artificial electromagnetic interference description model, and report the simulation results to the control node; wherein the natural electromagnetic environment description model is used to describe the impact of precipitation rate, cloud water content, oxygen absorption coefficient, and water vapor absorption coefficient on link performance; the inter-satellite interference description model is used to simulate interference between satellites and evaluate the impact of inter-satellite interference on link performance; and the artificial electromagnetic interference description model is used to simulate electromagnetic interference generated by various artificial sources and evaluate the impact of such electromagnetic interference on link performance;

[0197] The control node is also used to receive and store simulation results, and transmit the simulation results to the local control device.

[0198] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A communication link simulation method for a low-orbit satellite constellation, characterized in that: The method is applied to a simulation system, which includes a local control device, a control node, and multiple computing nodes; the method includes: During the initialization phase, the local control device transmits the simulation scenario and the static network topology of the low-orbit satellite constellation to each computing node through the control node; During the simulation phase, the local control device generates simulation tasks according to task requirements and sends the simulation tasks to the control node; When receiving a simulation task, the control node determines the target computing node for executing the simulation task and sends the simulation task to the target computing node; Upon receiving a simulation task, the target computing node simulates link performance based on pre-built natural electromagnetic environment description models, inter-satellite electromagnetic interference description models, and man-made electromagnetic interference description models, and reports the simulation results to the control node. The natural electromagnetic environment description model is used to describe the impact of precipitation rate, cloud water content, oxygen absorption coefficient, and water vapor absorption coefficient on link performance. The inter-satellite interference description model is used to simulate interference between satellites and evaluate the impact of inter-satellite interference on link performance. The man-made electromagnetic interference description model is used to simulate electromagnetic interference generated by various man-made sources and evaluate the impact of such electromagnetic interference on link performance. The control node receives and stores the simulation results and transmits the simulation results to the local control device.

2. The method according to claim 1, characterized in that The link performance simulation is performed based on the pre-built natural electromagnetic environment description model, inter-satellite electromagnetic interference description model, and man-made electromagnetic interference description model, including: Extracting a receiver name and a transmitter name from input link data and assigning unique identification information to a link consisting of a receiver and a transmitter; For each link, obtain performance data of the link before and after the interference, and determine whether the link has performance degradation based on the performance data before and after the interference; When the performance of the link is degraded, the link is determined to be an interfered link, and the performance data of the link is saved as a final output result.

3. The method according to claim 1, characterized in that The link performance simulation based on the pre-built natural electromagnetic environment description model, inter-satellite electromagnetic interference description model and artificial electromagnetic interference description model further includes: Based on the static network topology of the low-orbit satellite constellation, the raw link performance data in the absence of interference is calculated; generating an artificial interference signal in a simulation environment according to the artificial electromagnetic interference description model; Calculate the interference link performance data under interference conditions based on the original link performance data and the interference signal; Drawing a spectrum diagram of the artificial interference signal, and identifying the interference type according to the spectrum diagram; A correspondence between the interference type and the interference link performance data is established.

4. The method according to claim 1, wherein The link performance simulation based on the pre-built natural electromagnetic environment description model, inter-satellite electromagnetic interference description model and artificial electromagnetic interference description model further includes: Divide the simulation process into multiple time slices; In the current time slice, the network topology of the low-orbit satellite constellation is updated according to the satellite positions in the current time slice, and the network topology of the low-orbit satellite constellation in the next time slice is predicted; Calculate link performance data based on the updated network topology.

5. The method according to claim 4, characterized in that The method further comprises: The control node selects a computing node as an access terminal and sends a trajectory change instruction to the access terminal, instructing the access terminal to forward the trajectory change instruction to the local control device after receiving the trajectory change instruction; After receiving the orbit change instruction, the local control device finds the target satellite that needs to be adjusted according to the current orbital position of the satellite and the orbit change instruction, and adjusts the orbit parameters of the target satellite based on the orbit change information indicated by the orbit change instruction; The local control device recalculates and updates the link performance data based on the adjusted orbit parameters, and sends the updated link performance data to the control node; The control node sends instructions to the computing nodes affected by the track change instruction based on the updated link performance data; the instructions include: reloading the link performance data, pausing the simulation, and continuing the simulation.

6. The method according to claim 1, wherein The method further comprises: After receiving the simulation information initialization command sent by the control node, the computing node obtains node information and link information from the control node; The computing node traverses the link information and the node information to determine whether the link start node name in the link information is consistent with the computing node name indicated by the node information; When the link start node name in the link information is consistent with the computing node name indicated by the node information, the computing node creates a folder and downloads the link performance data to the folder; The computing node traverses the node information and loads the folder into each computing node indicated by the node information.

7. The method according to claim 1, characterized in that Determining a target computing node for executing the simulation task includes: Obtaining status information of each computing node; wherein the status information includes CPU utilization, memory occupancy, network traffic and number of tasks; For each computing node, based on a preset reward function and the state information of the computing node, determining a reward value for the computing node to perform the simulation task; The target computing node is determined based on the reward value of each computing node executing the simulation task.

8. The method according to claim 1 or 7, characterized in that The method further comprises: The control node monitors the status information of each computing node in real time; The control node calculates a load score to represent the load situation based on the status information of each computing node; For the highest computing node with the highest load score, when the task executed by the control node on the highest computing node is an interruptible task, the control node suspends the task executed on the highest computing node and transmits the computing status data of the task to the lowest computing node with the lowest load score, so as to instruct the lowest computing node to continue executing the task after successfully receiving the computing status data.

9. The method according to claim 1, characterized in that The process of building a pre-built natural electromagnetic environment description model includes: Constructing rain attenuation models, cloud attenuation models, and atmospheric attenuation models; wherein the rain attenuation model is used to describe the effects of precipitation rate, frequency, and propagation path length on signal power loss; the cloud attenuation model is used to describe the effects of cloud water content, frequency, and propagation path length on signal power loss; and the atmospheric attenuation model is used to describe the effects of oxygen absorption coefficient, water vapor absorption coefficient, frequency, and propagation path length on signal power loss; The natural electromagnetic environment description model is constructed according to the rain attenuation model, the cloud and fog attenuation model, and the atmospheric attenuation model.

10. A simulation system, characterized in that: The simulation system includes a local control device, a control node and multiple computing nodes; wherein: Local control device, used to transmit the simulation scenario and the static network topology of the low-orbit satellite constellation to each computing node through the control node during the initialization phase; The local control device is also used to generate simulation tasks according to task requirements during the simulation phase and send the simulation tasks to the control node; The control node is used to determine the target computing node for executing the simulation task when receiving the simulation task, and send the simulation task to the target computing node; The target computing node is configured to, upon receiving a simulation task, simulate link performance based on a pre-built natural electromagnetic environment description model, an inter-satellite electromagnetic interference description model, and an artificial electromagnetic interference description model, and report the simulation results to the control node; wherein the natural electromagnetic environment description model is used to describe the impact of precipitation rate, cloud water content, oxygen absorption coefficient, and water vapor absorption coefficient on link performance; the inter-satellite interference description model is used to simulate interference between satellites and evaluate the impact of inter-satellite interference on link performance; and the artificial electromagnetic interference description model is used to simulate electromagnetic interference generated by various artificial sources and evaluate the impact of such electromagnetic interference on link performance; The control node is also used to receive and store simulation results, and transmit the simulation results to the local control device.

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