A method for throughput-sensitive mega-constellation communication performance degradation analysis

Abstract

The application discloses a throughput-sensitive giant constellation communication performance degradation analysis method, and aims at solving the technical problems that the current constellation throughput performance measurement method is based on a fixed constellation which has been designed, the influence on the throughput performance lacks evaluation, and the method for measuring the change of the throughput performance lacks the method.The technical scheme comprises the following steps: collecting double-line metadata of a to-be-tested constellation, presetting a specific time period and a step; obtaining all available links and corresponding satellite names under each step according to the double-line metadata of the to-be-tested constellation, the preset specific time period and the step; splicing the all available links in time periods, and deleting according to a preset standard; simulating the to-be-tested constellation according to the all available links after the deletion, and obtaining the average number of available links in the preset specific time period.The method is suitable for application in the sensitivity test of the throughput of the constellation.

Description

Background Technology

[0001] In existing technologies, the method for parsing constellation double-line metadata and implementing orbit recursion is as follows:

[0002] Read and recognize constellation two-line metadata in a common format;

[0003] The model is initialized based on the SGP4 orbital model and the actual variables read.

[0004] The orbital state is deduced based on the current moment.

[0005] The steps for dividing the routing communication domain and gateway for a constellation configuration are as follows:

[0006] The constellation configuration is determined based on the six orbital elements of the satellites that make up the constellation: sub-constellations are divided according to the semi-major axis and orbital inclination, orbital planes are divided according to the right ascension of the ascending node, and satellites within the orbital plane are numbered and sorted according to the perigee distance plus the mean perigee angle.

[0007] Satellites in the same orbital plane are divided into the same communication domain, and adjacent satellites (nodes) within the domain can communicate unconditionally.

[0008] Each orbital plane is connected to a gateway node, and the connectivity between the gateway nodes is constrained by factors such as relative distance, relative speed, and Earth's occlusion.

[0009] The steps for pathfinding based on the node path table are as follows:

[0010] Based on the above division, considering intra-domain connectivity, the connectivity between gateway nodes is calculated and a connectivity matrix is ​​generated. If there is no connectivity, the corresponding value is -1, and if there is connectivity, the corresponding value is the communication delay.

[0011] Use pathfinding algorithms such as Dijkstra's algorithm to find all paths from the source node to the target node;

[0012] Record the requested bandwidth and the remaining available bandwidth of the satellite node for each request, and store the routing results;

[0013] The pathfinding results are retrieved upon request and displayed visually in the software.

[0014] However, current methods for measuring constellation performance, such as throughput, are based on fixed constellations with a completed design, where the number, positional distribution, and relative phase relationships of satellites remain essentially constant. There is a lack of methods to evaluate the impact of dynamic processes such as increases or decreases in the number of satellites and constellation reconfigurations on throughput and other performance metrics. Furthermore, there is a lack of methods to measure the constellation's sensitivity to changes in the number of satellites that lead to changes in throughput and other performance metrics. Summary of the Invention

[0015] To address the technical problems existing in current technologies, such as the lack of evaluation methods for assessing the impact of dynamic processes like satellite number increases or decreases and constellation reconfiguration on throughput and other performance metrics, and the lack of methods for measuring changes in throughput and other performance metrics, the present invention provides the following technical solution:

[0016] A method for analyzing the performance degradation of the Giant Scorpius communication system, which is sensitive to throughput, includes:

[0017] The steps for collecting dual-line metadata of the constellation to be tested, and for setting specific time periods and step sizes;

[0018] Based on the dual-line metadata of the constellation to be tested, a preset specific time period and step size, the steps to obtain all available links and corresponding satellite names under each step size are obtained;

[0019] The steps include splicing all available links by time period and then reducing them according to preset standards;

[0020] The step of simulating the constellation under test based on all the reduced available links to obtain the average number of available links in the preset specific time period.

[0021] Furthermore, a preferred implementation is provided, which displays all available links and corresponding satellite names for each step size in a table.

[0022] Furthermore, a preferred embodiment is provided in which the table includes start and end connection times.

[0023] Furthermore, a preferred embodiment is provided in which all available links under each step size are arranged in order of start and end connection times in the table.

[0024] Furthermore, a preferred implementation is provided in which all available links are spliced ​​together by time periods, with the integer and fractional parts respectively.

[0025] Furthermore, a preferred embodiment is provided, which also includes the step of obtaining a reduction ratio of the average available links.

[0026] Based on the same inventive concept, this invention also provides a device for analyzing the degradation of throughput-sensitive Giant Scorpius communication performance, comprising:

[0027] A module for collecting dual-line metadata of the constellation to be tested, and for setting specific time periods and step sizes;

[0028] Based on the dual-line metadata of the constellation to be tested, a preset specific time period and step size are used to obtain a module containing all available links and corresponding satellite names under each step size;

[0029] The module that splices all available links into time periods and then reduces them according to preset standards;

[0030] Based on all the reduced available links, the constellation to be tested is simulated to obtain the module of the average number of available links in the preset specific time period.

[0031] Based on the same inventive concept, the present invention also provides a computer storage medium for storing a computing program, wherein when the computer reads the computer program, the computer executes the method described thereon.

[0032] Based on the same inventive concept, the present invention also provides a computer, including a processor and a storage medium, wherein when the processor reads a computer program stored in the storage medium, the computer executes the method described thereon.

[0033] Based on the same inventive concept, the present invention also provides a computer program product, which, when executed, implements the method described.

[0034] Compared with the prior art, the advantages of the technical solution provided by the present invention are as follows:

[0035] This invention provides a method for analyzing the performance degradation of the Giant Spherical constellation communication system based on throughput sensitivity. By dynamically statistically analyzing and adjusting inter-satellite connectivity and link throughput, it addresses the challenges of throughput sensitivity testing under dynamically changing constellations. Compared to traditional static constellation evaluation methods, this dynamic statistical and splicing approach more accurately reflects the changing trends in the number of links and throughput under constantly changing constellation configurations. The dynamic statistical component improves testing accuracy, making simulation results closer to the real satellite operating environment.

[0036] This invention provides a method for analyzing the performance degradation of the Giant Scorpius communication system, which is sensitive to throughput. Through time-segmentation stitching technology, this scheme can rationally allocate the time points for link reduction, making the throughput reduction process smoother and more uniform. This stitching method avoids the abrupt changes in the link adjustment process in traditional methods, reduces the uncertainty in simulation results, and improves the stability and predictability of the results.

[0037] This invention provides a method for analyzing the performance degradation of the Giant Scorpius constellation communication system, which is sensitive to throughput. Through adjustments to simulation results, the final test results more accurately reflect the actual throughput after a reduction in the number of links. Compared to static simulation methods in existing research, this adjusted simulation can better simulate the impact of dynamic changes on throughput, improving the accuracy and practicality of assessing the impact of constellation dynamics on system performance.

[0038] This invention provides a method for analyzing the degradation of communication performance in the Giants constellation based on throughput sensitivity, which is suitable for use in sensitivity testing of the constellation's throughput. Attached Figure Description

[0039] Figure 1 This is a flowchart of the statistical calculation process.

[0040] Figure 2 Flowchart for calculating the integer part.

[0041] Figure 3 This is a flowchart for calculating the decimal part.

[0042] Figure 4 This is a diagram showing the number of available links before processing.

[0043] Figure 5 This is a diagram showing the number of available links after processing. Detailed Implementation

[0044] To make the advantages and benefits of the technical solution provided by the present invention clearer, the technical solution provided by the present invention will now be described in further detail with reference to the accompanying drawings, specifically:

[0045] Implementation Method 1: This implementation method provides a performance degradation analysis method for throughput-sensitive Giant Scorpius communication, including:

[0046] The steps for collecting dual-line metadata of the constellation to be tested, and for setting specific time periods and step sizes;

[0047] Based on the dual-line metadata of the constellation to be tested, a preset specific time period and step size, the steps to obtain all available links and corresponding satellite names under each step size are obtained;

[0048] The steps include splicing all available links by time period and then reducing them according to preset standards;

[0049] The step of simulating the constellation under test based on all the reduced available links to obtain the average number of available links in the preset specific time period.

[0050] Specifically:

[0051] A throughput sensitivity testing method for dynamically changing constellations is presented. This method assesses the impact of dynamic constellation configuration changes on throughput over a specific time period by statistically analyzing inter-satellite connectivity and link throughput, and by splicing time periods. The overall process comprises three main steps: statistically analyzing available links, splicing time periods, and adjusting the number of links based on simulation results.

[0052] include:

[0053] Count available links

[0054] Step input: constellation two-line metadata, specific time period and step size.

[0055] Process: Within a specified time period, at each time step, count the number of all available links between the source node and the target node. By recording all available links between the source node and the target node and their corresponding satellite names at each time point, generate a table containing the start and end times of connection.

[0056] Step output: A table (Table1) containing the number of available links and the corresponding satellite names for each time step.

[0057] Time period splicing

[0058] Step input: Table1 generated in the previous step.

[0059] Procedure: Sort the records in Table 1 in ascending order by "End of Connection Time" and "Start of Connection Time". Based on the calculated number of links to be reduced, concatenate time periods for both the integer and decimal parts, and select appropriate time periods and links for deletion to ensure that the reduction in the number of links within a specific time period remains uniform.

[0060] Step output: The concatenated table Table2 contains the reduced link records.

[0061] Adjust the number of links and calculate the simulation results.

[0062] Step input: The concatenated table Table2.

[0063] Process: Based on the link records in Table 2, the constellation system is simulated to calculate the average number of available links within a specific time period after adjustment.

[0064] Step output: Simulation results, including the average number of available links before and after the adjustment and the percentage reduction.

[0065] Through statistical analysis, splicing, and adjustment processes, the sensitivity of dynamically changing constellation configurations to throughput is quantitatively analyzed. The steps are logically interconnected, with the output of each step serving as the input for the next, ensuring the accuracy and validity of the final simulation results.

[0066] Implementation Method 2: This implementation method further defines the throughput-sensitive Giants constellation communication performance degradation analysis method provided in Implementation Method 2. It displays all available links and corresponding satellite names for each step size in a table.

[0067] Implementation Method 3: This implementation method further defines the throughput-sensitive Giant Scorpius communication performance degradation analysis method provided in Implementation Method 3. The table includes the start and end connection times.

[0068] Implementation Method 4: This implementation method further defines the throughput-sensitive Giant Star communication performance degradation analysis method provided in Implementation Method 1. In the table, all available links under each step size are arranged in order of start and end connection times.

[0069] Implementation Method 5: This implementation method further defines the throughput-sensitive Giant Star communication performance degradation analysis method provided in Implementation Method 1, by splicing the integer and fractional parts of all available links into time periods.

[0070] Implementation Method Six: This implementation method further defines the throughput-sensitive Giant Star communication performance degradation analysis method provided in Implementation Method One, and also includes the step of obtaining the reduction ratio of the average available links.

[0071] Implementation Method Seven: This implementation method provides a device for analyzing the degradation of throughput-sensitive Giant Scorpius communication performance, including:

[0072] A module for collecting dual-line metadata of the constellation to be tested, and for setting specific time periods and step sizes;

[0073] Based on the dual-line metadata of the constellation to be tested, a preset specific time period and step size are used to obtain a module containing all available links and corresponding satellite names under each step size;

[0074] The module that splices all available links into time periods and then reduces them according to preset standards;

[0075] Based on all the reduced available links, the constellation to be tested is simulated to obtain the module of the average number of available links in the preset specific time period.

[0076] Implementation Method 8: This implementation method provides a computer storage medium for storing a computing program. When the computer reads the computer program, the computer executes the method provided in Implementation Method 1.

[0077] Implementation Method Nine: This implementation method provides a computer, including a processor and a storage medium. When the processor reads a computer program stored in the storage medium, the computer executes the method provided in Implementation Method One.

[0078] Implementation Method 10: This implementation method provides a computer program product. As a computer program, when the computer program is executed, it implements the method provided in Implementation Method 1.

[0079] Implementation Method Eleven: Combination Figure 1-5 This embodiment describes the technical solution provided above in further detail through specific examples. Specifically:

[0080] Step 1: Based on the format of the two-line metadata record, read the parameter values ​​under different data segments and save them to the SGP4 track model structure variables;

[0081] Step 2: Based on Step 1, initialize the orbital model according to the physical meaning of the SGP4 orbital model variables, and obtain the six orbital roots under the double-row metadata orbital epoch and the position and velocity under the J2000 coordinate system.

[0082] Step 3: Combine the simulation time and simulation step size to calculate the time difference between the simulation time and the orbit epoch, substitute it into the orbit model calculation function, and perform orbit recursion and data output.

[0083] Step 4: Divide the giant constellations into different sub-constellations based on their orbital inclination or semi-major axis.

[0084] Step 5: Based on Step 4, divide the constellations into different orbital planes according to the right ascension of the ascending node and the orbital inclination.

[0085] Step 6: Based on Step 5, determine the relative phase relationship of satellites in the orbital plane according to the latitudinal argument (the sum of perigee angular distance and true perigee angle), and sort them accordingly;

[0086] Step 7: Based on the orbital planes and sub-constellations divided in Step 6, set up a routing domain for satellites in each orbital plane, set gateway connectivity conditions, enable satellite nodes to communicate within the domain, and restrict the connectivity of nodes in different domains.

[0087] Step 8: Based on the communication domain and link request set in Step 7, update the connectivity between nodes and output the connectivity status and latency between nodes for reference in the sensitivity testing method.

[0088] Step 9: Based on the connectivity calculated in Step 8, perform pathfinding and output the pathfinding results.

[0089] By statistically analyzing and splicing the satellite connectivity of the source and destination nodes within a certain time period T, the number of available links between the source and destination nodes can be reduced, thereby weakening the communication throughput capacity.

[0090] (I) Statistics

[0091] For the step-by-step calculation method, the available link status between the two locations at a series of time points is obtained, including the number of all available links between the source and destination nodes and the corresponding satellite names (numbers) at each time point. The neighboring nodes connected to the source node within the time period can be obtained. Neighboring nodes are those directly connected to the source and destination nodes without indirect connection through other nodes. The start and end times of the activation of the source / destination node's neighboring nodes are obtained in chronological order. The specific execution process is as follows:

[0092] Create a new header Table1: Satellite Name (Number) Start Connection Time End Connection Time

[0093] Read the name (number) of the neighboring node satellite of the j-th link at time i;

[0094] If the table contains Name_j, find the Name_j row and increment the end connection time of that row by 1; if the table does not contain the Name_j row, add a new Name_j row, set the start connection time of that row to i, and set the end connection time of that row to i.

[0095] Continue until j reaches the number of available links at the current time, then proceed to the next time i+1; continue until i reaches the end time of time period T.

[0096] Flowchart as follows Figure 1 As shown.

[0097] (II) Time Segmentation

[0098] Considering that the reduction in the number of available links needs to be uniform within a specified time period T, the set of neighboring satellite nodes connected to the source / destination node within time period T is called S. This method selects different connectivity time periods corresponding to members in S according to certain rules to meet the requirement of uniform reduction time. The specific steps are as follows:

[0099] For the statistically obtained Table1, sort the elements in the table in ascending order by the "End of Connection Time" column, and then sort the elements in the table in ascending order by the "Start of Connection Time" column for easy splicing and use;

[0100] After obtaining the average number of available links Ca2 at location D within time period T after weight reduction, the average number of links that need to be reduced, Cc = Ca1 - Ca2, can be obtained, which is the number of time periods that need to be spliced. Generally, Cc is not an integer, so Cc needs to be decomposed into an integer part CcI and a fractional part CcF, Cc = CcI + CcF, and spliced ​​separately.

[0101] Generate Table2 with the same header as Table1, and set the current number of links reduced, Cn, to 0;

[0102] Integer part:

[0103]

[0104] Decimal part:

[0105]

[0106] Flowchart as follows Figure 2 and 3 As shown.

[0107] The average number of available links at discrete times is calculated using the following formula:

[0108]

[0109] In the formula, T b For the connection start time, T e For the connection termination time, δ step T is the step size for discrete operation. e -T b For δ step multiples of C i For T b +i*δ step The number of available links at any given time.

[0110] The advantages are:

[0111] 1. It can disregard object configuration, making it simple, universal, intuitive, and effective;

[0112] 2. The task requirements can be met by limiting the depth of deletion, thus reducing the impact on other links;

[0113] 3. Considering the impact of deleting satellite nodes on link connectivity throughout the entire time period, ensure that the link remains largely uninterrupted during the set time period.

[0114] The disadvantages are:

[0115] 1. Each node deletion requires a comprehensive view of the global impact of the deletion operation, and the process of deleting nodes cannot completely avoid the influence of the deletion order;

[0116] 2. If the step size is reduced or the time period is extended, the calculation time will increase proportionally;

[0117] 3. Furthermore, there is currently no evidence to prove that using this method can minimize the number of satellites deleted.

[0118] Combination Figure 4-5 Experimental examples are provided:

[0119] Import the two-line metadata of the STARLINK constellation as of September 18, 2023, totaling 4729 satellites.

[0120] To satisfy the requirements of adjacent connectivity for co-orbital links and position-velocity constraints for inter-orbital links, satellites within the same orbital plane are assigned to the same domain. Based on the current Walker configuration of the XL constellation, there are 194 orbital planes, which can be divided into 194 domains. The number of domains contained in each sub-constellation is shown in Table 1.

[0121] Table 1 XL Communication Domain Division

[0122] Sub-constellations Number of communication domains G-1 72 G-4 72 G-2 17 G-3 5 G-5 28

[0123] The simulation process uses the following simplified assumptions and inferences:

[0124] Simplified Assumption 1: All nodes are permitted to connect to nodes in other domains. Since the inter-orbit forwarding settings of the XL constellation are unknown, to obtain all theoretically available links, it is assumed that there is a possibility of establishing links between inter-orbit satellites; that is, a node within each domain may establish a link with a node in an adjacent different domain. Therefore, for any given node, it is assumed that it can act as a gateway and possesses the "permission" to connect to nodes outside its domain.

[0125] Considering that there is no need for a quantitative description of the bandwidth and throughput of the XL constellation during the link degradation simulation, but rather a qualitative requirement to reduce the throughput to 1 / 10 of its original value, the bandwidth settings for the XL constellation do not use the actual uplink and downlink bandwidth of the XL. In this link simulation calculation, the bandwidth of the XL satellites is uniformly set to 10Mb / s.

[0126] Simplifying Assumption 2: Consistent Node Bandwidth. We assume all nodes have the same bandwidth, and do not consider bandwidth differences between satellites.

[0127] Corollary 2-1: All available links between the source and destination nodes intersect only at the source and destination nodes; other nodes do not overlap. To achieve the maximum transmission rate, when a link is established, the transmission rate of each node on that link is equal to its bandwidth. Therefore, when other available links between the two locations are established simultaneously, the nodes on that link are unavailable due to full-rate transmission. Ultimately, this makes the available links independent of each other, presenting as a cluster of curves starting from the source node and ending at the destination node, with no intersections between them. For ease of description, the concept of "number of available links" will be used instead of "throughput" in the following description.

[0128] Corollary 2-2: The number of available links does not exceed the minimum number of available nodes in the source and destination nodes. Based on the above assumption, since no two available links intersect, it can be further deduced that the number of available links n must be less than the number of nodes n that can connect to the source node. source The number of nodes n that can be connected to the target node destination The minimum value is expressed as:

[0129] n≤min{n source ndestination}

[0130] Therefore, under this assumption, the number of available links is constrained by the number of available links at the source and destination.

[0131] The simulation conditions are shown in Table 2:

[0132] Table 2 Simulation Condition Details

[0133]

[0134] Under normal circumstances, the average number of available links remains between 20 and 22. By analyzing the connectivity of the connected region during this time period and calculating to retain 1 / 10 of the available links, 133 satellites were identified as needing removal. The results are shown below:

[0135] Table 3 Comparison of the number of available links before and after the cleanup.

[0136]

[0137] The above description of several specific embodiments further details the technical solution provided by the present invention in order to highlight the advantages and benefits of the technical solution provided by the present invention. However, the above-described specific embodiments are not intended to limit the present invention. Any reasonable modifications and improvements to the present invention, combinations of embodiments, and equivalent substitutions based on the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for analyzing the performance degradation of the Giant Scorpius communication system, characterized in that, include: The steps for collecting dual-line metadata of the constellation to be tested, and for setting specific time periods and step sizes; Based on the dual-row metadata of the constellation to be tested, a specific time period and step size are preset, and a table containing all available links and corresponding satellite names under each step size is obtained. The steps include splicing all available links by time period and then reducing them according to preset standards; Based on all the reduced available links, the constellation to be tested is simulated to obtain the average number of available links in the preset specific time period. The preset criteria for time segment splicing and deletion include: The records in the table containing all available links and corresponding satellite names under each step size are sorted in ascending order by "end connection time" and "start connection time". Based on the calculated number of links to be reduced, the number of links to be reduced is split into an integer part CcI and a fractional part CcF. The integer part and the fractional part are spliced ​​together in time periods to ensure that the reduction of the number of links in a specific time period is kept uniform. Appropriate time periods and links are selected for deletion. The average number of available links during the preset specific time period is calculated using the following formula: In the formula, The connection begins at time . The connection ends at the time of connection termination. The step size for discrete operation. for Integer multiples of, for The number of available links at any given time.

2. The method for analyzing the degradation of throughput-sensitive Giants constellation communication performance according to claim 1, characterized in that, The table displays all available links and their corresponding satellite names for each specified step size.

3. The method for analyzing the degradation of throughput-sensitive Giant Scorpius communication performance according to claim 2, characterized in that, The table contains the start and end times of the connection.

4. The method for analyzing the degradation of throughput-sensitive Giants Convergence communication performance according to claim 3, characterized in that, In the table, all available links under each step size are arranged in order of start and end connection times.

5. The method for analyzing the degradation of throughput-sensitive Giant Scorpius communication performance according to claim 1, characterized in that, It also includes the step of obtaining the reduction ratio of the average available links.

6. A device for analyzing the degradation performance of the Giant Scorpius communication system, which is sensitive to throughput, characterized in that, To implement the method of claim 1, the method comprises: A module for collecting dual-line metadata of the constellation to be tested, and for setting specific time periods and step sizes; Based on the dual-line metadata of the constellation to be tested, a preset specific time period and step size are used to obtain a module containing all available links and corresponding satellite names under each step size; The module that splices all available links into time periods and then reduces them according to preset standards; Based on all the reduced available links, the constellation to be tested is simulated to obtain the module of the average number of available links in the preset specific time period.

7. A computer storage medium for storing computer programs, characterized in that, When the computer reads the computer program, the computer executes the method of claim 1.

8. A computer, comprising a processor and a storage medium, characterized in that, When the processor reads the computer program stored in the storage medium, the computer executes the method of claim 1.

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