Large-scale satellite network beam-hopping resource scheduling method and system based on cluster collaboration

Abstract

This invention discloses a beam-hopping resource scheduling method for large-scale satellite networks based on constellation collaboration, primarily addressing the problems of severe interference between adjacent satellites and low system capacity in existing large-scale low-Earth orbit satellite constellations under multi-coverage scenarios. The implementation scheme includes: dividing multiple satellites into a collaborative constellation, which comprises a backbone satellite and multiple auxiliary satellites; determining the coverage area of ​​the satellites, and allocating beam positions and collecting service requirements; the backbone satellite collecting beam positions and service requirements from all satellites in the constellation, sorting them according to the size of the service requirements, and calculating the active beam time slot matrix; the backbone satellite transmitting the active beam time slot matrix to the auxiliary satellites, calculating their respective service rates to ground users, and calculating the system capacity based on their respective service rates to complete resource scheduling. This invention reduces response time, increases system capacity, and can be applied to satellite communication networks.

Description

Technical Field

[0001] This invention belongs to the field of satellite beam hopping technology, and in particular to large-scale satellite constellations. It relates to a method for scheduling beam hopping resources in large-scale satellite networks to meet the needs of ground users and improve the system capacity of satellite constellations. It can be used in satellite communication networks. Background Technology

[0002] Satellite communication networks, with their advantages of wide coverage, relatively low construction costs, and high flexibility, will play a crucial role in the upcoming 6G era. To achieve broadband transmission and seamless coverage, low-Earth orbit (LEO) satellite constellations need to implement a multi-coverage strategy. However, this process faces numerous challenges. Due to the uneven geographical distribution of ground users and the high mobility of LEO satellites, the service demand in satellite observation areas exhibits significant spatiotemporal heterogeneity; that is, service demand is high at certain times and locations, while it is relatively low at others. Simultaneously, to maximize spectrum resource utilization efficiency, future satellite communication systems are planned to adopt a combination of full-frequency reuse and beam hopping technology. While this technology can improve spectrum utilization, it also brings new problems: in multi-coverage scenarios, how to flexibly allocate satellite beam resources, match limited satellite resources with non-uniform service demand, and adopt effective technical means to design inter-satellite anti-interference strategies to reduce co-channel interference and improve overall throughput has become a major challenge for LEO satellite systems.

[0003] In their paper "Multi-Satellite Cooperative Beam-hopping Resource Allocation Based on Interference Awareness," Hu Jinlong, Liu Jihong, and others first analyzed the interference experienced by ground terminals from service satellites and other satellites in low-Earth orbit (LEO) multi-satellite cooperative coverage scenarios. They then optimized resource allocation among multiple satellites to reduce beam interference and improve system throughput. However, this scheme relies on the resource allocation scheme of the previous satellite for each satellite's beam-hopping allocation, resulting in a long response time that severely impacts algorithm efficiency and reduces solution quality. Therefore, it is not suitable for large-scale LEO satellite scenarios.

[0004] Patent application number 202310493021.0 discloses a method for low-Earth orbit (LEO) satellites to avoid interference. First, it obtains adaptive power allocation for a cell based on cell weight priorities. Next, considering intra-satellite interference, it obtains a beam-hopping pattern design for a single satellite. Finally, considering inter-satellite interference, it rearranges the time slot matrix to avoid intra- and inter-satellite interference, thereby improving system throughput. However, this method only considers intra- and inter-satellite interference between two LEO satellites. Therefore, for situations with multiple overlapping coverage and more complex interference, the optimization model it provides cannot reduce interference between multiple satellites, resulting in a decrease in system capacity. Summary of the Invention

[0005] This paper aims to address the shortcomings of the existing technologies mentioned above by proposing a beam-hopping resource scheduling method for low-Earth orbit satellite networks based on constellation collaboration. This method aims to shorten response time, improve solution quality, and meet the needs of scenarios with multiple overlapping satellites.

[0006] To achieve the above objectives, the technical solution of the present invention includes:

[0007] 1. A method for scheduling beam hopping resources in low-Earth orbit satellite networks based on constellation collaboration, comprising:

[0008] Determine the coordinating constellation and its coverage area, divide the satellites in the constellation into wave positions and determine the satellite parameters;

[0009] The service demand Q for ground wavebands is calculated, and backbone satellites and auxiliary satellites are determined based on the satellite's orbital trajectory.

[0010] All auxiliary satellites transmit the service demand Q and wave position information to the backbone satellites. The backbone satellites prioritize the services based on the size of the service demand, providing service to wave positions with high demand first, followed by those with low demand.

[0011] Determine the active beam slot matrix H, which is used for beam scheduling of the satellite in each slot;

[0012] The backbone satellite will transmit the activation beam time slot matrix to the auxiliary satellite, calculate the service rate to ground users for each satellite, and calculate the system capacity D based on the service rate of each satellite.

[0013] Furthermore, determining the coordinated constellation and its coverage area includes determining the backbone satellites and auxiliary satellites and their respective coverage areas. Each satellite locks its location in a specific region, and a circle is drawn with the region as the center and the coverage radius of each satellite as the length. The area enclosed by this circle is the coverage area of ​​the satellite.

[0014] Furthermore, the step of determining backbone satellites and auxiliary satellites based on the satellite's orbital trajectory involves identifying the satellite at the center of its orbit as the backbone satellite and the satellites surrounding the backbone satellite as auxiliary satellites.

[0015] Furthermore, determining the active beam slot matrix H includes the following:

[0016] 7a) Based on the number of active beams M and the hopping beam period T, create an M*T empty active beam time slot matrix H;

[0017] 7b) The backbone satellites find the inactive spectral slots with the greatest service demand in the first time slot and add them to the active time slot matrix H;

[0018] 7c) The backbone satellite locates the next inactive strobe position with the greatest service demand, calculates the distance between it and the strobe positions in the active time slot matrix H, and determines whether the distance between the strobe positions is greater than the beam isolation radius R:

[0019] If it is greater than that, then add the wave position to the active beam time slot matrix H;

[0020] Otherwise, continue searching until all wave positions have been traversed.

[0021] 7d) If there are unassigned beam positions, insert them into the active beam slot matrix H.

[0022] 2. A low-Earth orbit satellite network hopping beam resource scheduling system based on constellation coordination, comprising:

[0023] The collaborative partitioning module is used to determine collaborative constellations, coverage areas, and wave positions.

[0024] The business statistics module is used to determine the business requirements Q for ground wave positions;

[0025] The master-slave architecture module is used to determine the backbone satellites and auxiliary satellites;

[0026] The information transmission module is used for information transmission between backbone satellites and collaborative satellites;

[0027] The matrix calculation module is used to calculate the active beam time slot matrix H for backbone satellites;

[0028] The service rate module is used to calculate the service rate C for backbone and auxiliary satellites.

[0029] The effective service rate module is used to calculate the effective service rate V for backbone satellites and auxiliary satellites, which is the smaller value between the service demand and the service rate.

[0030] The capacity calculation module is used to calculate the system capacity D for backbone and auxiliary satellites. This involves adding the effective service rates of the backbone and auxiliary satellites.

[0031] Compared with the prior art, the present invention has the following advantages:

[0032] As satellite constellations grow increasingly larger, traditional beam-hopping resource allocation methods, due to their long response times, low execution efficiency, and failure to consider multi-satellite coverage scenarios, can no longer meet the high-capacity requirements of satellite communication systems. To address this issue, this invention proposes a beam-hopping resource scheduling method for low-Earth orbit satellite networks based on cooperative constellations. This method considers multi-satellite coverage scenarios, divides the constellation into cooperative constellations, and identifies backbone and auxiliary satellites. Through information exchange between backbone and auxiliary satellites, the backbone satellite is responsible for overall calculations, effectively shortening the response time for resource allocation and meeting the needs of multi-satellite overlapping scenarios. Simultaneously, the modularization of the scheduling system improves execution efficiency and effectively increases the capacity of the entire satellite communication system.

[0033] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific examples are given below, and detailed descriptions are provided in conjunction with the accompanying drawings. Attached Figure Description

[0034] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0035] Figure 1 This is a flowchart illustrating the implementation of an embodiment of the low-orbit satellite network beam hopping resource scheduling method of the present invention.

[0036] Figure 2 yes Figure 1 The sub-flowchart for determining the active beam slot matrix H;

[0037] Figure 3 This is a block diagram of an embodiment of the low-orbit satellite network hopping beam resource scheduling system of the present invention;

[0038] Figure 4 This is a simulation result diagram of the low-orbit satellite capacity according to an embodiment of the present invention. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some examples of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0040] Satellite communication networks, primarily constructed from low-Earth orbit (LEO) satellite constellations, offer advantages such as wide coverage, low construction costs, and high flexibility, holding an irreplaceable position in the 6G era. To provide broadband transmission and seamless coverage, LEO satellite constellations need to achieve multiple coverage layers. Furthermore, due to the uneven geographical distribution of ground users and the high mobility of LEO satellites, service demand within the observed area exhibits spatiotemporal unevenness. Simultaneously, to achieve efficient spectrum utilization, future LEO satellite communication systems will need to employ a combination of full-frequency reuse and beam hopping.

[0041] Example 1: A method for scheduling beam skipping resources in low-Earth orbit satellite networks based on constellation collaboration.

[0042] Reference Figure 1 The implementation steps of this example include the following:

[0043] Step 1: Determine the initial parameters and cooperative constellations.

[0044] In existing low-Earth orbit (LEO) satellite systems, due to the small size and wide coverage of terminals, they are more susceptible to interference from neighboring LEO satellites. Therefore, in multi-satellite coverage scenarios, it is necessary not only to consider the on-demand allocation of satellite beam resources but also to rationally design anti-interference mechanisms between satellites to improve the overall system capacity. The larger the constellation, the more severe the inter-satellite interference, and the more difficult it is to meet high-capacity requirements. To achieve global coverage, large-scale constellations are still required. Constellation configurations mainly include: number of orbits, number of satellites per orbit, orbital altitude, orbital inclination, and phase factor. Large-scale constellation configurations can be constructed by increasing the number of orbits and the number of satellites per orbit.

[0045] As an example, the constellation configuration selected in this invention is shown in Table 1, with 30 orbits, 60 satellites per orbit, an orbital altitude of 508, an orbital inclination of 53, and a phase factor of 0.

[0046] Table 1 Constellation Configuration

[0047] parameter low-orbit satellites Orbital altitude (km) 508 track inclination 53 Zodiac Attributes Inclined orbit constellation Number of orbits 30 Number of satellites per orbit 60 Phase factor 0

[0048] In real-world scenarios, constellation configurations are primarily determined by business requirements.

[0049] When calculating the capacity of a low-Earth orbit satellite system, the following satellite parameters are typically involved: number of spectral bits, number of active beams, isolation radius, operating frequency, power, bandwidth, and hopping beam period. As an example, the parameters selected in this invention are shown in Table 2: spectral bit 475, number of active beams 16, isolation radius 80, operating frequency 30, power 500, bandwidth 500, hopping beam period 32, noise level -174 dB, backbone satellite signal gain 100, and auxiliary satellite signal gain 90.

[0050] Table 2 Satellite Parameters

[0051] parameter low-orbit satellites wave position 475 Number of active beams 16 Isolation radius (km) 80 Operating frequency (GHz) 30 Power (W) 500 Bandwidth (MHz) 500 Beam skipping period 32 noise decibels -174 Backbone satellite signal gain -132.66 Auxiliary satellite signal gain -130.01

[0052] In some instances, a coordinated constellation is typically formed by grouping nine satellites together, including one backbone satellite and eight auxiliary satellites. Based on the coverage radius, a circle is drawn with the region where the satellite is located as the center and the coverage radius of each satellite as the length. The area enclosed by this circle is the coverage area of ​​the satellite.

[0053] Step 2: Divide wave positions and determine business requirements.

[0054] 2.1) Dividing wave positions:

[0055] The process of dividing satellites within a constellation into wave positions includes the latitude and longitude of the wave positions and the number of wave positions.

[0056] This step is based on the satellite parameters in Table 2. The wave position is set to 475. Based on the number of wave positions, the wave position is divided in a cellular format, i.e., a regular hexagon, with the center of the cellular cell as the latitude and longitude of the wave position.

[0057] 2.2) Determining Business Requirements:

[0058] Service requirements are generated by ground terminals. That is, satellites collect ground service requirements Q through wide-area beams, and the size of the service requirements is determined by the amount of ground service data collected.

[0059] The business requirements include: work emails, information retrieval, online chat, voice and video conferencing, and file upload and download.

[0060] Step 3: Information exchange between satellites.

[0061] 3.1) Determine the backbone satellites and auxiliary satellites:

[0062] Based on the satellite's orbital trajectory, the satellite located at the center of its orbit will be identified as the backbone satellite.

[0063] Satellites surrounding the backbone satellites are designated as auxiliary satellites;

[0064] Based on the classification of backbone satellites and auxiliary satellites, ground service requirements Q are divided into service requirements Q1 and service requirements Q2, which correspond to the results collected by backbone satellites and auxiliary satellites, respectively.

[0065] 3.2) Information exchange between backbone satellites and auxiliary satellites:

[0066] The auxiliary satellites transmit operational requirements and position information to the backbone satellites via inter-satellite links;

[0067] Backbone satellites sort the acquired positions, prioritizing positions with high service demand and serving positions with low service demand later.

[0068] Step 4: Calculate the active beam time slot matrix H.

[0069] Reference Figure 2 This step includes:

[0070] 4.1) The backbone satellite creates an M*T empty active beam time slot matrix H based on the two satellite parameters M and T in Table 2;

[0071] 4.2) The backbone satellite finds the inactive saturation point with the greatest service demand in the first time slot and adds it to the active beam time slot matrix H;

[0072] 4.3) The backbone satellite locates the next inactive saturation point with the greatest service demand and calculates the distance d between it and the saturation point in the active beam time slot matrix H using the distance formula between two points:

[0073]

[0074] Where x1 is the x-coordinate of wave position 1, y1 is the y-coordinate of wave position 1, x2 is the x-coordinate of wave position 2, and y2 is the y-coordinate of wave position 2.

[0075] 4.4) Determine if the distance d between beam positions is greater than the beam isolation radius R:

[0076] If it is greater than, and the number of selected beams does not exceed the upper limit of the number of beams, then add the beam position to the active time slot matrix H;

[0077] Otherwise, continue searching until all positions have been traversed. If there are still unassigned positions, insert them into the active beam slot matrix H to complete the calculation of the active beam slot matrix H.

[0078] Step 5: Calculate the satellite service rate.

[0079] 5.1) Based on the power W and signal gain Sat1 of the backbone satellite in Table 2, calculate the signal power S1 of the backbone satellite:

[0080] S1 = W * 10 Sat1 / 10 ;

[0081] 5.2) Based on the power W and signal gain Sat2 in Table 2, the auxiliary satellite calculates its signal power S2:

[0082] S2 = W * 10 Sat2 / 10 ;

[0083] 5.3) The backbone satellite and auxiliary satellite each calculate their Gaussian noise power N1 and N2 based on the channel bandwidth B and noise decibels J in Table 2:

[0084] N1=N2=N=(B*10 6 )*(10 J / 10 ) / 10 3 ;

[0085] 5.4) Based on the channel bandwidth B in Table 2, the backbone satellites and auxiliary satellites calculate their respective service rates C1 and C2 to ground users:

[0086] C1 = B log2(1 + S1 / N)

[0087] C2 = R log2(1 + S2 / N).

[0088] Step 6: Calculate the low-Earth orbit satellite capacity based on the service rate.

[0089] 6.1) Compare the service rates C1 and C2 of the backbone satellites and auxiliary satellites to ground users with their respective service demands Q1 and Q2, and take the minimum value between the two to obtain the effective service rates V1 and V2:

[0090] V1 = min(C1, Q1)

[0091] V2 = min(C2, Q2)

[0092] Where V1 is the effective service rate of backbone satellites, V2 is the effective service rate of auxiliary satellites, Q1 is the service requirements of backbone satellites, and Q2 is the service requirements of auxiliary satellites;

[0093] 6.2) Add the effective service rates of backbone satellites and serving satellites to obtain the low-Earth orbit satellite capacity D:

[0094] D = V1 + V2.

[0095] Example 2: Low-Earth Orbit Satellite Network Beam Hopping Resource Scheduling System Based on Cluster Coordination.

[0096] See Figure 3 This example includes: Collaborative Partitioning Module 1, Business Statistics Module 2, Master-Slave Architecture Module 3, Information Transmission Module 4, Matrix Calculation Module 5, Service Rate Module 6, Effective Service Rate Module 7, and Capacity Calculation Module 8. Among them:

[0097] The collaborative segmentation module 1 is used to determine the collaborative constellations, coverage areas, and wave positions, providing basic data for the subsequent business statistics module 2 and clarifying the scope of statistics.

[0098] The business statistics module 2 determines the service demand Q of the ground wave position based on the statistical scope of the collaborative division module 1, and provides service demand data for the effective service rate calculation module 7;

[0099] The master-slave architecture module 3 is used to determine the backbone satellites and auxiliary satellites, and provides the information transmission module 4 with the positions of the backbone satellites and auxiliary satellites;

[0100] Information transmission module 4, based on the positions of backbone satellites and auxiliary satellites provided by master-slave architecture module 3, enables information transmission between backbone satellites and cooperative satellites, ensuring timely and accurate information transmission between satellites, and providing data transmission services for matrix calculation module 5;

[0101] Matrix calculation module 5, based on the data transmission service provided by information transmission module 4, calculates the active beam time slot matrix H for backbone satellites, optimizes signal transmission and resource utilization, and provides the active beam time slot matrix H for service rate module 6;

[0102] Service rate module 6 calculates the service rate of backbone satellites and auxiliary satellites based on the active beam time slot matrix H provided by matrix calculation module 5, providing a quantitative basis for service availability and quality, and providing service rate data to the effective service rate module.

[0103] The effective service rate module 7 calculates the effective service rate of backbone satellites and auxiliary satellites based on the business demand data provided by the business statistics module 2 and the service rate provided by the service rate module 6, ensuring that the supply meets the actual demand and providing effective service rate data to the capacity calculation module 8.

[0104] The capacity calculation module 8, based on the effective service rate provided by the service rate module 7, calculates the system capacity of the backbone satellite and auxiliary satellite, evaluates the overall processing capacity of the system, and ensures that the system can meet the needs of all users.

[0105] These modules are interconnected and interdependent, forming a highly efficient and flexible satellite communication architecture. By optimizing and coordinating the work of each module, the system's performance and coverage can be significantly improved.

[0106] The effectiveness of this invention can be further illustrated by the following simulation results.

[0107] I. Simulation Conditions

[0108] The settings are as follows: number of orbits 30, number of satellites per orbit 60, orbital altitude 508, orbital inclination 53, phase factor 0, beam position 475, number of active beams 16, isolation radius 80, operating frequency 30, power 500, bandwidth 500, hopping beam period 32, noise level -174 dB, backbone satellite signal gain -132.66, and auxiliary satellite signal gain -130.01.

[0109] II. Simulation Content

[0110] Under the above simulation conditions, the low-Earth orbit satellite network hopping beam resources were scheduled using the present invention and three existing resource scheduling methods: service-oriented, random scheduling, and round-robin scheduling. The results are as follows: Figure 4 .

[0111] from Figure 4 As can be seen, the present invention has a higher system capacity than the three existing methods, with an average improvement of 30%. At the same time, it has a lower response time and higher execution efficiency, indicating that the present invention is more suitable for satellite communication networks in large-scale constellations.

[0112] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing examples, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

[0113] It should be noted that the step numbers in the specification and claims of this invention are only for the purpose of clearly describing the embodiments of this invention and facilitating understanding, and their order is not limited.

Claims

1. A method for scheduling beam hopping resources in large-scale satellite networks based on constellation collaboration, comprising: Determine the coordinating constellation and its coverage area, divide the satellites in the constellation into wave positions and determine the satellite parameters; The service demand Q for ground wavebands is calculated, and backbone satellites and auxiliary satellites are determined based on the satellite's orbital trajectory. All auxiliary satellites transmit the service demand Q and wave position information to the backbone satellites. The backbone satellites prioritize the services based on the size of the service demand, providing service to wave positions with high demand first, followed by those with low demand. Determine the active beam slot matrix H, which is used for beam scheduling of the satellite in each slot; The backbone satellite will transmit the activation beam time slot matrix H to the auxiliary satellite, calculate the service rate to ground users for each satellite, and calculate the system capacity D based on the service rate of each satellite.

2. The method according to claim 1, characterized in that: The determination of the coordinated constellation and its coverage area includes determining the backbone satellites and auxiliary satellites and their respective coverage areas. Each satellite locks its location in a specific region, and a circle is drawn with the region as the center and the coverage radius of each satellite as the length. The area enclosed by the circle is the coverage area of ​​the satellite.

3. The method according to claim 1, characterized in that: The process of dividing satellites in a constellation into wave positions includes the latitude and longitude of the wave positions and the number of wave positions. The satellite parameters include total satellite power W, operating frequency P, signal power S, channel bandwidth B, noise decibels J, backbone satellite signal gain Sat1, auxiliary satellite signal gain Sat2, Gaussian noise power N, number of active beams M, hopping beam period T, cooperating constellation V, number of beam positions X, and isolation radius R, where the isolation radius refers to the distance between two beams.

4. The method according to claim 1, characterized in that: The service demand Q for each ground position is generated by the ground terminal and then acquired by the satellite through wide-area beamforming.

5. The method according to claim 1, characterized in that: The process of determining backbone satellites and auxiliary satellites based on satellite orbits involves identifying satellites located at the center of their orbits as backbone satellites and satellites surrounding them as auxiliary satellites.

6. The method according to claim 1, characterized in that: The business requirements include work emails, document retrieval, online chat, voice and video conferencing, and file upload and download.

7. The method according to claim 1, characterized in that: The determination of the active beam time slot matrix H is implemented as follows: 7a) Based on the number of active beams M and the hopping beam period T, create an M*T empty active beam time slot matrix H; 7b) The backbone satellites find the inactive spectral slots with the greatest service demand in the first time slot and add them to the active time slot matrix H; 7c) The backbone satellite locates the next inactive strobe position with the greatest service demand, calculates the distance between it and the strobe positions in the active time slot matrix H, and determines whether the distance between the strobe positions is greater than the beam isolation radius R: If the value is greater than the limit, and the number of selected beams does not exceed the upper limit of the number of beams, then add the beam position to the active beam time slot matrix H. Otherwise, continue searching until all wave positions have been traversed; 7d) If there are unassigned beam positions, insert them into the active beam slot matrix H.

8. The method according to claim 1, characterized in that: The backbone satellites and auxiliary satellites calculate their respective service rates to ground users, including the following: 8a) Backbone and auxiliary satellites calculate their respective signal power to ground users: S1=W*10 Sat1 / 10 S2=W*10 Sat2 / 10 Where S1 is the signal power of the backbone satellite, S2 is the signal power of the auxiliary satellite, W is the power, Sat1 is the signal gain of the backbone satellite, and Sat2 is the signal gain of the auxiliary satellite. 8b) The backbone satellites and auxiliary satellites calculate their respective noise power to ground users: N1=N2=N=(B*10 6 )*(10 J / 10 ) / 10 3 Where B is the channel bandwidth, J is the noise decibel, N1 is the backbone satellite noise power, N2 is the auxiliary satellite noise power, N1 and N2 are equal and are uniformly represented by N; 8c) Backbone and auxiliary satellites calculate their respective service rates to ground users based on the results of 8a) and 8b): C1 = Blog2(1 + S1 / N) C2 = Blog2(1 + S2 / N) Wherein, C1 is the backbone satellite service rate, and C2 is the auxiliary satellite service rate.

9. The method according to claim 1, characterized in that: The backbone satellites and auxiliary satellites calculate the system capacity D based on their respective service rates, including: Each service rate to ground users is compared with their business needs, and the smaller values ​​V1 and V2 of the two are taken: V1 = min(C1, Q1) V2 = min(C2, Q2) Wherein, V1 is the effective service rate of backbone satellites, V2 is the effective service rate of auxiliary satellites, C1 is the service rate of backbone satellites, C2 is the service rate of auxiliary satellites, Q1 is the service requirement of backbone satellites, and Q2 is the service requirement of auxiliary satellites. Then, add the effective service rates of the backbone satellites and the service satellites to obtain the system capacity D: D = V1 + V2.

10. A low-Earth orbit satellite network hopping beam resource scheduling system based on constellation coordination, comprising: The collaborative partitioning module is used to determine collaborative constellations, coverage areas, and wave positions. The business statistics module is used to determine the business requirements Q for ground wave positions; The master-slave architecture module is used to determine the backbone satellites and auxiliary satellites; The information transmission module is used for information transmission between backbone satellites and collaborative satellites; The matrix calculation module is used to calculate the active beam time slot matrix H for backbone satellites; The service rate module is used to calculate the service rate C for backbone and auxiliary satellites. The effective service rate module is used to calculate the effective service rate V for backbone satellites and auxiliary satellites, which is the smaller value between the service demand and the service rate. The capacity calculation module is used to calculate the system capacity D for backbone satellites and auxiliary satellites, which is to add the effective service rates of backbone satellites and auxiliary satellites.

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