Communication resource scheduling method, device, equipment and system of low-orbit satellite and medium

Abstract

The invention provides a communication resource scheduling method, device, equipment and system of a low earth orbit satellite and a medium, and relates to the technical field of low earth orbit satellite resource scheduling, and the method comprises the steps: generating a service information table according to an access request; wherein the access request is a request which is sent by the service terminal to communication resource scheduling equipment of a low earth orbit satellite and contains a service demand; acquiring resource state parameters of the low earth orbit satellite; generating a resource scheduling scheme according to the service information table, the resource state parameters and the multi-objective optimization model; wherein the multi-objective optimization model is a model for solving a resource scheduling scheme by adopting an improved particle swarm optimization algorithm; and performing communication resource dynamic scheduling on the low-orbit satellite based on the resource scheduling scheme to obtain a resource scheduling execution result. According to the technical scheme, communication resource dynamic scheduling is carried out on the low-orbit satellite based on the resource scheduling scheme, the resource scheduling execution result is obtained, dynamic collaborative allocation of resources is achieved, the resource utilization rate is increased, and high-priority service time delay is reduced.

Description

Technical Field

[0001] This invention relates to the field of low-Earth orbit satellite resource scheduling technology, and in particular to a method, apparatus, equipment, system and medium for scheduling communication resources of low-Earth orbit satellites. Background Technology

[0002] Low Earth Orbit (LEO) satellites, due to their advantages such as low orbital altitude, low transmission latency, and low link loss, have become an important component of global communication networks, widely used in scenarios such as emergency communication, IoT data backhaul, and broadband access in remote areas. As the scale of LEO satellite constellations expands and service types become increasingly diversified, encompassing high-definition video transmission, real-time monitoring data interaction, and emergency command signals, the demands on communication resources vary significantly across different services, greatly increasing the requirements for the dynamic and coordinated nature of resource scheduling.

[0003] Currently, in existing technologies, the scheduling of low-Earth orbit satellite communication resources mostly adopts a static allocation mode, mainly single-satellite autonomous scheduling. That is, each satellite allocates its own resources according to preset rules, such as allocating fixed bandwidth to different areas. In single-satellite autonomous scheduling, satellites allocate resources based on a preset service priority table. When resources are insufficient, low-priority services are directly rejected. Such single-satellite autonomous scheduling has the problem of low resource utilization, and static allocation cannot adapt to dynamic changes in services. For example, if there are sudden changes in service demand, resource scheduling cannot be carried out in a timely manner, resulting in resource scheduling failure and failing to meet real-time requirements.

[0004] Therefore, there is an urgent need for a method for scheduling communication resources for low-orbit satellites to achieve dynamic resource allocation and improve resource utilization. Summary of the Invention

[0005] This invention provides a method, apparatus, device, system, and medium for scheduling communication resources for low-Earth orbit (LEO) satellites. It addresses the shortcomings of existing single-satellite autonomous scheduling technologies, which allocate resources based on a preset service priority table. When resources are insufficient, low-priority services are directly rejected. This results in low resource utilization and static allocation that cannot adapt to dynamic changes in services. For example, sudden changes in service demands can prevent timely resource scheduling, leading to scheduling failures and failing to meet real-time requirements. The invention generates a resource scheduling scheme based on a service information table, resource status parameters, and a multi-objective optimization model. Based on this scheme, it dynamically schedules communication resources for LEO satellites, obtaining the scheduling execution results. This achieves dynamic and collaborative resource allocation, improves resource utilization, reduces latency for high-priority services, and enhances the system's anti-interference capabilities.

[0006] This invention provides a communication resource scheduling method for low-Earth orbit satellites, applicable to communication resource scheduling equipment for low-Earth orbit satellites, comprising the following steps.

[0007] A service information table is generated based on the access request; wherein, the access request is a request containing service requirements sent by the service terminal to the communication resource scheduling equipment of the low-Earth orbit satellite. Collect resource status parameters of low-Earth orbit satellites; A resource scheduling scheme is generated based on the business information table, resource status parameters, and a multi-objective optimization model; the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme. Based on the resource scheduling scheme, the communication resources of low-orbit satellites are dynamically scheduled, and the resource scheduling execution results are obtained.

[0008] According to the present invention, a method for scheduling communication resources of a low-Earth orbit (LEO) satellite includes resource status parameters such as channel occupancy rate, remaining bandwidth, and transmit power margin of the LEO satellite. The method involves collecting LEO satellite resource status parameters, including: collecting LEO satellite resource data; wherein the resource data includes channel usage duration, total channel usage duration, total LEO satellite bandwidth, allocated LEO satellite bandwidth, maximum LEO satellite transmit power, and current LEO satellite transmit power; and determining the LEO satellite resource status parameters based on the resource data. Specifically, the channel occupancy rate is the ratio of channel usage duration to total channel usage duration; the remaining bandwidth is the difference between the total LEO satellite bandwidth and the allocated LEO satellite bandwidth; and the transmit power margin is the difference between the maximum LEO satellite transmit power and the current LEO satellite transmit power.

[0009] According to the present invention, a communication resource scheduling method for low-Earth orbit satellites includes a service information table comprising service signal characteristics, service signal types, and service signal priorities.

[0010] According to the communication resource scheduling method for low-Earth orbit satellites provided by the present invention, after dynamically scheduling communication resources of low-Earth orbit satellites based on a resource scheduling scheme and obtaining the resource scheduling execution result, the method further includes: obtaining service transmission delay data based on the resource scheduling execution result; if the service transmission delay data is greater than a delay threshold, continuing to return to the step of generating a resource scheduling scheme based on a service information table, resource status parameters, and a multi-objective optimization model; if the service transmission delay data is less than or equal to the delay threshold, updating the model parameters of the multi-objective optimization model according to a preset period, and continuing to return to the step of generating a resource scheduling scheme based on a service information table, resource status parameters, and a multi-objective optimization model based on the updated model parameters.

[0011] The present invention also provides a communication resource scheduling device for low-Earth orbit satellites, which is applied to the communication resource scheduling equipment for low-Earth orbit satellites and includes the following modules: The information table generation module is used to generate a service information table based on the access request; wherein, the access request is a request containing service requirements sent by the service terminal to the communication resource scheduling equipment of the low-orbit satellite. The status parameter acquisition module is used to collect resource status parameters of low-orbit satellites; The scheduling scheme generation module is used to generate resource scheduling schemes based on the business information table, resource status parameters, and a multi-objective optimization model; wherein, the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme. The communication resource scheduling module is used to dynamically schedule communication resources for low-orbit satellites based on the resource scheduling scheme and obtain the resource scheduling execution results.

[0012] The present invention also provides a communication resource scheduling device for low-Earth orbit satellites, including a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that the processor executes the computer program to implement any of the communication resource scheduling methods for low-Earth orbit satellites described above.

[0013] The present invention also provides a communication resource scheduling system for low-Earth orbit satellites, including a service terminal, low-Earth orbit satellites, and communication resource scheduling equipment for low-Earth orbit satellites.

[0014] This invention also provides a communication resource scheduling system for low-Earth orbit (LEO) satellites. The LEO satellite communication resource scheduling equipment includes a service awareness module, a resource status monitoring module, a collaborative decision-making module, a resource allocation execution module, and a feedback optimization module. The service awareness module interacts with the resource status monitoring module, the collaborative decision-making module, and the feedback optimization module via an on-board bus and inter-satellite links. The collaborative decision-making module also interacts with the resource allocation execution module and the feedback optimization module via an on-board bus and inter-satellite links. The service awareness module is used to receive access requests sent by service terminals and generate a service information table based on the access requests. The resource status monitoring module is used to collect resource status parameters of low-orbit satellites; The collaborative decision-making module is used to generate resource scheduling schemes based on business information tables, resource status parameters, and multi-objective optimization models. The multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme. The resource allocation execution module is used to dynamically schedule communication resources for low-Earth orbit satellites based on the resource scheduling scheme and obtain the resource scheduling execution results. The feedback optimization module is used to obtain service transmission latency data based on the resource scheduling execution results; The collaborative decision-making module is also used to generate a resource scheduling scheme based on the business information table, resource status parameters, and multi-objective optimization model when the service transmission latency data is greater than the latency threshold. The feedback optimization module is also used to update the model parameters of the multi-objective optimization model according to a preset period when the service transmission latency data is less than or equal to the latency threshold. The collaborative decision-making module is also used to generate a resource scheduling scheme based on the updated multi-objective optimization model obtained from the updated model parameters, the business information table, and the resource status parameters.

[0015] The present invention also provides a communication resource scheduling system for low-Earth orbit satellites, wherein a service awareness module is deployed in the communication payload unit of the low-Earth orbit satellite, and the service awareness module includes a signal sensing sensor and a signal sensing processor. Signal sensing sensors are used to collect service signal frequency, service signal modulation method, and service signal bandwidth characteristics based on access requests; The signal sensing processor is used to identify the frequency, modulation method, and bandwidth characteristics of the acquired service signals and generate a service information table. The service information table includes service signal characteristics, service signal type, and service signal priority. The resource status monitoring module is deployed in the communication payload unit of the low-Earth orbit satellite. The resource status monitoring module includes resource monitoring sensors and a data compression processor. Resource monitoring sensors are used to collect resource data of low-Earth orbit satellites at a preset frequency. The resource data includes channel usage duration, total channel usage duration, total bandwidth of low-Earth orbit satellites, allocated bandwidth of low-Earth orbit satellites, maximum transmit power of low-Earth orbit satellites, and current transmit power of low-Earth orbit satellites. The data compression processor is used to determine resource status parameters based on resource data, including the channel occupancy rate, remaining bandwidth, and transmit power margin of the low-Earth orbit satellite. The channel occupancy rate is the ratio of the channel usage time to the total channel usage time. The remaining bandwidth is the difference between the total bandwidth of the low-Earth orbit satellite and the bandwidth already allocated to the low-Earth orbit satellite. The transmit power margin is the difference between the maximum transmit power of the low-Earth orbit satellite and the current transmit power of the low-Earth orbit satellite. The collaborative decision-making module includes the onboard computer of the primary low-Earth orbit satellite and the ground backup server; The onboard computer and ground backup server are used to build a multi-objective optimization model that uses an improved particle swarm optimization algorithm to solve resource scheduling schemes, and generate resource scheduling schemes based on the business information table, resource status parameters and the multi-objective optimization model. The resource allocation execution module includes a resource allocation controller and a resource allocation executor; The resource allocation controller is used to parse the resource scheduling scheme and obtain resource scheduling information; The resource allocation executor is used to dynamically schedule communication resources for low-Earth orbit satellites based on resource scheduling information and obtain the resource scheduling execution results. The feedback optimization module includes a feedback data acquisition unit and a parameter adjustment unit; Feedback data collectors are used to obtain service transmission latency data based on resource scheduling execution results; The parameter adjustment unit is used to update the model parameters of the multi-objective optimization model according to a preset period when the service transmission delay data is less than or equal to the delay threshold. The collaborative decision-making module is also used to generate a resource scheduling scheme based on the updated multi-objective optimization model obtained from the updated model parameters, the business information table, and the resource status parameters.

[0016] The present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a communication resource scheduling method for any of the low-orbit satellites described above.

[0017] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements a communication resource scheduling method for any of the low-orbit satellites described above.

[0018] This invention provides a method, apparatus, device, system, and medium for scheduling communication resources for low-Earth orbit (LEO) satellites. Applied to LEO satellite communication resource scheduling equipment, it generates a service information table based on access requests; wherein the access request is a request containing service requirements sent by a service terminal to the LEO satellite communication resource scheduling equipment; it collects resource status parameters of the LEO satellite; it generates a resource scheduling scheme based on the service information table, resource status parameters, and a multi-objective optimization model; wherein the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme; and it dynamically schedules communication resources for the LEO satellite based on the resource scheduling scheme to obtain the resource scheduling execution result. The technical solution of this invention addresses the problem in existing single-satellite autonomous scheduling where satellites allocate resources based on a preset service priority table. When resources are insufficient, low-priority services are directly rejected. This single-satellite autonomous scheduling suffers from low resource utilization and static allocation cannot adapt to dynamic changes in services. For example, if sudden service demands prevent timely resource scheduling, resource scheduling failures occur, failing to meet real-time requirements. The invention generates a resource scheduling scheme based on a service information table, resource status parameters, and a multi-objective optimization model. Based on this scheme, communication resources for low-Earth orbit satellites are dynamically scheduled to obtain the resource scheduling execution results. This achieves dynamic and collaborative resource allocation, improves resource utilization, reduces latency for high-priority services, and enhances the system's anti-interference capability. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is one of the flowcharts illustrating the communication resource scheduling method for low-orbit satellites provided by this invention.

[0021] Figure 2 This is the second flowchart illustrating the communication resource scheduling method for low-orbit satellites provided by this invention.

[0022] Figure 3 This is a schematic diagram of the communication resource scheduling device for low-orbit satellites provided by the present invention.

[0023] Figure 4 This is a schematic diagram of the communication resource scheduling device for low-orbit satellites provided by the present invention.

[0024] Figure 5 This is one of the structural schematic diagrams of the communication resource scheduling system for low-orbit satellites provided by the present invention.

[0025] Figure 6 This is the second schematic diagram of the communication resource scheduling system for low-orbit satellites provided by the present invention.

[0026] Figure label: 0: Communication resource scheduling system for low-Earth orbit satellites; 1: Service terminal; 2: Low-Earth orbit satellite; 3: Communication resource scheduling equipment for low-Earth orbit satellites; 31: Service sensing module; 32: Resource status monitoring module; 33: Collaborative decision-making module; 34: Resource allocation execution module; 35: Feedback optimization module; 311: Signal sensing sensor; 312: Signal sensing processor; 321: Resource status monitoring module; 322: Data compression processor; 331: Onboard computer; 332: Ground backup server; 341: Resource allocation controller; 342: Resource allocation executor; 351: Feedback data acquisition unit; 352: Parameter adjustment unit. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0028] The following is combined with Figure 1 The present invention describes a method for scheduling communication resources for low-Earth orbit (LEO) satellites. This method is applicable to LEO satellite communication resource scheduling situations. The execution subject of this method can be an electronic device, such as a LEO satellite communication resource scheduling device or a LEO satellite communication resource scheduling apparatus installed in the electronic device. The LEO satellite communication resource scheduling apparatus can be implemented by software, hardware, or a combination of both. Figure 1 This is one of the flowcharts illustrating the communication resource scheduling method for low-Earth orbit satellites provided by the present invention, such as... Figure 1 As shown, the method includes the following steps: 101, 102, 103 and 104.

[0029] Step 101: Generate a business information table based on the access request.

[0030] The access request is a request sent by the service terminal to the communication resource scheduling equipment of the low-orbit satellite, which includes the service requirements. The service requirements are a general description of the service type. The access request also includes basic information such as the terminal identifier of the service terminal. This embodiment does not limit this.

[0031] In this step, the service information table includes service signal characteristics, service signal type, and service signal priority.

[0032] Specifically, when a service terminal sends an access request containing a general description of the service type and a terminal identifier to the communication resource scheduling equipment of a low-Earth orbit satellite, the communication resource scheduling equipment of the low-Earth orbit satellite combines the general description of the service type, the terminal identifier, and the service signal characteristics collected by the communication resource scheduling equipment of the low-Earth orbit satellite to identify the service signal type, and dynamically determines the service signal priority through fuzzy hierarchical analysis, thereby generating a service information table, which includes service signal characteristics, service signal type, and service signal priority.

[0033] In one specific implementation, the service information table may also include the identity document (ID) of the service signal and the bandwidth requirements of the service signal; however, this embodiment does not limit this.

[0034] The advantages of this setup are that it generates a service information table, adds reliability requirements and transmission burstiness indicators to the service, and comprehensively considers these new indicators when calculating service signal priorities. Furthermore, it uses fuzzy hierarchical analysis to dynamically adjust service signal priorities, allowing for flexible updates based on service characteristics, overcoming the limitations of static priority rules, and ensuring that bursty high-priority services can quickly acquire resources.

[0035] Step 102: Collect resource status parameters of low-orbit satellites.

[0036] In this step, the resource status parameters include the channel occupancy rate, remaining bandwidth, and transmit power margin of the low-Earth orbit satellite; the resource status parameters also include the ID of the low-Earth orbit satellite, the remaining battery power, etc., which are not limited in this embodiment.

[0037] Specifically, the communication resource scheduling equipment of the low-Earth orbit satellite collects resource data, compresses the resource data, generates resource status parameters, and synchronizes the resource status parameters to the main low-Earth orbit satellite through an encrypted inter-satellite link. The main low-Earth orbit satellite then decrypts the resource status parameters.

[0038] In one specific embodiment, collecting resource status parameters of a low-Earth orbit (LEO) satellite includes: collecting resource data of the LEO satellite; wherein the resource data includes channel usage duration, total channel usage duration, total LEO satellite bandwidth, allocated LEO satellite bandwidth, maximum LEO satellite transmit power, and current LEO satellite transmit power; determining resource status parameters of the LEO satellite based on the resource data; wherein the channel occupancy rate in the resource status parameters is the ratio of channel usage duration to total channel usage duration, the remaining bandwidth in the resource status parameters is the difference between the total LEO satellite bandwidth and the allocated LEO satellite bandwidth, and the transmit power margin in the resource status parameters is the difference between the maximum LEO satellite transmit power and the current LEO satellite transmit power.

[0039] In this step, the resource data includes channel usage duration, total channel usage duration, total bandwidth of LEO satellites, allocated bandwidth of LEO satellites, maximum transmit power of LEO satellites, and current transmit power of LEO satellites.

[0040] Specifically, resource data for low-Earth orbit (LEO) satellites is collected. This data includes channel usage duration, total channel usage duration, total LEO satellite bandwidth, allocated LEO satellite bandwidth, maximum LEO satellite transmit power, and current LEO satellite transmit power. Based on this data, resource status parameters for LEO satellites are determined. Specifically, the channel occupancy rate is determined by the ratio of channel usage duration to total channel usage duration; the remaining bandwidth is determined by the difference between the total LEO satellite bandwidth and the allocated LEO satellite bandwidth; and the transmit power margin is determined by the difference between the maximum LEO satellite transmit power and the current LEO satellite transmit power.

[0041] Step 103: Generate a resource scheduling scheme based on the business information table, resource status parameters, and multi-objective optimization model.

[0042] In this step, the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme. The multi-objective optimization model takes f1 = maximizing resource utilization and f2 = minimizing the latency of high-priority services as objective functions, and takes resource utilization greater than or equal to 90% and high-priority service latency less than or equal to 50 milliseconds (ms) as constraints. Then, the improved particle swarm optimization algorithm is used to solve the optimal allocation scheme, thereby obtaining the resource scheduling scheme.

[0043] In the improved particle swarm optimization algorithm, the velocity update formula is expressed as: The position update formula is expressed as: ; Indicates inertia weight; and All of these represent learning factors, which may be the same or different. This indicates the current hour, but this embodiment does not limit this; and All of them represent random numbers in the interval [0,1], which can be the same or different. This embodiment does not limit this. Indicates the globally optimal solution; Indicates the current position of the particle; Indicates the particle's current velocity; Indicates that the particle is in The current hourly rate; Indicates that the particle is in The current hourly rate; Indicates that the particle is in The current hour's position; Indicates that the particle is in The current hour position. Furthermore, in the improved particle swarm optimization algorithm, the learning factors c1 and c2 are adaptively adjusted, dynamically changing according to the number of iterations. Initially, c1 is larger to enhance local search capabilities, while later, c2 is larger to enhance global search capabilities. In addition to resource utilization and high-priority service latency, the constraints of the multi-objective optimization model also consider satellite load balancing to avoid over-utilization of resources on any single satellite. This embodiment does not impose limitations on this aspect.

[0044] The improved particle swarm optimization algorithm obtains a multi-objective optimization model. The algorithm initializes the particle swarm, with each particle representing a resource allocation scheme. By iteratively calculating the velocity and position of the particles, the individual optimal solution and the global optimal solution are continuously updated until the optimal allocation scheme that satisfies the constraints is found. The optimal allocation scheme is then determined as the resource scheduling scheme.

[0045] Specifically, after obtaining the business information table and resource status parameters, the business information table and resource status parameters are substituted into the multi-objective optimization model. Combining the objective function of "maximizing resource utilization" and constraints in the multi-objective optimization model, a resource scheduling scheme is determined, which significantly reduces resource waste rate and improves overall resource utilization efficiency.

[0046] The advantage of this setup is that, when substituted into a multi-objective optimization model, the constraints of the multi-objective optimization model are increased to include a satellite load balancing index, i.e., the difference in resource utilization rate among satellites does not exceed 10%. When using the improved particle swarm optimization algorithm to solve the problem, the learning factor is adaptively adjusted to improve the convergence speed and optimization effect of the algorithm. In other words, by combining the objective function of "maximizing resource utilization" and the constraints in the multi-objective optimization model, a resource scheduling scheme is determined, which significantly reduces the resource waste rate and improves the overall resource utilization efficiency.

[0047] Step 104: Perform dynamic scheduling of communication resources for low-orbit satellites based on the resource scheduling scheme, and obtain the resource scheduling execution results.

[0048] Specifically, after obtaining the resource scheduling plan, the satellite hardware unit of the low-orbit satellite is controlled to perform resource allocation based on the resource scheduling plan, the resource scheduling execution result is obtained, and the resource scheduling execution result is sent to the service terminal.

[0049] In one specific embodiment, after dynamically scheduling communication resources for low-orbit satellites based on a resource scheduling scheme and obtaining the resource scheduling execution result, the method further includes: obtaining service transmission delay data based on the resource scheduling execution result; if the service transmission delay data is greater than a delay threshold, continuing to execute the step of generating a resource scheduling scheme based on the service information table, resource status parameters, and a multi-objective optimization model; if the service transmission delay data is less than or equal to the delay threshold, updating the model parameters of the multi-objective optimization model according to a preset period, and continuing to execute the step of generating a resource scheduling scheme based on the service information table, resource status parameters, and a multi-objective optimization model based on the updated model parameters.

[0050] In this step, the service transmission latency data is used to reflect the service transmission quality. The latency threshold is a pre-set value used to judge the service transmission latency data; this embodiment does not limit it.

[0051] Specifically, after dynamically scheduling communication resources for low-Earth orbit satellites based on the resource scheduling scheme and obtaining the resource scheduling execution result, the system obtains service transmission delay data based on the resource scheduling execution result; it determines whether the service transmission delay data is greater than the delay threshold. If the service transmission delay data is greater than the delay threshold, the system continues to return to the step of generating a resource scheduling scheme based on the service information table, resource status parameters, and multi-objective optimization model; if the service transmission delay data is less than or equal to the delay threshold, the model parameters of the multi-objective optimization model are updated according to a preset period, and the system continues to return to the step of generating a resource scheduling scheme based on the service information table, resource status parameters, and multi-objective optimization model based on the updated model parameters.

[0052] Figure 2 This is the second flowchart illustrating the communication resource scheduling method for low-Earth orbit satellites provided by this invention, as shown below. Figure 2 As shown, the specific steps include 201, 202, 203, 204, 205, 206 and 207.

[0053] Step 201: Generate a business information table based on the access request.

[0054] Step 202: Collect resource status parameters of low-orbit satellites.

[0055] Step 203: Generate a resource scheduling scheme based on the business information table, resource status parameters, and multi-objective optimization model.

[0056] Step 204: Perform dynamic scheduling of communication resources for low-orbit satellites based on the resource scheduling scheme, and obtain the resource scheduling execution results.

[0057] Step 205: Obtain service transmission delay data based on resource scheduling execution results.

[0058] Step 206: Determine whether to trigger recalculation based on service transmission delay data.

[0059] Specifically, if the service transmission delay data is greater than the delay threshold, a recalculation is triggered, and the process returns to step 203; if the service transmission delay data is less than or equal to the delay threshold, a recalculation is not triggered, and the process continues to step 207.

[0060] For example, the latency threshold could be 50ms. If the detected service transmission latency data is greater than the latency threshold of 50ms, the scheme is immediately recalculated and the process returns to step 203.

[0061] Step 207: Update the model parameters of the multi-objective optimization model according to the preset cycle.

[0062] Specifically, if the service transmission latency data is less than or equal to the latency threshold, it is determined that recalculation will not be triggered, the model parameters of the multi-objective optimization model are updated according to the preset period, and the execution step 203 is returned based on the updated model parameters.

[0063] This invention provides a communication resource scheduling method for low-Earth orbit (LEO) satellites, applied to LEO satellite communication resource scheduling equipment. The method involves generating a service information table based on access requests; wherein the access request is a request containing service requirements sent by a service terminal to the LEO satellite communication resource scheduling equipment; collecting resource status parameters of the LEO satellite; generating a resource scheduling scheme based on the service information table, resource status parameters, and a multi-objective optimization model; wherein the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme; and dynamically scheduling communication resources for the LEO satellite based on the resource scheduling scheme to obtain the resource scheduling execution result. The technical solution of this invention addresses the problem in existing single-satellite autonomous scheduling where satellites allocate resources based on a preset service priority table. When resources are insufficient, low-priority services are directly rejected. This single-satellite autonomous scheduling suffers from low resource utilization and static allocation cannot adapt to dynamic changes in services. For example, if sudden service demands prevent timely resource scheduling, resource scheduling failures occur, failing to meet real-time requirements. The invention generates a resource scheduling scheme based on a service information table, resource status parameters, and a multi-objective optimization model. Based on this scheme, communication resources for low-Earth orbit satellites are dynamically scheduled to obtain the resource scheduling execution results. This achieves dynamic and collaborative resource allocation, improves resource utilization, reduces latency for high-priority services, and enhances the system's anti-interference capability.

[0064] The communication resource scheduling device for low-Earth orbit satellites provided by the present invention will be described below. The communication resource scheduling device for low-Earth orbit satellites described below can be referred to in correspondence with the communication resource scheduling method for low-Earth orbit satellites described above.

[0065] Figure 3 This is a schematic diagram of the communication resource scheduling device for low-orbit satellites provided by the present invention, with reference to... Figure 3 As shown, a communication resource scheduling device for low-Earth orbit (LEO) satellites, the LEO satellite communication resource scheduling device 300 includes: an information table generation module 301, a status parameter acquisition module 302, a scheduling scheme generation module 303, and a communication resource scheduling module 304; wherein, The information table generation module 301 is used to generate a service information table based on the access request; wherein, the access request is a request containing service requirements sent by the service terminal to the communication resource scheduling equipment of the low-orbit satellite. The status parameter acquisition module 302 is used to acquire resource status parameters of low-orbit satellites; The scheduling scheme generation module 303 is used to generate a resource scheduling scheme based on the business information table, resource status parameters, and a multi-objective optimization model; wherein, the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme. The communication resource scheduling module 304 is used to dynamically schedule communication resources for low-orbit satellites based on the resource scheduling scheme and obtain the resource scheduling execution results.

[0066] In one example embodiment, resource status parameters include the channel occupancy rate, remaining bandwidth, and transmit power margin of the low-Earth orbit satellite.

[0067] In one example embodiment, the status parameter acquisition module 302 is specifically used for: acquiring resource data of the low-Earth orbit (LEO) satellite; wherein the resource data includes channel usage duration, total channel usage duration, total LEO satellite bandwidth, allocated LEO satellite bandwidth, maximum LEO satellite transmit power, and current LEO satellite transmit power; determining resource status parameters of the LEO satellite based on the resource data; wherein the channel occupancy rate in the resource status parameters is the ratio of channel usage duration to total channel usage duration, the remaining bandwidth in the resource status parameters is the difference between the total LEO satellite bandwidth and the allocated LEO satellite bandwidth, and the transmit power margin in the resource status parameters is the difference between the maximum LEO satellite transmit power and the current LEO satellite transmit power.

[0068] In one example embodiment, the service information table includes service signal characteristics, service signal types, and service signal priorities.

[0069] In one example embodiment, the device further includes a latency determination module. The latency determination module is configured to: after dynamically scheduling communication resources for low-Earth orbit satellites based on a resource scheduling scheme and obtaining the resource scheduling execution result, acquire service transmission latency data based on the resource scheduling execution result; if the service transmission latency data is greater than a latency threshold, continue to execute the step of generating a resource scheduling scheme based on the service information table, resource status parameters, and a multi-objective optimization model; if the service transmission latency data is less than or equal to the latency threshold, update the model parameters of the multi-objective optimization model according to a preset period, and continue to execute the step of generating a resource scheduling scheme based on the service information table, resource status parameters, and the multi-objective optimization model based on the updated model parameters.

[0070] The apparatus of this embodiment can be used to execute the method of any embodiment in the side embodiment of the communication resource scheduling method for low-Earth orbit satellites. Its specific implementation process and technical effects are similar to those in the side embodiment of the communication resource scheduling method for low-Earth orbit satellites. For details, please refer to the detailed description in the side embodiment of the communication resource scheduling method for low-Earth orbit satellites, which will not be repeated here.

[0071] Figure 4This is a schematic diagram of the communication resource scheduling equipment for low-Earth orbit satellites provided by the present invention, as shown below. Figure 4 As shown, the communication resource scheduling device for the low-Earth orbit (LEO) satellite may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440. The processor 410, communication interface 420, and memory 430 communicate with each other via the communication bus 440. The processor 410 can call logical instructions in the memory 430 to execute a communication resource scheduling method for the LEO satellite. This method includes: generating a service information table based on an access request; wherein the access request is a request containing service requirements sent by a service terminal to the LEO satellite's communication resource scheduling device; collecting resource status parameters of the LEO satellite; generating a resource scheduling scheme based on the service information table, resource status parameters, and a multi-objective optimization model; wherein the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme; and dynamically scheduling the communication resources of the LEO satellite based on the resource scheduling scheme to obtain the resource scheduling execution result.

[0072] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0073] Figure 5 This is one of the structural schematic diagrams of the communication resource scheduling system for low-orbit satellites provided by the present invention, such as... Figure 5 As shown, the communication resource scheduling system 0 for low-Earth orbit satellites includes a service terminal 1, a low-Earth orbit satellite 2, and communication resource scheduling equipment 3 for low-Earth orbit satellites.

[0074] The communication resource scheduling equipment 3 for low-orbit satellites includes a service awareness module 31, a resource status monitoring module 32, a collaborative decision-making module 33, a resource allocation execution module 34, and a feedback optimization module 35. The service awareness module interacts with the resource status monitoring module, the collaborative decision-making module, and the feedback optimization module through an on-board bus and an inter-satellite link, respectively. The collaborative decision-making module also interacts with the resource allocation execution module and the feedback optimization module through an on-board bus and an inter-satellite link.

[0075] The service perception module is used to receive access requests sent by service terminals and generate a service information table based on the access requests. The service perception module mainly uses fuzzy hierarchical analysis to dynamically adjust the priority of service signals, thereby generating a service information table. When a sudden emergency signal is detected, its priority is automatically raised to the highest level. This embodiment does not limit this aspect.

[0076] The resource status monitoring module is used to collect resource status parameters of low-orbit satellites; the collaborative decision-making module is used to generate resource scheduling schemes based on the business information table, resource status parameters and multi-objective optimization model.

[0077] Specifically, the service awareness module is deployed in the payload unit of each low-Earth orbit satellite to collect service signal characteristics, identify service signal types, and dynamically adjust service signal priorities; the resource status monitoring module is distributed in the communication payload of the low-Earth orbit satellite to collect resource data in real time and transmit it to the collaborative decision-making module; the collaborative decision-making module includes the onboard computer of the primary low-Earth orbit satellite and a ground backup server, adopting an onboard-primary and ground-secondary working mode, and generates a resource scheduling scheme based on service and resource data; the resource allocation execution module is used to receive scheduling instructions determined based on the resource scheduling scheme and control the satellite hardware unit to execute resource allocation; the feedback optimization module is used to collect the resource scheduling execution results based on resource allocation, determine service transmission quality data, and feed it back to the collaborative decision-making module to correct and optimize the model parameters of the multi-objective optimization model.

[0078] The system comprises the following modules: a multi-objective optimization model, which uses an improved particle swarm optimization algorithm to solve resource scheduling schemes; a resource allocation execution module, which dynamically schedules communication resources for low-Earth orbit satellites based on the resource scheduling scheme to obtain resource scheduling execution results; a feedback optimization module, which obtains service transmission delay data based on the resource scheduling execution results; a collaborative decision-making module, which generates a resource scheduling scheme based on the service information table, resource status parameters, and the multi-objective optimization model when the service transmission delay data exceeds a delay threshold; a feedback optimization module, which updates the model parameters of the multi-objective optimization model according to a preset period when the service transmission delay data is less than or equal to the delay threshold; and a collaborative decision-making module, which generates a resource scheduling scheme based on the updated multi-objective optimization model obtained from the updated model parameters, the service information table, and resource status parameters.

[0079] In one specific embodiment, Figure 6 This is the second schematic diagram of the communication resource scheduling system for low-orbit satellites provided by the present invention, as shown below. Figure 6 As shown, the service awareness module is deployed in the communication payload unit of the low-Earth orbit satellite. The service awareness module 31 includes a signal sensing sensor 311 and a signal sensing processor 312. The signal sensing sensor is used to collect service signal frequency, service signal modulation mode and service signal bandwidth characteristics based on access requests. The signal sensing processor is used to identify the collected service signal frequency, service signal modulation mode and service signal bandwidth characteristics and generate a service information table. The service information table includes service signal characteristics, service signal type and service signal priority.

[0080] The service perception module is deployed in the satellite payload unit of the low-orbit satellite and has signal analysis capabilities. When collecting service signal characteristics, it can usually use multi-dimensional feature extraction technology. In addition to the conventional frequency and bandwidth, it also includes features such as signal jitter rate and burstiness. After identifying the service type, the fuzzy hierarchical analysis method is used to dynamically adjust the service signal priority. This embodiment does not limit this.

[0081] The signal sensing sensor equipped in the service perception module is high-precision. The service perception module uses fuzzy hierarchical analysis to dynamically adjust the priority of service signals. When a sudden emergency signal is detected, the priority of the service signal is automatically raised to the highest level. This embodiment does not limit this.

[0082] Specifically, when a service terminal sends an access request to the service perception module, the module's signal sensors quickly collect the service signal frequency, modulation method, and bandwidth characteristics. Then, the data processor identifies the service signal type based on these characteristics, defining high-definition video transmission services as having fixed high bandwidth and continuous transmission characteristics, real-time monitoring data interaction services as having periodicity and low bandwidth characteristics, and emergency command signals as having bursty and high real-time characteristics. The steps for dynamically adjusting service signal priorities using fuzzy hierarchical analysis are as follows: First, a hierarchical structure is established. The target layer determines the priority of service signals; the criterion layer includes the urgency, real-time requirements, bandwidth requirements, and transmission duration of service signals; and the solution layer represents various pending services. Then, a fuzzy judgment matrix is ​​constructed to fuzzily evaluate the importance of each factor in the criterion layer and the solution layer relative to the criterion layer, using a 0-1 fuzzy scaling method. For example, if factor i is much more important than factor j, the scale is 1; important, the scale is 0.8; slightly important, the scale is 0.6; equally important, the scale is 0.5; slightly unimportant, the scale is 0.4; unimportant, the scale is 0.2; and very unimportant, the scale is 0. Next, the weight vector is calculated, i.e., the weight vector of each factor is calculated using the properties of the fuzzy consistency matrix. Finally, the comprehensive priority of each service is calculated based on the weight vector, ultimately generating a service information table. Furthermore, when a sudden emergency signal is detected, its urgency scale in the criterion layer is automatically set to 1, thereby elevating its priority to the highest level, and the service information table is updated.

[0083] The advantage of this setting is that the criterion layer increases the reliability requirements of the service. For services with extremely high reliability requirements, such as emergency command signals, a higher scale is given in the fuzzy judgment matrix. For example, when comparing the reliability requirements of emergency command signals and ordinary data transmission services, the scale is set to 0.8 to highlight their priority. This embodiment does not limit this.

[0084] The resource status monitoring module is deployed in the communication payload unit of the low-Earth orbit satellite. The resource status monitoring module 32 includes a resource monitoring sensor 321 and a data compression processor 322. The resource monitoring sensor is used to collect resource data of the low-Earth orbit satellite at a preset frequency. The resource data includes channel usage time, total channel usage time, total bandwidth of the low-Earth orbit satellite, allocated bandwidth of the low-Earth orbit satellite, maximum transmit power of the low-Earth orbit satellite, and current transmit power of the low-Earth orbit satellite. The data compression processor is used to determine resource status parameters based on the resource data. The channel occupancy rate, remaining bandwidth, and transmit power margin of the low-Earth orbit satellite are also included. The channel occupancy rate is the ratio of the channel usage time to the total channel usage time. The remaining bandwidth is the difference between the total bandwidth of the low-Earth orbit satellite and the allocated bandwidth of the low-Earth orbit satellite. The transmit power margin is the difference between the maximum transmit power of the low-Earth orbit satellite and the current transmit power of the low-Earth orbit satellite.

[0085] In this embodiment, after the data compression processor compresses the resource data to obtain the resource status data, it transmits the resource status data through the inter-satellite link. The preset frequency can be, for example, 100ms / time, but this embodiment does not limit it.

[0086] Specifically, the resource status monitoring module is distributed within the communication payload of the low-Earth orbit (LEO) satellite and includes multiple resource monitoring sensors and a data compression unit. The resource monitoring sensors collect resource data at a sampling frequency of 100ms / sample. This data includes channel usage duration, total channel usage duration, total LEO satellite bandwidth, allocated LEO satellite bandwidth, maximum LEO satellite transmit power, and current LEO satellite transmit power. The data compression processor is used to determine resource status parameters based on this data. Specifically, the LEO satellite's channel occupancy rate, remaining bandwidth, and transmit power margin are defined as follows: channel occupancy rate is the ratio of channel usage duration to total channel usage duration; remaining bandwidth is the difference between the total LEO satellite bandwidth and the allocated LEO satellite bandwidth; and transmit power margin is the difference between the maximum LEO satellite transmit power and the current LEO satellite transmit power.

[0087] For example, the resource status monitoring module still samples at a frequency of 100ms / time. When collecting resource data, the remaining satellite battery power is added as a parameter, because battery power affects the satellite's continuous communication capability. Data compression processing uses the LZW compression algorithm (a widely used lossless data compression algorithm that achieves data compression by establishing a string table). By establishing a string table, recurring strings are represented with shorter codes, further improving compression efficiency. Inter-satellite link transmission uses encrypted transmission. This setting ensures the security of resource status data.

[0088] The advantage of this setup is that the resource status monitoring module replaces the existing technology's 10-minute update cycle with a high-frequency sampling of 100ms / time. Combined with the improved particle swarm optimization algorithm to solve multi-objective models, it reduces the latency of high-priority services, significantly shortens response time, and meets real-time requirements.

[0089] The collaborative decision-making module 33 includes an onboard computer 331 for the primary low-Earth orbit satellite and a ground backup server 332. The onboard computer and the ground backup server are used to construct a multi-objective optimization model that uses an improved particle swarm optimization algorithm to solve resource scheduling schemes, and generate resource scheduling schemes based on the business information table, resource status parameters and the multi-objective optimization model.

[0090] The collaborative decision-making module is mainly based on an improved particle swarm optimization algorithm to construct a multi-objective optimization model. The objective function of the multi-objective optimization model includes maximizing resource utilization and minimizing the latency of high-priority services. When the ground station and the main low-Earth orbit satellite are communicating normally, the ground backup server verifies the resource scheduling scheme. When communication is interrupted, the main low-Earth orbit satellite makes independent decisions to ensure the normal execution of resource scheduling. At the same time, the backup power supply can be activated to ensure the continuous operation of the decision-making unit. This embodiment does not limit this aspect.

[0091] The advantage of this setup is that the collaborative decision-making module adopts a "spacecraft-based, ground-based" working mode. When communication between the ground station and the low-Earth orbit satellite is interrupted, the primary low-Earth orbit satellite can make independent decisions, avoiding the problem of complete system failure under the existing ground-based centralized scheduling mode, enhancing anti-interference and redundancy capabilities, and improving the anti-interference capability of the low-Earth orbit satellite communication resource scheduling system.

[0092] The resource allocation execution module 34 includes a resource allocation controller 341 and a resource allocation executor 342. The resource allocation controller is used to parse the resource scheduling scheme to obtain resource scheduling information. The resource allocation executor is used to dynamically schedule the communication resources of the low-orbit satellite according to the resource scheduling information to obtain the resource scheduling execution result.

[0093] Specifically, the resource allocation execution module consists of a resource allocation controller and a resource allocation executor. The resource allocation controller receives scheduling instructions from the collaborative decision-making module, which are determined based on the resource scheduling scheme. The scheduling instructions contain specific information about resource allocation, such as the channel and bandwidth allocated to a certain service. The resource allocation executor controls the communication hardware units of the low-Earth orbit satellite based on the parsed resource scheduling information, such as adjusting channel switches and setting bandwidth parameters, to complete the resource allocation, obtain the resource scheduling execution result, and send an acknowledgment signal containing the resource scheduling execution result to the service terminal.

[0094] The resource allocation actuator adopts a dual redundancy design to ensure that if one resource allocation controller fails, the other can immediately take over the work. When controlling the hardware unit, the resource allocation controller actuator adds a real-time monitoring function, such as monitoring whether the channel is successfully switched and whether the bandwidth is accurately set. If any abnormality is found, it will be corrected immediately.

[0095] The feedback optimization module 35 includes a feedback data collector 351 and a parameter adjustment unit 352. The feedback data collector is used to obtain service transmission delay data based on the resource scheduling execution result. The parameter adjustment unit is used to update the model parameters of the multi-objective optimization model according to a preset period when the service transmission delay data is less than or equal to the delay threshold. The collaborative decision-making module is also used to obtain an updated multi-objective optimization model based on the updated model parameters, and to generate a resource scheduling scheme based on the updated multi-objective optimization model, the service information table, and the resource status parameters.

[0096] The preset period could be, for example, updating the inertia weights of the particle swarm optimization algorithm every hour, thereby updating the model parameters of the multi-objective optimization model and continuously optimizing the resource scheduling scheme. In this embodiment, the preset period is not limited.

[0097] The service transmission latency data of the feedback data collector has been updated with a packet loss rate parameter. When updating the inertia weight of the particle swarm algorithm every hour, in addition to considering the time factor, the average latency and packet loss rate of the service are also taken into account. When the average latency is large, the inertia weight is appropriately reduced to enhance the local search capability; when the packet loss rate is high, the inertia weight is appropriately increased to enhance the global search capability.

[0098] Specifically, the feedback optimization module includes a feedback data collector and a parameter adjustment unit. The feedback data collector collects service transmission quality data in real time based on the received acknowledgment signals, such as transmission delay and bit error rate. The parameter adjustment unit updates the inertia weights of the particle swarm optimization algorithm hourly, using the following update formula: ,in, ω0 represents the initial inertia weight, t represents the current hour, and T represents the total number of hours. When the service latency exceeds the latency threshold, the relevant data is immediately fed back to the collaborative decision-making module, triggering a recalculation of the solution.

[0099] In summary, the communication resource scheduling system for low-orbit satellites provided in this application solves the problem of wasted idle resources of neighboring satellites when the resources of a single satellite are saturated through inter-satellite resource collaborative scheduling. Combined with the objective function and constraints of "maximizing resource utilization" in the multi-objective optimization model, it significantly reduces the resource waste rate and improves the overall resource utilization efficiency.

[0100] This invention provides a communication resource scheduling system for low-Earth orbit (LEO) satellites. The system includes a service terminal, LEO satellites, and LEO satellite communication resource scheduling equipment. The LEO satellite communication resource scheduling equipment includes a service awareness module, a resource status monitoring module, a collaborative decision-making module, a resource allocation execution module, and a feedback optimization module. The service awareness module interacts with the resource status monitoring module, collaborative decision-making module, and feedback optimization module via an on-board bus and inter-satellite links. The collaborative decision-making module also interacts with the resource allocation execution module and feedback optimization module via the on-board bus and inter-satellite links. The service awareness module receives access requests from the service terminal and generates a service information table based on the access requests. The service awareness module primarily uses fuzzy hierarchical analysis (AHP) to dynamically adjust the priority of service signals, thereby generating the service information table. The resource status monitoring module collects resource status parameters of the LEO satellites. The collaborative decision-making module generates a resource scheduling scheme based on the service information table, resource status parameters, and a multi-objective optimization model. The technical solution of this invention addresses the problem in existing single-satellite autonomous scheduling where satellites allocate resources based on a preset service priority table. When resources are insufficient, low-priority services are directly rejected. This single-satellite autonomous scheduling suffers from low resource utilization and static allocation cannot adapt to dynamic changes in services. For example, if sudden service demands prevent timely resource scheduling, resource scheduling failures occur, failing to meet real-time requirements. The invention generates a resource scheduling scheme based on a service information table, resource status parameters, and a multi-objective optimization model. Based on this scheme, communication resources for low-Earth orbit satellites are dynamically scheduled to obtain the resource scheduling execution results. This achieves dynamic and collaborative resource allocation, improves resource utilization, reduces latency for high-priority services, and enhances the system's anti-interference capability.

[0101] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the communication resource scheduling method for low-Earth orbit satellites provided by the above methods. The method includes: generating a service information table based on an access request; wherein the access request is a request containing service requirements sent by a service terminal to the communication resource scheduling device of the low-Earth orbit satellite; collecting resource status parameters of the low-Earth orbit satellite; generating a resource scheduling scheme based on the service information table, resource status parameters, and a multi-objective optimization model; wherein the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme; and dynamically scheduling the communication resources of the low-Earth orbit satellite based on the resource scheduling scheme to obtain the resource scheduling execution result.

[0102] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements a method for scheduling communication resources for low-Earth orbit satellites provided by the methods described above. This method includes: generating a service information table based on an access request; wherein the access request is a request containing service requirements sent by a service terminal to a communication resource scheduling device of the low-Earth orbit satellite; collecting resource status parameters of the low-Earth orbit satellite; generating a resource scheduling scheme based on the service information table, the resource status parameters, and a multi-objective optimization model; wherein the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme; and dynamically scheduling communication resources of the low-Earth orbit satellite based on the resource scheduling scheme to obtain a resource scheduling execution result.

[0103] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0104] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for scheduling communication resources for low-Earth orbit satellites, characterized in that, Communication resource scheduling equipment used in low-Earth orbit satellites includes: A service information table is generated based on the access request; wherein, the access request is a request containing service requirements sent by the service terminal to the communication resource scheduling equipment of the low-orbit satellite; Collect the resource status parameters of the low-orbit satellite; A resource scheduling scheme is generated based on the business information table, the resource status parameters, and the multi-objective optimization model; wherein the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme. Based on the resource scheduling scheme, the communication resources of the low-orbit satellite are dynamically scheduled to obtain the resource scheduling execution result.

2. The communication resource scheduling method for low-orbit satellites according to claim 1, characterized in that, The resource status parameters include the channel occupancy rate, remaining bandwidth, and transmit power margin of the low-Earth orbit satellite; the collection of the resource status parameters of the low-Earth orbit satellite includes: Collect the resource data of the low-orbit satellite; wherein, the resource data includes channel usage duration, total channel usage duration, total bandwidth of the low-orbit satellite, allocated bandwidth of the low-orbit satellite, maximum transmission power of the low-orbit satellite, and current transmission power of the low-orbit satellite; The resource status parameters of the low-Earth orbit satellite are determined based on the resource data; wherein, the channel occupancy rate in the resource status parameters is the ratio of the channel usage time to the total channel usage time, the remaining bandwidth in the resource status parameters is the difference between the total bandwidth of the low-Earth orbit satellite and the allocated bandwidth of the low-Earth orbit satellite, and the transmit power margin in the resource status parameters is the difference between the maximum transmit power of the low-Earth orbit satellite and the current transmit power of the low-Earth orbit satellite.

3. The communication resource scheduling method for low-orbit satellites according to claim 1, characterized in that, The service information table includes service signal characteristics, service signal types, and service signal priorities.

4. The communication resource scheduling method for low-orbit satellites according to claim 1, characterized in that, After performing dynamic scheduling of communication resources for the low-Earth orbit satellite based on the resource scheduling scheme and obtaining the resource scheduling execution result, the method further includes: Based on the resource scheduling execution result, obtain the service transmission latency data; If the service transmission delay data is greater than the delay threshold, continue to execute the step of generating a resource scheduling scheme based on the service information table, the resource status parameters and the multi-objective optimization model; If the service transmission delay data is less than or equal to the delay threshold, the model parameters of the multi-objective optimization model are updated according to a preset period, and the step of generating a resource scheduling scheme based on the service information table, the resource status parameters and the multi-objective optimization model is returned to be executed based on the updated model parameters.

5. A communication resource scheduling device for low-orbit satellites, characterized in that, Communication resource scheduling equipment used in low-Earth orbit satellites includes: The information table generation module is used to generate a service information table based on the access request; wherein, the access request is a request containing service requirements sent by the service terminal to the communication resource scheduling equipment of the low-orbit satellite; The status parameter acquisition module is used to acquire the resource status parameters of the low-orbit satellite; The scheduling scheme generation module is used to generate a resource scheduling scheme based on the business information table, the resource status parameters, and the multi-objective optimization model; wherein, the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme; The communication resource scheduling module is used to dynamically schedule the communication resources of the low-orbit satellite based on the resource scheduling scheme, and obtain the resource scheduling execution result.

6. A communication resource scheduling device for low-Earth orbit satellites, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the communication resource scheduling method for low-orbit satellites as described in any one of claims 1 to 4.

7. A communication resource scheduling system for low-Earth orbit satellites, characterized in that, It includes a service terminal, a low-Earth orbit satellite, and a communication resource scheduling device for the low-Earth orbit satellite as described in claim 6.

8. The communication resource scheduling system for low-orbit satellites according to claim 7, characterized in that, The communication resource scheduling equipment for the low-Earth orbit satellite includes a service awareness module, a resource status monitoring module, a collaborative decision-making module, a resource allocation execution module, and a feedback optimization module. The service awareness module interacts with the resource status monitoring module, the collaborative decision-making module, and the feedback optimization module via an on-board bus and inter-satellite links. The collaborative decision-making module also interacts with the resource allocation execution module and the feedback optimization module via an on-board bus and inter-satellite links. The service awareness module is used to receive the access request sent by the service terminal and generate a service information table based on the access request. The resource status monitoring module is used to collect the resource status parameters of the low-orbit satellite; The collaborative decision-making module is used to generate a resource scheduling scheme based on the business information table, the resource status parameters, and the multi-objective optimization model; wherein, the multi-objective optimization model is a model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme; The resource allocation execution module is used to dynamically schedule the communication resources of the low-orbit satellite based on the resource scheduling scheme, and obtain the resource scheduling execution result. The feedback optimization module is used to obtain service transmission latency data based on the resource scheduling execution result; The collaborative decision-making module is also used to generate a resource scheduling scheme based on the service information table, the resource status parameters, and the multi-objective optimization model when the service transmission delay data is greater than the delay threshold. The feedback optimization module is further configured to update the model parameters of the multi-objective optimization model according to a preset period when the service transmission delay data is less than or equal to the delay threshold. The collaborative decision-making module is also used to generate the resource scheduling scheme based on the updated multi-objective optimization model obtained from the updated model parameters, the business information table, and the resource status parameters.

9. The communication resource scheduling system for low-orbit satellites according to claim 8, characterized in that, The service awareness module is deployed in the communication payload unit of the low-Earth orbit satellite, and the service awareness module includes a signal sensing sensor and a signal sensing processor. The signal sensing sensor is used to collect service signal frequency, service signal modulation method and service signal bandwidth characteristics based on the access request; The signal sensing processor is used to identify the frequency, modulation method, and bandwidth characteristics of the acquired service signal, and generate the service information table; wherein, the service information table includes service signal characteristics, service signal type, and service signal priority; The resource status monitoring module is deployed in the communication payload unit of the low-orbit satellite, and the resource status monitoring module includes resource monitoring sensors and a data compression processor; The resource monitoring sensor is used to collect resource data of the low-orbit satellite at a preset frequency; wherein, the resource data includes channel usage duration, total channel usage duration, total bandwidth of the low-orbit satellite, allocated bandwidth of the low-orbit satellite, maximum transmission power of the low-orbit satellite, and current transmission power of the low-orbit satellite. The data compression processor is used to determine the resource status parameters based on the resource data; wherein, the channel occupancy rate, remaining bandwidth, and transmit power margin of the low-orbit satellite are: the channel occupancy rate is the ratio of the channel usage time to the total channel usage time; the remaining bandwidth is the difference between the total bandwidth of the low-orbit satellite and the allocated bandwidth of the low-orbit satellite; and the transmit power margin is the difference between the maximum transmit power of the low-orbit satellite and the current transmit power of the low-orbit satellite. The collaborative decision-making module includes the onboard computer of the primary low-Earth orbit satellite and a ground backup server. The onboard computer and the ground backup server are used to construct the multi-objective optimization model that uses an improved particle swarm optimization algorithm to solve the resource scheduling scheme, and generate the resource scheduling scheme based on the business information table, the resource status parameters and the multi-objective optimization model; The resource allocation execution module includes a resource allocation controller and a resource allocation executor; The resource allocation controller is used to parse the resource scheduling scheme to obtain resource scheduling information; The resource allocation executor is used to dynamically schedule the communication resources of the low-orbit satellite according to the resource scheduling information, and obtain the resource scheduling execution result. The feedback optimization module includes a feedback data acquisition unit and a parameter adjustment unit; The feedback data collector is used to obtain service transmission delay data based on the resource scheduling execution result; The parameter adjustment unit is used to update the model parameters of the multi-objective optimization model according to a preset period when the service transmission delay data is less than or equal to the delay threshold. The collaborative decision-making module is also used to obtain an updated multi-objective optimization model based on the updated model parameters, and to generate the resource scheduling scheme based on the updated multi-objective optimization model, the business information table, and the resource status parameters.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the communication resource scheduling method for low-orbit satellites as described in any one of claims 1 to 4.

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