Cloud ground station system, method and device for low earth orbit satellite internet of things

Abstract

This invention applies to the field of low-Earth orbit (LEO) satellite Internet of Things (IoT), providing a cloud-based ground station system, method, and apparatus for LEO satellite IoT. The cloud-based ground station system includes: a satellite-ground collaborative scheduling module for determining the amount of signal processing resources required during the transit of each LEO satellite; an orchestration management module for lifecycle management of each virtualized signal processing node before the LEO satellite transits; a network resource control module for orchestrating data routing links; a resource pool deployed on a cloud platform including several virtualized signal processing nodes managed by the orchestration management module, each virtualized signal processing node comprising an intermediate frequency (IF) unit, a baseband unit, and a protocol processing unit; and a core network module for forwarding processed data to the target server. This invention decomposes the traditional ground station signal processing function into independent virtualized components such as IF, baseband, and protocol processing, which run on a cloud platform, allowing for dynamic scaling based on service load and improving the ground station's scalability.

Description

Technical Field

[0001] This invention relates to the field of low-Earth orbit satellite Internet of Things (LEO) technology, and in particular to a cloud-based ground station system, method, and apparatus for LEO satellite Internet of Things. Background Technology

[0002] With the rapid development of Low Earth Orbit (LEO) satellite IoT constellations, seamless global data coverage has become possible. LEO satellite IoT utilizes LEO satellite constellations to provide wide-area communication services for terrestrial IoT terminals, making it particularly suitable for applications where terrestrial networks struggle to cover, such as marine monitoring, asset tracking, environmental monitoring, and agricultural IoT. In the entire LEO satellite communication link, the ground station, as a crucial hub connecting the LEO satellites and the terrestrial core network, has its network scale and layout directly determining the overall service capacity, stability, and construction cost of the ground station.

[0003] However, traditional low-Earth orbit satellite ground stations have tightly coupled hardware and software. Functions such as modulation and demodulation, and baseband processing are all fixed in dedicated hardware equipment. Each communication system requires a corresponding set of dedicated hardware, resulting in a high degree of isolation, low flexibility, long service deployment time, and high operating costs. This also makes the ground station system poorly expandable and unable to adapt to the development of new services. Summary of the Invention

[0004] This invention provides a cloud-based ground station system, method, and apparatus for low-Earth orbit satellite Internet of Things (LEO), which addresses the shortcomings of poor scalability in existing ground station systems and improves their scalability.

[0005] This invention provides a cloud-based ground station system for low-Earth orbit satellite Internet of Things, comprising: The satellite-ground collaborative scheduling module is used to obtain the orbit prediction information of each low-Earth orbit satellite in the low-Earth orbit satellite constellation and the service demand information of IoT terminals, and to determine the amount of signal processing resources required for each low-Earth orbit satellite during its transit based on the orbit prediction information and service demand information. The orchestration management module is used to manage the lifecycle of each virtualized signal processing node in the resource pool before the corresponding low-orbit satellite passes by, based on the amount of signal processing resources available. The network resource control module is used to dynamically orchestrate the data routing links between each virtualized signal processing node and the radio frequency front-end of the ground station; The resource pool deployed on the cloud platform includes several virtualized signal processing nodes managed by the orchestration management module. Each virtualized signal processing node includes an intermediate frequency processing unit, a baseband processing unit, and a protocol processing unit to sequentially process the digital signals transmitted by the radio frequency front end through intermediate frequency, baseband, and communication protocol processing. The core network module is used to forward the data processed by each virtualized signal processing node to the target server.

[0006] According to the cloud-based ground station system for low-Earth orbit satellite Internet of Things provided by the present invention, in the operation of lifecycle management of each virtualized signal processing node in the resource pool before the corresponding low-Earth orbit satellite passes by, based on the amount of signal processing resources, the orchestration management module is specifically used for: Determine whether the current available signal processing resources in the resource pool meet the signal processing resource requirements. If the conditions are not met, a preset resource preemption operation is performed based on the resource shortage between the amount of signal processing resources and the amount of available signal processing resources. The preset resource preemption operation includes releasing virtualized signal processing nodes that process low-priority services based on the resource shortage.

[0007] According to the cloud-based ground station system for low-Earth orbit satellite Internet of Things provided by the present invention, when the current available signal processing resources in the resource pool meet the signal processing resource requirements, the orchestration management module is further configured to: Before each low-orbit satellite passes overhead, the corresponding virtualized signal processing nodes are activated or expanded according to the available signal processing resources.

[0008] According to the cloud-based ground station system for low-Earth orbit satellite Internet of Things provided by the present invention, the satellite-ground collaborative scheduling module is further used for: Based on the orbital prediction information, predict the spatial position changes of each low-Earth orbit satellite relative to the ground station during its transit. Data routing link configuration information for each low-orbit satellite is generated based on the changes in its spatial position relative to the ground station during the transit of each low-orbit satellite. In the operation of dynamically orchestrating the data routing links between each virtualized signal processing node and the radio frequency front-end of the ground station, the network resource control module is specifically used for: Based on the data routing link configuration information corresponding to each low-orbit satellite, adjust the data routing link between each virtualized signal processing node and the radio frequency front-end of the ground station.

[0009] According to the present invention, a cloud-based ground station system for low-Earth orbit satellite Internet of Things is provided, wherein the data routing link configuration information corresponding to each low-Earth orbit satellite includes data routing link configuration information between a target intermediate frequency processing unit and at least one target baseband processing unit, and the target intermediate frequency processing unit is an intermediate frequency processing unit connected to the radio frequency front-end corresponding to the low-Earth orbit satellite. In generating data routing link configuration information for each low-Earth orbit satellite based on its spatial position relative to the ground station during its transit, the satellite-ground collaborative scheduling module is specifically used for: The number of baseband processing units required to be connected to the target intermediate frequency processing unit is determined based on the number of registered IoT terminals within the geographical area covered after the change in spatial location. Based on the idle status of the baseband processing units in each virtualized signal processing node in the resource pool, select the corresponding number of target baseband processing units according to the number of baseband processing units required to be connected to the target intermediate frequency processing unit. According to the preset data distribution strategy, the data routing link configuration information between the target intermediate frequency processing unit and each target baseband processing unit is determined.

[0010] According to the cloud-based ground station system for low-Earth orbit satellite Internet of Things provided by the present invention, in determining the amount of signal processing resources required during the transit of each low-Earth orbit satellite based on orbit prediction information and service demand information, the satellite-ground collaborative scheduling module is specifically used for: Based on the orbital prediction information, determine the total geographical area covered by each low-Earth orbit satellite during its transit. Based on the total geographical area and business needs information, determine the number of registered IoT terminals within the total geographical area and the size of IoT terminal data sent by each IoT terminal. Based on the number of registered IoT terminals within the total geographic area and the size of the IoT terminal data sent by each IoT terminal, determine the amount of signal processing resources required during the transit of each low-Earth orbit satellite.

[0011] According to the cloud-based ground station system for low-Earth orbit satellite Internet of Things provided by the present invention, the satellite-ground collaborative scheduling module is further used for: Based on the orbit prediction information, predict the Doppler frequency shift rate on the satellite-to-ground link for each low-Earth orbit satellite. The satellite-to-ground link includes the data routing link between the low-Earth orbit satellite and the radio frequency front-end. Before each low-orbit satellite passes overhead, the Doppler frequency shift rate is sent to the baseband processing unit connected to the radio frequency front-end in the corresponding satellite-to-ground link, so as to instruct the baseband processing unit to perform Doppler frequency shift compensation when receiving the baseband signal output by the intermediate frequency processing unit.

[0012] According to the cloud-based ground station system for low-Earth orbit satellite Internet of Things provided by the present invention, in the operation of predicting the Doppler frequency shift rate of change on the satellite-to-ground link of each low-Earth orbit satellite based on orbit prediction information, the satellite-to-ground cooperative scheduling module is specifically used for: Based on the orbital prediction information, determine the relative motion speed between each low-Earth orbit satellite and the ground station; Based on the relative motion speed between each low-Earth orbit satellite and the ground station, the Doppler frequency shift rate on the satellite-to-ground link of each low-Earth orbit satellite is predicted.

[0013] According to the cloud-based ground station system for low-Earth orbit satellite Internet of Things provided by the present invention, the baseband processing unit is specifically used for: When multiple IoT terminals covered by low-orbit satellites use unlicensed random access during their transit, a parallel demodulation mechanism is used to simultaneously detect and identify multiple random access preamble sequences in the received baseband signal.

[0014] This invention also provides a resource scheduling method for low-Earth orbit satellite Internet of Things (LEO), applicable to any of the aforementioned cloud-based ground station systems for LEO satellite Internet of Things, the method comprising: The satellite-ground collaborative scheduling module acquires the orbit prediction information of each low-Earth orbit satellite in the low-Earth orbit satellite constellation and the service demand information of IoT terminals, and determines the amount of signal processing resources required for each low-Earth orbit satellite during its transit based on the orbit prediction information and service demand information. The orchestration management module performs lifecycle management on each virtualized signal processing node in the resource pool before the corresponding low-orbit satellite passes by, based on the amount of signal processing resources available. The network resource control module dynamically arranges the data routing links between each virtualized signal processing node and the radio frequency front-end of the ground station; Each virtualized signal processing node in the resource pool deployed on the cloud platform sequentially processes the digital signals transmitted by the radio frequency front end into intermediate frequency, baseband, and communication protocol processing. The core network module forwards the data processed by each virtualized signal processing node to the target server.

[0015] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the resource scheduling method for low-Earth orbit satellite Internet of Things as described above.

[0016] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the resource scheduling method for low-Earth orbit satellite Internet of Things as described above.

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

[0018] This invention provides a cloud-based ground station system, method, and apparatus for low-Earth orbit satellite Internet of Things (LEO). By virtualizing and deploying intermediate frequency processing, baseband processing, and protocol processing functions on a cloud platform, and utilizing a satellite-ground collaborative scheduling module, an orchestration management module, and a network resource control module to manage each virtualized signal processing node in the resource pool, this invention not only improves the scalability of the ground station system but also enhances the cloud-based ground station system's service carrying capacity for large-scale LEO satellite constellations and massive IoT terminals. 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 a schematic diagram of the architecture of the cloud-based ground station system for low-Earth orbit satellite Internet of Things provided by the present invention.

[0021] Figure 2 This is a schematic diagram of data flow between the IoT terminal and the target server provided by the present invention.

[0022] Figure 3 This is a flowchart illustrating the lifecycle management of virtualized signal processing nodes by the orchestration management module provided by this invention.

[0023] Figure 4 This is a flowchart illustrating the resource scheduling method for low-Earth orbit satellite Internet of Things provided by the present invention.

[0024] Figure 5 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0025] 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.

[0026] The following is combined Figures 1 to 3 This invention describes a cloud-based ground station system for low-Earth orbit satellite Internet of Things (LEO). The cloud-based ground station system provided by this invention can be applied to narrowband IoT fields, as well as broadband IoT fields, etc. This embodiment uses its application in the narrowband IoT field as an example. Figure 1As shown, the cloud-based ground station system for low-Earth orbit satellite IoT includes a satellite-ground collaborative scheduling module 100, an orchestration management module 200, a network resource control module 300, a resource pool 400 deployed on a cloud platform, and a core network module 500. The resource pool 400 includes several virtualized signal processing nodes 410 managed by the orchestration management module 200. Each virtualized signal processing node 410 includes an intermediate frequency processing unit 411, a baseband processing unit 412, and a protocol processing unit 413.

[0027] Among them, the satellite-ground collaborative scheduling module 100 is used to obtain the orbit prediction information of each low-orbit satellite in the low-orbit satellite constellation and the service demand information of the Internet of Things terminal, and to determine the amount of signal processing resources required for each low-orbit satellite during its transit based on the orbit prediction information and service demand information.

[0028] Low Earth Orbit (LEO) satellites refer to satellites operating in near-Earth orbit used to provide IoT data relay services. An LEO satellite constellation is a network system composed of multiple LEO satellites to achieve wider and more continuous ground coverage. Orbit prediction information can carry data on the future positions and trajectories of LEO satellites, including, but not limited to, one or more of the following: the nadir trajectory of each LEO satellite within a specific future time period, its transit time window, and its zenith and azimuth angles relative to ground stations. In some application scenarios, orbit prediction information can be obtained from ephemeris servers.

[0029] The IoT terminal can be a narrowband IoT terminal, such as various sensors and monitors that require data transmission via low-Earth orbit satellites. Business requirement information can be the communication behavior characteristics of the IoT terminal, such as its geographic spatial distribution, including distribution density. Alternatively, business requirement information may also include the data reporting cycle, the average size of each data packet, and requirements for service quality such as latency and reliability. The business requirement information of the IoT terminal can be obtained by the satellite-ground collaborative scheduling module 100 from other servers or systems.

[0030] The amount of signal processing resources can be the size of all IoT terminal data relayed during the transit of a low-Earth orbit satellite. The satellite-ground collaborative scheduling module 100 estimates the required amount of signal processing resources based on orbit prediction information and service demand information.

[0031] The resource pool 400 deployed on the cloud platform includes several virtualized signal processing nodes 410 managed by the orchestration management module 200. Each virtualized signal processing node 410 includes an intermediate frequency processing unit 411, a baseband processing unit 412, and a protocol processing unit 413 to sequentially process the digital signals transmitted by the radio frequency front end through intermediate frequency, baseband, and communication protocol processing.

[0032] The cloud platform can be a public or private cloud infrastructure. The resource pool 400 includes several virtualized signal processing nodes 410 managed by the orchestration management module 200. In this embodiment, the virtualized signal processing nodes 410 can be deployed as containerized microservices and managed through a container orchestration platform.

[0033] Each virtualized signal processing node 410 contains an intermediate frequency processing unit 411, a baseband processing unit 412, and a protocol processing unit 413 to process the digital signals transmitted by the radio frequency front-end of the ground station in sequence. The radio frequency front-end is responsible for receiving the downlink radio frequency signals from the low-Earth orbit satellite, and performing amplification, filtering, down-conversion, and analog-to-digital conversion, ultimately outputting a digital intermediate frequency signal, i.e., the digital signal here.

[0034] For example, the intermediate frequency (IF) processing unit 411 performs IF processing on the received digital signal, including digital down-conversion, filtering, and resampling, to convert it into a baseband signal. The baseband processing unit 412 performs core physical layer processing on the baseband signal output by the IF processing unit 411, such as demodulation, channel decoding, and rate dematching of narrowband IoT signals. The protocol processing unit 413 processes the parts of the communication protocol stack above the physical layer, such as the Media Access Control (MAC) layer, Radio Link Control (RLC) layer, Packet Data Convergence Protocol (PDCP) layer, and Radio Resource Control (RRC) layer of the narrowband IoT protocol stack.

[0035] The orchestration management module 200 is used to manage the lifecycle of each virtualized signal processing node 410 in the resource pool 400 before the corresponding low-orbit satellite passes by, based on the amount of signal processing resources.

[0036] The orchestration management module 200 is connected to the satellite-ground coordinated scheduling module 100 and can receive the signal processing resource amount sent by the satellite-ground coordinated scheduling module 100. Lifecycle management includes the instantiation, startup, monitoring, scaling up / down, and / or eventual destruction of the virtualized signal processing nodes 410. The orchestration management module 200 can use Network Functions Virtualization (NFV) technology to manage the lifecycle of the virtualized signal processing nodes 410 in the resource pool 400. For example, the orchestration management module 200 may include a resource monitoring unit, which monitors the load status, processing latency, and available resource amount of each virtualized signal processing node 410 in real time. In some application scenarios, when the load of a virtualized signal processing node 410 exceeds a preset threshold, the resource monitoring unit triggers an elastic scaling mechanism, and the orchestration management module 200 automatically adds new virtualized signal processing nodes 410 to distribute the load.

[0037] The network resource control module 300 is used to dynamically arrange the data routing links between each virtualized signal processing node 410 and the radio frequency front end of the ground station.

[0038] The data routing link includes the data flow path of digital signals from the radio frequency front end to the corresponding intermediate frequency processing unit 411, then to the corresponding baseband processing unit 412, and finally to the protocol processing unit 413. The data routing link between the virtualized signal processing nodes 410 and the radio frequency front end of the ground station, which is dynamically orchestrated as described above, can be considered as follows: The network resource control module 300 can adopt software-defined networking (SDN) technology to flexibly configure and modify these links through a centralized controller, realizing on-demand scheduling of data routing links. That is, it can adjust each data routing link in real time according to business needs and changes in the position of low-Earth orbit satellites, so that the same resource pool 400 deployed on the cloud platform can simultaneously serve multiple low-Earth orbit satellite constellations and various IoT business types.

[0039] In some application scenarios, the network resource control module 300 interacts with the satellite-ground collaborative scheduling module 100 through the northbound interface to receive data routing link configuration information issued by the satellite-ground collaborative scheduling module 100, or interacts with the orchestration management module 200 through the northbound interface to receive data routing link configuration information forwarded by the orchestration management module 200. The network resource control module 300 controls the data routing links between each virtualized signal processing node 410 through the southbound interface.

[0040] The core network module 500 is used to forward the data processed by each virtualized signal processing node 410 to the target server.

[0041] The core network module 500 can be deployed on a cloud platform and communicates with the resource pool 400. It can be used to implement functions such as access authentication, mobility management, and session management for IoT terminals. In some application scenarios, a cloud-native 5G core network architecture can be adopted, supporting the NB-IoT protocol for non-terrestrial networks defined in the 3GPP standard. Data processed in the resource pool 400 can be transmitted to a designated server via the core network module 500.

[0042] The data transmission path of IoT terminals can be as follows: Figure 2 As shown, the IoT terminal 3000 sends a signal carrying IoT terminal data to the low-Earth orbit satellite 2000. The low-Earth orbit satellite 2000 forwards the signal to the radio frequency front-end 1000. The radio frequency front-end 1000 amplifies, filters, down-converts, and performs analog-to-digital conversion on the received signal, and finally outputs a digital signal to the corresponding intermediate frequency processing unit 411 in the resource pool 400. Then, after passing through the baseband processing unit 412 and the protocol processing unit 413 in sequence, it is sent to the target server 4000 through the core network module 500.

[0043] In this embodiment, by virtualizing and deploying the intermediate frequency processing, baseband processing, and protocol processing functions on a cloud platform, and using the satellite-ground collaborative scheduling module 100, the orchestration management module 200, and the network resource control module 300 to manage each virtualized signal processing node 410 in the resource pool 400, not only is the scalability of the ground station system improved, but also the service carrying capacity of the cloud-based ground station system for large-scale low-orbit satellite constellations and massive IoT terminals is enhanced.

[0044] In some embodiments, in determining the amount of signal processing resources required during the transit of each low-Earth orbit satellite based on orbit prediction information and service demand information, the satellite-ground coordinated scheduling module 100 is specifically used for: First, based on the orbital prediction information, determine the total geographical area covered by each low-orbit satellite during its transit.

[0045] The satellite-ground coordinated scheduling module 100 uses orbit prediction information to calculate the total geographical area swept by the communication beam of a single low-Earth orbit satellite during a complete transit. Alternatively, in some application scenarios, the total geographical area can be calculated as the sum of the coverage areas of all low-Earth orbit satellites transiting over a period of time. For example, if three low-Earth orbit satellites are transiting within the next 30 minutes, the total geographical area covered by these three satellites can be calculated.

[0046] Secondly, based on the total geographical area and business needs information, determine the number of registered IoT terminals within the total geographical area and the size of IoT terminal data sent by each IoT terminal.

[0047] For example, the calculated total geographical area is matched with the geographic spatial distribution of IoT terminals stored in the business requirement information to determine the number of registered IoT terminals within the total geographical area. Additionally, the data reporting characteristics of these IoT terminals, such as the average size of IoT terminal data, can also be obtained from the business requirement information.

[0048] Then, based on the number of registered IoT terminals within the total geographical area and the size of the IoT terminal data sent by each IoT terminal, the amount of signal processing resources required during the transit of each low-Earth orbit satellite is determined.

[0049] For example, the number of registered IoT terminals within the total geographic area is multiplied by the size of the IoT terminal data sent by each IoT terminal, and the product is used as the amount of signal processing resources required during the transit of each LEO satellite. Alternatively, this product can be multiplied by the processing coefficient of the virtualized node to obtain the amount of signal processing resources required during the transit of each LEO satellite.

[0050] In this embodiment, by integrating low-orbit satellite orbit information and ground terminal service information, it is possible to accurately predict future service load and allocate resources on demand, effectively solving the problems of resource waste and resource shortage.

[0051] Considering that the resources in resource pool 400 are not unlimited in actual operation, there may be situations where multiple tasks compete for resources, resulting in insufficient available resources to meet the newly predicted signal processing resource requirements. Therefore, in some embodiments, in the operation of lifecycle management of each virtualized signal processing node 410 in resource pool 400 before the corresponding low-Earth orbit satellite passes, based on the signal processing resource requirements, the orchestration management module 200 is specifically used to execute... Figure 3 The following steps are shown: Step 101: Determine whether the current available signal processing resources in resource pool 400 meet the required signal processing resources.

[0052] For example, step 101 can be executed by the resource monitoring unit within the orchestration management module 200. The available signal processing resources can be considered the maximum amount of data the resource pool can currently process. Exceeding this available signal processing resources may cause data congestion. The available signal processing resources are related to the resource pool's computing power, storage capacity, and / or network bandwidth. As described above, the resource monitoring unit monitors the load status, processing latency, and total available resources of all virtualized signal processing nodes 410 in the resource pool 400 in real time to determine the real-time available signal processing resources. If the current available signal processing resources are greater than the signal processing resource quantity, it indicates that the current available signal processing resources of the resource pool 400 meet the signal processing resource quantity requirement; otherwise, it is determined that the current available signal processing resources of the resource pool 400 do not meet the signal processing resource quantity requirement.

[0053] If the judgment result of step 101 is not satisfied, step 102 is executed; if the judgment result is satisfied, step 103 is executed.

[0054] Step 102: Perform a preset resource preemption operation based on the resource shortage between the amount of signal processing resources and the amount of available signal processing resources.

[0055] Resource shortage can be the difference between the amount of signal processing resources and the amount of available signal processing resources.

[0056] The preset resource preemption operation includes releasing virtualized signal processing nodes 410 that handle low-priority services based on resource shortages.

[0057] For example, the orchestration management module 200 can identify currently running, low-priority services based on a pre-defined service priority strategy. For instance, data collection services from IoT terminals can be categorized into different levels, such as high priority for emergency alarm data processing, medium priority for routine status reporting, and low priority for historical data recovery.

[0058] Based on the calculated resource shortage, the orchestration management module 200 selectively reduces or terminates virtualized signal processing nodes 410 that are processing low-priority services, thereby freeing up sufficient computing, storage, and network resources to meet the needs of upcoming high-priority low-Earth orbit satellite transit missions. In some application scenarios, the resource monitoring unit in the orchestration management module 200 can record relevant resource scheduling logs for subsequent auditing and strategy optimization.

[0059] This embodiment ensures that high-priority low-orbit satellite IoT communication tasks are processed first by distinguishing service priorities and dynamically adjusting resource allocation, thereby improving the reliability of the cloud-based ground station system under limited resource conditions.

[0060] Step 103: Before each low-orbit satellite passes overhead, activate or expand the corresponding virtualized signal processing node 410 according to the amount of signal processing resources.

[0061] In other words, when the orchestration management module 200 determines that the available resources in the current resource pool 400 are sufficient to meet the signal processing resource volume predicted by the satellite-ground collaborative scheduling module 100, it will deploy resources in advance. For example, if it is predicted that data from 1,000 terminals needs to be processed, requiring 10 virtualized signal processing nodes 410, then the orchestration management module 200 can deploy 10 instances to prevent resource waste.

[0062] Starting up can be achieved by running a pre-created virtualized signal processing node 410, for example, by calling the cloud platform's standard API interface based on a pre-made image of the virtualized signal processing node 410. Scaling up can be considered as increasing the number of virtualized signal processing nodes 410.

[0063] For example, suppose the satellite-ground coordinated scheduling module 100 predicts that a low-Earth orbit satellite will generate a processing demand requiring 15 virtualized signal processing nodes 410 when it passes overhead. After checking that there is more than 15 nodes available in the resource pool 400, the orchestration management module 200 will automatically start the 15 virtualized signal processing nodes 410 that are in a ready state by calling the cloud platform's API a few minutes before the low-Earth orbit satellite passes overhead. This ensures that when the digital signal sent by the radio frequency front end arrives at the resource pool 400, the corresponding instance is already in place and can be put into use immediately without waiting for a temporary resource allocation and loading process.

[0064] In this embodiment, by preparing signal processing resources in advance before the low-orbit satellite passes overhead, the processing delay introduced by real-time resource scheduling can be reduced, ensuring low latency and high efficiency in data processing.

[0065] In some embodiments, the satellite-ground coordinated scheduling module 100 is further configured to: predict the spatial position change of each low-orbit satellite in the low-orbit satellite constellation relative to the ground station during its transit based on the orbit prediction information; and generate data routing link configuration information corresponding to each low-orbit satellite based on the spatial position change of each low-orbit satellite relative to the ground station during its transit.

[0066] Among these, changes in spatial position can be predicted based on orbit prediction information. The space-ground coordinated scheduling module 100 can calculate the continuous trajectory of the low-orbit satellite during its transit, thereby obtaining parameters such as its instantaneous azimuth, zenith angle, and slant range relative to the ground station.

[0067] Based on the predicted spatial location changes, the satellite-ground coordinated scheduling module 100 generates corresponding data routing link configuration information. The data routing link configuration information can include how digital signals should flow from the ground station's radio frequency front-end to the corresponding virtualized signal processing node 410 in the resource pool 400 during different stages of low-Earth orbit satellite transit.

[0068] Based on this, in terms of dynamically arranging the data routing links between each virtualized signal processing node 410 and the radio frequency front-end of the ground station, the network resource control module 300 is specifically used to: adjust the data routing links between each virtualized signal processing node 410 and the radio frequency front-end of the ground station according to the data routing link configuration information corresponding to each low-orbit satellite.

[0069] For example, after receiving the data routing link configuration information issued by the satellite-ground collaborative scheduling module 100, the network resource control module 300 parses it into specific network control commands. These commands can be sent to network devices such as virtual switches in the cloud platform through the southbound interface, thereby adjusting the data routing links. The adjustment of the data routing links can be dynamic and continuous, thus achieving seamless switching of data routing links and ensuring the continuity of data upload services from IoT devices.

[0070] In this embodiment, the space-ground collaborative scheduling module 100 predicts the spatial position changes of low-orbit satellites and generates data routing link configuration information in advance. Then, the network resource control module 300 dynamically adjusts the data routing links based on this information, ensuring the stability of the data routing links during the transit of low-orbit satellites and solving the problems of signal interruption and reduced processing efficiency caused by changes in the position of low-orbit satellites.

[0071] In some embodiments, the data routing link configuration information corresponding to each low-Earth orbit satellite includes data routing link configuration information between the target intermediate frequency (IF) processing unit and at least one target baseband processing unit. The target IF processing unit is an IF processing unit connected to the radio frequency (RF) front-end corresponding to the low-Earth orbit satellite. Specifically, the target IF processing unit refers to the IF processing unit directly connected to the RF front-end of the ground station tracking the low-Earth orbit satellite. The at least one target baseband processing unit is a group of baseband processing units capable of processing the baseband signal output by the target IF processing unit.

[0072] In generating data routing link configuration information for each low-Earth orbit satellite based on its spatial position relative to the ground station during its transit, the satellite-ground collaborative scheduling module 100 is specifically used for: First, the number of baseband processing units that the target intermediate frequency processing unit needs to connect to is determined based on the number of registered IoT terminals within the geographical area covered after the change in spatial location.

[0073] For example, the satellite-ground coordinated scheduling module 100 first determines the geographical range currently covered by the low-orbit satellite's beam based on the real-time spatial position changes of the satellite. Then, it counts the number of registered IoT terminals within that range by analyzing the geographic spatial distribution of IoT terminals in the business requirement information.

[0074] For example, a baseband processing unit 412 can process access requests from up to 120 IoT terminals in parallel. If there are 1200 terminals in the coverage area, then theoretically at least 10 baseband processing units 412 are needed.

[0075] Secondly, based on the idle status of the baseband processing units 412 in each virtualized signal processing node 410 in the resource pool 400, the corresponding number of target baseband processing units are selected according to the number of baseband processing units required to be connected to the target intermediate frequency processing unit.

[0076] The idle status of the baseband processing unit 412 can be the load rate, and a corresponding number of instances can be selected from the low-load baseband processing units 412 as the target baseband processing units.

[0077] Then, according to the preset data distribution strategy, the data routing link configuration information between the target intermediate frequency processing unit and each target baseband processing unit is determined.

[0078] The satellite-ground collaborative scheduling module 100 needs to determine how data is distributed from a single target intermediate frequency processing unit to multiple target baseband processing units. For example, the preset data distribution strategy can be round-robin distribution, which sends data to each target baseband processing unit in sequence, or load balancing distribution, which prioritizes sending data to the currently idle target baseband processing unit, or hash-based distribution, which sends data from the same IoT terminal to the same target baseband processing unit based on information such as the IoT terminal's identifier, to facilitate session maintenance.

[0079] In this embodiment, considering that the processing speed of the baseband processing unit 412 is slower than that of the intermediate frequency processing unit 411, multiple target baseband processing units can be configured for a single target intermediate frequency processing unit. That is, according to the real-time changes in the number of IoT terminals within the low-orbit satellite coverage area, the corresponding number of target baseband processing units can be adjusted as needed, and load balancing can be achieved through flexible data distribution strategies. This improves the utilization efficiency of the processing resources within the resource pool 400 and ensures that the cloud-based ground station system can still maintain high efficiency and stability when facing dynamically changing business loads.

[0080] In some embodiments, the satellite-ground coordinated scheduling module 100 is further configured to: First, based on the orbit prediction information, predict the Doppler frequency shift rate on the satellite-to-ground link for each low-Earth orbit satellite. The satellite-to-ground link includes the data routing link between the low-Earth orbit satellite and the radio frequency front end.

[0081] Considering the high-speed orbit of low-Earth orbit (LEO) satellites around the Earth, there is a relative velocity between them and ground stations, causing a frequency shift in the LEO satellite signals received by the radio frequency front-end, also known as Doppler shift. During the transit of LEO satellites, the magnitude and direction of the Doppler shift continuously change. The rate of change of the Doppler shift is called the Doppler shift rate of change. Without Doppler shift compensation, the baseband processing unit 412 will be unable to accurately lock and demodulate the signal, resulting in communication interruption.

[0082] In some embodiments, in the operation of predicting the rate of change of Doppler frequency shift on the satellite-to-ground link of each low-Earth orbit satellite based on the orbit prediction information, the satellite-to-ground coordinated scheduling module 100 is specifically used to: determine the relative motion speed between each low-Earth orbit satellite and the ground station based on the orbit prediction information; and predict the rate of change of Doppler frequency shift on the satellite-to-ground link of each low-Earth orbit satellite based on the relative motion speed between each low-Earth orbit satellite and the ground station.

[0083] As mentioned above, the space-to-ground link includes the wireless communication path from the low-Earth orbit (LEO) satellite to the radio frequency (RF) front-end of the ground station. Using the acquired orbit prediction information, the space-to-ground coordination scheduling module 100 can calculate the position and velocity vector of the LEO satellite at each moment within the future transit time window. Based on this information, the space-to-ground coordination scheduling module 100 can calculate the radial velocity change of the LEO satellite relative to the ground station and derive the Doppler shift rate of change at multiple moments during the transit.

[0084] Then, before each low-orbit satellite passes overhead, each Doppler frequency shift rate is sent to the baseband processing unit 412 connected to the radio frequency front-end in the corresponding satellite-to-ground link, so as to instruct the baseband processing unit 412 to perform Doppler frequency shift compensation when receiving the baseband signal output by the intermediate frequency processing unit 411.

[0085] After completing the prediction calculations, the space-ground coordinated scheduling module 100 sends the calculated Doppler frequency shift rate information as a parameter configuration to the baseband processing unit 412, which will serve this transit, before each low-Earth orbit satellite passes over. Before starting signal processing, the baseband processing unit 412 can know the Doppler frequency shift rate of the data routing link at multiple times during the low-Earth orbit satellite transit. Based on this parameter configuration, the baseband processing unit 412 can actively adjust its internal frequency synchronization loop parameters or directly perform digital frequency compensation on the received baseband signal, thereby reducing the impact of the Doppler effect.

[0086] In this embodiment, the stability of the data routing link can be ensured during the transit of low-orbit satellites by introducing predictive Doppler frequency shift compensation.

[0087] In some embodiments, the baseband processing unit 412 is specifically used for: When multiple IoT terminals covered by low-orbit satellites use unlicensed random access during their transit, a parallel demodulation mechanism is used to simultaneously detect and identify multiple random access preamble sequences in the received baseband signal.

[0088] The random access preamble is a specific sequence of signal codes sent by an IoT terminal when initiating random access. Traditional processing methods may involve scanning the received signal serially or with limited concurrency to match these preamble sequences, which is inefficient.

[0089] In this embodiment, the baseband processing unit 412, as a software functional entity, can dynamically instantiate a large number of parallel processing threads or tasks in the virtualized environment in which it runs. When a baseband signal mixed with multiple terminal signals is received, the baseband processing unit 412 can distribute the signal to these parallel processing threads, each thread being responsible for detecting and identifying one or a set of specific random access preamble sequences.

[0090] In this embodiment, by introducing a parallel demodulation mechanism in the baseband processing unit 412, the access capacity and response speed of the cloud-based ground station system can be improved, and the access latency and collision probability of IoT terminals can be reduced.

[0091] In some embodiments, after the low-Earth orbit satellite transit ends, the orchestration management module 200 releases or reduces the virtualized signal processing nodes 410 that are no longer needed according to a pre-configured strategy, and reclaims computing and storage resources.

[0092] In some application scenarios, suppose a low-Earth orbit (LEO) satellite IoT operator deploys a LEO satellite constellation in a target area, responsible for collecting data from 5,000 environmental monitoring IoT terminals within that area. Each IoT terminal reports data every 30 minutes, with a data packet size of 200 bytes.

[0093] When using traditional ground station solutions, operators need to build multiple fixed ground stations within the coverage area. Each ground station needs to be equipped with dedicated baseband processing equipment. The initial construction investment is large, and due to the lack of coordination between ground stations, only a single ground station within the coverage area can provide services when low-orbit satellites pass over, resulting in uneven resource utilization.

[0094] In the cloud-based ground station system of this invention, resource pool 400 is deployed on a cloud platform, and multiple ground stations are integrated into a unified resource pool 400 through virtualization technology. The satellite-ground collaborative scheduling module 100, based on low-Earth orbit satellite orbit prediction information, predicts that three low-Earth orbit satellites will pass over the area sequentially within the next 30 minutes, and that approximately 1200-1800 IoT terminals will be received during each satellite's transit. Based on the prediction results, the orchestration management module 200 pre-activates 15 virtualized signal processing nodes 410, each capable of processing access requests from approximately 120 IoT terminals in parallel. The network resource control module 300 orchestrates data routing links, or it can dynamically allocate bandwidth.

[0095] When a low-Earth orbit (LEO) satellite begins its transit, the virtualized signal processing node 410 is already in a ready state, without waiting for real-time resource scheduling. The baseband processing unit 412 employs a parallel demodulation mechanism, completing the detection and identification of thousands of random access preamble sequences within 10 seconds. Furthermore, compensation parameters are dynamically configured based on the Doppler shift rate to ensure stable link quality throughout the high-speed movement of the LEO satellite.

[0096] After the transit is completed, the orchestration management module 200 automatically releases nodes that are no longer needed and reclaims computing resources for use by subsequent transit windows or other businesses, thereby improving resource utilization.

[0097] Figure 4 This is a flowchart illustrating the resource scheduling method for low-Earth orbit satellite Internet of Things provided by the present invention, as shown below. Figure 4 As shown, the method includes the following: Step 201: The satellite-ground collaborative scheduling module obtains the orbit prediction information of each low-Earth orbit satellite in the low-Earth orbit satellite constellation and the service demand information of the Internet of Things terminal, and determines the amount of signal processing resources required for each low-Earth orbit satellite during its transit based on the orbit prediction information and service demand information.

[0098] Step 202: The orchestration management module performs lifecycle management on each virtualized signal processing node in the resource pool before the corresponding low-orbit satellite passes by, based on the amount of signal processing resources.

[0099] Step 203: The network resource control module dynamically arranges the data routing links between each virtualized signal processing node and the radio frequency front-end of the ground station.

[0100] Step 204: Each virtualized signal processing node in the resource pool deployed on the cloud platform sequentially processes the digital signals transmitted by the radio frequency front end into intermediate frequency, baseband, and communication protocol processing.

[0101] Step 205: The core network module forwards the data processed by each virtualized signal processing node to the target server.

[0102] In this embodiment, by virtualizing and deploying intermediate frequency processing, baseband processing, and protocol processing functions on a cloud platform, and using a satellite-ground collaborative scheduling module, an orchestration management module, and a network resource control module to manage each virtualized signal processing node in the resource pool, not only is the scalability of the ground station system improved, but the service carrying capacity of the cloud-based ground station system for large-scale low-orbit satellite constellations and massive IoT terminals is also enhanced.

[0103] Figure 5 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 5 As shown, the electronic device may include: a processor 610, a communications interface 620, a memory 630, and a communications bus 640, wherein the processor 610, the communications interface 620, and the memory 630 communicate with each other through the communications bus 640. The processor 610 can call logic instructions in the memory 630 to execute a resource scheduling method for low-Earth orbit satellite IoT, applicable to any of the aforementioned cloud-based ground station systems for low-Earth orbit satellite IoT. This method includes: a satellite-ground collaborative scheduling module acquiring orbit prediction information for each low-Earth orbit satellite in the low-Earth orbit satellite constellation and service requirement information for IoT terminals, and determining the amount of signal processing resources required for each low-Earth orbit satellite during its transit based on the orbit prediction information and service requirement information; an orchestration management module performing lifecycle management on each virtualized signal processing node in the resource pool before the corresponding low-Earth orbit satellite transits, based on the amount of signal processing resources; a network resource control module dynamically orchestrating data routing links between each virtualized signal processing node and the radio frequency front-end of the ground station; each virtualized signal processing node in the resource pool deployed on the cloud platform sequentially processing the digital signals transmitted by the radio frequency front-end using intermediate frequency, baseband, and communication protocols; and a core network module forwarding the processed data from each virtualized signal processing node to the target server.

[0104] Furthermore, the logical instructions in the aforementioned memory 630 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, in essence, 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 described in 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.

[0105] 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 resource scheduling method for low-Earth orbit satellite Internet of Things (LEO) provided by the above methods, and apply it to any of the above-mentioned cloud-based ground station systems for LEO satellite Internet of Things. The method includes: a satellite-ground collaborative scheduling module acquiring orbit prediction information of each LEO satellite in the LEO satellite constellation and service demand information of the Internet of Things terminal, and determining the amount of signal processing resources required for each LEO satellite during its transit based on the orbit prediction information and service demand information; an orchestration management module performing lifecycle management on each virtualized signal processing node in the resource pool before the corresponding LEO satellite transits according to the amount of signal processing resources; a network resource control module dynamically orchestrating the data routing links between each virtualized signal processing node and the radio frequency front-end of the ground station; each virtualized signal processing node in the resource pool deployed on the cloud platform sequentially performing intermediate frequency, baseband, and communication protocol processing on the digital signals sent by the radio frequency front-end; and a core network module forwarding the data processed by each virtualized signal processing node to the target server.

[0106] 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 is implemented to perform the resource scheduling method for low-Earth orbit satellite Internet of Things (LEO) provided by the above methods. This method is applied to any of the cloud-based ground station systems for LEO satellite Internet of Things. The method includes: a satellite-ground collaborative scheduling module acquiring orbit prediction information of each LEO satellite in the LEO satellite constellation and service demand information of the Internet of Things terminal, and determining the amount of signal processing resources required for each LEO satellite during its transit based on the orbit prediction information and service demand information; an orchestration management module performing lifecycle management on each virtualized signal processing node in the resource pool before the corresponding LEO satellite transits according to the amount of signal processing resources; a network resource control module dynamically orchestrating the data routing links between each virtualized signal processing node and the radio frequency front-end of the ground station; each virtualized signal processing node in the resource pool deployed on the cloud platform sequentially performing intermediate frequency, baseband, and communication protocol processing on the digital signals sent by the radio frequency front-end; and a core network module forwarding the processed data from each virtualized signal processing node to the target server.

[0107] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0108] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0109] 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 cloud-based ground station system for low-Earth orbit satellite Internet of Things, characterized in that, include: The satellite-ground collaborative scheduling module is used to obtain the orbit prediction information of each low-Earth orbit satellite in the low-Earth orbit satellite constellation and the service demand information of the Internet of Things terminal, and to determine the amount of signal processing resources required for each low-Earth orbit satellite during its transit based on the orbit prediction information and the service demand information. The orchestration management module is used to perform lifecycle management of each virtualized signal processing node in the resource pool before the corresponding low-orbit satellite passes by, based on the amount of signal processing resources. The network resource control module is used to dynamically arrange the data routing links between each virtualized signal processing node and the radio frequency front-end of the ground station; A resource pool deployed on a cloud platform includes several virtualized signal processing nodes managed by the orchestration management module. Each virtualized signal processing node includes an intermediate frequency processing unit, a baseband processing unit, and a protocol processing unit to sequentially process the digital signals transmitted by the radio frequency front end using intermediate frequency, baseband, and communication protocol methods. The core network module is used to forward the data processed by each of the virtualized signal processing nodes to the target server.

2. The cloud-based ground station system according to claim 1, characterized in that, In the operation of lifecycle management of each virtualized signal processing node in the resource pool before the corresponding low-Earth orbit satellite passes over, based on the amount of signal processing resources, the orchestration management module is specifically used for: Determine whether the current available signal processing resources in the resource pool meet the required signal processing resource quantity; If the conditions are not met, a preset resource preemption operation is performed based on the resource shortage between the amount of signal processing resources and the amount of available signal processing resources. The preset resource preemption operation includes releasing virtualized signal processing nodes that process low-priority services based on the resource shortage.

3. The cloud-based ground station system according to claim 2, characterized in that, If the current available signal processing resources in the resource pool meet the required signal processing resource quantity, the orchestration management module is further configured to: Before each of the aforementioned low-orbit satellites passes overhead, the corresponding virtualized signal processing nodes are activated or expanded according to the amount of signal processing resources available.

4. The cloud-based ground station system according to any one of claims 1 to 3, characterized in that, The satellite-ground coordinated scheduling module is also used for: Based on the orbit prediction information, predict the spatial position change of each of the low-Earth orbit satellites in the low-Earth orbit satellite constellation relative to the ground station during their transit; Data routing link configuration information for each of the low-orbit satellites is generated based on the changes in their spatial position relative to the ground station during their transit. In terms of dynamically orchestrating the data routing links between the virtualized signal processing nodes and the radio frequency front-end of the ground station, the network resource control module is specifically used for: Based on the data routing link configuration information corresponding to each of the low-orbit satellites, adjust the data routing link between each of the virtualized signal processing nodes and the radio frequency front-end of the ground station.

5. The cloud-based ground station system according to claim 4, characterized in that, The data routing link configuration information corresponding to each of the low-orbit satellites includes the data routing link configuration information between the target intermediate frequency processing unit and at least one target baseband processing unit. The target intermediate frequency processing unit is an intermediate frequency processing unit connected to the radio frequency front-end of the low-orbit satellite. In the operation of generating data routing link configuration information for each of the low-Earth orbit satellites based on their spatial position changes relative to the ground station during their transit, the satellite-ground collaborative scheduling module is specifically used for: The number of baseband processing units required to be connected to the target intermediate frequency processing unit is determined based on the number of registered IoT terminals within the geographical area covered after the change in spatial location. Based on the idle status of the baseband processing units in each virtualized signal processing node in the resource pool, select the corresponding number of target baseband processing units according to the number of baseband processing units required to be connected to the target intermediate frequency processing unit; According to the preset data distribution strategy, the data routing link configuration information between the target intermediate frequency processing unit and each of the target baseband processing units is determined.

6. The cloud-based ground station system according to any one of claims 1 to 3, characterized in that, In determining the amount of signal processing resources required during the transit of each of the low-Earth orbit satellites based on the orbit prediction information and the service demand information, the satellite-ground coordinated scheduling module is specifically used for: Based on the orbit prediction information, determine the total geographical area covered by each of the low-orbit satellites during its transit. Based on the total geographical area and the business demand information, determine the number of registered IoT terminals within the total geographical area and the size of IoT terminal data sent by each IoT terminal. The amount of signal processing resources required during the transit of each low-Earth orbit satellite is determined based on the number of registered IoT terminals within the total geographical area and the size of the IoT terminal data sent by each IoT terminal.

7. The cloud-based ground station system according to any one of claims 1 to 3, characterized in that, The satellite-ground coordinated scheduling module is also used for: Based on the orbit prediction information, predict the Doppler frequency shift rate on the satellite-to-ground link where each of the low-Earth orbit satellites is located, wherein the satellite-to-ground link includes the data routing link between the low-Earth orbit satellite and the radio frequency front end; Before each of the low-orbit satellites passes overhead, the Doppler frequency shift rate of each satellite is sent to the baseband processing unit connected to the radio frequency front-end in the corresponding satellite-to-ground link, so as to instruct the baseband processing unit to perform Doppler frequency shift compensation when receiving the baseband signal output by the intermediate frequency processing unit.

8. The cloud-based ground station system according to claim 7, characterized in that, In the operation of predicting the Doppler shift rate of change on the satellite-to-ground link for each of the aforementioned low-Earth orbit satellites based on the orbit prediction information, the satellite-to-ground coordinated scheduling module is specifically used for: Based on the orbit prediction information, determine the relative motion speed between each of the low-Earth orbit satellites and the ground station; Based on the relative motion speed between each low-Earth orbit satellite and the ground station, the Doppler frequency shift rate on the satellite-to-ground link of each low-Earth orbit satellite is predicted.

9. The cloud-based ground station system according to any one of claims 1 to 3, characterized in that, The baseband processing unit is specifically used for: When multiple IoT terminals covered by the low-orbit satellite use unlicensed random access during its transit, a parallel demodulation mechanism is used to simultaneously detect and identify multiple random access preamble sequences in the received baseband signal.

10. A resource scheduling method for low-Earth orbit satellite Internet of Things, characterized in that, Applied to the cloud-based ground station system as described in any one of claims 1 to 9, the method comprises: The satellite-ground collaborative scheduling module acquires the orbit prediction information of each low-Earth orbit satellite in the low-Earth orbit satellite constellation and the service demand information of the Internet of Things terminal, and determines the amount of signal processing resources required for each low-Earth orbit satellite during its transit based on the orbit prediction information and the service demand information. The orchestration management module performs lifecycle management on each virtualized signal processing node in the resource pool before the corresponding low-orbit satellite passes by, based on the amount of signal processing resources. The network resource control module dynamically arranges the data routing links between each virtualized signal processing node and the radio frequency front-end of the ground station; Each virtualized signal processing node in the resource pool deployed on the cloud platform sequentially processes the digital signal transmitted by the radio frequency front end into intermediate frequency, baseband, and communication protocol processing. The core network module forwards the data processed by each virtualized signal processing node to the target server.

11. An electronic device 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 resource scheduling method for low-Earth orbit satellite Internet of Things as described in claim 10.

12. 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 resource scheduling method for low-Earth orbit satellite Internet of Things as described in claim 10.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the resource scheduling method for low-Earth orbit satellite Internet of Things as described in claim 10.

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