Interference data calculation method and apparatus, and storage medium

Abstract

The present disclosure relates to an interference data calculation method and apparatus, and a storage medium. The method comprises: for a multi-shell NGSO satellite system, using a spatial probability-based interference analysis method to determine total interference data from a communication link of the multi-shell NGSO satellite system to a communication link of a GSO satellite system. In this way, the total interference data from the communication link of the multi-shell NGSO satellite system to the communication link of the GSO satellite system can be determined, and the calculation overhead is low and the efficiency is high.

Description

Interference data calculation method and device, and storage medium TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of communications, and particularly relates to an interference data calculation method and device and storage medium. BACKGROUND

[0002] Large-scale low-orbit satellite Internet has attracted widespread attention in recent years and becomes an important supplement and expansion of global communication networks. A non-geostationary orbit (NGSO) satellite system can provide high-speed, low-latency Internet services with global coverage by deploying a large number of near-earth orbit NGSO satellites, and has a significant advantage in remote and underdeveloped areas. In this context, the frequency compatibility problem of low-orbit satellite Internet and other adjacent frequency systems has become an obstacle to its development, and the frequency compatibility coordination problem with geostationary orbit (GSO) satellite systems is a major challenge.

[0003] SUMMARY

[0004] The interference data calculation method, device and storage medium provided by the embodiments of the present disclosure are used to solve the problem of how to calculate the total interference data of the communication link of a multi-shell NGSO satellite system on the communication link of a GSO satellite system.

[0005] The embodiments of the present disclosure provide an interference data calculation method, device and storage medium.

[0006] According to a first aspect of the embodiments of the present disclosure, an interference data calculation method is provided, comprising: for a multi-shell NGSO satellite system, using a spatial probability interference analysis method to determine the total interference data of the communication link of the multi-shell NGSO satellite system on the communication link of a GSO satellite system.

[0007] In the above embodiments, the total interference data of the communication link of the multi-shell NGSO satellite system on the communication link of the GSO satellite system can be determined, and the calculation overhead is low and the efficiency is high.

[0008] According to a second aspect of the embodiments of the present disclosure, an interference data calculation device is provided, comprising: a processing module configured to, for a multi-shell NGSO satellite system, use a spatial probability interference analysis method to determine the total interference data of the communication link of the multi-shell NGSO satellite system on the communication link of a GSO satellite system.

[0009] According to a third aspect of the embodiments of the present disclosure, a communication device is provided, comprising: one or more processors; a memory coupled to the processors, the memory having instructions stored thereon that, when executed by the processors, cause the communication device to perform the method of the first aspect.

[0010] According to a fourth aspect of the present disclosure, a storage medium is provided that stores instructions which, when executed on a communication device, cause the communication device to perform the method described in the first aspect. Attached Figure Description

[0011] Figure 1 is an architecture diagram of a communication system provided in an embodiment of this disclosure;

[0012] Figure 2 is a flowchart of an interference data calculation method provided in an embodiment of this disclosure;

[0013] Figure 3 is a schematic diagram of interference between an NGSO satellite system and a GSO satellite system downlink, according to an embodiment of this disclosure.

[0014] Figure 4 is a flowchart of S1 in an interference data calculation method provided in an embodiment of this disclosure;

[0015] Figure 5 is a flowchart of step S11 in an interference data calculation method provided in an embodiment of this disclosure;

[0016] Figure 6 is a schematic diagram of an orbital shell and a gridded orbital shell provided in an embodiment of the present disclosure;

[0017] Figure 7 is a flowchart of a spatial probability-based simulation method provided in an embodiment of this disclosure;

[0018] Figure 8 is a schematic diagram of a model used to calculate the spatial probability density of a satellite according to an embodiment of this disclosure;

[0019] Figure 9 is a schematic diagram comparing the accuracy of two different calculation strategies provided in the embodiments of this disclosure;

[0020] Figure 10 is a schematic diagram of approximating a trapezoidal region as a rectangular region during integration according to an embodiment of this disclosure;

[0021] Figure 11 is a schematic diagram showing the difference in accuracy between the two probability calculation methods provided in the embodiments of this disclosure and the geocentric angle;

[0022] Figure 12 is a schematic diagram of interference between an NGSO satellite system and a GSO satellite system provided in an embodiment of this disclosure;

[0023] Figure 13 is a flowchart of a time-stepping-based simulation method provided in an embodiment of this disclosure;

[0024] Figure 14 is a flowchart of another interference data calculation method provided in an embodiment of this disclosure;

[0025] Figure 15 is a schematic diagram of an interference simulation result provided by an embodiment of this disclosure;

[0026] Figure 16 is a structural diagram of an interference data calculation device provided in an embodiment of this disclosure;

[0027] Figure 17 is a structural diagram of a communication device provided in an embodiment of this disclosure;

[0028] Figure 18 is a structural diagram of a chip provided in an embodiment of this disclosure. Detailed Implementation

[0029] This disclosure provides a method, apparatus, and storage medium for calculating interference data.

[0030] In a first aspect, embodiments of this disclosure propose an interference data calculation method, comprising: for a multi-shell NGSO satellite system, using a spatial probability interference analysis method to determine the total interference data of the communication link of the multi-shell NGSO satellite system to the communication link of the GSO satellite system.

[0031] In the above embodiments, it is possible to determine the total interference data between the communication link of the multi-shell NGSO satellite system and the communication link of the GSO satellite system, with low computational overhead and high efficiency.

[0032] In conjunction with some embodiments of the first aspect, in some embodiments, a spatial probability interference analysis method is used to determine the total interference data of the communication link of the multi-shell NGSO satellite system to the communication link of the GSO satellite system, including: using a spatial probability interference analysis method to determine the interference probability data of the communication link of the NGSO satellite subsystem of each shell in the multi-shell NGSO satellite system to the communication link of the GSO satellite system; and determining the total interference data based on the interference probability data of multiple shells.

[0033] In the above embodiments, the spatial probability interference analysis method is used to determine the interference probability data of the communication link of the single-shell NGSO satellite subsystem to the communication link of the GSO satellite system. Then, based on the interference probability data of multiple shells, the total interference data is determined. Compared with calculating the total interference data of the communication link of the NGSO satellite system to the communication link of the GSO satellite system of multiple shells together, the complexity can be reduced and the computational efficiency can be improved.

[0034] In conjunction with some embodiments of the first aspect, in some embodiments, a spatial probability interference analysis method is used to determine the interference probability data of the communication link of the NGSO satellite subsystem of each shell in the multi-shell NGSO satellite system to the communication link of the GSO satellite system. This includes: using a spatial probability interference analysis method to determine multiple shell configurations of each shell, as well as the configuration probabilities and interference data corresponding to the shell configurations; and determining the interference probability data of each shell based on the configuration probabilities and interference data corresponding to the multiple shell configurations of each shell.

[0035] In conjunction with some embodiments of the first aspect, in some embodiments, a spatial probability interference analysis method is used to determine multiple shell configurations for each shell layer and the configuration probabilities corresponding to the shell configurations, including: using a spatial probability interference analysis method to divide each shell layer by a specified geocentric angle to determine multiple shell configurations; and determining the configuration probabilities corresponding to each shell configuration based on the latitude and longitude intervals determined by the specified geocentric angle for each shell configuration.

[0036] In the above embodiments, the rasterization method in the spatial probability interference analysis method is optimized. Based on the latitude and longitude interval determined by a specified geocentric angle for each shell configuration, the configuration probability corresponding to the shell configuration is determined, which can improve the simulation accuracy.

[0037] In conjunction with some embodiments of the first aspect, in some embodiments, determining the interference probability data of each shell layer based on the configuration probabilities and interference data corresponding to the multiple shell layer configurations of each shell layer includes: sampling the configuration probabilities and interference data corresponding to the multiple shell layer configurations of each shell layer according to the sorting of the interference data to determine the sample shell layer configuration among the multiple shell layer configurations of each shell layer; and determining the interference probability data of each shell layer based on the configuration probabilities and interference data corresponding to the sample shell layer configuration of each shell layer.

[0038] In the above embodiments, sample shell configurations are obtained by sampling multiple shell configurations of each shell, and then the interference probability data of each shell is determined based on the configuration probability and interference data corresponding to the sample shell configuration of each shell, which can save computational overhead and improve computational efficiency.

[0039] In conjunction with some embodiments of the first aspect, in some embodiments, the configuration probabilities and interference data corresponding to multiple shell configurations of each shell layer are sampled according to the sorting of the interference data to determine the sample shell configuration among the multiple shell configurations of each shell layer. This includes: sorting the configuration probabilities and interference data corresponding to multiple shell configurations of each shell layer from smallest to largest according to the interference data, and dividing the interference data into two groups of data with a preset value; sampling the first group of data at a preset interval, and retaining the maximum value of the second group of data and deleting other data; and determining the sample shell configuration among the multiple shell configurations of each shell layer based on the equally spaced sampling result and the maximum value retained in the second group of data.

[0040] In conjunction with some embodiments of the first aspect, in some embodiments, determining the total interference data based on the interference probability data of multiple shells includes: performing convolution calculation on the interference probability data of multiple shells to determine the total interference probability data.

[0041] In the above embodiments, convolution calculation is performed on the interference probability data of multiple shells to determine the total interference probability data, which can reduce complexity, save computational overhead, and improve computational efficiency.

[0042] In conjunction with some embodiments of the first aspect, in some embodiments, convolution calculation is performed on the interference probability data of multiple shells, including: converting the interference probability data of multiple shells into linear values; and performing convolution calculation on the linear values ​​of multiple shells.

[0043] In conjunction with some embodiments of the first aspect, in some embodiments, the communication link of a multi-shell NGSO satellite system includes at least one of the following: an uplink between at least one NGSO satellite of the multiple shells and an NGSO earth station; and a downlink between at least one NGSO satellite of the multiple shells and an NGSO earth station.

[0044] In conjunction with some embodiments of the first aspect, in some embodiments, the communication link of the GSO satellite system includes at least one of the following: an uplink between the GSO satellite and the GSO earth station; and a downlink between the GSO satellite and the GSO earth station.

[0045] Secondly, embodiments of this disclosure provide an interference data calculation device, wherein the first device includes at least one of a transceiver module and a processing module; wherein the interference data calculation device is used to execute an optional implementation of the first aspect.

[0046] Thirdly, embodiments of this disclosure provide a communication device, which includes: one or more processors; and a memory coupled to the processors, the memory storing instructions that, when executed by the processors, cause the communication device to perform the method described in the first aspect.

[0047] Fourthly, embodiments of this disclosure provide a storage medium storing instructions that, when executed on a communication device, cause the communication device to perform the method described in the optional implementation of the first aspect.

[0048] Fifthly, embodiments of this disclosure provide a program product that, when executed by a communication device, causes the communication device to perform the method described in the optional implementation of the first aspect.

[0049] In a sixth aspect, embodiments of this disclosure provide a computer program that, when run on a computer, causes the computer to perform the method as described in the alternative implementation of the first aspect.

[0050] In a seventh aspect, embodiments of this disclosure provide a chip or chip system. The chip or chip system includes processing circuitry configured to perform the method described in the optional implementation of the first aspect above.

[0051] Understandably, the aforementioned interference data calculation device, communication equipment, storage medium, program product, computer program, chip, or chip system are all used to execute the methods proposed in the embodiments of this disclosure. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0052] This disclosure provides a method, apparatus, and storage medium for calculating interference data. In some embodiments, the terms "interference data calculation method" and "information processing method," "communication method," etc., can be used interchangeably.

[0053] This disclosure is not exhaustive, but merely illustrative of some embodiments, and is not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment can be arbitrarily interchanged. Furthermore, the optional implementation methods in a particular embodiment can be arbitrarily combined; moreover, the embodiments can be arbitrarily combined, for example, some or all steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0054] In each of the disclosed embodiments, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of the embodiments are consistent and can be referenced by each other. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0055] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure.

[0056] In this embodiment of the disclosure, unless otherwise stated, elements expressed in the singular form, such as "a," "an," "the," "the," "the," "the," "the," "the," "this," etc., can mean "one and only one," or "one or more," "at least one," etc. For example, when using articles such as "a," "an," "the," etc. in translation, the noun following the article can be understood as either a singular expression or a plural expression.

[0057] In the embodiments of this disclosure, "multiple" refers to two or more.

[0058] In some embodiments, the terms “at least one of”, “one or more”, “a plurality of”, “multiple”, etc., may be used interchangeably.

[0059] In some embodiments, the notation "at least one of A and B", "A and / or B", "A in one case, B in another", "in response to one case A, in response to another case B", etc., may include the following technical solutions depending on the situation: in some embodiments, A (execute A regardless of B); in some embodiments, B (execute B regardless of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); in some embodiments, A and B (both A and B are executed). The same applies when there are more branches such as A, B, C, etc.

[0060] In some embodiments, the notation "A or B" may include the following technical solutions, depending on the situation: in some embodiments, A (execution of A regardless of B); in some embodiments, B (execution of B regardless of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The same applies when there are more branches such as A, B, C, etc.

[0061] The prefixes "first," "second," etc., used in the embodiments of this disclosure are merely for distinguishing different descriptive objects and do not impose restrictions on the position, order, priority, quantity, or content of the descriptive objects. The description of the descriptive objects is found in the claims or the context of the embodiments, and the use of prefixes should not constitute unnecessary restrictions. For example, if the descriptive object is a "field," the ordinal numbers preceding "field" in "first field" and "second field" do not restrict the position or order of the "fields." "First" and "second" do not restrict whether the "fields" they modify are in the same message, nor do they restrict the order of "first field" and "second field." Similarly, if the descriptive object is a "level," the ordinal numbers preceding "level" in "first level" and "second level" do not restrict the priority between "levels." Furthermore, the number of descriptive objects is not limited by ordinal numbers and can be one or more. For example, in "first device," the number of "devices" can be one or more. Furthermore, the objects modified by different prefixes can be the same or different. For example, if the object being described is "device", then "first device" and "second device" can be the same device or different devices, and their types can be the same or different. Similarly, if the object being described is "information", then "first information" and "second information" can be the same information or different information, and their content can be the same or different.

[0062] In some embodiments, “including A,” “containing A,” “for indicating A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0063] In some embodiments, the terms “in response to…”, “in response to determining…”, “in the case of…”, “when…”, “if…”, “if…”, etc., can be used interchangeably.

[0064] In some embodiments, the terms “greater than”, “greater than or equal to”, “not less than”, “more than”, “more than or equal to”, “not less than”, “higher than”, “higher than or equal to”, “not lower than”, and “above” can be used interchangeably, as can the terms “less than”, “less than or equal to”, “not greater than”, “less than”, “less than or equal to”, “not more than”, “lower than”, “lower than or equal to”, “not higher than”, and “below”.

[0065] In some embodiments, devices, etc., can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. Terms such as “device”, “equipment”, “circuit”, “network element”, “node”, “function”, “unit”, “section”, “system”, “network”, “chip”, “chip system”, “entity”, and “subject” can be used interchangeably.

[0066] In some embodiments, "network" can be interpreted as devices included in a network (e.g., access network devices, core network devices, etc.).

[0067] In some embodiments, the terms "access network device (AN device)," "radio access network device (RAN device)," "base station (BS)," "radio base station," "fixed station," "node," "access point," "transmission point (TP)," "reception point (RP)," "transmission / reception point (TRP)," "panel," "antenna panel," "antenna array," "cell," "macro cell," "small cell," "femto cell," "pico cell," "sector," "cell group," "serving cell," "carrier," "component carrier," "bandwidth part (BWP)," and "access network element" can be used interchangeably.

[0068] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", "subscriber station", "mobile unit", "subscriber unit", "wireless unit", "remote unit", "mobile device", "wireless device", "wireless communication device", "remote device", "mobile subscriber station", "access terminal", "mobile terminal", "wireless terminal", "remote terminal", "handset", "user agent", "mobile client", and "client" can be used interchangeably.

[0069] In some embodiments, access network devices, core network devices, or network devices can be replaced by terminals. For example, embodiments of this disclosure can also be applied to structures where communication between access network devices, core network devices, or network devices and terminals is replaced by communication between multiple terminals (e.g., device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, the structure can also be configured such that the terminal has all or part of the functions of the access network device. Furthermore, terms such as "uplink" and "downlink" can be replaced with terms corresponding to communication between terminals (e.g., "sidelink"). For example, uplink channel, downlink channel, etc., can be replaced with sidelink channel, and uplink link, downlink, etc., can be replaced with sidelink link.

[0070] In some embodiments, the terminal may be replaced by an access network device, a core network device, or a network device. In this case, the access network device, core network device, or network device may also be configured to have all or some of the functions of the terminal.

[0071] In some embodiments, the acquisition of data, information, etc., may comply with the laws and regulations of the country where the location is situated.

[0072] In some embodiments, data, information, etc., may be obtained with the user's consent.

[0073] Furthermore, each element, each row, or each column in the table of this disclosure can be implemented as an independent embodiment, and any combination of any element, any row, or any column can also be implemented as an independent embodiment.

[0074] Figure 1 is an architecture diagram of a communication system provided in an embodiment of this disclosure.

[0075] As shown in Figure 1, the communication system 100 includes a terminal 101 and a network device 102.

[0076] In some embodiments, terminal 101 includes, but is not limited to, at least one of the following: mobile phone, wearable device, Internet of Things device, car with communication function, smart car, tablet computer, computer with wireless transceiver function, virtual reality (VR) terminal device, augmented reality (AR) terminal device, wireless terminal device in industrial control, wireless terminal device in self-driving, wireless terminal device in remote medical surgery, wireless terminal device in smart grid, wireless terminal device in transportation safety, wireless terminal device in smart city, and wireless terminal device in smart home.

[0077] In some embodiments, network device 102 may include at least one of access network device and core network device.

[0078] In some embodiments, the access network device is, for example, a node or device that connects a terminal to a wireless network. The access network device may include, but is not limited to, at least one of the following in a 5G communication system: evolved Node B (eNB), next-generation eNB (ng-eNB), next-generation Node B (gNB), node B (NB), home node B (HNB), home evolved node B (HeNB), radio backhaul device, radio network controller (RNC), base station controller (BSC), base transceiver station (BTS), base band unit (BBU), mobile switching center, base station in a 6G communication system, open RAN, cloud RAN, base station in other communication systems, and access node in a Wi-Fi system.

[0079] In some embodiments, the core network equipment may be a single device, including a first network element, a second network element, etc., or it may be multiple devices or a group of devices, each including all or part of the first network element, second network functions, etc. Network functions may be virtual or physical. The core network may include, for example, at least one of the evolved packet core (EPC), 5G core network (5GCN), and next-generation core (NGC).

[0080] In some embodiments, the first network element is, for example, a network data analytics function (NWDAF).

[0081] In some embodiments, the second network element is, for example, the access and mobility management function (AMF).

[0082] In some embodiments, the first network element is designed to support network automation and intelligence by analyzing and utilizing network data to optimize network performance, manage network resources, and provide a better user experience.

[0083] In some embodiments, NWDAF is a key component of the fifth-generation (5G) network architecture, defined by the 3rd generation partnership project (3GPP) in the 5G standard.

[0084] In some embodiments, the second network element is used for access control and mobility management of terminal access to the operator's network, including functions such as mobility state management, allocation of temporary user identity identifiers, authentication and authorization of users, and its name is not limited thereto.

[0085] It is understood that the communication system described in this disclosure is for the purpose of more clearly illustrating the technical solutions of this disclosure, and does not constitute a limitation on the technical solutions proposed in this disclosure. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions proposed in this disclosure are also applicable to similar technical problems.

[0086] The following embodiments of this disclosure can be applied to the communication system 100 shown in FIG1, or to some of the main bodies, but are not limited thereto. The main bodies shown in FIG1 are illustrative. The communication system may include all or some of the main bodies in FIG1, or may include other main bodies outside of FIG1. ​​The number and form of each main body are arbitrary. Each main body may be physical or virtual. The connection relationship between the main bodies is illustrative. The main bodies may not be connected or may be connected. The connection can be in any way, it can be a direct connection or an indirect connection, it can be a wired connection or a wireless connection.

[0087] The embodiments disclosed herein can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), Super 3G, IMT-Advanced, 4th Generation Mobile Communication System (4G), 5th Generation Mobile Communication System (5G), 5G New Radio (NR), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New Radio Access (NX), Future Generation Radio Access (FX), Global System for Mobile Communications (GSM), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, and Ultra-Wideband. The technologies used include UWB (Ultra-Wideband), Bluetooth (a registered trademark), public land mobile network (PLMN) networks, device-to-device (D2D) systems, machine-to-machine (M2M) systems, Internet of Things (IoT) systems, vehicle-to-everything (V2X) systems, systems utilizing other communication methods, and next-generation systems built upon them. Furthermore, multiple systems can be combined (e.g., a combination of LTE or LTE-A with 5G).

[0088] In related technologies, how to calculate the total interference data of the communication link of the multi-shell NGSO satellite system to the communication link of the GSO satellite system is an urgent problem to be solved.

[0089] Based on this, embodiments of this disclosure provide a method, apparatus, and storage medium for calculating interference data. The method includes: for a multi-shell NGSO satellite system, employing a spatial probability interference analysis method to determine the total interference data between the communication link of the multi-shell NGSO satellite system and the communication link of the GSO satellite system. This enables the determination of the total interference data between the communication link of the multi-shell NGSO satellite system and the communication link of the GSO satellite system, with low computational overhead and high efficiency.

[0090] Figure 2 is a flowchart illustrating an interference data calculation method according to an embodiment of the present disclosure. As shown in Figure 2, this disclosure relates to an interference data calculation method, which includes:

[0091] S1. For multi-shell NGSO satellite systems, the spatial probability interference analysis method is used to determine the total interference data of the communication link of the multi-shell NGSO satellite system to the communication link of the GSO satellite system.

[0092] Large-scale low-Earth orbit (LEO) satellite internet has received widespread attention in recent years, becoming an important supplement and extension to global communication networks. Non-Geostationary Orbit (NGSO) satellite systems, by deploying a large number of low-Earth orbit (LEO) NGSO satellites, can provide high-speed, low-latency internet services with global coverage, offering significant advantages, especially in remote and underdeveloped regions. Against this backdrop, frequency compatibility issues between LEO satellite internet and other co-channel or adjacent-channel systems have become an obstacle to its development. Among these, frequency compatibility coordination with Geostationary Orbit (GSO) satellite systems is a major challenge, as illustrated in Figure 3.

[0093] Among them, GSO satellites operate in Earth orbit at an altitude of approximately 36,000 km, possessing advantages such as relative stationary position relative to the ground and extremely wide Earth coverage. Therefore, many important services, such as broadcasting and navigation, are deployed via GSO satellites. Combined with their significantly higher manufacturing and launch costs compared to low-Earth orbit satellites, the GSO satellite system holds a high position in frequency coordination, and other co-channel and adjacent-channel satellite systems must meet considerably stringent interference protection standards to ensure the protection of the GSO satellite system. Due to the necessity of protecting the GSO satellite system, some simulation-based interference calculation and analysis methods have been proposed. However, the methods commonly used in these technologies suffer from low efficiency when analyzing complex, large-scale constellation systems.

[0094] In related technologies, spatial probability interference analysis methods are mainly applied to the interference analysis of communication links of single-shell NGSO satellite systems on communication links of GSO satellite systems.

[0095] In this embodiment of the disclosure, a spatial probability interference analysis method is employed for multi-shell NGSO satellite systems to determine the total interference data between the communication links of the multi-shell NGSO satellite system and the communication links of the GSO satellite system. This method can determine the total interference data between the communication links of the multi-shell NGSO satellite system and the GSO satellite system with low computational overhead and high efficiency.

[0096] In some embodiments, the communication link of a multi-shell NGSO satellite system includes at least one of the following:

[0097] Uplink between at least one NGSO satellite with multiple shells and an NGSO earth station;

[0098] Downlink between at least one NGSO satellite with multiple shells and an NGSO earth station.

[0099] In some embodiments, the communication link of the GSO system includes at least one of the following:

[0100] Uplink between GSO satellite and GSO earth station;

[0101] Downlink between GSO satellites and GSO earth stations.

[0102] In some embodiments, for a multi-shell NGSO satellite system, a spatial probability interference analysis method is used to determine the uplink between at least one NGSO satellite and an NGSO earth station in multiple shells of the multi-shell NGSO satellite system, and the total interference data between the uplink between the GSO satellite and the GSO earth station in the GSO satellite system.

[0103] In some embodiments, for a multi-shell NGSO satellite system, a spatial probability interference analysis method is used to determine the downlink between at least one NGSO satellite and an NGSO earth station in multiple shells of the multi-shell NGSO satellite system, and the total interference data between the uplink between the GSO satellite and the GSO earth station in the GSO satellite system.

[0104] In some embodiments, for a multi-shell NGSO satellite system, a spatial probability interference analysis method is used to determine the total interference data of the uplink between at least one NGSO satellite and an NGSO earth station in multiple shells of the multi-shell NGSO satellite system and the downlink between GSO satellites and GSO earth stations in the GSO satellite system.

[0105] In some embodiments, for a multi-shell NGSO satellite system, a spatial probability interference analysis method is used to determine the downlink between at least one NGSO satellite and an NGSO earth station in multiple shells of the multi-shell NGSO satellite system, and the total interference data of the downlink between the GSO satellite and the GSO earth station in the GSO satellite system.

[0106] As shown in Figure 4, in some embodiments, S201, for multi-shell NGSO satellite systems, a spatial probability interference analysis method is used to determine the total interference data between the communication link of the multi-shell NGSO satellite system and the communication link of the GSO satellite system, including:

[0107] S11: Using spatial probability interference analysis, determine the probability data of interference between the communication links of each shell NGSO satellite subsystem and the communication links of the GSO system in the multi-shell NGSO satellite system.

[0108] In this embodiment of the disclosure, a spatial probability interference analysis method is used to determine the interference probability data of the communication link of the NGSO satellite subsystem of each shell in the multi-shell NGSO satellite system to the communication link of the GSO system.

[0109] As shown in Figure 5, in some embodiments, S11: using a spatial probability interference analysis method, the interference probability data of the communication link of each shell NGSO satellite subsystem in the multi-shell NGSO satellite system to the communication link of the GSO system is determined, including:

[0110] S111: Using spatial probability interference analysis, determine multiple shell configurations for each shell, as well as the configuration probabilities and interference data corresponding to the shell configurations.

[0111] S112: Determine the interference probability data for each shell based on the configuration probabilities and interference data corresponding to multiple shell configurations for each shell.

[0112] Understandably, spatial probability-based interference analysis methods simulate the spatial distribution of interference sources and their impact on communication links through statistical and probabilistic models of satellite positions, thereby evaluating the system's performance under different interference conditions. This method typically models the reachable region of NGSO satellite positions in the NGSO satellite system as an orbital shell, and then rasterizes the orbital shell with a certain precision, as illustrated in Figure 6. The overall workflow of this method is shown in Figure 7.

[0113] The simulation process for the spatial probability interference analysis method used by a single-shell NGSO satellite system on a GSO satellite system is as follows:

[0114] 1. Set the latitude and longitude coordinates of the GSO earth station of the GSO satellite system and the NGSO earth station of the NGSO satellite system on the Earth's surface, and complete the location and antenna modeling of the earth station.

[0115] 2. Set the orbital longitude of the GSO satellite and complete the modeling of the GSO satellite position and antenna.

[0116] 3. Set the basic parameters such as the altitude, inclination, and number of orbital satellites for each NGSO satellite in the NGSO satellite system, and complete the modeling and rasterization of the orbital shell of the NGSO satellite system.

[0117] 4. Traverse the grid with the reference satellite (i.e., the NGSO satellite) and generate a shell configuration for each grid cell, or a shell configuration, and assign the configuration probability of the shell configuration to the probability that the reference satellite is located in that grid cell.

[0118] 5. Under each shell configuration, each system earth station selects link-connecting satellites, as shown in Figure 3.

[0119] 6. Based on the completed link modeling, perform lumped interference calculation on the disturbed link, and obtain the probability weight of the calculation result as the configuration probability of the corresponding shell configuration.

[0120] 7. Traverse all shell configurations to obtain the probability data of interference between a single-shell NGSO satellite system and the GSO satellite system link.

[0121] In this embodiment, a spatial probability interference analysis method is used to determine multiple shell configurations for each shell, as well as the configuration probabilities and interference data corresponding to the shell configurations.

[0122] In some embodiments, S111: using a spatial probability interference analysis method to determine multiple shell configurations for each shell layer, as well as configuration probabilities and interference data corresponding to the shell configurations, includes: using a spatial probability interference analysis method to divide each shell layer by a specified geocentric angle to determine multiple shell configurations; and determining the configuration probability corresponding to each shell configuration based on the latitude and longitude interval determined by the specified geocentric angle for each shell configuration.

[0123] Understandably, when using spatial probability-based interference analysis, a shell-based rasterization process is required first, typically using geocentric angle division. Furthermore, when calculating the probability of the reference satellite (i.e., the NGSO satellite) being located in each region, the geocentric angle-based probability calculation method in ITU-R S.1257 is referenced. This method contains some approximations, which significantly reduce accuracy. Simulations show that the satellite position probability calculated using geocentric angles for all divided regions is approximately 96%, a loss of 4%. To improve simulation accuracy, the circular region shown in ITU-R S.1257 is considered to be changed to a very small rectangular region, as shown in Figure 8.

[0124] Regarding the probability P that the track passes through the region h According to ITU-R S.1529,

[0125] Where L is the latitude of the satellite's nadir point.

[0126] Unlike the ITU-R S.1257 model, the average length of the region is no longer the same as that of the circular region. Therefore, the average length I needs to be calculated for the rectangular region. m As shown below:

[0127] Where Δ long Δ la These represent the geocentric angles of the region in terms of longitude and latitude, respectively, r c The geocentric angle corresponding to the distance between two tangent orbits.

[0128] Therefore, the probability P of a satellite landing in the region while its orbit passes through it is... i :

[0129] Therefore, the probability of the satellite's position is:

[0130] It can be seen that this is actually the satellite positioning probability formula used in the final part of this paper. Based on this, let this region be infinitely small, then we have:

[0131] Equation (4) is actually an approximation, assuming that the arc length corresponding to the region in the longitude direction is approximately equal to the arc length corresponding to the geocentric angle in the longitude direction. Since the region being analyzed is very small, this approximation is reasonable.

[0132] Where R e Let L be the Earth's radius, L be the latitude of the region, d_long be the increment of the region's longitude, and d_latitude be the increment of the region's latitude. Based on this, the probability density over this refined region is calculated using the following formula:

[0133] Where i is the orbital inclination, this formula is actually the same as the description of the probability density of circular orbits in ITU-R S.1529. This indicates that the latitude and longitude-based satellite position probability derivation method in ITU-R S.1529 is actually similar to that in ITU-R S.1257. The difference is that ITU-R S.1257 uses this method to directly describe the position probability of a region, while the derivation in this section uses this method to analyze a very small region and calculate the corresponding probability density. Based on this, the idea of ​​integration can be used to calculate the position probability more accurately.

[0134] Obviously, the probability result obtained based on the idea of ​​integration will be better than the method in ITU-R S.1257. Therefore, we consider making improvements based on this: In order to save unnecessary simulation time, we still consider dividing the orbital plane with a fixed geocentric angle. When calculating the position probability, we convert the geocentric angle interval relationship of the region into the latitude and longitude interval relationship. We then integrate (6) according to the required latitude and longitude interval to obtain the probability of the satellite being located in each region.

[0135] According to this method, the total probability sum calculated after dividing the orbital shell into regions at a 3dB beamwidth for each segmented orbital shell is shown in Figure 9.

[0136] As can be seen, the regional probability sums obtained using the integration method are all around 100%, which means there is almost no loss of precision. It is important to note that the integration method extracts the latitude and longitude intervals of the region divided by the geocentric angle. However, for the region divided by the geocentric angle, the corresponding latitude and longitude interval is actually a trapezoid. Therefore, the integration method actually approximates the integration interval, as shown in Figure 10.

[0137] To investigate whether such approximation significantly affects the results, the probability density was integrated over a region with a central latitude of 30° using trapezoidal and approximate rectangular intervals under different geocentric angles for regional division. The actual and approximate probabilities of the region were obtained, and the difference between the actual and approximate probabilities was calculated. Furthermore, a probability was calculated for this region using the geocentric angle, and the difference between the actual and approximate probabilities was also calculated. The final result is shown in Figure 11.

[0138] As can be seen, the accuracy loss increases significantly with the increase of the geocentric angle, and the larger the geocentric angle, the greater the accuracy loss per geocentric angle step. This can be explained by the fact that under larger geocentric angles, the integration interval is larger, and approximating the trapezoid as a rectangle naturally leads to a larger error. However, in reality, due to the narrow beamwidth of the earth station, the geocentric angles determined are usually very small. Therefore, a better analysis method is considered to be: using the geocentric angle determined by the 3dB beamwidth of the earth station as the dividing standard to divide the orbital shell to save unnecessary simulation time, then determining the latitude and longitude intervals of each divided region, and calculating the region probability by integral of the equation. This calculation method is not more complicated than the geocentric angle-based scheme, and the final probability accuracy is even better than ITU-R S.1257.

[0139] In this embodiment, a spatial probability-based interference analysis method is employed. Each shell layer is divided at a specified geocentric angle to determine multiple shell layer configurations. Based on the latitude and longitude intervals determined by the specified geocentric angle for each shell layer configuration, the configuration probability corresponding to that configuration is determined. This embodiment optimizes the rasterization method, thereby improving simulation accuracy.

[0140] In some embodiments, interference from a typical NGSO satellite system's communication link to a GSO satellite system's communication link is considered. The interference is mainly determined by the direction of the interfering end, the direction of the interfered end, the distance between them, and the feeder loss. Taking downlink interference as an example, as shown in Figure 12, the main beam of the NGSO satellite antenna points to the NGSO earth station and simultaneously interferes with the GSO earth station in the direction of off-axis angle θ3. The interfered GSO earth station receives this interference at a gain of off-axis angle θ4. The radiation gain in the direction of interference and the receiving gain in the direction of interference are given by the relevant antenna pattern.

[0141] The satellite-to-ground link is typically modeled using a free-space loss model that incorporates shadowing fading, atmospheric loss, and ground object loss. Therefore, the downlink interference power of the interfering satellite to the disturbed GSO earth station can be given by the following expression: P r [dBW] = P t [dBW]+G t (θ3)[dBi]+L f [dB]+G r (θ4)[dBi].

[0142] Among them, P t For the NGSO satellite's transmission power, G t (θ3) represents the transmit gain of the NGSO satellite downlink to the GSO earth station direction, L f For link loss, G r (θ4) represents the receiving gain of the GSO earth station in the direction of the NGSO satellite.

[0143] It should be noted that the above example is also applicable to the calculation of uplink interference power. The embodiments of this disclosure can calculate and determine the interference data corresponding to the shell configuration using the above expressions.

[0144] In some embodiments, S112: Determining the interference probability data of each shell layer based on the configuration probabilities and interference data corresponding to the multiple shell layer configurations of each shell layer includes: sampling the configuration probabilities and interference data corresponding to the multiple shell layer configurations of each shell layer according to the sorting of the interference data to determine the sample shell layer configuration among the multiple shell layer configurations of each shell layer; and determining the interference probability data of each shell layer based on the configuration probabilities and interference data corresponding to the sample shell layer configuration of each shell layer.

[0145] In this embodiment of the disclosure, the configuration probabilities and interference data corresponding to multiple shell configurations of each shell are sampled according to the sorting of the interference data to determine the sample shell configurations among the multiple shell configurations of each shell. This can filter out a portion of the configuration probabilities and interference data corresponding to the shell configurations, and it has been verified that this does not affect the accuracy of the calculation. Furthermore, based on the configuration probabilities and interference data corresponding to the sample shell configurations of each shell, the interference probability data of each shell can be determined, which can optimize the algorithm and save computational overhead.

[0146] In some embodiments, the configuration probabilities and interference data corresponding to multiple shell configurations of each shell are sampled according to the sorting of the interference data to determine the sample shell configuration among the multiple shell configurations of each shell, including: sorting the configuration probabilities and interference data corresponding to multiple shell configurations of each shell from smallest to largest according to the interference data, and dividing the interference data into two groups of data with a preset value; sampling the first group of data at a preset interval, and retaining the maximum value of the second group of data and deleting other data; and determining the sample shell configuration among the multiple shell configurations of each shell based on the sampling results at equal intervals and the maximum value retained in the second group of data.

[0147] In some embodiments, the preset value is to sort the interference data from smallest to largest, and the data that is in the top 99.9% of the sorted data.

[0148] Please refer to Figure 2. After executing S11, continue to execute S12.

[0149] S12: Determine the total interference data based on the interference probability data of multiple shells.

[0150] In this embodiment of the disclosure, after obtaining the interference probability data of each of the multiple shells, the total interference data can be determined based on the interference probability data of the multiple shells.

[0151] In some embodiments, interference calculation is performed using a time-sampling-based simulation analysis method. This method divides time into multiple discrete small steps to progressively simulate the position changes and link states of each communication node in the satellite system. The overall simulation flow of the time-sampling method is shown in Figure 13.

[0152] The simulation process of the NGSO satellite system using the time sampling method for the GSO satellite system is as follows:

[0153] 1. Set the latitude and longitude coordinates of the GSO earth station of the GSO satellite system and the NGSO earth station of the NGSO satellite system on the Earth's surface, and complete the location and antenna modeling of the earth station.

[0154] 2. Set the orbital longitude of the GSO satellite and complete the modeling of the GSO satellite position and antenna.

[0155] 3. Set the basic parameters such as the altitude, inclination, and number of orbital satellites for each NGSO satellite in the NGSO satellite system, and complete the initial modeling of the NGSO satellite positions and antennas.

[0156] 4. The location information of the communication nodes is sampled based on the time stepping method to obtain "snapshots" of the simulation scene at different sampling times.

[0157] 5. Under each "snapshot", the GSO earth station of the GSO satellite system and the NGSO earth station of the NGSO satellite system select the linked satellites, as shown in Figure 3.

[0158] 6. Based on the link modeling completed in each "snapshot", perform lumped interference calculation on the disturbed links.

[0159] 7. Traverse all "snapshots" to obtain the probability data of interference between the NGSO satellite system and the GSO satellite system link.

[0160] Regarding interference assessment methods for large-scale low-Earth orbit (LEO) NGSO and GSO satellite systems, some embodiments use traditional spatial probabilistic methods to simulate and evaluate single-orbit shell large-scale LEO NGSO satellite system scenarios. In other embodiments, a simplified rasterization method for the spatial probabilistic approach in the Walker constellation system is observed, which can reduce simulation overhead by a factor of several times compared to traditional methods, making spatial probabilistic simulation methods more efficient. Such methods can also be used in the technical solutions of this disclosure. In some embodiments, a stochastic geometric approach is used to analytically evaluate the probability distribution of indicators such as the signal-to-interference-plus-noise ratio (SINR) of the satellite system to the ground. Although this cannot perfectly align with actual conditions, it can provide a very quick and rough assessment method for the initial design of the satellite system. As for time-sampling simulation methods, many studies use them, and they will not be specifically listed here.

[0161] Among them, the simulation method based on time sampling needs to continuously calculate the position information of each NGSO satellite in the NGSO satellite system according to the sampling step size. The simulation calculation overhead increases with the increase of the scale of NGSO satellites, so it is gradually becoming difficult to adapt to the scenario modeling and simulation analysis of the current ultra-large-scale NGSO satellite system.

[0162] Compared to time-sampling methods, spatial probability-based simulation methods do not require continuous estimation of the orbital positions of NGSO satellites, saving considerable computational overhead and thus are generally more efficient.

[0163] However, when the NGSO satellite system has multiple shells (all orbital planes with the same inclination and orbital altitude are called an orbital shell), since there is no correlation between the positions of NGSO satellites in different orbital shells, the spatial probability method needs to generate a set of shell configurations and configuration probabilities for each shell separately, and then arrange and combine the shell configurations and configuration probabilities between different shells to obtain all the shell configurations and configuration probabilities of the multi-shell NGSO satellite system.

[0164] In some embodiments, S12: Determining total interference data based on the interference probability data of multiple shells includes: performing convolution calculation on the interference probability data of multiple shells to determine the total interference probability data.

[0165] Understandably, for a multi-shell NGSO satellite system with M shells, assuming each shell is divided into N configuration data points, and the total interference probability data is obtained by summing the N configuration data points from the M shells, the complexity of the spatial probabilistic method is O(N). M The complexity increases exponentially with the number of shell layers, which significantly affects simulation efficiency.

[0166] This disclosure addresses the problem that spatial probability-based simulation analysis methods become unusable in scenarios where the communication link of an NGSO satellite system interferes with the communication link of a GSO satellite system, due to the exponential increase in simulation overhead when dealing with large-scale, complex, multi-shell NGSO satellite systems. It primarily proposes a novel, efficient simulation analysis method. This method applies a spatial probability-based simulation method to each shell of the NGSO satellite system to obtain multiple sets of interference probability data. These interference probability data are then fitted into multiple sets of probability density functions. Finally, these probability density functions are convolved to obtain the statistical data of the lumped interference of the entire system, i.e., the total interference data. The proposed method simplifies the exponential increase in complexity that originally occurred with the number of shells to a linear increase in complexity, significantly improving simulation efficiency.

[0167] In the simulation scenario of interference from a multi-shell NGSO satellite system to a GSO earth station, the positions of the satellites in each shell are independent, and the GSO earth station's pointing direction is fixed. Therefore, the interference from each shell to the GSO earth station is independent. Based on this property, a more efficient simulation analysis method is proposed. The overall flow of this method is shown in Figure 14, and its specific implementation is as follows:

[0168] 1. For each shell of a multi-shell satellite system with M orbital shells, N shell configurations and configuration probabilities are generated for each shell using a spatial probability simulation method. The simulation process of spatial probability is shown in Figure 7.

[0169] 2. For each orbital shell, spatial probability interference analysis was used to obtain the probability data f1, f2, ..., f of each shell with respect to interference from the GSO earth station. M ;

[0170] 3. For the probability data of interference in each shell, convolution is used to process the data to obtain the probability data of lumped interference of all shells to the GSO earth station: f1*f2*...*f M Here, "*" represents convolution, and f is the probability data corresponding to lumped interference.

[0171] The reason this operation is feasible is that lumped disturbances are a linear sum of all disturbances, while for several independent random variables X1, X2, ..., X... M ,satisfy:

[0172] The proposed method performs separate interference analysis calculations based on spatial probability methods for each shell, and only performs convolution processing on the interference data of all shells at the end. Therefore, the complexity is O(MN), which is linear with the increase of the number of shells, effectively reducing the simulation overhead.

[0173] In this embodiment, convolution calculation is performed on the interference probability data of multiple shells to determine the total interference probability data. The required complexity is O(MN), which is linear with the increase of the number of shells, and can effectively reduce the computational overhead.

[0174] In some embodiments, convolution calculation is performed on the interference probability data of multiple shells, including: converting the interference probability data of multiple shells into linear values; and performing convolution calculation on the linear values ​​of multiple shells.

[0175] Understandably, when performing convolution processing on interference probability data, since the interference data is generally in dB units, it first needs to be converted into linear values. This is because convolution of probability functions does not hold true under non-linear relationships. For example:

[0176] [-100dB]+[0dB]≠[-50dB]+[-50dB]; where [.] represents converting dB to a linear value.

[0177] In this embodiment of the disclosure, the interference probability data of multiple shells is converted into linear values; convolution calculation is performed on the linear values ​​of multiple shells to determine the total interference probability data, which can reduce complexity, reduce computational overhead, and improve efficiency.

[0178] The beneficial effect of this disclosure is that it proposes a simulation analysis method for interference between the communication links of NGSO satellite systems and GSO satellite systems, applicable to various complex scenarios. It effectively utilizes the high simulation efficiency of spatial probabilistic simulation methods, solving the problem of significantly increased simulation overhead when dealing with complex satellite networks. To verify the feasibility and superiority of this method, specific simulation tests are conducted below.

[0179] To address the interference scenario of the communication link of a multi-shell NGSO satellite system on the communication link of a GSO satellite system, we first model the GSO earth station and its pointing direction. Then, we model NGSO earth stations with low-Earth orbit and high-Earth orbit shells around the GSO earth station. The interference link is determined through the satellite selection strategies of the GSO and NGSO earth stations, and the interference data of the two shells on the GSO earth station are obtained separately. Finally, the probability data of the lumped interference of these shells on the GSO earth station is calculated using the method mentioned above. This data can be further processed to obtain the cumulative distribution function (CDF) and complementary cumulative distribution function (CCDF) curves of various interference-related indicators. Table 1 below shows the parameters used in the simulation test, and Figure 15 shows the interference curves of the corresponding parameters under the time step and the proposed method.

[0180] Table 1

[0181] As shown in Figure 15, the two curves have a high degree of overlap, indicating that the embodiments of this disclosure can obtain simulation results with high consistency with the time-stepping method when analyzing interference scenarios of multi-shell NGSO satellite systems, and the simulation overhead is significantly reduced (the time spent generating time-stepped satellite orbit extrapolation data for the two shells exceeded 20 minutes in this simulation, but the proposed method only took less than 20 seconds). Furthermore, the time-stepping method does not easily determine the appropriate simulation time and step size to achieve convergence, which is not a problem for spatial probability methods. Finally, this simulation verifies the downlink interference scenario, but the technical solution proposed in this disclosure is also applicable to uplink interference analysis scenarios.

[0182] This disclosure recognizes that the motions of satellites in each shell of a multi-shell NGSO satellite system are independent, and the pointing of the disturbed GSO earth station is fixed, indicating that the interference from each shell to the GSO earth station is independent. When calculating interference, the interference from each shell needs to be summed to obtain the lumped interference. This satisfies a fundamental probabilistic property: the probability distribution of the sum of independent random variables is the convolution of the probability density functions of these independent random variables. Therefore, this disclosure utilizes this property to realize the probability distribution of lumped interference in a multi-shell NGSO satellite system by first calculating the interference probability density of each shell separately and then performing a convolution. This simplifies the exponential complexity of the original spatial probability simulation analysis method, which increases with the number of shells, to linear complexity, significantly reducing simulation overhead.

[0183] This disclosure also proposes an apparatus for implementing any of the above methods. For example, an apparatus is proposed that includes units or modules for implementing the steps performed by the apparatus in any of the above methods.

[0184] It should be understood that the division of units or modules in the above device is only a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, the units or modules in the device can be implemented by a processor calling software: for example, the device includes a processor connected to a memory containing instructions. The processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of the units or modules in the above device. The processor can be, for example, a general-purpose processor, such as a Central Processing Unit (CPU) or a microprocessor, and the memory can be internal or external to the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits. The functionality of some or all of the units or modules can be achieved through the design of these hardware circuits, which can be understood as one or more processors. For example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC). The functionality of some or all of the units or modules is achieved through the design of the logical relationships between the components within the circuit. In another implementation, the hardware circuit can be implemented using a programmable logic device (PLD). Taking a field-programmable gate array (FPGA) as an example, it can include a large number of logic gates. The connection relationships between the logic gates are configured through configuration files, thereby achieving the functionality of some or all of the units or modules. All units or modules of the above device can be implemented entirely through processor-called software, entirely through hardware circuits, or partially through processor-called software with the remaining parts implemented through hardware circuits.

[0185] In this embodiment, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction read and execute capabilities, such as a Central Processing Unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. The logical relationships of the aforementioned hardware circuits are fixed or reconfigurable. For example, the processor is a hardware circuit implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. Furthermore, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a Neural Network Processing Unit (NPU), a Tensor Processing Unit (TPU), or a Deep Learning Processing Unit (DPU).

[0186] Figure 16 is a schematic diagram of the structure of the interference data calculation device proposed in an embodiment of this disclosure. As shown in Figure 16, the interference data calculation device 10 may include at least one of a transceiver module 11, a processing module 12, etc.

[0187] In some embodiments, the processing module 12 is used to determine the total interference data of the communication link of the multi-shell NGSO satellite system to the communication link of the GSO system by employing a spatial probability interference analysis method for the multi-shell NGSO satellite system.

[0188] The processing module 12 described above is used to execute at least one of the processing steps performed by the interference data calculation device 10 in any of the above methods (but not limited to this), which will not be described in detail here.

[0189] In some embodiments, the transceiver module may include a transmitting module and / or a receiving module, which may be separate or integrated. Optionally, the transceiver module may be interchangeable with a transceiver.

[0190] In some embodiments, the processing module may be a single module or may include multiple sub-modules. Optionally, the multiple sub-modules may each perform all or part of the steps required by the processing module. Optionally, the processing module may be interchangeable with a processor.

[0191] Figure 17 is a schematic diagram of the structure of the communication device 8100 proposed in an embodiment of this disclosure. The communication device 8100 can be an interference data calculation device, or a chip, chip system, or processor that supports the interference data calculation device in implementing any of the above methods. The communication device 8100 can be used to implement the methods described in the above method embodiments, and for details, please refer to the description in the above method embodiments.

[0192] As shown in Figure 17, the communication device 8100 includes one or more processors 8101. The processor 8101 can be a general-purpose processor or a dedicated processor, such as a baseband processor or a central processing unit (CPU). The baseband processor can be used to process communication protocols and communication data, while the CPU can be used to control communication devices (e.g., base stations, baseband chips, terminal devices, terminal device chips, DUs or CUs, etc.), execute programs, and process program data. Optionally, the communication device 8100 can be used to execute any of the above methods. Optionally, one or more processors 8101 can be used to invoke instructions to cause the communication device 8100 to execute any of the above methods.

[0193] In some embodiments, the communication device 8100 further includes one or more transceivers 8103. When the communication device 8100 includes one or more transceivers 8103, the transceivers 8103 perform at least one of the communication steps such as sending and / or receiving in the above method (e.g., S201B, S203B to S207B, S201C to S203C, S205C to S208C, S201D, S203D to S206D, S209D, S210D, but not limited thereto), and the processor 8101 performs at least one of other steps (e.g., S201A to S203A, S202B, S208B, S209B, S204C, S209C, S210C, S202D, S207D, S208D, but not limited thereto). In optional embodiments, the transceiver may include a receiver and / or a transmitter, which may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, interface, etc., can be used interchangeably; the terms transmitter, transmitting unit, transmitter, transmitting circuit, etc., can be used interchangeably; and the terms receiver, receiving unit, receiver, receiving circuit, etc., can be used interchangeably.

[0194] In some embodiments, the communication device 8100 further includes one or more memories 8102 for storing data. Optionally, all or part of the memories 8102 may be located outside the communication device 8100. In optional embodiments, the communication device 8100 may include one or more interface circuits 8104. Optionally, the interface circuits 8104 are connected to the memories 8102 and can be used to receive data from the memories 8102 or other devices, and to send data to the memories 8102 or other devices. For example, the interface circuits 8104 can read data stored in the memories 8102 and send the data to the processor 8101.

[0195] The communication device 8100 described in the above embodiments may be a network device or a terminal, but the scope of the communication device 8100 described in this disclosure is not limited thereto, and the structure of the communication device 8100 may not be limited by FIG17. The communication device may be a standalone device or a part of a larger device. For example, the communication device may be: (1) a standalone integrated circuit IC, or chip, or chip system or subsystem; (2) a collection of one or more ICs, optionally, the IC collection may also include storage components for storing data and programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, terminal device, smart terminal device, cellular phone, wireless device, handheld device, mobile unit, vehicle device, network device, cloud device, artificial intelligence device, etc.; (6) others, etc.

[0196] Figure 18 is a schematic diagram of the structure of chip 8200 according to an embodiment of this disclosure. For cases where the communication device 8100 can be a chip or a chip system, the schematic diagram of chip 8200 shown in Figure 18 can be referenced, but is not limited thereto.

[0197] Chip 8200 includes one or more processors 8201. Chip 8200 is used to perform any of the above methods.

[0198] In some embodiments, chip 8200 further includes one or more interface circuits 8202. Optionally, terms such as interface circuit, interface, and transceiver pin can be used interchangeably. In some embodiments, chip 8200 further includes one or more memories 8203 for storing data. Optionally, all or part of the memories 8203 may be located outside of chip 8200. Optionally, interface circuit 8202 is connected to memory 8203, and interface circuit 8202 can be used to receive data from memory 8203 or other devices, and interface circuit 8202 can be used to send data to memory 8203 or other devices. For example, interface circuit 8202 can read data stored in memory 8203 and send the data to processor 8201.

[0199] In some embodiments, the interface circuit 8202 performs at least one of the communication steps, such as sending and / or receiving, in the above-described method. For example, the interface circuit 8202 performing the communication steps, such as sending and / or receiving, in the above-described method means that the interface circuit 8202 performs data interaction between the processor 8201, the chip 8200, the memory 8203, or the transceiver device. In some embodiments, the processor 8201 performs at least one of the other steps.

[0200] This disclosure also proposes a storage medium storing instructions that, when executed on a communication device 8100, cause the communication device 8100 to perform any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but not limited thereto; it may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but not limited thereto; it may also be a temporary storage medium.

[0201] This disclosure also provides a program product that, when executed by the communication device 8100, causes the communication device 8100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0202] This disclosure also proposes a computer program that, when run on a computer, causes the computer to perform any of the above methods.

[0203] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0204] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0205] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for calculating interference data, characterized in that, include: For multi-shell non-Geostationary orbit (NGSO) satellite systems, a spatial probability interference analysis method is used to determine the total interference data between the communication links of the multi-shell NGSO satellite system and the communication links of the geostationary orbit (GSO) satellite system.

2. The method as described in claim 1, characterized in that, The method employing spatial probability interference analysis to determine the total interference data between the communication link of the multi-shell NGSO satellite system and the communication link of the GSO satellite system includes: The spatial probability interference analysis method is used to determine the interference probability data of the communication link of the NGSO satellite subsystem of each shell in the multi-shell NGSO satellite system to the communication link of the GSO satellite system. The total interference data is determined based on the interference probability data of multiple shells.

3. The method as described in claim 2, characterized in that, The method employing spatial probability interference analysis to determine the probability data of interference between the communication links of each NGSO satellite subsystem in the multi-shell NGSO satellite system and the communication links of the GSO satellite system includes: A spatial probability-based interference analysis method is used to determine multiple shell configurations for each shell layer, as well as the configuration probabilities and interference data corresponding to the shell configurations. The interference probability data for each shell is determined based on the configuration probabilities and interference data corresponding to multiple shell configurations for each shell.

4. The method as described in claim 3, characterized in that, The method employing spatial probability interference analysis to determine multiple shell configurations for each shell layer, and the configuration probabilities corresponding to the shell configurations, includes: A spatial probability-based disturbance analysis method is used to divide each shell layer by a specified geocentric angle, thereby determining multiple shell layer configurations; The configuration probability corresponding to each shell configuration is determined based on the latitude and longitude interval determined by the specified geocentric angle.

5. The method as described in claim 3 or 4, characterized in that, The step of determining the interference probability data for each shell based on the configuration probabilities and interference data corresponding to multiple shell configurations for each shell includes: For the configuration probabilities and interference data corresponding to multiple shell configurations of each shell, sampling is performed according to the sorting of the interference data to determine the sample shell configuration among the multiple shell configurations of each shell. Based on the configuration probability and interference data corresponding to the sample shell configuration of each shell, the interference probability data of each shell is determined.

6. The method as described in claim 5, characterized in that, The process of sampling configuration probabilities and interference data corresponding to multiple shell configurations for each shell layer, based on the sorting of the interference data, to determine the sample shell configuration among the multiple shell configurations for each shell layer includes: For each shell layer, the configuration probabilities and interference data corresponding to multiple shell configurations are sorted from smallest to largest according to the interference data, and the interference data is divided into two groups of data with a preset value. The first set of data in the two sets of data is sampled at preset intervals, and the maximum value of the second set of data in the two sets of data is retained while other data is deleted. Based on the equally spaced sampling results and the maximum value retained in the second set of data, the sample shell configurations among multiple shell configurations of each shell are determined.

7. The method according to any one of claims 2 to 6, characterized in that, The step of determining the total interference data based on the interference probability data of multiple shells includes: The total interference probability data is determined by performing convolution calculations on the interference probability data of multiple shells.

8. The method as described in claim 7, characterized in that, The convolution calculation of the interference probability data of multiple shells includes: The interference probability data of the multiple shells are converted into linear values; The linear values ​​of the multiple shells are convolved.

9. The method according to any one of claims 1 to 8, characterized in that, The communication link of the multi-shell NGSO satellite system includes at least one of the following: Uplink between at least one NGSO satellite with multiple shells and an NGSO earth station; Downlink between at least one NGSO satellite with multiple shells and an NGSO earth station.

10. The method according to any one of claims 1 to 8, characterized in that, The communication link of the GSO satellite system includes at least one of the following: Uplink between GSO satellite and GSO earth station; Downlink between GSO satellites and GSO earth stations.

11. A device for calculating interference data, characterized in that, include: The processing module is used to determine the total interference data between the communication link of the multi-shell NGSO satellite system and the communication link of the GSO satellite system by employing a spatial probability interference analysis method for the multi-shell NGSO satellite system.

12. A communication device, characterized in that, include: One or more processors; A memory coupled to the processor, the memory storing instructions that, when executed by the processor, cause the communication device to perform the method of any one of claims 1 to 10.

13. A storage medium storing instructions, characterized in that, When the instructions are executed on a communication device, the communication device performs the method as described in any one of claims 1 to 10.

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