A method and apparatus for reducing rain fade effects on a satellite gateway station communication link

Abstract

The application discloses a method and device for reducing the influence of rain attenuation on a satellite gateway station communication link, and belongs to the field of satellite communication. The application extracts real-time space-time coupled signal characteristics containing rain attenuation influence through historical multiple rounds of interaction data of the gateway station and the satellite, including transmission / reception power, frequency, and position information of both parties of communication, then adopts a double-target optimization deep learning model to synchronously predict power compensation values and frequency compensation values, and finally determines the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round according to the power compensation values and the frequency compensation values, so as to ensure that the gateway station transmits signals to the satellite at the optimal transmission power and frequency in the Nth round of communication, thereby dynamically compensating the rain attenuation of the link. Furthermore, the technical problem that the existing satellite gateway station rain attenuation resistance scheme excessively depends on meteorological data and only adjusts the signal power, and has hysteresis in response speed and limitations in compensation efficiency is solved.

Description

Technical Field

[0001] This application relates to the field of satellite communication technology, and in particular to a method and apparatus for reducing the impact of rain attenuation on satellite gateway communication links. Background Technology

[0002] In satellite communication systems, rain attenuation is one of the core environmental factors leading to link performance degradation. When radio waves pass through rainy areas, the absorption and scattering of electromagnetic waves by raindrops cause a sharp attenuation of signal power. This attenuation effect has significant frequency dependence (e.g., Ka-band attenuation can be more than 10 times that of C-band) and spatial variability (the median annual rain attenuation exceeds 30 dB in tropical rainforests, while it is less than 5 dB in deserts). The signal quality degradation caused by rain attenuation leads to a deterioration in the carrier-to-noise ratio (C / N) and an increase in the bit error rate (BER). In extreme cases, it may cause communication link interruptions, seriously threatening the availability and service quality of satellite communication systems.

[0003] Therefore, when designing and maintaining satellite communication systems, the impact of rain attenuation needs to be considered, and corresponding technical measures should be taken to reduce its influence on communication. Existing rain attenuation mitigation schemes generally adopt a technical approach of "predicting attenuation based on meteorological data - single-dimensional power adjustment." For example, patent publication number CN118038290A, entitled "A Ground-to-Space Collaborative Rain Attenuation Mitigation Method and System Based on Deep Learning Feature Framework," relies on ground meteorological station data to drive compensation decisions; another example is patent publication number CN117692081A, entitled "A Method and System for Predicting Rainfall Attenuation in Satellite Communication," which also relies on meteorological data to drive compensation decisions. However, existing rain attenuation mitigation schemes have the following drawbacks:

[0004] (1) Inherent latency of meteorological data links: Existing solutions heavily rely on ground-based meteorological stations or satellite-borne rainfall monitoring equipment to obtain real-time rainfall rate data. This technical architecture suffers from three layers of latency: data acquisition latency: meteorological sensor sampling intervals are typically ≥1 minute, making it impossible to capture the sudden characteristics of rainstorms (rainfall intensity change timescale ≤10 seconds); information transmission latency: the backhaul latency of meteorological data from the gateway station to the satellite reaches hundreds of milliseconds (especially in GEO satellite scenarios); model calculation latency: attenuation calculations based on models such as ITU-R P.618 require iterative calculations, further increasing processing latency. This cumulative latency causes compensation actions to always lag behind actual attenuation, increasing the risk of link interruption by more than 40% in rainstorm scenarios.

[0005] (2) Limitations of single-parameter adjustment: According to Mie scattering theory, the rain attenuation intensity has a nonlinear relationship with the ratio (λ / D) of the electromagnetic wave wavelength (λ) and the equivalent diameter of the raindrop: when the signal frequency (carrier frequency) increases, causing the wavelength to shorten to the size of a raindrop (e.g., in the Ka band, λ≈1cm, D≈2-3mm), the rain attenuation intensity increases exponentially (α∝f). 2.6 This spectral selective attenuation results in a carrier-to-noise ratio (C / N) loss of up to 10 dB during heavy rainfall in fixed-frequency operating mode. However, existing solutions employ a fixed-frequency operating mode and only propose a power compensation mechanism, failing to dynamically adjust the signal frequency.

[0006] There are currently no effective solutions to the technical problems of existing satellite gateway station rain attenuation schemes, which rely too much on meteorological data and only adjust signal power, resulting in lag in response speed and limitations in compensation effectiveness. Summary of the Invention

[0007] The embodiments of this disclosure provide a method and apparatus for reducing the impact of rain attenuation on satellite gateway communication links, so as to at least solve the technical problems of existing satellite gateway anti-rain attenuation schemes that rely too much on meteorological data and only adjust signal power, resulting in lag in response speed and limitations in compensation effectiveness.

[0008] According to one aspect of the present disclosure, a method for reducing the impact of rain attenuation on satellite gateway station communication links is provided, comprising: before the gateway station transmits a signal in the Nth round to the satellite, determining gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1; wherein, the gateway station signal information in the Nith round includes the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nith round, and the reception power and reception frequency of the gateway station signal received by the satellite in the Nith round; the satellite feedback signal information in the Nith round includes the transmission power and transmission frequency of the signal transmitted by the satellite to the gateway station in the Nith round, and the reception power and reception frequency of the gateway station signal received by the satellite in the Nith round; The receiving power and frequency of the satellite signal received by the gateway station in round Ni; i = 1 to k; a signal feature series is constructed based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1; wherein the signal feature series consists of the signal features from round Nk to round N-1; the signal feature series is analyzed using a pre-trained deep learning model to determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in round N; and the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in round N are determined based on the power compensation value and the frequency compensation value.

[0009] According to another aspect of the present disclosure, a storage medium is also provided, the storage medium including a stored program, wherein, when the program is executed, a processor performs any of the methods described above.

[0010] According to another aspect of the present disclosure, an apparatus for reducing the impact of rain attenuation on satellite gateway station communication links is also provided, comprising: an information determination module, configured to determine gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1 before the gateway station transmits the signal of round N to the satellite; wherein, the gateway station signal information of round Ni includes the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in round Ni, and the receiving power and receiving frequency of the gateway station signal received by the satellite in round Ni; the satellite feedback signal information of round Ni includes the transmission power and transmission frequency of the signal transmitted by the satellite to the gateway station in round Ni, and the receiving power and receiving frequency of the gateway station signal received by the satellite in round Ni. The system includes: a received satellite signal power and frequency; i = 1 to k; a feature determination module, used to construct a signal feature series based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1; wherein the signal feature series consists of signal features from round Nk to round N-1; a compensation value determination module, used to analyze the signal feature series using a pre-trained deep learning model to determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in round N; and a power and frequency determination module, used to determine the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in round N based on the power compensation value and the frequency compensation value.

[0011] According to another aspect of the present disclosure, an apparatus for reducing the impact of rain attenuation on satellite gateway communication links is also provided, comprising: a processor; and a memory connected to the processor, configured to provide the processor with instructions for processing the following steps: before the gateway station transmits a signal in the Nth round to the satellite, determining gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1; wherein the gateway station signal information in round Ni includes the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in round Ni, and the reception power and reception frequency of the gateway station signal received by the satellite in round Ni; the satellite feedback signal information in round Ni includes the transmission power and transmission frequency of the signal transmitted by the satellite to the gateway station in round Ni. The signal transmission power and frequency of the signal transmitted by the gateway station, and the receiving power and frequency of the satellite signal received by the gateway station in the Nith round; i = 1 to k; a signal feature series is constructed based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from the Nkth to the N-1th rounds; wherein the signal feature series consists of the signal features from the Nkth to the N-1th rounds; the signal feature series is analyzed using a pre-trained deep learning model to determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in the Nth round; and the transmission power and frequency of the signal transmitted by the gateway station to the satellite in the Nth round are determined based on the power compensation value and the frequency compensation value.

[0012] Before the gateway station transmits the Nth round of signals to the satellite, this application determines the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1 through the control center inside the gateway station. By determining the various signal parameters (transmit / receive power, frequency) and location information of the communication link itself, real-time self-extraction and predictive perception of rain attenuation characteristics are achieved, providing a forward-looking basis for subsequent compensation strategies. Then, based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1, the control center constructs a series of signal characteristics. Without waiting for ground meteorological station data (delay ≥ 1 minute), it directly extracts the spatiotemporal coupling attenuation characteristics (end-to-end delay < 10ms) from the signal and location information exchanged between the gateway station and the satellite, constructing an autonomous decision-making system that does not rely on external data, laying the foundation for real-time self-triggering of rain attenuation response. Secondly, the control center uses a pre-trained deep learning model to analyze the signal feature series and determine the power compensation and frequency compensation values ​​for the signal transmitted by the gateway station to the satellite in the Nth round. This model achieves power-frequency coordinated prediction through dual-objective optimization, providing precise adjustment commands for subsequent dual adjustment of power and frequency. Finally, based on the power compensation and frequency compensation values, the control center determines the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round. This ensures that in the Nth round of communication, the gateway station transmits signals to the satellite with optimal transmission power and frequency, thereby dynamically compensating for rain attenuation in the link and keeping the signal in a suitable operating state. This solves the technical problems of existing satellite gateway station rain attenuation anti-rain data schemes that rely too heavily on meteorological data and only adjust signal power, resulting in lag in response speed and limitations in compensation effectiveness. Attached Figure Description

[0013] The accompanying drawings, which are included to provide a further understanding of this disclosure and form part of this application, illustrate exemplary embodiments of the present disclosure and are used to explain the disclosure, but do not constitute an undue limitation thereof. In the drawings:

[0014] Figure 1 This is a hardware structure block diagram of a computing device for implementing the method described in Embodiment 1 of this disclosure;

[0015] Figure 2 This is a schematic diagram of the hardware architecture of a system for reducing the impact of rain attenuation on satellite gateway communication links according to Embodiment 1 of this disclosure;

[0016] Figure 3 This is a flowchart of a method for reducing the impact of rain attenuation on satellite gateway communication links according to Embodiment 1 of this application;

[0017] Figure 4 This is a schematic diagram of the communication process between the satellite and the gateway station according to Embodiment 1 of this application;

[0018] Figure 5 This is a schematic diagram of the message sent by the gateway station to the satellite in the (N-1)th round according to Embodiment 1 of this application;

[0019] Figure 6 This is a schematic diagram of the message sent by the satellite to the gateway station in the N-1th round according to Embodiment 1 of this application;

[0020] Figure 7 This is a schematic diagram of the message sent by the gateway station to the satellite in the Nth round according to Embodiment 1 of this application;

[0021] Figure 8 This is a schematic diagram of a message sent by a satellite to a gateway station in the Nth round, according to Embodiment 1 of this application.

[0022] Figure 9 This is a schematic diagram of the framework of the deep learning model according to Embodiment 1 of this application;

[0023] Figure 10 This is a schematic diagram of the device for reducing the impact of rain attenuation on satellite gateway communication links according to Embodiment 2 of this application;

[0024] Figure 11 This is a schematic diagram of the device for reducing the impact of rain attenuation on satellite gateway communication links according to Embodiment 3 of this application. Detailed Implementation

[0025] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this disclosure.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] Example 1

[0028] According to this embodiment, a method embodiment for reducing the impact of rain attenuation on satellite gateway communication links is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0029] The method embodiments provided in this example can be executed on a server or similar computing device. Figure 1 A hardware block diagram of a computing device is shown for implementing a method to reduce the impact of rain attenuation on satellite gateway communication links. (See diagram for example.) Figure 1 As shown, a computing device may include one or more processors (processors may include, but are not limited to, microprocessors such as MCUs or programmable logic devices such as FPGAs), memory for storing data, transmission devices for communication functions, and input / output interfaces. The memory, transmission devices, and input / output interfaces are connected to the processor via a bus. In addition, it may also include a display, keyboard, and cursor control device connected to the input / output interfaces. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, a computing device may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0030] It should be noted that the aforementioned one or more processors and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element in a computing device. As involved in the embodiments of this disclosure, the data processing circuits serve as processor control (e.g., selection of a variable resistor termination path connected to an interface).

[0031] The memory can be used to store software programs and modules of application software, such as the program instruction / data storage device corresponding to the method for reducing the impact of rain attenuation on satellite gateway communication links in the embodiments of this disclosure. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the above-mentioned method for reducing the impact of rain attenuation on satellite gateway communication links. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the computing device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0032] The transmission device is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the computing device's communications provider. In one example, the transmission device includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0033] The display can be, for example, a touchscreen liquid crystal display (LCD), which allows users to interact with the user interface of the computing device.

[0034] It should be noted here that, in some optional embodiments, the above... Figure 1 The computing device shown may include hardware elements (including circuitry), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. It should be noted that... Figure 1 This is only one instance of a specific particular instance, and is intended to illustrate the types of components that may exist in the aforementioned computing devices.

[0035] Figure 2 This is a schematic diagram of a system for reducing the impact of rain attenuation on satellite gateway communication links, as described in this embodiment. (Refer to...) Figure 2 As shown, the system includes a satellite 10 and a gateway station 20. The satellite 10 transmits each communication message to the ground-based gateway station 20. Each time the gateway station 20 sends uplink data to the satellite, it adjusts the signal transmission power and frequency based on the currently received message and previous communication messages before sending the corresponding message back to the satellite 10. The gateway station 20 is equipped with a control center that analyzes the currently received message and previous communication messages, and adjusts the signal transmission power and frequency based on the analysis results.

[0036] It should be noted that the control center in gateway station 20 can be equipped with the hardware structure described above.

[0037] Under the aforementioned operating environment, according to the first aspect of this embodiment, a method for reducing the impact of rain attenuation on satellite gateway station communication links is provided. This method comprises... Figure 2 The control center in the gateway station 20 shown is implemented. Figure 3 A flowchart illustrating the method is shown below. (Refer to...) Figure 3 As shown, the method includes:

[0038] S302: Before the gateway station transmits the signal of the Nth round to the satellite, determine the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1; wherein, the gateway station signal information of the Nith round includes the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nith round, and the receiving power and receiving frequency of the gateway station signal received by the satellite in the Nith round; the satellite feedback signal information of the Nith round includes the transmission power and transmission frequency of the signal transmitted by the satellite to the gateway station in the Nith round, and the receiving power and receiving frequency of the satellite signal received by the gateway station in the Nith round; i = 1~k;

[0039] S304: Construct a signal feature series based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1; wherein the signal feature series consists of the signal features from round Nk to round N-1;

[0040] S306: Using a pre-trained deep learning model, analyze the signal feature series to determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in the Nth round; and

[0041] S308: Based on the power compensation value and the frequency compensation value, determine the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round.

[0042] In this embodiment of the invention, a single round of communication is defined as the completion of a complete two-way signal interaction process between the gateway station and the satellite: the gateway station first sends a signal containing a message to the satellite via the uplink; after receiving and processing the signal from the gateway station, the satellite returns a signal containing the corresponding message to the gateway station via the downlink, such as... Figure 4 As shown. In addition, the gateway station has a pre-installed database for storing all messages generated during the two-way signal interaction between the gateway station and the satellite.

[0043] Before the gateway station 20 sends the Nth round of signals to the satellite 10, the control center pre-set within the gateway station 20 determines the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1 (corresponding to step S302). Specifically, the control center first retrieves all messages generated during the communication process between the gateway station 20 and the satellite 10 from the database for rounds Nk to N-1, parses the messages, and then extracts the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1 from the messages. The value of k can be customized according to the actual application scenario. By determining the various signal parameters (transmit / receive power, frequency) and location information of the communication link itself, real-time self-extraction and predictive perception of rain attenuation characteristics are achieved, providing a forward-looking basis for subsequent compensation strategies.

[0044] Taking N=10 and k=5 as an example, before the gateway station 20 sends the signal for the 10th round to the satellite 10, the control center needs to determine the gateway station signal information, satellite feedback signal information, gateway station position information, and satellite position information for rounds 5 to 9 (i.e., rounds 5, 6, 7, 8, and 9, a total of 5 rounds). Specifically, the gateway station signal information for each round from 5 to 9 includes the transmission power and frequency of the signal transmitted by the gateway station 20 to the satellite 10 in the current round, and the receiving power and frequency of the gateway station signal received by the satellite 10 in the current round. The satellite feedback signal information for each round from 5 to 9 includes the transmission power and frequency of the signal transmitted by the satellite 10 to the gateway station 20 in the current round, and the receiving power and frequency of the satellite signal received by the gateway station 20 in the current round. Taking the gateway station signal information and satellite feedback signal information from the 9th round as an example, the gateway station signal information for this round includes the transmission power and frequency of the signal transmitted by gateway station 20 to satellite 10 in the 9th round, and the receiving power and frequency of the gateway station signal received by satellite 10 in the 9th round. The satellite feedback signal information for this round includes the transmission power and frequency of the signal transmitted by satellite 10 to gateway station 20 in the 9th round, and the receiving power and frequency of the satellite signal received by gateway station 20 in the 9th round.

[0045] Then, the control center inside the gateway station 20 constructs a series of signal characteristics based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1 (corresponding to step S304). In this way, without waiting for ground meteorological station data (delay ≥ 1 minute), it directly extracts the spatiotemporally coupled signal characteristics including the rain attenuation effect from the signal information and location information of the gateway station-satellite interaction (end-to-end delay < 10ms), constructing an autonomous decision-making system that does not rely on external data (such as meteorological data), laying the foundation for realizing real-time self-triggering of rain attenuation response.

[0046] Next, the control center inside the gateway station 20 uses a pre-trained deep learning model to analyze the signal feature series and determine the power compensation and frequency compensation values ​​of the signal transmitted by the gateway station to satellite 10 in the Nth round (corresponding to step S306). Specifically, a deep learning model can be pre-trained, with the goal of accurately predicting the power compensation and frequency compensation values ​​of the signal transmitted by the gateway station to the satellite in the current round based on the signal features from multiple historical rounds. That is, the deep learning model is required to learn the impact of rain attenuation on the power and frequency of the two-way communication signal between the gateway station and the satellite from the signal features from multiple historical rounds, and provide corresponding power and frequency compensation values ​​from these impacts. Afterward, the trained deep learning model is deployed in the control center, allowing the control center to use the deep learning model to analyze the signal feature series to determine the power compensation and frequency compensation values ​​of the signal transmitted by the gateway station to the satellite in the Nth round. In this way, the control center realizes a closed loop from feature input to compensation decision, providing precise adjustment commands for subsequent dual adjustment of power and frequency.

[0047] Finally, the control center inside the gateway station 20 determines the transmission power and transmission frequency of the signal transmitted by the gateway station 20 to the satellite 10 in the Nth round based on the power compensation value and the frequency compensation value (corresponding to step S308). Specifically, the control center uses the power compensation value ΔP output by the deep learning model, combined with the nominal transmission power P of the current round... nom (e.g., a typical value of 35 dBW for the Ka band), using formula P tx =P nom +ΔP calculates the target transmit power. The control center uses the frequency compensation value Δf output by the deep learning model, combined with the channel center frequency f. center (e.g., 28GHz), through formula f tx =f center +Δf determines the target transmission frequency. In this way, the control center achieves a complete closed loop from compensation value calculation to hardware parameter determination, ensuring that in the Nth round of communication, the gateway station 20 sends signals to the satellite 10 with optimal transmission power and frequency, thereby dynamically compensating for rain attenuation in the link and keeping the signal in a suitable operating state.

[0048] As described in the background section, existing rain attenuation mitigation solutions heavily rely on ground-based meteorological stations or satellite-borne rainfall monitoring equipment to obtain real-time rainfall rate data, resulting in a lag in response speed. Furthermore, existing solutions employ a fixed-frequency operating mode and only propose power compensation mechanisms, failing to dynamically adjust the signal frequency, thus limiting their compensation effectiveness.

[0049] In view of this, before the gateway station sends the Nth round of signals to the satellite, the control center inside the gateway station determines the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1. By determining the various signal parameters (transmit / receive power, frequency) and location information of the communication link itself, real-time self-extraction and predictive perception of rain attenuation characteristics are achieved, providing a forward-looking basis for subsequent compensation strategies. Then, based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1, the control center constructs a series of signal characteristics. Without waiting for ground meteorological station data (delay ≥ 1 minute), it directly extracts the spatiotemporal coupling attenuation characteristics (end-to-end delay < 10ms) from the signal and location information exchanged between the gateway station and the satellite, constructing an autonomous decision-making system that does not rely on external data, laying the foundation for real-time self-triggering of rain attenuation response. Secondly, the control center uses a pre-trained deep learning model to analyze the signal feature series and determine the power compensation and frequency compensation values ​​for the signal transmitted by the gateway station to the satellite in the Nth round. This model achieves power-frequency coordinated prediction through dual-objective optimization, providing precise adjustment commands for subsequent dual adjustment of power and frequency. Finally, based on the power compensation and frequency compensation values, the control center determines the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round. This ensures that in the Nth round of communication, the gateway station transmits signals to the satellite with optimal transmission power and frequency, thereby dynamically compensating for rain attenuation in the link and keeping the signal in a suitable operating state. This solves the technical problems of existing satellite gateway station rain attenuation anti-rain data schemes that rely too heavily on meteorological data and only adjust signal power, resulting in lag in response speed and limitations in compensation effectiveness.

[0050] Optionally, the gateway signal information for round Ni is determined through the following steps: obtaining a first message sent by the satellite to the gateway in round Ni; wherein the first message includes a first message ID of the first message, a second message ID of a second message received by the satellite from the gateway in round Ni, the received power and received frequency of the gateway signal received by the satellite in round Ni, the transmitted power and transmitted frequency of the signal transmitted by the satellite to the gateway in round Ni, the satellite's position information, and a data area; obtaining the second message ID and the received power and received frequency of the gateway signal received by the satellite in round Ni from the first message. Rate; Query the second message received by the satellite from the gateway station in the Ni round from the preset database according to the second message ID; and obtain the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Ni round from the second message; wherein the second message includes the second message ID of the second message, the third message ID of the third message received by the gateway station from the satellite in the N-(i+1) round, the reception power and reception frequency of the satellite signal received by the gateway station in the N-(i+1) round, the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Ni round, the satellite position information of the gateway station, and the data area.

[0051] In this embodiment of the invention, the formats of messages sent from a gateway station to a satellite and messages sent from a satellite to a gateway station are defined. Specifically, the message sent from the gateway station to the satellite mainly includes four parts: the first part is the message ID of the message sent by the gateway station to the satellite in the current round; the second part is the relevant information of the message received by the gateway station from the satellite in the previous round (i.e., the round before the current round) (including message ID, received satellite signal power, and received frequency); the third part is the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the current round, as well as the gateway station's location information in the current round; and the fourth part is the data area, such as... Figure 5 and Figure 7 As shown. The message sent by the satellite to the gateway station mainly includes four parts. The first part is the message ID of the message sent by the satellite to the gateway station in the current round. The second part is the relevant information of the message received by the satellite from the gateway station in the current round (including message ID, received signal power and received frequency from the gateway station). The third part is the transmission power and transmission frequency of the signal transmitted by the satellite to the gateway station in the current round, as well as the satellite's position information in the current round. The fourth part is the data area, such as... Figure 6 and Figure 8 As shown.

[0052] Therefore, in determining the gateway station signal information for round Ni, the control center can first obtain the first message sent by the satellite to the gateway station in round Ni. For example, i=1 is used as an illustration. Figure 6 As shown, the first message includes the first message ID of the first message, the second message ID of the second message received by the satellite from the gateway station in the N-1th round, the received power and received frequency of the gateway station signal received by the satellite in the N-1th round, the transmitted power and transmitted frequency of the signal transmitted by the satellite to the gateway station in the N-1th round, the satellite position information of the satellite, and the data area.

[0053] Then, the control center can obtain the second message ID (corresponding to) from the first message. Figure 6 The data includes the "message ID of the message received in round N-1" and the received power and frequency of the gateway signal received by the satellite in round Ni. Furthermore, based on the second message ID, the system queries a preset database for the second message received by the satellite from the gateway in round N-1, and retrieves the transmission power and frequency of the signal transmitted by the gateway to the satellite in round N-1 from the second message. (Referring to...) Figure 5 As shown, the second message includes the second message ID of the second message (corresponding to...). Figure 5 The "message ID of the message sent in round N-1" and the third message ID of the third message received by the gateway station from the satellite in round N-2 (corresponding to...) Figure 5 The data includes the message ID of the message received in the (N-2)th round, the receiving power and frequency of the satellite signal received by the gateway station in the (N-2)th round, the transmitting power and frequency of the signal transmitted by the gateway station to the satellite in the (N-1)th round, the satellite location information of the gateway station, and the data area.

[0054] In this way, the gateway signal information of round Ni can be quickly and accurately determined from the messages of historical rounds.

[0055] Optionally, the satellite feedback signal information for the Nith round is determined by the following steps: obtaining the transmission power and transmission frequency of the signal transmitted by the satellite to the gateway station in the Nith round from the first message; and analyzing the signal transmitted by the satellite to the gateway station in the Nith round to determine the receiving power and receiving frequency of the satellite signal received by the gateway station in the Nith round.

[0056] In this embodiment of the invention, the control center continues to use the example of i=1 above when determining the satellite feedback signal information for the Nith round, referring to... Figure 6As shown, the control center can directly obtain the transmission power and frequency of the signal transmitted by the satellite to the gateway station in round N-1 from the first message. The control center needs to analyze the signal transmitted by the satellite to the gateway station in round N-1 to determine the reception power and frequency of the satellite signal received by the gateway station in round N-1. Furthermore, before the gateway station sends a message to the satellite in round N, the control center needs to write the analyzed reception power and frequency of the satellite signal received in round N-1 into the second part of the message, referring to... Figure 7 As shown.

[0057] In this way, a portion of the satellite feedback signal information for round Ni can be quickly and accurately obtained from the messages of historical rounds, while the other portion can be determined by analyzing the signal.

[0058] Optionally, the gateway location information and satellite location information for the Nith round are determined by the following steps: obtaining the satellite location information for the Nith round from the first message; and obtaining the gateway location information for the Nith round from the second message.

[0059] In this embodiment of the invention, the example of i=1 above is continued, referring to... Figure 6 As shown, since the fourth part of the first message contains the satellite's position information in the (N-1)th round of communication, the satellite's position information in the (N-1)th round can be directly obtained from the first message. Similarly, referring to... Figure 5 As shown, since the fourth part of the second message contains the location information of the gateway station in the communication of the N-1th round, the location information of the gateway station in the N-1th round can be directly obtained from the second message.

[0060] Optionally, the operation of constructing a signal feature series based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1 includes: extracting features independently from the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Ni and then concatenating them to obtain the signal features of round Ni; i = 1 to k; and constructing the signal feature series based on the signal features from round Nk to round N-1.

[0061] In this embodiment of the invention, continuing with the example of N=10 and k=5, after the control center determines the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds 5 to 9, it can extract features from each of these information for each round. The extracted features are then concatenated, and the concatenated features serve as the signal features for the corresponding round. These signal features integrate temporal and spatial features. Subsequently, based on the signal features from rounds 5 to 9, the control center constructs a spatiotemporally coupled signal feature series, providing a data-driven decision-making basis for subsequent power and frequency dual regulation.

[0062] Optionally, the pre-trained deep learning model includes an input layer, a bidirectional temporal coding layer, a spatial attention layer, and a fully connected prediction layer; wherein the fully connected prediction layer includes one hidden unit and two output units; and the operation of using the pre-trained deep learning model to analyze the signal feature series and determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in the Nth round includes: sending the signal feature series to the bidirectional temporal coding layer through the input layer, extracting temporal features from the signal feature series through the bidirectional temporal coding layer; and outputting the time-series features from the bidirectional temporal coding layer. The sequence feature vector is concatenated with the gateway station location features and satellite location features of round N-1 to form a spatial-temporal joint feature vector; the spatial-temporal joint feature vector is input into the spatial attention layer for further processing; and the enhanced feature vector output by the spatial attention layer is transmitted to the fully connected prediction layer, where it undergoes nonlinear transformation through the hidden unit. One of the two output units outputs the power compensation value of the signal transmitted by the gateway station to the satellite in round N, and the other of the two output units outputs the frequency compensation value of the signal transmitted by the gateway station to the satellite in round N.

[0063] In this embodiment of the invention, reference is made to Figure 9 As shown, the pre-trained deep learning model includes an input layer, a bidirectional temporal coding layer, a spatial attention layer, and a fully connected prediction layer. The fully connected prediction layer includes one hidden unit and two output units. The signal feature series X = [x...] N-k ,x N-(k+1) ,...,x N-1 ], where x N-k Let x be the signal feature of the Nkth round. N-(k+1) Let x be the signal feature of the N-(k+1)th round. N-1 Signal characteristics of round N-1. i ∈R DWhere i = 1 to k, and D = feature dimension. In this embodiment, D = 3, which represents the three dimensions of power, frequency, and position coordinates. Continuing with the example of N = 10 and k = 5, the signal feature series X = [x5, x6, ..., x9].

[0064] The signal feature series X = [x N-k ,x N-(k+1) ,...,x N-1 The input layer passes the signal to a bidirectional temporal coding layer, which encodes the series of signal features into a temporal context-aware feature vector representation. Specifically, the bidirectional temporal coding layer (BiLSTM) captures the forward temporal dependency of the i-th signal feature. and backward temporal dependency The forward and backward temporal dependencies are then concatenated to obtain the temporal features of each signal feature. Where H is the dimension of the unidirectional hidden layer, i = 1 to k. Then, the temporal features of all signal features in the signal feature series are combined to obtain the temporal feature vector H = [h...]. N-k ,h N-(k+1) ,...,h N-1 ].

[0065] Next, the temporal feature vector H output by the bidirectional temporal coding layer is concatenated with the gateway location features and satellite location features from the (N-1)th round to form a spatial-temporal joint feature vector V = [h N-k ,h N-(k+1) ,...,h N-1 ,f 1,N-k ,f 1,N-(k+1) ,...,f 1,N-1 ,f 2,N-k ,f 2,N-(k+1) ,...,f 2,N-1 ]. Where, f 1,N-k Let f be the location feature of the gateway station in round Nk. 1,N-(k+1) Let f be the location feature of the gateway station in the N-(k+1)th round. 1,N-1 For the location characteristics of the gateway station in round N-1, f 2,N-k For the satellite position features in round Nk, f 2,N-(k+1) For the satellite position characteristics in the N-(k+1)th round, f 2,N-1 This represents the satellite position features for the (N-1)th round. Next, the spatial-temporal joint feature vector V is input into the spatial attention layer. After further processing by the spatial attention layer, an enhanced feature vector V′ is output, where V′ = LayerNorm(V+A), and A = SV∈R. d d represents the attention head dimension, and S represents the similarity matrix. Q = WQ V, K = W K V, V = W V V, W Q W K and W V The Query(Q), Key(K), and Value(V) matrices are generated by linear transformation of the spatial-temporal joint feature vector V.

[0066] Finally, the enhanced feature vector V′ output by the spatial attention layer is transmitted to the fully connected prediction layer. After nonlinear transformation by the hidden unit, one of the two output units outputs the power compensation value ΔP of the signal transmitted by the gateway station to the satellite in the Nth round, and the other outputs the frequency compensation value Δf of the signal transmitted by the gateway station to the satellite in the Nth round.

[0067] Optionally, the operation of determining the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round based on the power compensation value and the frequency compensation value includes: obtaining the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the (N-1)th round from the second message; and determining the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round based on the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the (N-1)th round, according to the power compensation value and the frequency compensation value.

[0068] In this embodiment of the invention, during the process of determining the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round based on the power compensation value and the frequency compensation value, the control center can not only determine the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round, but also... center (e.g., 28GHz) and nominal transmit power P nom Based on the compensation (such as a typical Ka-band value of 35 dBW), the transmit power P of the signal transmitted by the gateway station to the satellite in the N-1th round can also be obtained from the second message. N-1 and transmission frequency f N-1 Then through formula P N =P N-1 +ΔP calculates the transmission power of the signal transmitted by the gateway station to the satellite in the Nth round, using the formula f N =f N-1 +Δf is the transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round. In this way, millisecond-level dynamic adjustment of transmission parameters (power + frequency) is achieved, enabling the signal to maintain optimal operating conditions under complex channel conditions such as rain attenuation.

[0069] In addition, refer to Figure 1As shown, according to a second aspect of this embodiment, a storage medium is provided. The storage medium includes a stored program, wherein, when the program is executed, a processor performs any of the methods described above.

[0070] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0071] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, 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 is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0072] Example 2

[0073] Figure 10 An apparatus for reducing the impact of rain attenuation on satellite gateway communication links according to this embodiment is shown, which corresponds to the method described in Embodiment 1. Reference Figure 10As shown, the device includes: an information determination module 1010, used to determine the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1 before the gateway station transmits the signal for round N to the satellite; wherein, the gateway station signal information for round Ni includes the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in round Ni, and the receiving power and receiving frequency of the gateway station signal received by the satellite in round Ni; the satellite feedback signal information for round Ni includes the transmission power and transmission frequency of the signal transmitted by the satellite to the gateway station in round Ni, and the receiving power and receiving frequency of the satellite signal received by the gateway station in round Ni; i = 1 to k; Feature determination module 1020, used to construct a signal feature series based on the gateway station signal information, satellite feedback signal information, gateway station location information and satellite location information from round Nk to round N-1; wherein the signal feature series consists of the signal features from round Nk to round N-1; Compensation value determination module 1030, used to analyze the signal feature series using a pre-trained deep learning model to determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in round N; and power and frequency determination module 1040, used to determine the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in round N based on the power compensation value and the frequency compensation value.

[0074] Optionally, the gateway signal information for round Ni is determined through the following steps: obtaining a first message sent by the satellite to the gateway in round Ni; wherein the first message includes a first message ID of the first message, a second message ID of a second message received by the satellite from the gateway in round Ni, the received power and received frequency of the gateway signal received by the satellite in round Ni, the transmitted power and transmitted frequency of the signal transmitted by the satellite to the gateway in round Ni, the satellite's position information, and a data area; obtaining the second message ID and the received power and received frequency of the gateway signal received by the satellite in round Ni from the first message. Rate; Query the second message received by the satellite from the gateway station in the Ni round from the preset database according to the second message ID; and obtain the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Ni round from the second message; wherein the second message includes the second message ID of the second message, the third message ID of the third message received by the gateway station from the satellite in the N-(i+1) round, the reception power and reception frequency of the satellite signal received by the gateway station in the N-(i+1) round, the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Ni round, the satellite position information of the gateway station, and the data area.

[0075] Optionally, the satellite feedback signal information for the Nith round is determined by the following steps: obtaining the transmission power and transmission frequency of the signal transmitted by the satellite to the gateway station in the Nith round from the first message; and analyzing the signal transmitted by the satellite to the gateway station in the Nith round to determine the receiving power and receiving frequency of the satellite signal received by the gateway station in the Nith round.

[0076] Optionally, the gateway location information and satellite location information for the Nith round are determined by the following steps: obtaining the satellite location information for the Nith round from the first message; and obtaining the gateway location information for the Nith round from the second message.

[0077] Optionally, the operation of constructing a signal feature series based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1 includes: extracting features independently from the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Ni and then concatenating them to obtain the signal features of round Ni; i = 1 to k; and constructing the signal feature series based on the signal features from round Nk to round N-1.

[0078] Optionally, the pre-trained deep learning model includes an input layer, a bidirectional temporal coding layer, a spatial attention layer, and a fully connected prediction layer; wherein the fully connected prediction layer includes one hidden unit and two output units; and the operation of using the pre-trained deep learning model to analyze the signal feature series and determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in the Nth round includes: sending the signal feature series to the bidirectional temporal coding layer through the input layer, extracting temporal features from the signal feature series through the bidirectional temporal coding layer; and outputting the time-series features from the bidirectional temporal coding layer. The sequence feature vector is concatenated with the gateway station location features and satellite location features of round N-1 to form a spatial-temporal joint feature vector; the spatial-temporal joint feature vector is input into the spatial attention layer for further processing; and the enhanced feature vector output by the spatial attention layer is transmitted to the fully connected prediction layer, where it undergoes nonlinear transformation through the hidden unit. One of the two output units outputs the power compensation value of the signal transmitted by the gateway station to the satellite in round N, and the other of the two output units outputs the frequency compensation value of the signal transmitted by the gateway station to the satellite in round N.

[0079] Optionally, the operation of determining the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round based on the power compensation value and the frequency compensation value includes: obtaining the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the (N-1)th round from the second message; and determining the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round based on the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the (N-1)th round, according to the power compensation value and the frequency compensation value.

[0080] Therefore, according to this embodiment, before the gateway station sends the Nth round of signals to the satellite, the information determination module 1010 determines the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from the Nkth round to the N-1th round. By determining the various signal parameters (transmit / receive power, frequency) and location information of the communication link itself, real-time self-extraction and predictive perception of rain attenuation characteristics are achieved, providing a forward-looking basis for subsequent compensation strategies. Then, the feature determination module 1020 constructs a signal feature series based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from the Nkth round to the N-1th round. Without waiting for ground meteorological station data (delay ≥ 1 minute), it directly extracts the spatiotemporal coupling attenuation characteristics (end-to-end delay < 10ms) from the signal information and location information of the gateway station-satellite interaction, constructing an autonomous decision-making system that does not rely on external data, laying the foundation for real-time self-triggering of rain attenuation response. Secondly, the compensation value determination module 1030 uses a pre-trained deep learning model to analyze the signal feature series and determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in the Nth round. This model achieves power-frequency coordinated prediction through dual-objective optimization, providing precise adjustment instructions for subsequent dual adjustment of power and frequency. Finally, the power and frequency determination module 1040 determines the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round based on the power compensation value and the frequency compensation value. This ensures that in the Nth round of communication, the gateway station transmits the signal to the satellite with the optimal transmission power and frequency, thereby dynamically compensating for rain attenuation in the link and keeping the signal in a suitable working state. This solves the technical problems of existing satellite gateway station rain attenuation anti-rain data schemes that rely too much on meteorological data and only adjust signal power, resulting in lag in response speed and limitations in compensation effectiveness.

[0081] Example 3

[0082] Figure 11 An apparatus for reducing the impact of rain attenuation on satellite gateway communication links according to this embodiment is shown, which corresponds to the method described in Embodiment 1. Reference Figure 11As shown, the device includes: a processor 1110; and a memory 1120, connected to the processor 1110, for providing the processor 1110 with instructions to process the following steps: before the gateway station transmits the signal of the Nth round to the satellite, determine the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1; wherein, the gateway station signal information of the Nith round includes the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nith round, and the receiving power and receiving frequency of the gateway station signal received by the satellite in the Nith round; the satellite feedback signal information of the Nith round includes the transmission power of the signal transmitted by the satellite to the gateway station in the Nith round. The signal characteristics are determined by the following parameters: power and transmission frequency; received power and received frequency of the satellite signal received by the gateway station in round Ni; i = 1 to k; a signal feature series is constructed based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1; wherein the signal feature series consists of the signal features from round Nk to round N-1; the signal feature series is analyzed using a pre-trained deep learning model to determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in round N; and the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in round N are determined based on the power compensation value and the frequency compensation value.

[0083] Optionally, the gateway signal information for round Ni is determined through the following steps: obtaining a first message sent by the satellite to the gateway in round Ni; wherein the first message includes a first message ID of the first message, a second message ID of a second message received by the satellite from the gateway in round Ni, the received power and received frequency of the gateway signal received by the satellite in round Ni, the transmitted power and transmitted frequency of the signal transmitted by the satellite to the gateway in round Ni, the satellite's position information, and a data area; obtaining the second message ID and the received power and received frequency of the gateway signal received by the satellite in round Ni from the first message. Rate; Query the second message received by the satellite from the gateway station in the Ni round from the preset database according to the second message ID; and obtain the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Ni round from the second message; wherein the second message includes the second message ID of the second message, the third message ID of the third message received by the gateway station from the satellite in the N-(i+1) round, the reception power and reception frequency of the satellite signal received by the gateway station in the N-(i+1) round, the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Ni round, the satellite position information of the gateway station, and the data area.

[0084] Optionally, the satellite feedback signal information for the Nith round is determined by the following steps: obtaining the transmission power and transmission frequency of the signal transmitted by the satellite to the gateway station in the Nith round from the first message; and analyzing the signal transmitted by the satellite to the gateway station in the Nith round to determine the receiving power and receiving frequency of the satellite signal received by the gateway station in the Nith round.

[0085] Optionally, the gateway location information and satellite location information for the Nith round are determined by the following steps: obtaining the satellite location information for the Nith round from the first message; and obtaining the gateway location information for the Nith round from the second message.

[0086] Optionally, the operation of constructing a signal feature series based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1 includes: extracting features independently from the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Ni and then concatenating them to obtain the signal features of round Ni; i = 1 to k; and constructing the signal feature series based on the signal features from round Nk to round N-1.

[0087] Optionally, the pre-trained deep learning model includes an input layer, a bidirectional temporal coding layer, a spatial attention layer, and a fully connected prediction layer; wherein the fully connected prediction layer includes one hidden unit and two output units; and the operation of using the pre-trained deep learning model to analyze the signal feature series and determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in the Nth round includes: sending the signal feature series to the bidirectional temporal coding layer through the input layer, extracting temporal features from the signal feature series through the bidirectional temporal coding layer; and outputting the time-series features from the bidirectional temporal coding layer. The sequence feature vector is concatenated with the gateway station location features and satellite location features of round N-1 to form a spatial-temporal joint feature vector; the spatial-temporal joint feature vector is input into the spatial attention layer for further processing; and the enhanced feature vector output by the spatial attention layer is transmitted to the fully connected prediction layer, where it undergoes nonlinear transformation through the hidden unit. One of the two output units outputs the power compensation value of the signal transmitted by the gateway station to the satellite in round N, and the other of the two output units outputs the frequency compensation value of the signal transmitted by the gateway station to the satellite in round N.

[0088] Optionally, the operation of determining the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round based on the power compensation value and the frequency compensation value includes: obtaining the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the (N-1)th round from the second message; and determining the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round based on the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the (N-1)th round, according to the power compensation value and the frequency compensation value.

[0089] Therefore, according to this embodiment, before the gateway station sends the Nth round of signals to the satellite, the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1 are first determined. By determining the various signal parameters (transmit / receive power, frequency) and location information of the communication link itself, real-time self-extraction and predictive perception of rain attenuation characteristics are achieved, providing a forward-looking basis for subsequent compensation strategies. Then, based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1, a series of signal characteristics is constructed. Without waiting for ground meteorological station data (delay ≥ 1 minute), the spatiotemporal coupling attenuation characteristics are directly extracted from the signal information and location information of the gateway station-satellite interaction (end-to-end delay < 10ms), constructing an autonomous decision-making system that does not rely on external data, laying the foundation for real-time self-triggering of rain attenuation response. Secondly, a pre-trained deep learning model is used to analyze the signal feature series, determining the power compensation and frequency compensation values ​​for the signal transmitted by the gateway station to the satellite in the Nth round. This model achieves power-frequency coordinated prediction through dual-objective optimization, providing precise adjustment instructions for subsequent power and frequency dual adjustment. Finally, based on the power compensation and frequency compensation values, the transmission power and frequency of the signal transmitted by the gateway station to the satellite in the Nth round are determined to ensure that the gateway station transmits signals to the satellite with optimal transmission power and frequency in the Nth round of communication, thereby dynamically compensating for rain attenuation in the link and keeping the signal in a suitable operating state. This solves the technical problems of existing satellite gateway station rain attenuation anti-rain data schemes that rely too heavily on meteorological data and only adjust signal power, resulting in lag in response speed and limitations in compensation effectiveness.

[0090] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0091] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0092] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0093] 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 units can be selected to achieve the purpose of this embodiment according to actual needs.

[0094] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0095] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it 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 all or 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, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0096] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for reducing the impact of rain attenuation on satellite gateway communication links, characterized in that, include: Before the gateway station transmits the signal for the Nth round to the satellite, the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1 are determined. Specifically, the gateway station signal information for round Ni includes the transmission power and frequency of the signal transmitted by the gateway station to the satellite in round Ni, and the receiving power and frequency of the gateway station signal received by the satellite in round Ni. The satellite feedback signal information for round Ni includes the transmission power and frequency of the signal transmitted by the satellite to the gateway station in round Ni, and the receiving power and frequency of the satellite signal received by the gateway station in round Ni; i = 1 to k. Based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1, a signal feature series is constructed; wherein the signal feature series consists of the signal features from round Nk to round N-1. Using a pre-trained deep learning model, the signal feature series is analyzed to determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in the Nth round; and Based on the power compensation value and the frequency compensation value, the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round are determined.

2. The method according to claim 1, characterized in that, The following steps are used to determine the gateway signal information for round Ni: Obtain the first message sent by the satellite to the gateway station in the Nith round; The first message includes the first message ID of the first message, the second message ID of the second message received by the satellite from the gateway station in the Ni round, the receiving power and receiving frequency of the gateway station signal received by the satellite in the Ni round, the transmitting power and transmitting frequency of the signal transmitted by the satellite to the gateway station in the Ni round, the satellite position information of the satellite, and the data area. Obtain the second message ID and the received power and frequency of the gateway signal received by the satellite in the Ni round from the first message; Based on the second message ID, query the preset database for the second message received by the satellite from the gateway station in the Nith round; as well as The transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Ni-th round are obtained from the second message; wherein the second message includes the second message ID of the second message, the third message ID of the third message received by the gateway station from the satellite in the N-(i+1)-th round, the reception power and reception frequency of the satellite signal received by the gateway station in the N-(i+1)-th round, the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Ni-th round, the satellite position information of the gateway station, and the data area.

3. The method according to claim 2, characterized in that, The satellite feedback signal information for round Ni is determined through the following steps: Obtain from the first message the transmission power and frequency of the signal transmitted by the satellite to the gateway station in round Ni; and The signal transmitted by the satellite to the gateway station in the Ni round is analyzed to determine the received power and frequency of the satellite signal received by the gateway station in the Ni round.

4. The method according to claim 2, characterized in that, The following steps are used to determine the gateway location information and satellite location information for round Ni: Obtain the satellite position information for round Ni from the first message; and Obtain the gateway location information for round Ni from the second message.

5. The method according to claim 1, characterized in that, The operation of constructing a series of signal characteristics based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1 includes: After independently extracting features from the gateway signal information, satellite feedback signal information, gateway location information, and satellite location information in round Ni, the signals are concatenated to obtain the signal features of round Ni; i = 1 to k; and Based on the signal characteristics from round Nk to round N-1, the signal characteristic series is constructed.

6. The method according to claim 1, characterized in that, The pre-trained deep learning model includes an input layer, a bidirectional temporal coding layer, a spatial attention layer, and a fully connected prediction layer; wherein the fully connected prediction layer includes one hidden unit and two output units. Furthermore, the operation of analyzing the signal feature series using a pre-trained deep learning model to determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in the Ni-th round includes: The signal feature series is sent to the bidirectional timing coding layer through the input layer, and the timing feature is extracted from the signal feature series through the bidirectional timing coding layer. The temporal feature vector output by the bidirectional temporal coding layer is concatenated with the gateway location features and satellite location features from the (N-1)th round to form a spatial-temporal joint feature vector; The spatial-temporal joint feature vector is input into the spatial attention layer for further processing; and The enhanced feature vector output by the spatial attention layer is transmitted to the fully connected prediction layer. After nonlinear transformation by the hidden unit, one of the two output units outputs the power compensation value of the signal transmitted by the gateway station to the satellite in the Nth round, and the other of the two output units outputs the frequency compensation value of the signal transmitted by the gateway station to the satellite in the Nth round.

7. The method according to claim 2, characterized in that, The operation of determining the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round based on the power compensation value and the frequency compensation value includes: Obtain from the second message the transmission power and frequency of the signal transmitted by the gateway station to the satellite in the (N-1)th round; and Based on the transmission power and frequency of the signal transmitted by the gateway station to the satellite in the (N-1)th round, the transmission power and frequency of the signal transmitted by the gateway station to the satellite in the Nth round are determined according to the power compensation value and the frequency compensation value.

8. A storage medium, characterized in that, The storage medium includes a stored program, wherein, when the program is executed, the method described in any one of claims 1 to 7 is performed by a processor.

9. A device for reducing the impact of rain attenuation on satellite gateway communication links, characterized in that, include: The information determination module is used to determine the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1 before the gateway station transmits the signal for round N to the satellite. Specifically, the gateway station signal information for round Ni includes the transmission power and frequency of the signal transmitted by the gateway station to the satellite in round Ni, and the receiving power and frequency of the gateway station signal received by the satellite in round Ni. The satellite feedback signal information for round Ni includes the transmission power and frequency of the signal transmitted by the satellite to the gateway station in round Ni, and the receiving power and frequency of the satellite signal received by the gateway station in round Ni; i = 1 to k. The feature determination module is used to construct a signal feature series based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1; wherein the signal feature series is composed of the signal features from round Nk to round N-1. The compensation value determination module is used to analyze the signal feature series using a pre-trained deep learning model to determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in the Nth round; and The power and frequency determination module is used to determine the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round based on the power compensation value and the frequency compensation value.

10. A device for reducing the impact of rain attenuation on satellite gateway communication links, characterized in that, include: processor; as well as A memory, connected to the processor, for providing the processor with instructions to perform the following processing steps: Before the gateway station transmits the signal for the Nth round to the satellite, the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information for rounds Nk to N-1 are determined. Specifically, the gateway station signal information for round Ni includes the transmission power and frequency of the signal transmitted by the gateway station to the satellite in round Ni, and the receiving power and frequency of the gateway station signal received by the satellite in round Ni. The satellite feedback signal information for round Ni includes the transmission power and frequency of the signal transmitted by the satellite to the gateway station in round Ni, and the receiving power and frequency of the satellite signal received by the gateway station in round Ni; i = 1 to k. Based on the gateway station signal information, satellite feedback signal information, gateway station location information, and satellite location information from round Nk to round N-1, a signal feature series is constructed; wherein the signal feature series consists of the signal features from round Nk to round N-1. Using a pre-trained deep learning model, the signal feature series is analyzed to determine the power compensation value and frequency compensation value of the signal transmitted by the gateway station to the satellite in the Nth round; and Based on the power compensation value and the frequency compensation value, the transmission power and transmission frequency of the signal transmitted by the gateway station to the satellite in the Nth round are determined.

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