A satellite communication method, device and storage medium

Abstract

The application discloses a satellite communication method and device and a storage medium. The method comprises the following steps: determining the adaptability between different sub-bands of a satellite and different beams of the satellite; constructing a chromosome population composed of multiple chromosome vectors; initializing the chromosome vectors according to the adaptability; constructing an adaptive function, wherein the adaptive function is used to indicate the severity of the co-frequency interference of multiple coverage areas after the sub-bands are allocated to the beams according to the chromosome vectors; iteratively optimizing the chromosome population by the adaptive function according to a genetic algorithm, and determining an optimized chromosome vector; and allocating corresponding sub-bands to the beams according to the optimized chromosome vector, and performing satellite communication. Thus, the sub-band with the lowest fitness for each beam can be determined, and the interference between the sub-bands can be avoided.

Description

Technical Field

[0001] This application relates to the field of satellite communication technology, and in particular to a satellite communication method, apparatus, and storage medium. Background Technology

[0002] Currently, modern satellites, especially high-throughput communication satellites and low-Earth orbit constellations, employ multi-beam scanning technology to cover ground areas. Through phased array antennas or reflector feed systems, a single satellite can generate multiple independent beams B1~B1. m (For example, a single Starlink satellite can generate approximately 8 to 16 beams), each pointing to a different geographical area and reusing the same frequency band (such as the Ku or Ka band). This Space Division Multiple Access (SDMA) technology, also known as multi-beam frequency reuse, significantly improves spectrum utilization efficiency, multiplying the capacity of satellite systems.

[0003] Because antennas cannot achieve an ideal "needle beam," the resulting sidelobes and edge roll-off (ERO) cause signal leakage into adjacent beam regions. Therefore, when the coverage areas of two co-frequency beams overlap (e.g., at the edge of the user's domain), the receiver receives both useful and interfering signals simultaneously, severely reducing the signal-to-interference-plus-noise ratio (SINR). Furthermore, high-spectral-efficiency multiplexing strategies (such as 4-color multiplexing being denser than 7-color multiplexing) shorten the spacing between co-frequency beams, further exacerbating interference.

[0004] Therefore, satellite communications employing multi-beam scanning technology can experience unwanted signal interference between beams in the same frequency band due to beam sidelobes and edge roll-off. Thus, avoiding co-band beam interference while meeting the communication needs of various coverage areas has become a pressing technical problem to be solved.

[0005] The publication number is CN112558474A, and the title is "A Control Method for Low-Earth Orbit Satellite Communication Links Based on a Multi-Objective Genetic Algorithm." It includes: obtaining the terminal's operational route and the different positions of the current satellite within a future timeframe, and predicting the start time and handover time of a single coverage satellite's communication connection to the terminal; obtaining a directed graph of the terminal-satellite handover relationship based on the start time and handover time of the single coverage satellite's communication connection to the terminal; using the Pareto multi-objective genetic algorithm to filter the handover paths in the directed graph of the terminal-satellite handover relationship to find the optimal handover path; and controlling the handover between the low-Earth orbit satellite and the terminal based on the optimal handover path.

[0006] The publication number is CN120509638A, and the name is a multi-satellite task scheduling method based on genetic algorithm. It includes: integrating scheduling cycle constraints, task uniqueness constraints, equipment protection time constraints, and frequency band and orbit type matching constraints; introducing a simulated annealing local search mechanism into the genetic algorithm, accepting inferior solutions by probability to escape local optima, and dynamically adjusting the mutation probability according to changes in population fitness; setting an early stopping mechanism to terminate the iteration in advance when the fitness does not improve continuously; and finally generating a scheduling scheme.

[0007] Regarding the technical problem of co-band beam interference in satellite communications using multi-beam scanning technology, which occurs while meeting the communication needs of various coverage areas, no effective solution has yet been proposed. Summary of the Invention

[0008] The embodiments of this disclosure provide a satellite communication method, apparatus, and storage medium to at least solve the technical problem in the prior art where satellite communication using multi-beam scanning technology generates co-band beam interference while meeting the communication needs of various coverage areas.

[0009] According to one aspect of the present disclosure, a satellite communication method is provided, comprising: determining the adaptability between different sub-frequency bands of a satellite and different beams of the satellite, wherein the beams cover multiple coverage areas; constructing a chromosome population composed of multiple chromosome vectors, wherein each chromosome vector is composed of multiple bits, and a predetermined number of bits in the chromosome vectors correspond to a beam of the satellite, for indicating the sub-frequency band used by the corresponding beam in a binary encoding manner; initializing the chromosome vectors according to the adaptability; constructing an adaptation function, wherein the adaptation function is used to indicate the severity of co-channel interference in multiple coverage areas after allocating sub-frequency bands to each beam according to the chromosome vectors; iteratively optimizing the chromosome population according to the adaptation function using a genetic algorithm, and determining an optimized chromosome vector; and allocating corresponding sub-frequency bands to each beam according to the optimized chromosome vectors, and performing satellite communication.

[0010] 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.

[0011] According to another aspect of the present disclosure, a satellite communication device is also provided, comprising: an adaptability determination module, configured to determine the adaptability between different sub-frequency bands of a satellite and different beams of a satellite, wherein the beams cover multiple coverage areas; a chromosome construction module, configured to construct a chromosome population composed of multiple chromosome vectors, wherein each chromosome vector is composed of multiple bits, and a predetermined number of bits in the chromosome vectors correspond to a beam of the satellite, used to indicate the sub-frequency band used by the corresponding beam through binary encoding; a chromosome initialization module, configured to initialize the chromosome vectors according to the adaptability; an fitness function construction module, configured to construct a fitness function, wherein the fitness function indicates the severity of co-frequency interference in multiple coverage areas after allocating sub-frequency bands to each beam according to the chromosome vectors; a genetic algorithm module, configured to iteratively optimize the chromosome population through the fitness function according to a genetic algorithm, and determine the optimized chromosome vectors; and a communication module, configured to allocate corresponding sub-frequency bands to each beam according to the optimized chromosome vectors and perform satellite communication.

[0012] According to another aspect of the present disclosure, a satellite communication device 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: determining the adaptability between different sub-frequency bands of a satellite and different beams of a satellite, wherein the beams cover multiple coverage areas; constructing a chromosome population composed of multiple chromosome vectors, wherein each chromosome vector is composed of multiple bits, and a predetermined number of bits in the chromosome vectors correspond to a beam of the satellite, used to indicate the sub-frequency band used by the corresponding beam in a binary encoding manner; initializing the chromosome vectors according to the adaptability; constructing an adaptation function, wherein the adaptation function is used to indicate the severity of co-channel interference in multiple coverage areas after allocating sub-frequency bands to each beam according to the chromosome vectors; iteratively optimizing the chromosome population through the adaptation function according to a genetic algorithm, and determining an optimized chromosome vector; and allocating corresponding sub-frequency bands to each beam according to the optimized chromosome vectors, and performing satellite communication.

[0013] In this embodiment, the compatibility between different sub-bands and different beams of the satellite is determined based on the characteristic parameters of the coverage area of ​​each beam related to satellite communication. A chromosome population is constructed, representing the sub-band allocation scheme in binary encoding, based on the chromosome vector corresponding to each beam, where every two bits correspond to the sub-band selection of one beam. The chromosome population is initialized based on the compatibility, and a fitness function is constructed to quantify the severity of co-channel interference. The chromosome population is iteratively optimized using a genetic algorithm, and finally, sub-bands are allocated to each beam based on the optimal chromosome vector. This allows for the determination of the sub-band with the lowest fitness for each beam, thereby avoiding interference between co-channels.

[0014] Therefore, by using the above method, an adaptation function is constructed based on the characteristic parameters of satellite communication. A logistic regression model is then used to determine the sub-frequency bands that can be adapted to each beam, thus meeting the communication needs of the coverage areas of each beam. Furthermore, a genetic algorithm is used to determine the sub-frequency bands corresponding to each beam, thereby avoiding co-band beam interference while meeting the communication needs of each coverage area. Attached Figure Description

[0015] The accompanying drawings, which are included to provide a further understanding of this disclosure and form part of this application, illustrate exemplary embodiments of this disclosure and are used to explain this disclosure, but do not constitute an undue limitation of this disclosure. In the drawings:

[0016] Figure 1 This is a schematic diagram of the hardware structure of a satellite used to implement the method described in Embodiment 1 of this application;

[0017] Figure 2 This is a flowchart illustrating the satellite communication method according to Embodiment 1 of this application;

[0018] Figure 3 This is a schematic diagram of a satellite performing multi-beam scanning according to Embodiment 1 of this application;

[0019] Figure 4 This is a schematic diagram of the overlap of two co-band beams of a satellite according to Embodiment 1 of this application;

[0020] Figure 5 This is a schematic diagram of the overlap of three co-frequency band beams of a satellite according to Embodiment 1 of this application;

[0021] Figure 6 This is a schematic diagram of the satellite communication device according to Embodiment 2 of this application; and

[0022] Figure 7 This is a schematic diagram of the satellite communication device according to Embodiment 3 of this application. Detailed Implementation

[0023] 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.

[0024] 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.

[0025] According to this embodiment, a method embodiment of a satellite communication method 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. Also, 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.

[0026] Figure 1 A schematic diagram of the hardware architecture of satellite 10 according to this embodiment is shown. (Reference) Figure 1 As shown, satellite 10 includes an integrated electronic system, which includes a processor, a memory, a bus management module, and a communication interface. The memory is connected to the processor, allowing the processor to access the memory, read program instructions stored in the memory, read data from the memory, or write data to the memory. The bus management module is connected to the processor and also to a bus such as a CAN bus. Thus, the processor can communicate with onboard peripherals connected to the bus through the bus managed by the bus management module. Furthermore, the processor also communicates with devices such as cameras, star sensors, telemetry and command transponders, and data transmission equipment via the communication interface. 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 satellite may also include components that are larger than... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0027] It should be noted that, Figure 1One or more processors and / or other data processing circuits shown herein may generally be referred to as "data processing circuitry". This data processing circuitry may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry 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 embodiments of this disclosure, the data processing circuitry serves as processor control (e.g., selection of a variable resistor termination path connected to an interface).

[0028] Figure 1 The memory shown can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the method for determining the communication frequency band corresponding to the beam 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, that is, to implement the above-mentioned method for determining the communication frequency band corresponding to the beam in the application program. 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.

[0029] It should be noted here that, in some optional embodiments, the above... Figure 1 The 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 devices.

[0030] Under the above operating environment, according to the first aspect of this embodiment, a satellite communication method is provided. Figure 2 A flowchart illustrating the method is shown below. (Refer to...) Figure 2 As shown, the method includes:

[0031] S202: Determine the compatibility between different sub-bands of the satellite and different beams of the satellite, wherein the beams cover multiple coverage areas respectively;

[0032] S204: Construct a chromosome population consisting of multiple chromosome vectors, where each chromosome vector consists of multiple bits, and a predetermined number of bits in the chromosome vectors correspond to a beam of a satellite, used to indicate the sub-band used by the corresponding beam through binary encoding;

[0033] S206: Initialize the chromosome vector according to the adaptability;

[0034] S208: Construct an adaptation function, which indicates the severity of co-channel interference in multiple coverage areas after sub-bands are allocated to each beam according to the chromosome vector;

[0035] S210: Based on the genetic algorithm, the chromosome population is iteratively optimized using a fitness function, and the optimal chromosome vector is determined; and

[0036] S212: Assign corresponding sub-bands to each beam according to the optimized chromosome vector and perform satellite communication.

[0037] Specifically, Figure 3 A schematic diagram illustrating multi-beam scanning of a satellite according to this embodiment is shown. (Reference) Figure 3 As shown, satellite 10 uses m beams B1~B1 respectively. m Simultaneously covering multiple coverage areas S1~S m .

[0038] For example, beam B1 covers area S1, which contains corresponding wave positions P1 to P3. Beam B1 is used to scan wave positions P1 to P3 and can provide satellite communication services to the covered wave positions P1 to P3. Beam B2 covers area S2, which contains corresponding wave positions P4 to P6. Beam B2 is used to scan wave positions P4 to P6 and can provide satellite communication services to the covered wave positions P4 to P6; ...; beam B m The covered area is S m Coverage area S m The inner corresponding wave position P n-2 ~P n Thus, beam B m Used for wave position P n-2 ~P n Perform a scan, and beam B m It can be directed to the covered wave position P n-2 ~P n It provides satellite communication services. Thus, satellite 10 can switch between corresponding positions using m beams and provide satellite communication services to each corresponding position in a time-division manner.

[0039] For the frequency band allocated to satellite 10, this embodiment uses a four-color multiplexing method to divide it into four non-overlapping sub-bands N0~N3, based on each beam B1~B m Coverage area S1~S m Parameters related to satellite communication are used to determine whether each sub-band N0~N3 is suitable for each beam B1~B. mThis refers to the compatibility between sub-bands and beams. Thus, satellite 10 can select suitable sub-bands from sub-bands N0~N3 and allocate them to each beam B1~B1. m (S202).

[0040] Preferably, the frequencies used in sub-bands N0 to N3 increase sequentially.

[0041] For each beam B i Set the corresponding chromosome vector X. Each two bits in the chromosome vector X correspond to a beam B. i Used for the corresponding beam B i The sub-band used is used for encoding (S204).

[0042] Furthermore, according to each beam B1~B m Coverage area S1~S m The adapted sub-bands, and the codes corresponding to each sub-band in step S204 above, are used to randomly generate multiple chromosome vectors X1~X2. n .

[0043] Therefore, for each chromosome vector X1~X n According to each beam B i Uniform sampling is performed on the available sub-bands, and the sub-bands are randomly selected from each chromosome vector X1~X. n Each beam B in the middle i The sub-bands used are then encoded accordingly to encode the corresponding bits, thereby encoding the chromosome vectors X1~X. n The value is initialized (S206).

[0044] The beams B1~B1 are allocated according to the chromosome vector X. m In the case of sub-bands, based on the severity of co-channel interference caused by the overlapping area of ​​two co-channel beams and the severity of co-channel interference caused by the overlapping area of ​​three co-channel beams, an adaptive function S(X) is constructed to reflect the severity of co-channel interference in the coverage area of ​​satellite 10 as a whole (S208).

[0045] Then, based on the initialized chromosome vectors X1~X n The optimal chromosome vector X is determined by iterative optimization of the fitness function S(X) using a genetic algorithm. best (S210).

[0046] Based on the optimized chromosome vector X best Determine each beam B1~B m The corresponding sub-frequency band enables satellite communication (S212).

[0047] Thus, while meeting the communication needs of each coverage area, satellite communication can be achieved without interference from beams in the same frequency band.

[0048] As described in the background section, modern satellites, especially high-throughput communication satellites and low-Earth orbit constellations, currently employ multi-beam scanning technology to cover ground areas. Through phased array antennas or reflector feed systems, a single satellite can generate multiple independent beams B1~B1. m (For example, a single Starlink satellite can generate approximately 8-16 beams), each pointing to a different geographical area and reusing the same frequency band (such as the Ku or Ka band). This Space Division Multiple Access (SDMA) technology, also known as multi-beam frequency reuse, significantly improves spectrum utilization efficiency, multiplying the capacity of satellite systems. Because antennas cannot achieve an ideal "needle-shaped beam," the resulting beam sidelobes and edge roll-off (ERO) cause signal leakage into adjacent beam regions. Therefore, when the coverage areas of two co-frequency beams overlap (e.g., at the edge of the network), the receiver receives both useful and interfering signals simultaneously, severely reducing the signal-to-interference-plus-noise ratio (SINR). Furthermore, high-spectrum-efficiency reuse strategies (such as 4-color reuse being denser than 7-color reuse) shorten the spacing between co-frequency beams, further exacerbating interference. Thus, satellite communication using multi-beam scanning technology, due to beam sidelobes and edge roll-off, can lead to undesirable signal interference between beams in the same frequency band. Therefore, how to avoid co-band beam interference while meeting the communication needs of various coverage areas has become an urgent technical problem to be solved.

[0049] In view of this, according to the technical solution described in this embodiment, the adaptability between different sub-bands of the satellite and different beams is determined based on the characteristic parameters of the coverage area of ​​each beam related to satellite communication. Based on the chromosome vector corresponding to each beam, a chromosome population is constructed to represent the sub-band allocation scheme using binary encoding, where every two bits correspond to the sub-band selection of one beam. The chromosome population is initialized based on the adaptability, and a fitness function is constructed to quantify the severity of co-channel interference. The chromosome population is iteratively optimized using a genetic algorithm, and finally, sub-bands are allocated to each beam based on the optimal chromosome vector. This allows for the determination of the sub-band with the lowest fitness for each beam, thereby avoiding interference between co-channels.

[0050] Therefore, by using the above method, an adaptation function is constructed based on the characteristic parameters of satellite communication. A logistic regression model is then used to determine the sub-frequency bands that can be adapted to each beam, thus meeting the communication needs of the coverage areas of each beam. Furthermore, a genetic algorithm is used to determine the sub-frequency bands corresponding to each beam, thereby avoiding co-band beam interference while meeting the communication needs of each coverage area.

[0051] Optionally, the operation of initializing the chromosome vector according to the adaptability includes: for each chromosome vector, determining the sub-band used by each beam by random sampling according to the adaptability; and encoding the corresponding bits in each chromosome vector according to the determined sub-band used by each beam.

[0052] Specifically, according to each beam B1~B m Coverage area S1~S m Parameters related to satellite communication are used to determine whether each sub-band N0~N3 is suitable for each beam B1~B. m That is, the sub-frequency bands N0~N3 and the coverage areas S1~S3 can be determined. m Adaptability.

[0053] Furthermore, for beams B1~B m Set the corresponding chromosome vector X. Define the chromosome vector X = [x1, x2, ..., x...]. 2m ] T In this context, each two bits in the chromosome vector X correspond to a beam, meaning that for each beam B... i or coverage area S i The corresponding bit is x 2i-1 and x 2i That is, every two bits x 2i-1 and x 2i Used for the corresponding beam B i The sub-frequency bands used for encoding are employed.

[0054] Table 1 shows the sub-band corresponding beam B. i The encoding method.

[0055] Table 1

[0056]

[0057] According to each coverage area S1~S m The adapted sub-bands, and according to the codes corresponding to each sub-band N0~N3 shown in Table 1, randomly generate multiple chromosome vectors X1~X n ,in:

[0058] Xk =[x k,1 , x k,2 , x k,3 , ..., x k,2m ] T .

[0059] Therefore, for each chromosome vector X1~X n According to each beam B i Uniform sampling is performed using the available sub-bands, and the sub-bands are randomly selected from each chromosome vector X1~X. n Each beam B in the middle i The sub-band used, and accordingly the corresponding bit x k,2i-1 and x k,2i Encode the chromosome vectors X1~X n The values ​​are initialized.

[0060] Optionally, the operation of constructing the fitness function includes constructing the fitness function S(X) as described below:

[0061] S(X) = 2·I1(X) + 6·I2(X).

[0062] Where I1(X) represents the number of overlapping regions formed by beams of two identical sub-bands when the sub-bands of each beam are allocated according to the chromosome vector X; and I2(X) represents the number of overlapping regions formed by beams of three identical sub-bands when the sub-bands of each beam are allocated according to the chromosome vector X.

[0063] Specifically, Figure 4 A schematic diagram showing the overlap of two co-band beams of a satellite according to this embodiment is shown. (Reference) Figure 4 As shown, the coverage areas S1 and S2 of beams B1 and B2 overlap. Therefore, when beams B1 and B2 use the same sub-frequency band, two types of co-channel interference will occur in the overlapping area S1: beam B2 will interfere with users establishing communication via beam B1; and beam B1 will interfere with users establishing communication via beam B2.

[0064] Figure 5 A schematic diagram showing the overlap of three co-band beams of a satellite according to this embodiment is shown. (Reference) Figure 5As shown, the coverage areas S1 to S3 of beams B1 to B3 overlap. Therefore, when beams B1 to B3 use the same sub-frequency band, six types of co-channel interference will occur in the overlapping area SD2. Specifically, beams B2 and B3 will interfere with users establishing communication via beam B1; beams B1 and B3 will interfere with users establishing communication via beam B2; and beams B1 and B2 will interfere with users establishing communication via beam B3.

[0065] Therefore, formula S(X) can reflect the severity of co-channel interference within the satellite coverage area as a whole. Among them, 2·I1(X) reflects the severity of co-channel interference caused by the overlapping area of ​​two co-channel beams within the satellite coverage area; 6·I2(X) reflects the severity of co-channel interference caused by the overlapping area of ​​three co-channel beams within the satellite coverage area.

[0066] Optionally, the iterative optimization operation of the chromosome population according to the genetic algorithm includes: performing crossover and mutation operations on the chromosome population as the parent population to determine the child population corresponding to the parent population; calculating the fitness of chromosome vectors in the parent population and child population respectively according to the fitness function; and selecting a predetermined number of chromosome vectors as the new parent population in the order of fitness from small to large among the chromosome vectors in the parent population and child population.

[0067] Specifically, to determine the optimal chromosome vector X best In this embodiment, a genetic algorithm is used to initialize the chromosome vectors X1~X2. n Iterative optimization is performed. The core objective is to continuously improve the quality of chromosomes in the population by simulating the mechanisms of natural selection and genetic variation. The fitness function S(X) is used as a constraint; a smaller value indicates better chromosome performance. Therefore, the selection strategy should be guided by minimization.

[0068] In each generation iteration, firstly, based on the parent population (i.e., the n chromosomes X1~X of the current generation), n Crossover and mutation operations are performed to generate new subpopulations. Crossover involves exchanging different chromosome segments to create new gene structures, thus preserving population diversity while inheriting desirable traits. Mutation, on the other hand, randomly alters a chromosome at a low probability, allowing the population to escape local optima. Through these operations, n new chromosomes X are generated. n+1 To X 2n This constitutes a subpopulation.

[0069] Subsequently, the parent and child populations are merged into an extended population containing 2n chromosomes, and the fitness value S(X) of each chromosome is calculated. Since a lower value of the fitness function S(X) indicates a better chromosome, all individuals are sorted in ascending order of fitness, and the n chromosomes with the lowest fitness are selected to form the parent population for the next generation.

[0070] The above iterative process is repeated until the preset termination conditions are met, such as reaching the maximum number of iterations or the fitness improvement tending to stabilize.

[0071] Therefore, this embodiment uses a genetic algorithm for iterative optimization to ultimately output the globally optimal chromosome X. best This corresponds to the minimum fitness S(X) among all generated individuals.

[0072] Optionally, the operation of allocating corresponding sub-bands to each beam according to the optimized chromosome vector includes: determining the value indicated by the bit in the optimized chromosome vector corresponding to each beam; and determining the sub-band allocated to each beam according to the determined value.

[0073] Specifically, for each beam B1~B m , sequentially from X best Extract the corresponding bits. For example, when allocating sub-bands for beam Bᵢ, read X. best The 2i-1 and 2i bits in the equation, i.e., x2ᵢ -1 x2ᵢ. These two bits form a two-bit binary number, which can be 00, 01, 10, or 11. Convert this binary value to a decimal number, for example, 00 corresponds to 0; 01 corresponds to 1; 10 corresponds to 2; and 11 corresponds to 3. This value is the sub-band index number of the beam.

[0074] Therefore, based on the index number obtained by converting the bit values, the actual sub-frequency band uniquely assigned to beam Bᵢ can be determined from the sub-frequency bands preset by the system, thereby avoiding co-channel interference.

[0075] Optionally, the operation of determining the compatibility between different sub-bands of the satellite and different beams of the satellite includes: obtaining the following characteristic parameters of multiple coverage areas: the average rainfall rate of the coverage area; the user density of the coverage area; the service traffic demand of the coverage area; the beam elevation angle of the beam corresponding to the coverage area; and the atmospheric water vapor density of the coverage area; and determining the compatibility between different sub-bands of the satellite and different beams of the satellite based on the characteristic parameters.

[0076] Specifically, in this embodiment, each coverage area S1~S2 is acquired. m Characteristic parameters F1~F related to satellite communication mThe feature parameters include the following five parameters:

[0077] Average rainfall rate (mm / h). The average rainfall rate directly determines the severity of rain attenuation in the Ka band. Within the Ka band, the higher the frequency, the shorter the wavelength, and the higher the sensitivity to rainfall. The 38 GHz band is approximately three times more sensitive to rainfall than the 28 GHz band.

[0078] User density (number of users / km) 2 User density directly determines the total network capacity and coverage reliability required. High-density areas with high user density (F2) require larger bandwidth or more robust frequency bands (such as 28 GHz).

[0079] Business traffic requirements (Mbps / km) 2 Traffic demand measures the total amount of data a network needs to carry within a specific geographical area, directly determining the required network capacity and spectrum resource allocation strategy. Higher traffic demand necessitates greater bandwidth (e.g., 38 GHz).

[0080] Beam elevation angle (degrees). The lower the beam elevation angle, the longer the propagation path, the more significant the rain attenuation and atmospheric loss, and the greater the impact on high-frequency signals (such as 38GHz).

[0081] Atmospheric water vapor density (g / m³) 3 Atmospheric water vapor density reflects the absorption of high-frequency bands (>30 GHz) more directly than relative humidity.

[0082] Among them, for the feature parameters F1~F m Any characteristic parameter F in i ,have:

[0083]

[0084] in,

[0085] For coverage area S i The average rainfall rate;

[0086] For coverage area S i User density;

[0087] For coverage area S i The business traffic requirements;

[0088] For coverage area S i Corresponding beam B i The beam elevation angle; and

[0089] Corresponding to coverage area S i Atmospheric water vapor density.

[0090] Therefore, according to each beam B1~B m Coverage area S1~S m Parameters related to satellite communication are used to determine the relationship between each sub-band N0~N3 and each beam B1~B m The compatibility between them.

[0091] Optionally, the operation of determining the adaptability between different sub-bands of the satellite and different beams of the satellite according to the characteristic parameters includes: inputting the characteristic parameters of the coverage area into the logistic regression model corresponding to different sub-bands, and determining the adaptability between different sub-bands and different beams.

[0092] Specifically, it will be connected with each coverage area S1~S m The corresponding feature parameters F1~F m The data are input into the logistic regression models L0(F)~L3(F) corresponding to the sub-bands, and the correspondence between each sub-band and each coverage area S1~S is determined based on the logistic regression models. m Adaptability , where i=1~m, j=1~5.

[0093] Among them, the logistic regression models L0(F) to L3(F) all adopt the form of the logistic regression model shown below, only the specific parameters are different for different models:

[0094] (1); and

[0095] H(F)=k0+k1*f1+k2*f2+k3*f3+k4*f4+k5*f5 (2)

[0096] Here, f1 to f5 correspond to the five characteristics mentioned above: average rainfall rate, user density, service traffic demand, beam elevation angle, and atmospheric water vapor density.

[0097] For the logistic regression models L0(F)~L3(F) corresponding to different sub-bands N0~N3, the parameters k0~k5 take different values.

[0098] Therefore, the logistic regression model L(F) outputs a value between 0 and 1 based on the input feature parameter F. When L(F) ≥ 0.5, it indicates that the sub-band is compatible with the corresponding coverage area and can be used in that coverage area.

[0099] If L0(F1)≥0.5, it means that the beam B1 corresponding to the coverage area S1 can meet the communication requirements of the coverage area S1 by using sub-band N0.

[0100] If L0(F2) < 0.5, it means that the beam B2 corresponding to the coverage area S2 using sub-band N0 will not be able to meet the communication requirements of the coverage area S2.

[0101] If L2(F2)≥0.5, it means that the beam B2 corresponding to the coverage area S2, using sub-band N2, will be able to meet the communication requirements of the coverage area S2.

[0102] This allows us to determine the sub-bands N0~N3 and the coverage areas S1~S1. m The adaptability is shown in Table 2, which illustrates the adaptability of each sub-band to each coverage area.

[0103] Table 2

[0104]

[0105] In this context, "Y" indicates that the sub-frequency band and the coverage area are compatible, while "N" indicates that the sub-frequency band and the coverage area are not compatible.

[0106] In addition, refer to Figure 1 As 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.

[0107] Therefore, according to this embodiment, the adaptability between different sub-bands of the satellite and different beams is determined based on the characteristic parameters of the coverage area of ​​each beam in relation to satellite communication. A chromosome population is constructed, representing the sub-band allocation scheme in binary encoding, based on the chromosome vector corresponding to each beam, where every two bits correspond to the sub-band selection of one beam. The chromosome population is initialized based on the adaptability, and a fitness function is constructed to quantify the severity of co-channel interference. The chromosome population is iteratively optimized using a genetic algorithm, and finally, sub-bands are allocated to each beam based on the optimal chromosome vector. This allows for the determination of the sub-band with the lowest fitness for each beam, thereby avoiding interference between co-channels.

[0108] Therefore, by using the above method, an adaptation function is constructed based on the characteristic parameters of satellite communication. A logistic regression model is then used to determine the sub-frequency bands that can be adapted to each beam, thus meeting the communication needs of the coverage areas of each beam. Furthermore, a genetic algorithm is used to determine the sub-frequency bands corresponding to each beam, thereby avoiding co-band beam interference while meeting the communication needs of each coverage area.

[0109] 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.

[0110] 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.

[0111] Example 2

[0112] Figure 6 A satellite communication device 600 according to a first aspect of this embodiment is shown, which corresponds to the method described according to the first aspect of Embodiment 1. Reference Figure 6 As shown, the device 600 includes: an adaptability determination module 610, used to determine the adaptability between different sub-frequency bands of the satellite and different beams of the satellite, wherein the beams cover multiple coverage areas respectively; a chromosome construction module 620, used to construct a chromosome population composed of multiple chromosome vectors, wherein the chromosome vectors are composed of multiple bits, and a predetermined number of bits in the chromosome vectors correspond to a beam of the satellite, used to indicate the sub-frequency band used by the corresponding beam in a binary encoding manner; a chromosome initialization module 630, used to initialize the chromosome vectors according to the adaptability; an fitness function construction module 640, used to construct a fitness function, wherein the fitness function is used to indicate the severity of co-channel interference in multiple coverage areas after allocating sub-frequency bands to each beam according to the chromosome vectors; a genetic algorithm module 650, used to iteratively optimize the chromosome population through the fitness function according to the genetic algorithm, and determine the optimized chromosome vectors; and a communication module 660, used to allocate corresponding sub-frequency bands to each beam according to the optimized chromosome vectors and perform satellite communication.

[0113] Optionally, the adaptability determination module 610 includes: a feature parameter acquisition submodule, used to acquire feature parameters of multiple coverage areas; and a logistic regression submodule, used to input the feature parameters of the coverage areas into logistic regression models corresponding to different sub-frequency bands, and determine the adaptability between different sub-frequency bands and different beams.

[0114] Optionally, the chromosome initialization module 630 includes: a random sampling module for determining the sub-band used by each beam in a random sampling manner based on each chromosome vector and the fitness; and an encoding sub-module for encoding the corresponding bits in each chromosome vector according to the determined sub-band used by each beam.

[0115] Optionally, the genetic algorithm module 650 includes: a mutation and crossover submodule, used to perform crossover and mutation operations on the chromosome population as the parent population to determine the child population corresponding to the parent population; a fitness calculation submodule, used to calculate the fitness of chromosome vectors in the parent population and child population respectively according to the fitness function; and a sorting and filtering submodule, used to sort the chromosome vectors in the parent population and child population in ascending order of fitness and filter a predetermined number of chromosome vectors as the new parent population.

[0116] Therefore, according to this embodiment, the adaptability between different sub-bands of the satellite and different beams is determined based on the characteristic parameters of the coverage area of ​​each beam in relation to satellite communication. A chromosome population is constructed, representing the sub-band allocation scheme in binary encoding, based on the chromosome vector corresponding to each beam, where every two bits correspond to the sub-band selection of one beam. The chromosome population is initialized based on the adaptability, and a fitness function is constructed to quantify the severity of co-channel interference. The chromosome population is iteratively optimized using a genetic algorithm, and finally, sub-bands are allocated to each beam based on the optimal chromosome vector. This allows for the determination of the sub-band with the lowest fitness for each beam, thereby avoiding interference between co-channels.

[0117] Therefore, by using the above method, an adaptation function is constructed based on the characteristic parameters of satellite communication. A logistic regression model is then used to determine the sub-frequency bands that can be adapted to each beam, thus meeting the communication needs of the coverage areas of each beam. Furthermore, a genetic algorithm is used to determine the sub-frequency bands corresponding to each beam, thereby avoiding co-band beam interference while meeting the communication needs of each coverage area.

[0118] Example 3

[0119] Figure 7 A satellite communication device 700 according to a first aspect of this embodiment is shown, which corresponds to the method described according to the first aspect of Embodiment 1. Reference Figure 7As shown, the device 700 includes: a processor 710; and a memory 720 connected to the processor 710, for providing the processor 710 with instructions to perform the following processing steps: determining the adaptability between different sub-frequency bands of the satellite and different beams of the satellite, wherein the beams cover multiple coverage areas respectively; constructing a chromosome population composed of multiple chromosome vectors, wherein each chromosome vector is composed of multiple bits, and a predetermined number of bits in the chromosome vectors correspond to a beam of the satellite, for indicating the sub-frequency band used by the corresponding beam in a binary encoding manner; initializing the chromosome vectors according to the adaptability; constructing an adaptation function, wherein the adaptation function is used to indicate the severity of co-channel interference in multiple coverage areas after allocating sub-frequency bands to each beam according to the chromosome vectors; iteratively optimizing the chromosome population through the adaptation function according to a genetic algorithm, and determining the optimized chromosome vectors; and allocating corresponding sub-frequency bands to each beam according to the optimized chromosome vectors, and performing satellite communication.

[0120] Optionally, the operation of initializing the chromosome vector according to the adaptability includes: for each chromosome vector, determining the sub-band used by each beam by random sampling according to the adaptability; and encoding the corresponding bits in each chromosome vector according to the determined sub-band used by each beam.

[0121] Optionally, the operation of constructing the fitness function includes constructing the fitness function S(X) as described below:

[0122] S(X) = 2·I1(X) + 6·I2(X).

[0123] Where I1(X) represents the number of overlapping regions formed by beams of two identical sub-bands when the sub-bands of each beam are allocated according to the chromosome vector X; and I2(X) represents the number of overlapping regions formed by beams of three identical sub-bands when the sub-bands of each beam are allocated according to the chromosome vector X.

[0124] Optionally, the iterative optimization operation of the chromosome population according to the genetic algorithm includes: performing crossover and mutation operations on the chromosome population as the parent population to determine the child population corresponding to the parent population; calculating the fitness of chromosome vectors in the parent population and child population respectively according to the fitness function; and selecting a predetermined number of chromosome vectors as the new parent population in the order of fitness from small to large among the chromosome vectors in the parent population and child population.

[0125] Optionally, the operation of allocating corresponding sub-bands to each beam according to the optimized chromosome vector includes: determining the value indicated by the bit in the optimized chromosome vector corresponding to each beam; and determining the sub-band allocated to each beam according to the determined value.

[0126] Optionally, the operation of determining the compatibility between different sub-bands of the satellite and different beams of the satellite includes: obtaining the following characteristic parameters of multiple coverage areas: the average rainfall rate of the coverage area; the user density of the coverage area; the service traffic demand of the coverage area; the beam elevation angle of the beam corresponding to the coverage area; and the atmospheric water vapor density of the coverage area; and determining the compatibility between different sub-bands of the satellite and different beams of the satellite based on the characteristic parameters.

[0127] Optionally, the operation of determining the adaptability between different sub-bands of the satellite and different beams of the satellite according to the characteristic parameters includes: inputting the characteristic parameters of the coverage area into the logistic regression model corresponding to different sub-bands, and determining the adaptability between different sub-bands and different beams.

[0128] Therefore, according to this embodiment, the adaptability between different sub-bands of the satellite and different beams is determined based on the characteristic parameters of the coverage area of ​​each beam in relation to satellite communication. A chromosome population is constructed, representing the sub-band allocation scheme in binary encoding, based on the chromosome vector corresponding to each beam, where every two bits correspond to the sub-band selection of one beam. The chromosome population is initialized based on the adaptability, and a fitness function is constructed to quantify the severity of co-channel interference. The chromosome population is iteratively optimized using a genetic algorithm, and finally, sub-bands are allocated to each beam based on the optimal chromosome vector. This allows for the determination of the sub-band with the lowest fitness for each beam, thereby avoiding interference between co-channels.

[0129] Therefore, by using the above method, an adaptation function is constructed based on the characteristic parameters of satellite communication. A logistic regression model is then used to determine the sub-frequency bands that can be adapted to each beam, thus meeting the communication needs of the coverage areas of each beam. Furthermore, a genetic algorithm is used to determine the sub-frequency bands corresponding to each beam, thereby avoiding co-band beam interference while meeting the communication needs of each coverage area.

[0130] 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.

[0131] 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.

[0132] 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.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] 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 satellite communication method, characterized in that, include: The process involves determining the compatibility between different sub-frequency bands of a satellite and different beams of the satellite, wherein each beam covers multiple coverage areas. This determination includes: acquiring the following characteristic parameters of the multiple coverage areas: the average rainfall rate of the coverage area; the user density of the coverage area; the service traffic demand of the coverage area; the beam elevation angle of the beam corresponding to the coverage area; and the atmospheric water vapor density of the coverage area; and determining the compatibility between different sub-frequency bands of the satellite and different beams of the satellite based on these characteristic parameters. The operation of determining the adaptability between different sub-bands of the satellite and different beams of the satellite based on the feature parameters specifically includes: inputting the feature parameters of the coverage area into the logistic regression model corresponding to the different sub-bands, and determining the adaptability between the different sub-bands and the different beams; A chromosome population consisting of multiple chromosome vectors is constructed, wherein each chromosome vector consists of multiple bits, and a predetermined number of bits in the chromosome vectors correspond to a beam of the satellite, used to indicate the sub-band used by the corresponding beam through binary encoding. The chromosome vector is initialized based on the adaptability. Construct an adaptation function, wherein the adaptation function is used to indicate the severity of co-channel interference in the plurality of coverage areas after sub-bands are allocated to each beam according to the chromosome vector; According to the genetic algorithm, the chromosome population is iteratively optimized using the fitness function to determine the optimal chromosome vector; and Based on the optimized chromosome vector, each beam is assigned a corresponding sub-band, and satellite communication is performed.

2. The method according to claim 1, characterized in that, The operation of initializing the chromosome vector according to the adaptability includes: For each chromosome vector, the sub-band used by each beam is determined by random sampling based on the fitness; and The corresponding bits in each chromosome vector are encoded according to the sub-bands used by each determined beam.

3. The method according to claim 1, characterized in that, The operation of constructing the fitness function includes constructing the fitness function S(X) as described below: ,in I1(X) represents the number of overlapping regions formed by beams from two identical sub-bands when the sub-bands of each beam are allocated according to the chromosome vector X. as well as I2(X) represents the number of overlapping regions formed by beams from three identical sub-bands when the sub-bands of the beams are allocated according to the chromosome vector X.

4. The method according to claim 3, characterized in that, The iterative optimization operation of the chromosome population according to the genetic algorithm includes: The chromosome population is used as the parent population for crossover and mutation operations to determine the child population corresponding to the parent population; The fitness of chromosome vectors in the parent population and the child population are calculated based on the fitness function, respectively; and Chromosome vectors from the parent population and the child population are selected in ascending order of fitness to form a predetermined number of new parent populations.

5. The method according to claim 4, characterized in that, The operation of assigning corresponding sub-bands to each beam based on the optimized chromosome vector includes: Determine the values ​​indicated by the bits corresponding to each beam in the optimized chromosome vector; and Based on the determined values, the sub-bands allocated to each of the beams are determined.

6. 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 5 is performed by a processor.

7. A satellite communication device, characterized in that, include: The adaptability determination module is used to determine the adaptability between different sub-frequency bands of a satellite and different beams of the satellite, wherein the beams cover multiple coverage areas. The operation of determining the adaptability between different sub-frequency bands of the satellite and different beams of the satellite includes: acquiring the following characteristic parameters of the multiple coverage areas: the average rainfall rate of the coverage area; the user density of the coverage area; the service traffic demand of the coverage area; the beam elevation angle of the beam corresponding to the coverage area; and the atmospheric water vapor density of the coverage area; and determining the adaptability between different sub-frequency bands of the satellite and different beams of the satellite based on the characteristic parameters. The operation of determining the adaptability between different sub-bands of the satellite and different beams of the satellite based on the feature parameters specifically includes: inputting the feature parameters of the coverage area into the logistic regression model corresponding to the different sub-bands, and determining the adaptability between the different sub-bands and the different beams; A chromosome construction module is used to construct a chromosome population consisting of multiple chromosome vectors, wherein each chromosome vector consists of multiple bits, and a predetermined number of bits in the chromosome vectors correspond to a beam of the satellite, used to indicate the sub-band used by the corresponding beam in a binary encoding manner; A chromosome initialization module is used to initialize the chromosome vector according to the adaptability. An adaptation function construction module is used to construct an adaptation function, wherein the adaptation function is used to indicate the severity of co-channel interference in the multiple coverage areas after sub-bands are allocated to each beam according to the chromosome vector; A genetic algorithm module is used to iteratively optimize the chromosome population using the fitness function according to a genetic algorithm, and to determine the optimized chromosome vector; and The communication module is used to allocate corresponding sub-frequency bands to each beam according to the optimized chromosome vector and to perform satellite communication.

8. A satellite communication device, 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: The process involves determining the compatibility between different sub-frequency bands of a satellite and different beams of the satellite, wherein each beam covers multiple coverage areas. This determination includes: acquiring the following characteristic parameters of the multiple coverage areas: the average rainfall rate of the coverage area; the user density of the coverage area; the service traffic demand of the coverage area; the beam elevation angle of the beam corresponding to the coverage area; and the atmospheric water vapor density of the coverage area; and determining the compatibility between different sub-frequency bands of the satellite and different beams of the satellite based on these characteristic parameters. The operation of determining the adaptability between different sub-bands of the satellite and different beams of the satellite based on the feature parameters specifically includes: inputting the feature parameters of the coverage area into the logistic regression model corresponding to the different sub-bands, and determining the adaptability between the different sub-bands and the different beams; A chromosome population consisting of multiple chromosome vectors is constructed, wherein each chromosome vector consists of multiple bits, and a predetermined number of bits in the chromosome vectors correspond to a beam of the satellite, used to indicate the sub-band used by the corresponding beam through binary encoding. The chromosome vector is initialized based on the adaptability. Construct an adaptation function, wherein the adaptation function is used to indicate the severity of co-channel interference in the plurality of coverage areas after sub-bands are allocated to each beam according to the chromosome vector; According to the genetic algorithm, the chromosome population is iteratively optimized using the fitness function to determine the optimal chromosome vector; and Based on the optimized chromosome vector, each beam is assigned a corresponding sub-band, and satellite communication is performed.

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