Satellite-based resource allocation methods, devices, and computer-readable storage media

Abstract

The present application discloses a satellite-based resource allocation method, device and computer-readable storage medium. The method includes: determining the constraints corresponding to the multiple beams according to the bandwidth and power allocated to the multiple beams; determining the signal-to-noise power ratio of the multiple beams according to the bandwidth and power corresponding to the multiple beams; determining the channel communication capacity of the multiple beams according to the bandwidth and power corresponding to the multiple beams; calculating the capacity ratio according to the channel communication capacity of the multiple beams and the corresponding capacity requirements of the multiple beams; calculating the signal-to-noise power ratio deviation between the multiple beams according to the signal-to-noise power ratio, and calculating the capacity ratio deviation between the multiple beams according to the capacity ratio, constructing a resource allocation model according to the signal-to-noise power ratio deviation and the capacity ratio deviation; and solving the resource allocation model according to the constraints based on the particle swarm algorithm to determine the resource allocation scheme.

Description

Technical Field

[0001] The present application relates to the field of satellite technology, and in particular to a satellite-based resource allocation method, device, and computer-readable storage medium. Background Art

[0002] With the rapid growth of communication service demand, the resource allocation problem of high-throughput satellite systems has become a major research hotspot in the field of space communication technology. Among them, multi-beam technology has been widely used in modern satellite communication systems, so that bandwidth and power and other resources can be allocated to multiple beams for communication transmission. However, the traditional bandwidth and power allocation adopts a fixed average allocation strategy, resulting in equal resources provided by each beam, which does not conform to the actual situation where the requirements of each beam vary greatly, and the resource utilization rate is also low.

[0003] Currently, no effective solution has been proposed to the technical problem that the fixed average allocation strategy adopted in the above-mentioned prior art results in equal resources provided by each beam, which does not conform to the actual situation where the requirements of each beam vary greatly and the resource utilization rate is low. Summary of the invention

[0004] The embodiments of the present application provide a satellite-based resource allocation method, device, and computer-readable storage medium to at least solve the technical problem in the prior art that a fixed average allocation strategy is adopted, resulting in equal resources provided by each beam, which does not conform to the actual situation where the requirements of each beam vary greatly, and results in low resource utilization.

[0005] According to one aspect of an embodiment of the present application, a satellite-based resource allocation method is provided, including: determining constraints corresponding to multiple beams based on bandwidths and powers allocated to the multiple beams; determining the signal-to-noise power ratio of the multiple beams based on the bandwidths and powers corresponding to the multiple beams; determining the channel communication capacity of the multiple beams based on the bandwidths and powers corresponding to the multiple beams; calculating the capacity ratio based on the channel communication capacity of the multiple beams and the corresponding capacity requirements of the multiple beams; calculating the signal-to-noise power ratio deviation between the multiple beams based on the signal-to-noise power ratio, and calculating the capacity ratio deviation between the multiple beams based on the capacity ratio, constructing a resource allocation model based on the signal-to-noise power ratio deviation and the capacity ratio deviation; and solving the resource allocation model based on the constraints based on a particle swarm algorithm to determine a resource allocation plan.

[0006] According to another aspect of an embodiment of the present application, a satellite-based resource allocation device is also provided, including: a condition determination module, used to determine the constraint conditions corresponding to multiple beams according to the bandwidth and power allocated to the multiple beams; a power ratio determination module, used to determine the signal-to-noise power ratio of the multiple beams according to the bandwidth and power corresponding to the multiple beams; a capacity determination module, used to determine the channel communication capacity of the multiple beams according to the bandwidth and power corresponding to the multiple beams; a capacity ratio determination module, used to calculate the capacity ratio according to the channel communication capacity of the multiple beams and the corresponding capacity requirements of the multiple beams; a model construction module, used to calculate the signal-to-noise power ratio deviation between the multiple beams according to the signal-to-noise power ratio, and calculate the capacity ratio deviation between the multiple beams according to the capacity ratio, and construct a resource allocation model according to the signal-to-noise power ratio deviation and the capacity ratio deviation; and a scheme determination module, used to solve the resource allocation model according to the constraint conditions based on the particle swarm algorithm to determine the resource allocation scheme.

[0007] According to another aspect of an embodiment of the present application, a satellite-based resource allocation device is also provided, including: a processor; and a memory, connected to the processor, for providing the processor with instructions for processing the following processing steps: determining constraints corresponding to multiple beams based on the bandwidth and power allocated to the multiple beams; determining the signal-to-noise power ratio of the multiple beams based on the bandwidth and power corresponding to the multiple beams; determining the channel communication capacity of the multiple beams based on the bandwidth and power corresponding to the multiple beams; calculating the capacity ratio based on the channel communication capacity of the multiple beams and the corresponding capacity requirements of the multiple beams; calculating the signal-to-noise power ratio deviation between the multiple beams based on the signal-to-noise power ratio, and calculating the capacity ratio deviation between the multiple beams based on the capacity ratio, and constructing a resource allocation model based on the signal-to-noise power ratio deviation and the capacity ratio deviation; and solving the resource allocation model according to the constraints based on a particle swarm algorithm to determine a resource allocation plan.

[0008] According to another aspect of an embodiment of the present application, there is also provided an integrated electronic system, including a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the above method.

[0009] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0010] In the embodiment of the present application, in the process of optimizing the power and bandwidth allocated to each beam, the satellite calculates the signal-to-noise power ratio and the capacity ratio according to the power and bandwidth allocated to each beam, and determines the deviation of the noise power ratio and the capacity ratio of each beam from other beams according to the noise power ratio and the capacity ratio, so as to determine the power and bandwidth corresponding to each beam as the optimal resource allocation scheme with the minimum resource deviation, so that the technical scheme can allocate the corresponding power and bandwidth to each beam, so as to obtain the communication quality of each beam that is almost the same, and realize the fairness of resource allocation. And the technical scheme can better match the actual needs of different beams by dynamically adjusting the bandwidth and power allocation, avoid the waste and uneven allocation of resources, so as to more effectively cope with the changing communication load and user needs, thereby improving the overall resource utilization. The technical scheme can optimize the communication quality of each beam by finely adjusting the signal-to-noise power ratio and the channel communication capacity, so that the satellite can maintain high-quality communication services even when the network load is high or the environmental conditions are poor. And the technical scheme can accurately identify and respond to the needs of each beam by calculating the capacity demand and actual communication capacity of each beam. This solves the technical problem in the prior art that a fixed average allocation strategy is adopted, resulting in equal resources provided by each beam, which does not conform to the actual situation where the requirements of each beam vary greatly and has low resource utilization. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0012] Figure 1 is a hardware structure block diagram for implementing the satellite according to Embodiment 1 of the present application;

[0013] Figure 2 is a schematic diagram of a resource allocation system according to Embodiment 1 of the present application;

[0014] Figure 3 is a flowchart of a satellite-based resource allocation method according to the first aspect of Embodiment 1 of the present application;

[0015] Figure 4 is a sequential flow chart of the satellite-based resource allocation method according to Example 1 of the present application;

[0016] Figure 5 is a schematic diagram of a satellite-based resource allocation device according to Embodiment 2 of the present application; and

[0017] Figure 6This is a schematic diagram of a satellite-based resource allocation device according to Example 3 of the present application. DETAILED DESCRIPTION

[0018] In order to enable those skilled in the art to better understand the technical solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only embodiments of a part of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present application.

[0019] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0020] Example 1

[0021] Figure 1 A schematic diagram showing the hardware architecture of the satellite. Figure 1 As shown, the satellite 100 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, so that the processor can access the memory, read the 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 is also connected to a bus such as a CAN bus. Therefore, the processor can communicate with the satellite-borne peripherals connected to the bus through the bus managed by the bus management module. In addition, the processor is also connected to communication devices such as cameras, star sensors, measurement and control transponders, and data transmission equipment via the communication interface. It can be understood by those skilled in the art that Figure 1 The structure shown is for illustration only and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0022] It should be noted that Figure 1The one or more processors and / or other data processing circuits shown in the figure may generally be referred to as "data processing circuits" herein. The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computing device. As involved in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0023] Figure 1 The memory shown in the figure can be used to store software programs and modules of application software, such as the program instruction / data storage device corresponding to the satellite-based resource allocation method in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, the satellite-based resource allocation method of the above-mentioned application is realized. The memory may include a high-speed random access memory and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory.

[0024] It should be noted that, in some optional embodiments, the above Figure 1 The devices shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. Figure 1 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the above described apparatus.

[0025] Figure 2 is a schematic diagram of a resource allocation system according to this embodiment. Figure 2 As shown, the system includes: a satellite 100 and a ground system 200.

[0026] The satellite 100 communicates with the ground system 200 via beams.

[0027] refer to Figure 2 As shown, at the same time, the satellites 100 can be m Each beam simultaneously scans different wave positions in the coverage area corresponding to the ground system 200. In this embodiment, for example, each beam can be specified to scan the wave positions in a specified area. For example, the area covered by beam 1 is Sb 1. Coverage area Sb 1 corresponds to the wave position Pb 1~ Pb 3, so beam 1 is used for wave position Pb 1~ Pb 3 scans, and beam 1 can be directed to the covered wave position Pb 1~ Pb 3 provides satellite communication services; the area covered by beam 2 is Sb 2. Coverage area Sb 2 corresponds to the wave position Pb 4~ Pb 6, so beam 2 is used for wave position Pb 4~ Pb 6 is scanned, and beam 2 can be directed to the covered wave position Pb 4~ Pb 6Provide satellite communication services; ...; beam m The area covered is Sb m , coverage area Sb m Corresponding wave position Pb v-2 ~ Pb v , so that the beam m For wave alignment Pb v-2 ~ Pb v Scanning and beam m The wave position covered Pb v-2 ~ Pb v Provide satellite communication services. Thus, satellite 100 can m The beams are switched between corresponding wave positions, and satellite communication services are provided for each corresponding wave position in a time-division manner.

[0028] In the above operating environment, according to the first aspect of this embodiment, a satellite-based resource allocation method is provided. The method comprises: Figure 2 The satellite 100 shown in FIG. Figure 3 A schematic diagram showing the process of the method is shown in FIG. Figure 3 As shown, the method includes:

[0029] S 302: Determine constraint conditions corresponding to the multiple beams according to bandwidths and powers allocated to the multiple beams;

[0030] S 304: Determine signal-to-noise power ratios of the multiple beams according to bandwidths and powers corresponding to the multiple beams;

[0031] S 306: Determine channel communication capacities of the multiple beams according to bandwidths and powers corresponding to the multiple beams;

[0032] S308: Calculate a capacity ratio according to the channel communication capacities of the plurality of beams and the corresponding capacity requirements of the plurality of beams;

[0033] S 310: Calculate a signal-to-noise power ratio deviation between the multiple beams according to the signal-to-noise power ratio, calculate a capacity ratio deviation between the multiple beams according to the capacity ratio, and construct a resource allocation model according to the signal-to-noise power ratio deviation and the capacity ratio deviation; and

[0034] S 312: Based on the particle swarm algorithm, the resource allocation model is solved according to the constraints and the resource allocation plan is determined.

[0035] Specifically, the total bandwidth resource of satellite 100 is B t , the total power resource is P t , so that the satellite 100 can use the total bandwidth resources B t Assigned to each beam i ( i =1~ m ), and the total power resource P t Assigned to each beam i Each beam i The allocated bandwidth is B i , the power allocated is P i . Thus, satellite 100 will as well as As a constraint for allocating bandwidth and power.

[0036] Furthermore, the satellite 100 calculates the signal-to-noise power ratio according to the preset calculation formula related to the beam. i Corresponding bandwidth and power calculation beam i Signal-to-noise power ratio SNR i The satellite 100 calculates the communication capacity of the channel according to the preset calculation formula according to the beam i Corresponding bandwidth and power calculation beam i The communication capacity of the channel C i Among them, the signal-to-noise power ratio and channel communication capacity are used to indicate the communication quality and communication efficiency of the beam.

[0037] Furthermore, the satellite 100 acquires the beam in advance i Capacity requirements T i , where capacity requirementsT i For indicating beam i The minimum data transmission rate can be determined based on the beam i In the covered area Sb i In the example, the amount of data that can be transmitted in a beam hopping time slot is determined by the ratio between the beam hopping time slots (i.e., T i = data volume / beam-hopping time slot). The beam-hopping time slot represents the beam i In the covered area Sb i The time interval used to transmit data for each wave bit.

[0038] Furthermore, the satellite 100 is based on the beam i The signal-to-noise power ratio is used to calculate the signal-to-noise power ratio deviation. S The signal-to-noise power ratio deviation is used to indicate the i The deviation between the signal-to-noise power ratio of the beam and the signal-to-noise power ratio of the other beams. Then the satellite 100 determines the deviation between the signal-to-noise power ratio of the beam and the signal-to-noise power ratio of the other beams. i Capacity ratio calculation capacity ratio deviation A . The capacity ratio deviation A Used to indicate each beam i The deviation between the capacity ratio of the beam and the capacity ratio of other beams.

[0039] Then the satellite 100 obtains a preset deviation from the signal-to-noise power ratio S The corresponding weight value a 1 and capacity ratio deviation A The corresponding weight value a 2. The weight value a 1 and a 2 is set based on experience. Then the satellite 100 is based on the signal-to-noise power ratio deviation S and the corresponding weight values a 1 and capacity ratio deviation A and the corresponding weight values a 2. Build the corresponding resource allocation model: FA = a 1× S + a 2× A .in FA Indicates the minimum allocated resource value, which is used to indicate that the resource deviation between beams is the minimum, that is, the resource allocation model is used to allocate the minimum resource to the beam. i Allocate bandwidth and power so that FA Minimum.

[0040] Furthermore, the satellite 100 determines the minimum allocated resources based on the resource allocation model by using the particle swarm algorithm, subject to the constraints. as well as . Thus the particle swarm algorithm is as follows:

[0041] First, satellite 100 initializes the particle 1~ n Initial position , ,... , initial velocity , ,... , the initial individual optimal position , ,... , the initial global optimal position , ,... , initial inertia weight ω 0, learning factor c 1. c 2. Random Numbers r 1. r 2. Initialization position , ,... All meet the constraints.

[0042] And among them ;

[0043] ;

[0044] …

[0045] .

[0046] in Indicates j Particle beam i The initial bandwidth of Indicates j Particle beam i The initial power, j =1~ n .

[0047] Afterwards, the satellite 100 updates the particles according to the iterative formula of the particle swarm algorithm. j The individual optimal position and the global optimal position of the group, where the iterative formula of the particle swarm algorithm is:

[0048] V j k+1 = ωk V j k + c 1 r 1( P j k - X j k )+ c 2 r 2( G k - X j k ) (1)

[0049] X j k+1 = X j k + V j k+1 (2)

[0050] in k Indicates the number of iterations; i represents the particle number, j =1~ n ; V j k , X j k Particles j Speed ​​and position before update; V j k+1 , X j k+1 Particles j Updated speed and position; P j k , G k Particles j The individual best position of and the global best position of the group; ω k Indicates the use of preset PID Inertia weight after module update; c 1. c 2 represents the learning factor; r 1. r 2 represents a random number between 0 and 1.

[0051] For example, in the first iteration, the iteration formula of the particle swarm algorithm is:

[0052] V j 1 = ω 0 V j 0 + c 1 r 1( P j 0 - X j 0 )+ c 2 r 2( G 0- X j 0 ) (3)

[0053] X j 1 = X j 0 + V j 1 (4)

[0054] Furthermore, the satellite 100 is pre-configured with PID module, so that the satellite 100 passes PID Module inertia weight ω 0 to update and get the next iteration ω 1, and generate the updated individual best position P j 1 and the global optimal position G 1.

[0055] More specifically, satellite 100 sends individual optimal positions P j 0 Bring it into the resource allocation model to calculate the optimal position of the individual P j 0 Corresponding allocated resource value FA ( P j 0 ). And the satellite 100 will also send the position of each particle X j 0 Bring it into the resource allocation model to calculate the location X j0 Corresponding allocated resource value FA ( X j 0 ). After that, the satellite 100 will allocate resource value FA ( P j 0 ) and allocate resource values FA ( X j 0 ) for comparison, when FA ( P j 0 )≥ FA ( X j 0 ), then the individual best position for the next iteration P j 1 = X j 0 .when FA ( P j 0 )< FA ( X j 0 ), then the individual optimal position P j 1 = P j 0 The satellite 100 then sends the individual best positions of each particle to P j 0 Compare and take the smallest individual best position as the global best position G 1. Thus, the satellite 100 generates an updated individual best position P j 1 and the global optimal position G 1.

[0056] Furthermore, the satellite 100 uses the iterative formula of the particle swarm algorithm to calculate the inertia weight ω 1. Individual Optimal Position P j 1 and the global optimal position G 1 Continue the second iteration calculation until the preset number of iterations is reached.

[0057] For example, the preset number of iterations is 3, so that the satellite 100 generates the global best position at the third iteration. G 3 as the minimum allocated resource value FA The resource allocation scheme of the satellite 100 is based on the global optimal position. G 3 Corresponding beam i The bandwidth and power of each beam i Allocate bandwidth and power.

[0058] As described in the background technology, with the rapid growth of communication service demand, the resource allocation problem of high-throughput satellite systems has become a major research hotspot in the field of space communication technology. Among them, multi-beam technology has been widely used in modern satellite communication systems, so that resources such as bandwidth and power can be allocated to multiple beams for communication transmission. However, the traditional bandwidth and power allocation adopts a fixed average allocation strategy, resulting in equal resources provided by each beam, which does not conform to the actual situation where the requirements of each beam are quite different, and the resource utilization rate is also low.

[0059] In view of the technical problems described above, through the technical solutions of the embodiments of the present application, in the process of optimizing the power and bandwidth allocated to each beam, the satellite calculates the signal-to-noise power ratio and the capacity ratio according to the power and bandwidth allocated to each beam, and determines the deviation of the noise power ratio and the capacity ratio of each beam from other beams according to the noise power ratio and the capacity ratio, so as to determine the power and bandwidth corresponding to each beam as the optimal resource allocation scheme with the minimum resource deviation, so that the technical solution can allocate the corresponding power and bandwidth to each beam, so as to obtain the communication quality of each beam that is almost the same, and realize the fairness of resource allocation. In addition, the technical solution can better match the actual needs of different beams by dynamically adjusting the bandwidth and power allocation, avoiding the waste and uneven allocation of resources, so as to more effectively cope with the changing communication load and user needs, thereby improving the overall resource utilization. The technical solution can optimize the communication quality of each beam by finely adjusting the signal-to-noise power ratio and the channel communication capacity, so that the satellite can maintain high-quality communication services even when the network load is high or the environmental conditions are poor. In addition, this technical solution can accurately identify and respond to the needs of each beam by calculating the capacity requirements and actual communication capacity of each beam, thereby solving the technical problem in the prior art that a fixed average allocation strategy is adopted, resulting in equal resources provided by each beam, which does not conform to the actual situation where the requirements of each beam vary greatly, and has low resource utilization.

[0060] Optionally, the operation of determining the signal-to-noise power ratio of multiple beams based on the bandwidth and power corresponding to the multiple beams includes: calculating the receiving power of the receiving end based on the pre-calculated free space path loss between the transmitting end and the receiving end and the power allocated to the multiple beams; and calculating the signal-to-noise power ratio based on the receiving power of the receiving end and the bandwidth allocated to the multiple beams.

[0061] Specifically, during satellite communication, signal attenuation may occur, so the satellite 100 is used as a transmitter to communicate with the receiver (i.e., the ground system 200), and the free space path loss between the transmitter and the receiver is calculated. L The free space path loss is L The calculation formula is:

[0062] .

[0063] in It represents the wavelength of electromagnetic waves; d Indicates the distance between the transmitter and the receiver.

[0064] Furthermore, the satellite 100 obtains a preset transmitting end antenna gain g t , Receiver Antenna Gain g r And other attenuation L o , and then according to the free space path loss between the transmitter and the receiver L , Transmitter antenna gain g t , Receiver Antenna Gain g r And other attenuation L o Calculate the received power at the receiving end P r The receiving power at the receiving end is P r The calculation formula is:

[0065] .

[0066] in P i represents the transmit power (i.e., the power allocated to the beam i power); g t Indicates the antenna gain at the transmitting end; g t Indicates the antenna gain at the receiving end; L o Indicates other attenuation.

[0067] Furthermore, the satellite 100 receives power according to the receiving end P r and assigned to the beam i Bandwidth B i , calculate the signal-to-noise power ratio SNR i . The signal-to-noise power ratio SNR i The calculation formula is:

[0068] .

[0069] in N i Represents the pre-acquired beam i Intrinsic noise power spectral density.

[0070] Therefore, this technical solution can accurately evaluate the attenuation of the signal from the transmitter to the receiver by introducing the precise calculation of the free space path loss. This technical solution combines the influence of the antenna gain of the transmitter and the receiver, as well as other possible external attenuation factors, so that the prediction of the received power at the receiver is more accurate. In addition, this technical solution combines the received power at the receiver with the bandwidth of each beam to calculate the signal-to-noise power ratio of each beam, so that bandwidth resources can be flexibly allocated according to the real-time signal-to-noise ratio, thereby maximizing the throughput and energy efficiency of the overall network while ensuring communication quality.

[0071] Optionally, the operation of determining the channel communication capacity of multiple beams based on the bandwidth and power corresponding to the multiple beams includes: calculating the channel communication capacity of the multiple beams based on the signal-to-noise power ratio calculated based on the power allocated to the multiple beams and the bandwidth allocated to the multiple beams.

[0072] Specifically, the satellite 100 calculates the signal-to-noise power ratio SNR i and assigned to the beam i Bandwidth B i , calculate beam i The communication capacity of the channel C i The communication capacity of the channel is C i The calculation formula is:

[0073] .

[0074] Therefore, this technical solution calculates the communication capacity of each channel based on the actual signal quality and bandwidth of each beam, overcoming the limitation of the traditional method of using a unified standard for all beams, and fully tapping the unique communication potential of each beam, thereby significantly improving the overall communication efficiency of the system without increasing additional hardware costs.

[0075] Optionally, the signal-to-noise power ratio deviation between multiple beams is calculated based on the signal-to-noise power ratio, and the capacity ratio deviation between multiple beams is calculated based on the capacity ratio, and the operation of constructing a resource allocation model based on the signal-to-noise power ratio deviation and the capacity ratio deviation includes: calculating the signal-to-noise power ratio average value based on the signal-to-noise power ratio of multiple beams; calculating the signal-to-noise power ratio of multiple beams and the signal-to-noise power ratio deviation of the signal-to-noise power ratio average value; calculating the capacity ratio average value based on the capacity ratio of multiple beams; calculating the capacity ratio deviation of multiple beams and the capacity ratio average value; and constructing a resource allocation model based on the signal-to-noise power ratio deviation, the capacity ratio deviation and corresponding weights.

[0076] Specifically, the satellite 100 is based on the beam i Signal-to-noise power ratio SNR i Calculate the average signal-to-noise power ratio The signal-to-noise power ratio is The calculation formula is:

[0077] .

[0078] Then the satellite 100 is based on the beam i Signal-to-noise power ratio SNR i SNR , calculate beam i Signal-to-noise power ratio SNR i SNR The signal-to-noise power ratio deviation S . The signal-to-noise power ratio deviation S The calculation formula is:

[0079] .

[0080] Furthermore, the satellite 100 is based on the beam i Capacity ratio CT i Calculate the average capacity ratio The capacity ratio is The calculation formula is:

[0081] .

[0082] Then the satellite 100 is based on the beam i Capacity ratio CT i and capacity ratio average , calculate beam i Capacity ratio CT i and capacity ratio average Capacity ratio deviation A . The capacity ratio deviation A The calculation formula is:

[0083] .

[0084] Furthermore, the satellite 100 obtains a preset deviation from the signal-to-noise power ratio S The corresponding weight value a 1 and capacity ratio deviation A The corresponding weight value a 2. The weight value a 1 and a 2 is set based on experience, and a 1+ a 2=1. Then the satellite 100 is based on the signal-to-noise power ratio deviation S and the corresponding weight values a 1 and capacity ratio deviation A and the corresponding weight values a 2. Build the corresponding resource allocation model: FA = a 1× S + a 2× A .

[0085] Therefore, by setting weights for the signal-to-noise power ratio deviation and the capacity ratio deviation respectively, the system can take into account the requirements of both signal quality and transmission efficiency when allocating resources, so that even in the face of complex and changeable communication environments, it can ensure that resources are used most effectively, thereby ensuring the quality of communication and maximizing the overall benefits of the system.

[0086] Optionally, the operation of solving the resource allocation model according to the constraint conditions based on the particle swarm algorithm to determine the resource allocation scheme includes: calculating the average value of the distance between the position of each particle and the global optimal position according to the position of each particle and the global optimal position; using a preset PID The module calculates the average value of the distance to determine the updated inertia weight; and uses the particle swarm algorithm with the updated inertia weight to solve the resource allocation model according to the constraint conditions to determine the resource allocation plan.

[0087] Specifically, the satellite 100 needs to update the inertia weight ω k , each particle will be obtained j ( j =1~ n ) of the previous iteration X j k-1 Position and the current global best position G k-1 , and then calculate each particle j Location X j k-1 With the global best position G k-1 The sum of the distances between them is then used to calculate the average of the sum of the distances. e k :

[0088] .

[0089] Furthermore, the satellite 100 utilizes PID Module pair average e k Perform calculations to determine the updated inertia weight ω k Satellite 100 then uses the updated inertial weight ω k The particle swarm algorithm solves the resource allocation model according to the constraints and determines the resource allocation plan.

[0090] Therefore, the technical solution calculates the average value of the sum of the distances between the positions of each particle and the global optimal position, and accurately determines the inertia weight according to the update trend of each particle indicated by the average value of the distances.

[0091] Optionally, using the preset PID The module calculates the average value of the distance and determines the updated inertia weight operation, including: PID The module's preset proportional weights, integral weights, and differential weights process the average value to determine the updated inertia weight.

[0092] Specifically, PID The module includes a proportional unit, an integral unit and a differential unit. PID The module's proportional unit uses the proportional value calculation formula based on the average value e k , calculate the ratio value CP k The formula for calculating the ratio is:

[0093] CP k = e k .

[0094] Furthermore, the satellite 100 passes PID The module's integral unit uses the integral value calculation formula based on the average value e k , calculate the integral value CI k The integral value calculation formula is:

[0095] .

[0096] in e j Indicates j The average value calculated over the rounds of iterations.

[0097] Furthermore, the satellite 100 passes PID The module's differential unit uses the differential value calculation formula based on the average value e k , calculate the differential value CD k The differential value calculation formula is:

[0098] CD k = e k - e k-1 .

[0099] in e k Indicates k -The average value calculated in 1 round of iterations.

[0100] Further, PID The module also presets proportional weights WP , Points weight WI and differential weight WD , so that the satellite 100 is based on PID Module preset proportional weights WP And the corresponding ratio value CP k , integral weight WI And the corresponding integral value CI k , differential weight WD And the corresponding differential value CD k Perform a weighted sum operation to determine the updated inertia weight ωk :

[0101] .

[0102] Therefore, this technical solution utilizes PID The module can effectively reduce overshoot and ensure calculation stability through comprehensive adjustment of the three parts of proportion, integration and differentiation.

[0103] In summary, reference Figure 4 As shown, the satellite 100 determines the power and bandwidth allocated to each beam in the following order:

[0104] S401: The satellite 100 determines constraint conditions corresponding to the multiple beams according to bandwidths and powers allocated to the multiple beams;

[0105] S402: The satellite 100 calculates the receiving end receiving power according to the pre-calculated free space path loss between the transmitting end and the receiving end;

[0106] S403: The satellite 100 calculates a signal-to-noise power ratio according to the receiving end receiving power and the bandwidths allocated to the multiple beams;

[0107] S404: The satellite 100 calculates channel communication capacities of the multiple beams according to a signal-to-noise power ratio calculated based on the powers allocated to the multiple beams and bandwidths allocated to the multiple beams;

[0108] S405: The satellite 100 calculates a capacity ratio according to the channel communication capacities of the multiple beams and the corresponding capacity requirements of the multiple beams;

[0109] S406: The satellite 100 calculates an average signal-to-noise power ratio according to the signal-to-noise power ratios of the multiple beams;

[0110] S407: The satellite 100 calculates the signal-to-noise power ratios of the multiple beams and the signal-to-noise power ratio deviation of the average value of the signal-to-noise power ratios;

[0111] S408: The satellite 100 calculates an average capacity ratio according to the capacity ratios of the multiple beams;

[0112] S409: The satellite 100 calculates the capacity ratios of the multiple beams and the capacity ratio deviation of the average capacity ratio;

[0113] S410: The satellite 100 constructs a resource allocation model according to the signal-to-noise power ratio deviation, the capacity ratio deviation and corresponding weights;

[0114] S411: The satellite 100 solves the resource allocation model according to the constraint conditions based on the particle swarm algorithm and determines the resource allocation plan.

[0115] In addition, according to a second aspect of this embodiment, an integrated electronic system is provided, including a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to implement the steps of the above method.

[0116] In addition, according to a third aspect of this embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0117] Therefore, according to this embodiment, in the process of optimizing the power and bandwidth allocated to each beam, the satellite calculates the signal-to-noise power ratio and the capacity ratio according to the power and bandwidth allocated to each beam, and determines the deviation of the noise power ratio and the capacity ratio of each beam from other beams according to the noise power ratio and the capacity ratio, so as to determine the power and bandwidth corresponding to each beam as the optimal resource allocation scheme with the minimum resource deviation, so that the technical scheme can allocate corresponding power and bandwidth to each beam, so as to obtain almost the same communication quality of each beam, and realize the fairness of resource allocation. In addition, the technical scheme can better match the actual needs of different beams by dynamically adjusting the bandwidth and power allocation, avoid the waste and uneven allocation of resources, so as to more effectively cope with the changing communication load and user needs, thereby improving the overall resource utilization. The technical scheme can optimize the communication quality of each beam by finely adjusting the signal-to-noise power ratio and the channel communication capacity, so that the satellite can maintain high-quality communication services even when the network load is high or the environmental conditions are poor. In addition, this technical solution can accurately identify and respond to the needs of each beam by calculating the capacity requirements and actual communication capacity of each beam, thereby solving the technical problem in the prior art that a fixed average allocation strategy is adopted, resulting in equal resources provided by each beam, which does not conform to the actual situation where the requirements of each beam vary greatly, and has low resource utilization.

[0118] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0119] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0120] Example 2

[0121] Figure 5 The satellite-based resource allocation device 500 according to this embodiment is shown, and the device 500 corresponds to the method according to the first aspect of embodiment 1. Figure 5 As shown, the device 500 includes: a condition determination module 510, which is used to determine the constraint conditions corresponding to the multiple beams according to the bandwidth and power allocated to the multiple beams; a power ratio determination module 520, which is used to determine the signal-to-noise power ratio of the multiple beams according to the bandwidth and power corresponding to the multiple beams; a capacity determination module 530, which is used to determine the channel communication capacity of the multiple beams according to the bandwidth and power corresponding to the multiple beams; a capacity ratio determination module 540, which is used to calculate the capacity ratio according to the channel communication capacity of the multiple beams and the corresponding capacity requirements of the multiple beams; a model construction module 550, which is used to calculate the signal-to-noise power ratio deviation between the multiple beams according to the signal-to-noise power ratio, and calculate the capacity ratio deviation between the multiple beams according to the capacity ratio, and construct a resource allocation model according to the signal-to-noise power ratio deviation and the capacity ratio deviation; and a scheme determination module 560, which is used to solve the resource allocation model according to the constraint conditions based on the particle swarm algorithm to determine the resource allocation scheme.

[0122] Optionally, the power ratio determination module 520 includes: a first calculation submodule, used to calculate the receiving power of the receiving end based on the pre-calculated free space path loss between the transmitting end and the receiving end and the power allocated to multiple beams; a second calculation submodule, used to calculate the signal-to-noise power ratio based on the receiving power of the receiving end and the bandwidth allocated to multiple beams.

[0123] Optionally, the capacity determination module 530 includes: a third calculation submodule, used to calculate the channel communication capacity of the multiple beams according to the signal-to-noise power ratio calculated based on the power allocated to the multiple beams and the bandwidth allocated to the multiple beams.

[0124] Optionally, the model construction module 550 includes: a fourth calculation submodule, used to calculate the signal-to-noise power ratio average value based on the signal-to-noise power ratio of multiple beams; a fifth calculation submodule, used to calculate the signal-to-noise power ratio of multiple beams and the signal-to-noise power ratio deviation of the signal-to-noise power ratio average value; a sixth calculation submodule, used to calculate the capacity ratio average value based on the capacity ratio of multiple beams; a seventh calculation submodule, used to calculate the capacity ratio of multiple beams and the capacity ratio deviation of the capacity ratio average value; and a construction submodule, used to construct a resource allocation model based on the signal-to-noise power ratio deviation, the capacity ratio deviation and the corresponding weights.

[0125] Optionally, the solution determination module 560 includes: an eighth calculation submodule, for calculating the average value of the distance between the position of each particle and the global optimal position according to the position of each particle and the global optimal position; a first determination submodule, for using a preset PID The module calculates the average value of the distance to determine the updated inertia weight; and the second determination submodule is used to solve the resource allocation model according to the constraint conditions using the particle swarm algorithm of the updated inertia weight to determine the resource allocation plan.

[0126] Optionally, the first determination submodule includes: a weight determination unit for determining PID The module's preset proportional weights, integral weights, and differential weights process the average value to determine the updated inertia weight.

[0127] Therefore, according to this embodiment, in the process of optimizing the power and bandwidth allocated to each beam, the satellite calculates the signal-to-noise power ratio and the capacity ratio according to the power and bandwidth allocated to each beam, and determines the deviation of the noise power ratio and the capacity ratio of each beam from other beams according to the noise power ratio and the capacity ratio, so as to determine the power and bandwidth corresponding to each beam as the optimal resource allocation scheme with the minimum resource deviation, so that the technical scheme can allocate corresponding power and bandwidth to each beam, so as to obtain almost the same communication quality of each beam, and realize the fairness of resource allocation. In addition, the technical scheme can better match the actual needs of different beams by dynamically adjusting the bandwidth and power allocation, avoid the waste and uneven allocation of resources, so as to more effectively cope with the changing communication load and user needs, thereby improving the overall resource utilization. The technical scheme can optimize the communication quality of each beam by finely adjusting the signal-to-noise power ratio and the channel communication capacity, so that the satellite can maintain high-quality communication services even when the network load is high or the environmental conditions are poor. In addition, this technical solution can accurately identify and respond to the needs of each beam by calculating the capacity requirements and actual communication capacity of each beam, thereby solving the technical problem in the prior art that a fixed average allocation strategy is adopted, resulting in equal resources provided by each beam, which does not conform to the actual situation where the requirements of each beam vary greatly, and has low resource utilization.

[0128] Example 3

[0129] Figure 6 The satellite-based resource allocation device 600 according to the first aspect of this embodiment is shown, and the device 600 corresponds to the method according to the first aspect of embodiment 1. Figure 6 As shown, the device 600 includes: a processor 610; and a memory 620, which is connected to the processor 610 and is used to provide the processor 610 with instructions for processing the following processing steps: determining constraints corresponding to multiple beams according to the bandwidth and power allocated to the multiple beams; determining the signal-to-noise power ratio of the multiple beams according to the bandwidth and power corresponding to the multiple beams; determining the channel communication capacity of the multiple beams according to the bandwidth and power corresponding to the multiple beams; calculating the capacity ratio according to the channel communication capacity of the multiple beams and the corresponding capacity requirements of the multiple beams; calculating the signal-to-noise power ratio deviation between the multiple beams according to the signal-to-noise power ratio, and calculating the capacity ratio deviation between the multiple beams according to the capacity ratio, and constructing a resource allocation model according to the signal-to-noise power ratio deviation and the capacity ratio deviation; and solving the resource allocation model according to the constraints based on the particle swarm algorithm to determine the resource allocation plan.

[0130] Optionally, the operation of determining the signal-to-noise power ratio of multiple beams based on the bandwidth and power corresponding to the multiple beams includes: calculating the receiving power of the receiving end based on the pre-calculated free space path loss between the transmitting end and the receiving end and the power allocated to the multiple beams; and calculating the signal-to-noise power ratio based on the receiving power of the receiving end and the bandwidth allocated to the multiple beams.

[0131] Optionally, the operation of determining the channel communication capacity of multiple beams based on the bandwidth and power corresponding to the multiple beams includes: calculating the channel communication capacity of the multiple beams based on the signal-to-noise power ratio calculated based on the power allocated to the multiple beams and the bandwidth allocated to the multiple beams.

[0132] Optionally, the signal-to-noise power ratio deviation between multiple beams is calculated based on the signal-to-noise power ratio, and the capacity ratio deviation between multiple beams is calculated based on the capacity ratio, and the operation of constructing a resource allocation model based on the signal-to-noise power ratio deviation and the capacity ratio deviation includes: calculating the signal-to-noise power ratio average value based on the signal-to-noise power ratio of multiple beams; calculating the signal-to-noise power ratio of multiple beams and the signal-to-noise power ratio deviation of the signal-to-noise power ratio average value; calculating the capacity ratio average value based on the capacity ratio of multiple beams; calculating the capacity ratio deviation of multiple beams and the capacity ratio average value; and constructing a resource allocation model based on the signal-to-noise power ratio deviation, the capacity ratio deviation and corresponding weights.

[0133] Optionally, the operation of solving the resource allocation model according to the constraint conditions based on the particle swarm algorithm to determine the resource allocation scheme includes: calculating the average value of the distance between the position of each particle and the global optimal position according to the position of each particle and the global optimal position; using a preset PID The module calculates the average value of the distance to determine the updated inertia weight; and uses the particle swarm algorithm with the updated inertia weight to solve the resource allocation model according to the constraint conditions to determine the resource allocation plan.

[0134] Optionally, using the preset PID The module calculates the average value and determines the updated inertia weight operation, including: PID The module's preset proportional weights, integral weights, and differential weights process the average value to determine the updated inertia weight.

[0135] Therefore, according to this embodiment, in the process of optimizing the power and bandwidth allocated to each beam, the satellite calculates the signal-to-noise power ratio and the capacity ratio according to the power and bandwidth allocated to each beam, and determines the deviation of the noise power ratio and the capacity ratio of each beam from other beams according to the noise power ratio and the capacity ratio, so as to determine the power and bandwidth corresponding to each beam as the optimal resource allocation scheme with the minimum resource deviation, so that the technical scheme can allocate corresponding power and bandwidth to each beam, so as to obtain almost the same communication quality of each beam, and realize the fairness of resource allocation. In addition, the technical scheme can better match the actual needs of different beams by dynamically adjusting the bandwidth and power allocation, avoid the waste and uneven allocation of resources, so as to more effectively cope with the changing communication load and user needs, thereby improving the overall resource utilization. The technical scheme can optimize the communication quality of each beam by finely adjusting the signal-to-noise power ratio and the channel communication capacity, so that the satellite can maintain high-quality communication services even when the network load is high or the environmental conditions are poor. In addition, this technical solution can accurately identify and respond to the needs of each beam by calculating the capacity requirements and actual communication capacity of each beam, thereby solving the technical problem in the prior art that a fixed average allocation strategy is adopted, resulting in equal resources provided by each beam, which does not conform to the actual situation where the requirements of each beam vary greatly, and has low resource utilization.

[0136] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0137] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0138] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0139] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0140] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0141] If the integrated unit is implemented in the form of 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. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0142] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A satellite-based resource allocation method, characterized in that: include: Determining constraints corresponding to the plurality of beams according to bandwidths and powers allocated to the plurality of beams; determining signal-to-noise power ratios of the plurality of beams based on the bandwidths and the powers corresponding to the plurality of beams; determining channel communication capacities of the plurality of beams according to the bandwidths and the powers corresponding to the plurality of beams; calculating a capacity ratio according to channel communication capacities of the plurality of beams and corresponding capacity requirements of the plurality of beams; Calculating a signal-to-noise power ratio deviation between the multiple beams according to the signal-to-noise power ratio, and calculating a capacity ratio deviation between the multiple beams according to the capacity ratio, and constructing a resource allocation model according to the signal-to-noise power ratio deviation and the capacity ratio deviation; as well as The resource allocation model is solved according to the constraint conditions based on the particle swarm algorithm to determine the resource allocation plan, wherein The operation of calculating the signal-to-noise power ratio deviation between the multiple beams according to the signal-to-noise power ratio, and calculating the capacity ratio deviation between the multiple beams according to the capacity ratio, and constructing a resource allocation model according to the signal-to-noise power ratio deviation and the capacity ratio deviation, including: calculating a signal-to-noise power ratio average value according to the signal-to-noise power ratio of the multiple beams, wherein the signal-to-noise power ratio average value The calculation formula is: ， in SNR i Representation beam i The signal-to-noise power ratio is m, where m represents the number of beams. Calculate the signal-to-noise power ratio deviation between the signal-to-noise power ratios of the plurality of beams and the average value of the signal-to-noise power ratios, wherein the signal-to-noise power ratio deviation S The calculation formula is: ； The capacity ratio average value is calculated according to the capacity ratios of the plurality of beams, wherein the capacity ratio average value The calculation formula is: ， in CT i Representation beam i Capacity ratio; Calculate the capacity ratio deviation of the capacity ratios of the plurality of beams and the capacity ratio average value, wherein the capacity ratio deviation A The calculation formula is: ； And constructing the resource allocation model according to the signal-to-noise power ratio deviation, the capacity ratio deviation and corresponding weights: FA = a 1× S + a 2× A ， in a 1 indicates the preset deviation from the signal-to-noise power ratio S The corresponding weight value, a 2 indicates deviation from capacity ratio A The corresponding weight value, weight value a 1 and a 2 is set based on experience, and a 1+ a 2=1, where FA Indicates the minimum allocated resource value, which is used to indicate that the resource deviation between each beam is the smallest, that is, the resource allocation model is used to allocate the minimum resource to the beam. i Allocate bandwidth and power so that FA Minimum, among which The operation of solving the resource allocation model according to the constraint conditions based on the particle swarm algorithm to determine the resource allocation scheme includes: calculating the position of each particle j according to the position of each particle and the global optimal position X j k-1 With the global optimal position G k-1 The average distance between e k : ； Where n represents the number of particles; Using the preset PID The module calculates the average value of the distance to determine the updated inertia weight; and uses the particle swarm algorithm of the updated inertia weight to solve the resource allocation model according to the constraint conditions to determine the resource allocation plan, wherein Using the preset PID The module calculates the average value of the distance and determines the operation of the updated inertia weight, including: PID The module's proportional unit uses a proportional value calculation formula based on the average value e k , calculate the ratio value CP k , where the ratio value calculation formula is: CP k = e k ； Through the PID The module's integral unit uses the integral value calculation formula based on the average value e k , calculate the integral value CI k , where the integral value calculation formula is: ， in e j Indicates j The average value calculated by round iterations; Through the PID The differential unit of the module uses the differential value calculation formula according to the average value e k , calculate the differential value CD k , where the differential value calculation formula is: CD k = e k - e k-1 ， in e k Indicates k -The average value calculated in 1 round of iterations; According to the PID Module preset proportional weights WP , Points weight WI and differential weight WD The average value of the distance is processed to determine the updated inertia weight ω k : ω k = CP k * WP + CI k * WI + CD k * WD 。 2. The method according to claim 1, characterized in that The operation of determining the signal-to-noise power ratios of the plurality of beams according to the bandwidths and the powers corresponding to the plurality of beams comprises: Calculating the receiving end receiving power according to the pre-calculated free space path loss between the transmitting end and the receiving end and the power allocated to the plurality of beams; and The signal-to-noise power ratio is calculated according to the receiving end receiving power and the bandwidth allocated to the multiple beams.

3. The method according to claim 2, characterized in that The operation of determining the channel communication capacity of the plurality of beams according to the bandwidths and the powers corresponding to the plurality of beams comprises: The channel communication capacities of the plurality of beams are calculated according to signal-to-noise power ratios calculated based on the powers allocated to the plurality of beams and bandwidths allocated to the plurality of beams.

4. A satellite-based resource allocation device, characterized in that: include: A condition determination module, configured to determine constraint conditions corresponding to the plurality of beams according to bandwidths and powers allocated to the plurality of beams; a power ratio determination module, configured to determine the signal-to-noise power ratios of the multiple beams according to the bandwidths and the powers corresponding to the multiple beams; A capacity determination module, configured to determine the channel communication capacity of the multiple beams according to the bandwidths and the powers corresponding to the multiple beams; A capacity ratio determination module, configured to calculate a capacity ratio according to the channel communication capacities of the plurality of beams and the corresponding capacity requirements of the plurality of beams; a model building module, configured to calculate a signal-to-noise power ratio deviation between the multiple beams according to the signal-to-noise power ratio, calculate a capacity ratio deviation between the multiple beams according to the capacity ratio, and build a resource allocation model according to the signal-to-noise power ratio deviation and the capacity ratio deviation; as well as A solution determination module is used to solve the resource allocation model according to the constraint conditions based on the particle swarm algorithm to determine the resource allocation solution, wherein The operation of calculating the signal-to-noise power ratio deviation between the multiple beams according to the signal-to-noise power ratio, and calculating the capacity ratio deviation between the multiple beams according to the capacity ratio, and constructing a resource allocation model according to the signal-to-noise power ratio deviation and the capacity ratio deviation, including: calculating a signal-to-noise power ratio average value according to the signal-to-noise power ratio of the multiple beams, wherein the signal-to-noise power ratio average value The calculation formula is: ， in SNR i Representation beam i The signal-to-noise power ratio is m, where m represents the number of beams. Calculate the signal-to-noise power ratio deviation between the signal-to-noise power ratios of the plurality of beams and the average value of the signal-to-noise power ratios, wherein the signal-to-noise power ratio deviation S The calculation formula is: ； The capacity ratio average value is calculated according to the capacity ratios of the plurality of beams, wherein the capacity ratio average value The calculation formula is: ， in CT i Representation beam i Capacity ratio; Calculate the capacity ratio deviation of the capacity ratios of the plurality of beams and the capacity ratio average value, wherein the capacity ratio deviation A The calculation formula is: ； And constructing the resource allocation model according to the signal-to-noise power ratio deviation, the capacity ratio deviation and corresponding weights: FA = a 1× S + a 2× A ， in a 1 indicates the preset deviation from the signal-to-noise power ratio S The corresponding weight value, a 2 indicates deviation from capacity ratio A The corresponding weight value, weight value a 1 and a 2 is set based on experience, and a 1+ a 2=1, where FA Indicates the minimum allocated resource value, which is used to indicate that the resource deviation between each beam is the smallest, that is, the resource allocation model is used to allocate the minimum resource to the beam. i Allocate bandwidth and power so that FA Minimum, among which The operation of solving the resource allocation model according to the constraint conditions based on the particle swarm algorithm to determine the resource allocation scheme includes: calculating the position of each particle j according to the position of each particle and the global optimal position X j k-1 With the global optimal position G k-1 The average distance between e k : ； Where n represents the number of particles; Using the preset PID The module calculates the average value of the distance to determine the updated inertia weight; and uses the particle swarm algorithm of the updated inertia weight to solve the resource allocation model according to the constraint conditions to determine the resource allocation plan, wherein Using the preset PID The module calculates the average value of the distance and determines the operation of the updated inertia weight, including: PID The module's proportional unit uses a proportional value calculation formula based on the average value e k , calculate the ratio value CP k , where the ratio value calculation formula is: CP k = e k ； Through the PID The module's integral unit uses the integral value calculation formula based on the average value e k , calculate the integral value CI k , where the integral value calculation formula is: ， in e j Indicates j The average value calculated by round iterations; Through the PID The differential unit of the module uses the differential value calculation formula according to the average value e k , calculate the differential value CD k , where the differential value calculation formula is: CD k = e k - e k-1 ， in e k Indicates k -The average value calculated in 1 round of iterations; According to the PID Module preset proportional weights WP , Points weight WI and differential weight WD The average value of the distance is processed to determine the updated inertia weight ω k : ω k = CP k * WP + CI k * WI + CD k * WD 。 5. A satellite-based resource allocation device, characterized in that: include: processor; as well as A memory, connected to the processor, configured to provide the processor with instructions for processing the following processing steps: Determining constraints corresponding to the plurality of beams according to bandwidths and powers allocated to the plurality of beams; determining signal-to-noise power ratios of the plurality of beams based on the bandwidths and the powers corresponding to the plurality of beams; determining channel communication capacities of the plurality of beams according to the bandwidths and the powers corresponding to the plurality of beams; calculating a capacity ratio according to channel communication capacities of the plurality of beams and corresponding capacity requirements of the plurality of beams; Calculating a signal-to-noise power ratio deviation between the multiple beams according to the signal-to-noise power ratio, and calculating a capacity ratio deviation between the multiple beams according to the capacity ratio, and constructing a resource allocation model according to the signal-to-noise power ratio deviation and the capacity ratio deviation; as well as The resource allocation model is solved according to the constraint conditions based on the particle swarm algorithm to determine the resource allocation plan.

6. An integrated electronic system comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method of claim 1, wherein The operation of calculating the signal-to-noise power ratio deviation between the multiple beams according to the signal-to-noise power ratio, and calculating the capacity ratio deviation between the multiple beams according to the capacity ratio, and constructing a resource allocation model according to the signal-to-noise power ratio deviation and the capacity ratio deviation, including: calculating a signal-to-noise power ratio average value according to the signal-to-noise power ratio of the multiple beams, wherein the signal-to-noise power ratio average value The calculation formula is: ， in SNR i Representation beam i The signal-to-noise power ratio is m, where m represents the number of beams. Calculate the signal-to-noise power ratio deviation between the signal-to-noise power ratios of the plurality of beams and the average value of the signal-to-noise power ratios, wherein the signal-to-noise power ratio deviation S The calculation formula is: ； The capacity ratio average value is calculated according to the capacity ratios of the plurality of beams, wherein the capacity ratio average value The calculation formula is: ， in CT i Representation beam i Capacity ratio; Calculate the capacity ratio deviation of the capacity ratios of the plurality of beams and the capacity ratio average value, wherein the capacity ratio deviation A The calculation formula is: ； And constructing the resource allocation model according to the signal-to-noise power ratio deviation, the capacity ratio deviation and corresponding weights: FA = a 1× S + a 2× A ， in a 1 indicates the preset deviation from the signal-to-noise power ratio S The corresponding weight value, a 2 indicates deviation from capacity ratio A The corresponding weight value, weight value a 1 and a 2 is set based on experience, and a 1+ a 2=1, where FA Indicates the minimum allocated resource value, which is used to indicate that the resource deviation between each beam is the smallest, that is, the resource allocation model is used to allocate the minimum resource to the beam. i Allocate bandwidth and power so that FA Minimum, among which The operation of solving the resource allocation model according to the constraint conditions based on the particle swarm algorithm to determine the resource allocation scheme includes: calculating the position of each particle j according to the position of each particle and the global optimal position X j k-1 With the global optimal position G k-1 The average distance between e k : ； Where n represents the number of particles; Using the preset PID The module calculates the average value of the distance to determine the updated inertia weight; and uses the particle swarm algorithm of the updated inertia weight to solve the resource allocation model according to the constraint conditions to determine the resource allocation plan, wherein Using the preset PID The module calculates the average value of the distance and determines the operation of the updated inertia weight, including: PID The module's proportional unit uses a proportional value calculation formula based on the average value e k , calculate the ratio value CP k , where the ratio value calculation formula is: CP k = e k ； Through the PID The module's integral unit uses the integral value calculation formula based on the average value e k , calculate the integral value CI k , where the integral value calculation formula is: ， in e j Indicates j The average value calculated by round iterations; Through the PID The differential unit of the module uses the differential value calculation formula according to the average value e k , calculate the differential value CD k , where the differential value calculation formula is: CD k = e k - e k-1 ， in e k Indicates k -The average value calculated in 1 round of iterations; According to the PID Module preset proportional weights WP , Points weight WI and differential weight WD The average value of the distance is processed to determine the updated inertia weight ω k : ω k = CP k * WP + CI k * WI + CD k * WD 。 7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to claim 1 are implemented.

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