A satellite hybrid hop beam allocation method and device and a storage medium

Abstract

The application discloses a satellite hybrid hop-beam allocation method and device and a storage medium, and relates to the technical field of satellite communication. The method comprises the following steps: determining a regular beam and a wandering beam corresponding to a target cluster in a current hop-beam period; defining a wave position allocation variable and a power allocation variable corresponding to the wave position of different hop-beam time slots of the wandering beam in the current hop-beam period; defining a chromosome vector according to the wave position allocation variable and the power allocation variable, and initializing the chromosome vector to obtain a chromosome population; constructing a fitness function; iteratively optimizing the chromosome population by using a genetic algorithm to determine an optimal chromosome vector; and determining an optimal joint allocation mode of the wave position and the power of the wandering beam of the target cluster in the current hop-beam period according to the optimal chromosome vector. Thus, the application realizes time slot-beam-power three-dimensional cooperative joint allocation of the target cluster in a single hop-beam period under a low-orbit satellite hybrid hop-beam architecture.

Description

Technical Field

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

[0002] Currently, beam hopping technology is widely used in resource allocation for low-Earth orbit satellite communication systems. Existing technologies have proposed a hybrid beam hopping architecture that combines fixed beams and wandering beams. In the practical application of this hybrid architecture, the satellite coverage area is divided into multiple bandgap clusters. Fixed beams are assigned to corresponding bandgap clusters using conventional scanning methods to achieve basic coverage; while wandering beams can flexibly scan across clusters.

[0003] For example, publication number CN109450498A, entitled "A Beam-hopping Method for High-throughput Satellite Communication Systems," describes a method that uniformly clusters the total beam according to service requirements. It establishes an objective function based on these requirements, monitors whether the edge beam distance between adjacent clusters is equal to 2R and whether they are operational. If not, the performance is satisfactory, and the spectral efficiency is directly calculated. If so, interference avoidance measures are implemented, and then the spectral efficiency is calculated. The KKT conditions are used to solve for the number of time slots in the closed-form solution. Finally, the value of the closed-form solution is rounded down and optimized to obtain the optimal capacity allocation.

[0004] For example, CN118101035A, entitled "A Beamforming Method for Beam-hopping Satellite Communication," is based on the construction of a downlink signal reception model, a downlink channel model, and an achievable rate model. It constructs a model to solve the sum rate maximization optimization problem of the joint all-digital beamforming and the spot lighting mode, obtaining the optimal spot lighting mode and the optimal all-digital beamforming matrix. Then, based on the optimal all-digital beamforming matrix, it constructs an optimization problem to solve the all-digital beamforming matrix and the hybrid beamforming matrix, obtaining the optimal hybrid beamforming matrix, which is used to illuminate each spot in the communication ground area by the target satellite under beam-hopping period.

[0005] As is well known, a position cluster consists of multiple positions. According to conventional beam scanning technology, within a single beam-hopping period (BHP), the beam scans different positions within the position cluster in different beam-hopping slots (BHS). However, in a hybrid beam-hopping architecture, within a single BHP, not only does a fixed beam scan each position of the position cluster using conventional beam scanning technology, but at least one wandering beam also scans each position. Therefore, how to schedule the scanning positions and scanning power of the wandering beam is a crucial technical problem that needs to be solved. Currently, however, no scheduling scheme for the scanning positions and scanning power of the wandering beam has been proposed, making it impossible to optimize the scheduling of the wandering beam's positions and power.

[0006] There is currently no effective solution to the technical problem in the existing technology that cannot optimize the scheduling of the wave position and power of the wandering beam. Summary of the Invention

[0007] The embodiments of this disclosure provide a satellite hybrid hopping beam allocation method, apparatus, and storage medium to at least solve the technical problem in the prior art that it is impossible to optimize the scheduling of the wave positions and power of wandering beams.

[0008] According to one aspect of the present disclosure, a satellite hybrid beam-hopping allocation method is provided, comprising: determining a scanning beam corresponding to a target cluster within a current beam-hopping period, wherein the scanning beam includes a conventional beam and a wandering beam; defining a position allocation variable and a power allocation variable corresponding to the positions of different beam-hopping time slots of the wandering beam within the current beam-hopping period; defining a chromosome vector based on the position allocation variable and the power allocation variable, and initializing the chromosome vector to obtain a chromosome population, wherein the chromosome vector represents the joint allocation method of the target cluster with the corresponding positions and powers of each beam-hopping time slot and each scanning beam within the current beam-hopping period; constructing a fitness function, wherein the fitness function is related to the total transmitted data volume of the target cluster, the load transmission ratio of each position of the target cluster, and the total interference power of the wandering beam within the current beam-hopping period; iteratively optimizing the chromosome population using a genetic algorithm based on the fitness function to determine the optimal chromosome vector; and determining the optimal joint allocation method of the positions and powers of the wandering beams of the target cluster within the current beam-hopping period based on the optimal chromosome vector.

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

[0010] According to another aspect of the present disclosure, a satellite hybrid beam hopping allocation device is also provided, comprising: a scanning beam determination module, configured to determine a scanning beam corresponding to a target cluster within the current beam hopping period, wherein the scanning beam includes a conventional beam and a wandering beam; an allocation variable definition module, configured to define a wave position allocation variable and a power allocation variable corresponding to the wave positions of the wandering beam in different beam hopping time slots within the current beam hopping period; and a chromosome vector definition module, configured to define a chromosome vector based on the wave position allocation variable and the power allocation variable, and initialize the chromosome vector to obtain a chromosome population, wherein the chromosome vector represents the target cluster in the current beam hopping period. The system includes: a joint allocation method for the time slots of each hopping beam in the current period and the corresponding positions and powers of each scanning beam; a fitness function construction module for constructing a fitness function, which is related to the total amount of transmitted data of the target cluster in the current hopping beam period, the load transmission ratio of each position of the target cluster, and the total interference power of the wandering beams; an iterative optimization module for iteratively optimizing the chromosome population using a genetic algorithm based on the fitness function to determine the optimal chromosome vector; and an optimal joint allocation method determination module for determining the optimal joint allocation method of the positions and powers of the wandering beams of the target cluster in the current hopping beam period based on the optimal chromosome vector.

[0011] According to another aspect of the present disclosure, a satellite hybrid beam-hopping allocation 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 a scanning beam corresponding to a target cluster within the current beam-hopping period, wherein the scanning beam includes a conventional beam and a wandering beam; defining a preamplitude allocation variable and a power allocation variable corresponding to the preamplitude of the wandering beam in different beam-hopping time slots within the current beam-hopping period; defining a chromosome vector based on the preamplitude allocation variable and the power allocation variable, and initializing the chromosome vector to obtain a chromosome species. A population is formed, where the chromosome vector represents the joint allocation of the target cluster's hop beam time slots with the corresponding positions and powers of each scanning beam in the current hop beam cycle. A fitness function is constructed, which is related to the total amount of data transmitted by the target cluster in the current hop beam cycle, the load transmission ratio of each position of the target cluster, and the total interference power of the wandering beams. Based on the fitness function, a genetic algorithm is used to iteratively optimize the chromosome population to determine the optimal chromosome vector. And based on the optimal chromosome vector, the optimal joint allocation of the target cluster's positions and powers of the wandering beams in the current hop beam cycle is determined.

[0012] This application addresses the hybrid hopping beam architecture for low-Earth orbit (LEO) satellites, which combines conventional fixed cluster beams with cross-cluster wandering scanning beams. Based on the joint allocation requirements of time slots, beams, and power for the target cluster within a single hopping beam cycle, it first determines the conventional beams and wandering beams corresponding to the target cluster within the current hopping beam cycle. Then, it defines the wavelet allocation variables and power allocation variables for the wandering beams in different hopping beam time slots and corresponding wavelets. Next, based on the wavelet allocation variables and power allocation variables, it defines a chromosome vector characterizing the joint allocation method of wavelets and power for each scanning beam and each hopping beam for the target cluster within the current hopping beam cycle. Finally, it initializes this chromosome vector to obtain a chromosome population. Subsequently, a fitness function is constructed that is related to the total amount of transmitted data of the target cluster in the current hopping beam cycle, the load transmission ratio matching degree of each wave position of the target cluster, and the total interference power of the wandering beam. Finally, using this fitness function as the quantitative evaluation basis, a genetic algorithm is used to perform genetic operations such as selection, crossover, and mutation on the chromosome population and to perform iterative optimization until the algorithm convergence condition is met. Then, the optimal chromosome vector of the optimal joint allocation method for the corresponding target cluster is determined, so as to realize the precise joint allocation of time slot-beam-power of the target cluster in the current hopping beam cycle.

[0013] Thus, this application realizes the three-dimensional coordinated allocation of time slots, beams, and power of target clusters within a single hop beam cycle under the hybrid hop beam architecture of low-orbit satellites, solving the technical problem in the prior art that it is impossible to optimize the scheduling of wave positions and power of wandering beams. Attached Figure Description

[0014] 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: Figure 1 This is a schematic diagram of the coverage area scanned by conventional beam and wandering beam according to Embodiment 1 of this disclosure; Figure 2 This is a hardware structure block diagram of a computing device for implementing the method described in Embodiment 1 of this disclosure; Figure 3 This is a schematic flowchart of the satellite hybrid beam hopping allocation method according to Embodiment 1 of this disclosure; Figure 4 This is a schematic diagram of the wave cluster structure according to Embodiment 1 of this disclosure; Figure 5A This is a schematic diagram of the wave position division of the chromosome vector according to the method described in Embodiment 1 of this disclosure; Figure 5B This is a schematic diagram of the division of wave position blocks according to the method described in Embodiment 1 of this disclosure; Figure 5CThis is a schematic diagram of the power block division according to the method described in Embodiment 1 of this disclosure; Figure 6 This is a schematic diagram of a satellite hybrid beam hopping allocation device according to Embodiment 2 of this disclosure; Figure 7 This is a schematic diagram of a satellite hybrid beam hopping allocation device according to Embodiment 3 of this disclosure. Detailed Implementation

[0015] 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.

[0016] 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.

[0017] Example 1

[0018] According to this embodiment, a method embodiment for satellite hybrid beam hopping allocation is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0019] Figure 1 A schematic diagram of the coverage area scanned by conventional beam and wandering beam according to Embodiment 1 of this disclosure is shown. (Reference) Figure 1 As shown, the coverage area of ​​satellite 10 is divided into m wavelet clusters, and satellite 10 has m conventional beams. Corresponding to wave position clusters Conventional beam Used for wave position clusters It performs scanning and provides satellite communication services. However, due to a portion of the wavelength clusters... The increased communication demands exceed those of conventional beamforming. Communication capabilities are required, therefore a wandering beam is needed. Assist conventional beam Wavelet clusters with increased scanning communication requirements Among them, wandering beam It can move between different beam hops and multiple beam clusters, but only one beam cluster is assigned for scanning within a single beam hop period. Here, i represents the i-th moving beam. For ease of explanation, this application focuses on the target beam cluster within a single beam hop period. Only wave position scheduling within this wave position cluster is considered.

[0020] Figure 2 Further shown Figure 1 A schematic diagram of the hardware architecture of Zhongwei Satellite-10. (Reference) Figure 2 As shown, satellite 10 includes an integrated electronic system, which comprises 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 2 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 2 The more or fewer components shown, or having the same Figure 2 The different configurations shown.

[0021] It is worth noting that the aforementioned spaceborne peripherals connected to the CAN bus can be one or multiple. These spaceborne peripherals include, but are not limited to, GNSS modules, fiber optic gyroscopes, and high-torque flywheels. Further details will not be elaborated upon here.

[0022] It should be noted that, Figure 2One 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).

[0023] Figure 2 The memory shown can be used to store software programs and modules of application software, such as the program instruction / data storage device corresponding to the beam scanning allocation method in the embodiments of this disclosure. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby implementing the beam scanning allocation method of the application described above. 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.

[0024] It should be noted here that, in some optional embodiments, the above... Figure 2 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 2 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.

[0025] Under the aforementioned operating environment, according to the first aspect of this embodiment, a satellite hybrid beam hopping allocation method is provided, which consists of... Figure 2 The integrated electronic system shown is implemented. Figure 3 A flowchart illustrating the method is shown below. (Refer to...) Figure 3 As shown, the method includes: S302: Determine the scanning beam corresponding to the target cluster within the current hopping beam cycle, wherein the scanning beam includes a regular beam and a wandering beam; S304: Define the beam position allocation variables and power allocation variables corresponding to the beam positions of different hop beam slots within the current hop beam period of the wandering beam; S306: Define a chromosome vector based on the wave position allocation variable and the power allocation variable, and initialize the chromosome vector to obtain a chromosome population. The chromosome vector represents the joint allocation method of the target cluster with the corresponding wave position and power of each hop beam time slot and each scanning beam in the current hop beam cycle. S308: Construct a fitness function, which is related to the total amount of transmitted data of the target cluster in the current hopping beam period, the load transmission ratio matching degree of each wave position of the target cluster, and the total interference power of the wandering beam. S310: Based on the fitness function, use a genetic algorithm to iteratively optimize the chromosome population and determine the optimal chromosome vector; and S312: Based on the optimal chromosome vector, determine the optimal joint allocation of wave position and power of the wandering beam of the target cluster within the current hopping beam period.

[0026] In this embodiment, in order to target wave clusters A scan is performed; within the current BHP, the integrated electronic system targets multiple wavelet clusters. One of the target clusters Determine the corresponding conventional beam and wandering beam (Corresponding to step S302). Wherein, This represents the total number of beams within the wandering beam subset.

[0027] Specifically, in this embodiment, satellite 10 is configured with a total of Each scanning beam is divided into A conventional beam and One wandering beam. The number of wandering beams. With the number of scanning beams And the number of conventional beams The relationship is: - (1) Among them, conventional beam Used with the corresponding wavelet cluster Assign scanning, and each wandering beam It can move between different BHPs and multiple wave position clusters, but only for one target cluster (e.g., the target cluster) within a BHP period. ,but (Scan)

[0028] Then, the integrated electronic system defines the wandering beam. Wave position allocation variables corresponding to the wave positions in different hop beam slots within the current hop beam cycle. and power allocation variables (Corresponding to step S304).

[0029] Specifically, in this embodiment, the integrated electronic system employs a time-slot hopping beam mechanism, dividing the time axis into continuous beam-hopping periods (BHPs), each BHP lasting for a duration of [duration missing]. Each BHP is further divided into There are 10 equal-length minimum hop beamslot (BHS) units, where the hop beamslots are numbered as follows: The duration of a single hop beam time slot can be obtained using the following formula. : (2) Then, refer to Figure 4 As shown, target cluster Include One wave position (wave position numbered as follows) Conventional beam Fixed allocation target cluster In the target cluster The beam transitions between beam positions according to a preset scanning sequence and a fixed timing sequence, maintaining a relatively constant power. However, the wandering beam... The scanning order and power within the target cluster Z0 can be scheduled.

[0030] Therefore, within the current BHP, the integrated electronic system targets the cluster. Determine the corresponding conventional beam and wandering beam Then, for each wandering beam Each combination of hop beam time slot t and each beam position b is configured with a separate beam position allocation variable. The wave position allocation variable This is used to characterize whether the corresponding wandering beam is allocated to the corresponding position in the corresponding hop beam time slot; its value is a binary number. (Regarding position allocation variables...) This will be explained in detail later.

[0031] Meanwhile, the integrated electronic system configures power allocation variables individually for each combination of wandering beam, each hopping beam slot, and each wave position. This power allocation variable characterizes the transmit power of the corresponding wandering beam when it is allocated to the corresponding hop beam time slot. Regarding the power allocation variable... This will be explained in detail later.

[0032] In addition, the integrated electronic system will have a pre-set conventional beam. Conventional wave position allocation variables If conventional beam In the t-th time slot of the current BHP, it is allocated to the target cluster. If the wave position is b, then the regular wave position allocation variable... =1, otherwise this regular wave position allocation variable =0. Among them, conventional beam... The same time slot must be allocated to a single wavelet to ensure continuous communication, that is: , (3) Correspondingly, the integrated electronic system will pre-set the conventional beam. Conventional power allocation variables It should be noted that this is a conventional power allocation variable. For conventional beam target cluster in time slot t The transmit power of wave position b. Among them, the conventional beam power variable... Basically constant, that is = ( (Pre-set conventional beam fixed power).

[0033] Therefore, integrated electronic systems can allocate variables based on wave position. and power allocation variables The scanning position sequence and power allocation of each wandering beam within the current BHP are scheduled.

[0034] Subsequently, the integrated electronic system will define the conventional beam. All regular wave position allocation variables and wandering beam Wave position allocation variables Power allocation variables An ordered integration is performed, resulting in a chromosome vector R. The reference vector is... Figure 5A As shown, the gene loci of chromosome vector R are divided into wave position block Y and power block P. Wave position block Y is used to characterize the wave position allocation variables of the wandering beam. The power block P is used to characterize the power allocation variables of the wandering beam. The wave position block Y and power block P will be described in detail below. Then, the integrated electronic system completes the initialization operation of the chromosome vector R according to the preset population size, thereby obtaining a chromosome population composed of multiple initialized chromosome vectors (corresponding to step S306).

[0035] Furthermore, the integrated electronic system is designed to adapt to target clusters within the current beam-hopping cycle. The fitness function for solving resource allocation optimization is based on the target cluster. The fitness function is constructed based on the total transmitted data volume of the internal scanning beam, the load transmission ratio matching degree of each wave position in the target cluster, and the total interference power generated by the wandering beam. By assigning preset weights to each index and performing weighted calculations, a fitness function that can quantify the merits of the chromosome vector allocation scheme is obtained (corresponding to step S308).

[0036] Then, the integrated electronic system uses the chromosome population as the initial solution set for the genetic algorithm. Using the constructed fitness function as the quantitative evaluation criterion, it sequentially performs selection, crossover, and mutation genetic operations on the chromosome population. After each genetic operation, the fitness value of all chromosome vectors within the population is calculated using the fitness function. Based on the fitness values, the overall performance of the allocation scheme corresponding to each chromosome vector is evaluated, and the chromosome vector with better performance is retained for the next generation of the population. This iterative process of genetic operations and fitness value calculation is repeated until the preset algorithm convergence condition is met. At this point, the chromosome vector with the optimal fitness value within the population is determined as the optimal chromosome vector for target cluster resource allocation within the current beam-hopping cycle (corresponding to step S310).

[0037] Finally, based on the optimal chromosome vector, the integrated electronic system determines the optimal joint allocation of the wave position and power of the wandering beam of the target cluster within the current hopping beam period (corresponding to step S312).

[0038] As described in the background section, a position cluster consists of multiple positions. According to conventional beam scanning techniques, within a single beam-hopping period (BHP), the beam scans different positions within the position cluster in different beam-hopping slots (BHS). However, in a hybrid beam-hopping architecture, within a single BHP, not only does a fixed beam scan each position of the position cluster using conventional beam scanning techniques, but at least one wandering beam also scans each position. Therefore, how to schedule the scanning positions and scanning power of the wandering beam is a crucial technical problem that needs to be solved. Currently, however, no scheduling scheme for the scanning positions and scanning power of the wandering beam has been proposed, making it impossible to optimize the scheduling of the wandering beam's positions and power.

[0039] In view of this, this application addresses the hybrid hopping beam architecture of low-Earth orbit satellites that combines conventional fixed cluster beams with cross-cluster wandering scanning beams. Based on the joint allocation requirements of time slots, beams, and power for the target cluster within a single hopping beam cycle, it first determines the conventional beams and wandering beams corresponding to the target cluster within the current hopping beam cycle. Then, it defines the wavelet allocation variables and power allocation variables for the wandering beams in different hopping beam time slots and corresponding wavelets. Next, based on the wavelet allocation variables and power allocation variables, it defines a chromosome vector that characterizes the joint allocation method of wavelets and power for each hopping beam time slot and each scanning beam for the target cluster within the current hopping beam cycle, and initializes this chromosome vector to obtain a chromosome population. Subsequently, a fitness function is constructed that relates to the total transmitted data volume of the target cluster within the current beam-hopping cycle, the load transmission ratio matching degree of each position of the target cluster, and the total interference power of the wandering beam. Finally, using this fitness function as the quantitative evaluation basis, a genetic algorithm is employed to perform selection, crossover, and mutation operations on the chromosome population and iteratively optimize it until the algorithm convergence condition is met. This determines the optimal chromosome vector for the optimal joint allocation method of the corresponding target cluster, achieving precise joint allocation of time slots, beams, and power for the target cluster within the current beam-hopping cycle. This solves the technical problem in existing technologies where the scheduling of positions and power of wandering beams cannot be optimized.

[0040] Optionally, the operation of defining the wave position allocation variable corresponding to the wave position of different hop beam slots in the current hop beam period includes: defining a subset of wandering beams that have been allocated to the target cluster in the current hop beam period, and defining wave position allocation variables for the wandering beams in the subset of wandering beams. Wherein, if the wandering beam is allocated to the target wave position of the target cluster in one hop beam slot of the current hop beam period, the value of the corresponding wave position allocation variable is 1, and if the wandering beam is not allocated to the target wave position of the target cluster in one hop beam slot of the current hop beam period, the value of the corresponding wave position allocation variable is 0.

[0041] Specifically, the integrated electronic system will first allocate all beams to the target cluster within the current beam-hopping period. The wandering beams that provide supplementary communication are then gathered together to form a dedicated subset of wandering beams. Among them, the wandering beam subset This indicates that among all wandering beams, the current BHP has been assigned to the target cluster. The wandering beam. Then, the integrated electronic system defines the beam assignment variable only for the wandering beams in this subset of wandering beams. Where k represents the k-th wandering beam, ,and Represents a wandering beam subset The total number of beams within; b represents the target cluster. The b-th wave position, b=1~ ; t represents the t-th time slot of the current BHP, where t=1~ .thereby This indicates whether the k-th wandering beam scans the target cluster in the t-th hop beam slot of the current hop beam period. The b-th wave position. If =1 indicates scanning; otherwise, it indicates no scanning.

[0042] The integrated electronic system will then target the wandering beam subset. Each wandering beam within, combined with each hopping beam time slot and target cluster divided by the current hopping beam period. Each included wave position is matched one by one with the defined wave position assignment variables. For example, if a wandering beam The target cluster was assigned in the second hopping beam time slot. The fourth wave position will then allow the integrated electronic system to move the beam. The wave position allocation variable values ​​corresponding to the second time slot and the fourth wave position are set to 1, that is... =1. Then, the integrated electronic system will move the wandering beam. The second hopping beam slot was not assigned to the target cluster. The wave position allocation variable values ​​corresponding to other wave positions are set to 0. Similarly, the wandering beam... For combinations of other time slots and wave positions, the 0 and 1 values ​​of the wave position allocation variable are defined one by one according to the above rules.

[0043] Therefore, by first defining the wandering beam subset of the target cluster and then defining the wave position allocation variable, this application limits the scope of the wave position allocation variable definition and reduces invalid calculations.

[0044] Optionally, after defining a position allocation variable for the wandering beams within the wandering beam subset, a corresponding first constraint condition is set, wherein the first constraint condition includes: within the current hopping beam period, the wandering beams in the wandering beam subset are fixedly assigned to target clusters, scanned only between positions of the target clusters, and the same wandering beam can only be assigned to one position in the same hopping beam time slot; and in the same hopping beam time slot, each position of the target cluster can only be scanned by one scanning beam.

[0045] Specifically, after defining the wave position allocation variables for each wandering beam in the wandering beam subset, the integrated electronic system will further set the corresponding first constraint conditions to standardize the scanning range and allocation relationship of the wandering beams.

[0046] Specifically, the integrated electronic system first limits all wandering beams in the current entire hopping beam cycle to be fixedly assigned to the target cluster within this subset of wandering beams. On, and only in the target cluster The scanning between different wave positions within the beam must not jump to wave positions in other wave position clusters. Simultaneously, it is required that the same wandering beam, within the same hopping beam time slot, can only be assigned to the target cluster. A single wave position cannot appear simultaneously on two or more wave positions, that is: , (4) Furthermore, the integrated electronic system is also constrained within the same hopping beam time slot, targeting clusters. Any given wave position can only be covered by one scanning beam from either the conventional beam or the wandering beam; two beams are not allowed to scan the same wave position simultaneously, thus avoiding beam collisions and signal interference. That is: (5) Therefore, by setting this constraint, the service range and scheduling boundary of the wandering beam can be clearly defined, avoiding resource chaos caused by disordered scanning of beams across clusters.

[0047] Optionally, the operation of defining the power allocation variables corresponding to the positions of different hop beam timeslots within the current hop beam period of the wandering beam includes: defining the power allocation variables of the scanning positions of the wandering beams within the target cluster within the current hop beam timeslot, wherein the power allocation variables are the transmit power of each scanning beam in a specified timeslot and a specified position; after defining the power allocation variables for the wandering beams within the wandering beam subset, setting the corresponding second constraint conditions, wherein the second constraint conditions are: the transmit power is a non-negative value, the transmit power cannot be greater than the maximum transmit power of a single wandering beam, and the total transmit power of all scanning beams within the target cluster cannot exceed the total satellite power threshold.

[0048] Specifically, after defining the wavelet allocation variable, the integrated electronic system further defines the power allocation variable. This power allocation variable characterizes the actual transmit power of the wandering beam in each hop beam slot and corresponding wavelet position within the target cluster. In other words, the power allocation variable... This indicates that the k-th wandering beam is in the t-th hopping beam slot and the target cluster. The transmit power of wave position b. After defining the power allocation variables, the integrated electronic system sets a second constraint to regulate the power values: First, the transmit power of each wandering beam must be non-negative and must not exceed the maximum allowable transmit power of that beam itself. Second, within the current hopping beam period, the sum of the transmit powers of all regular beams and wandering beams within the target cluster must not exceed the total allowable power threshold of the entire satellite system. ,Right now: (6) This ensures that the power distribution is within the limits that the hardware can handle.

[0049] By setting a second constraint, the integrated electronic system can ensure that the transmit power of each wandering beam is within a reasonable and safe operating range, avoiding equipment damage due to power anomalies or overload. Simultaneously, by imposing an upper limit constraint on the total transmit power of all scanning beams within the target cluster, it can ensure the controllable allocation of satellite power resources and prevent system anomalies caused by power exceeding limits.

[0050] Optionally, the operation of defining the chromosome vector based on the wavelet allocation variable and the power allocation variable includes: defining the first gene position of the chromosome vector using bit encoding based on the first constraint of the wavelet allocation variable; and defining the second gene position of the chromosome vector using binary numerical encoding based on the second constraint of the power allocation variable.

[0051] Specifically, the integrated electronic system constructs chromosome vectors based on the wavelet allocation variable and the power allocation variable, and uses segmented coding methods respectively.

[0052] refer to Figure 5B As shown, the wave position block Y of the chromosome vector R can be divided into multiple beam blocks YB. k ,in Each beam block YB k It can be divided into multiple time slot blocks YS t ,in Each time slot block YS t Include yb b , Therefore, beam assignment variables It can be generated by the k-th beam block YB k The t-th time slot block YS t The b-th bit yb b Characterization.

[0053] Therefore, the integrated electronic system first encodes the portion of the chromosome vector representing the relationship between beam slots and beam allocation based on the first constraint condition corresponding to the beam allocation variable, forming the first gene bit of beam allocation block Y. This gene bit directly reflects the beam allocation state of each wandering beam in different slots. The bit encoding corresponds to the beam allocation variable. Each bit corresponds to a variable value (0 = no allocation, 1 = allocation), and the length of the wavelet block Y. It can be calculated using the following formula: = (7) In addition, refer to Figure 5C As shown, the power block P of the chromosome vector R can be divided into multiple beam blocks PB.k ,in Each beam block PB k It can be divided into multiple time slot blocks PS t ,in Each time slot block PS t Include Power encoding block PP b , Therefore, beam assignment variables It can be generated by the k-th beam block PB k The t-th time slot block PB t The b-th power coding block PP b Characterization. Each power-coded block (PP) b It includes multiple bits representing the power value in a binary encoded manner, where each power encoded block PP b The number of bits can be determined based on beam allocation variables. The numerical range and precision are determined.

[0054] Therefore, based on the second constraint condition corresponding to the power allocation variable, the integrated electronic system uses binary numerical encoding to encode the portion representing the transmit power of each beam, forming the second bit of the power block P, wherein each power encoding block PP b The binary encoded values ​​correspond to continuous power distribution variables. Each indicator code bit corresponds to one The value of . The actual encoded length of power block P. It can be calculated using the following formula: (8) in, The length of each power-coded block (i.e., the number of bits).

[0055] It should be noted that the length of this real number encoding is the same as... The meaning of the variables corresponds, that is, only when When =1, the corresponding real-number encoded bits are valid. Therefore, during the initialization of the chromosome vector R, for The combination of k, b, and t with =0 corresponds to the power coding block (i.e., the k-th beam block PB). k The t-th time slot block PB t The b-th power coding block PP b The value is also set to zero directly, thereby reducing the computational load of the genetic algorithm.

[0056] By combining bit-based encoding with binary numerical encoding, the joint encoding of the wave position and power of the wandering beam is achieved, thus forming a complete chromosome vector for subsequent iterative optimization.

[0057] Optionally, the operation of constructing the fitness function includes: pre-determining a first weighting coefficient corresponding to the total amount of transmitted data, a second weighting coefficient corresponding to the load transmission ratio, and a third weighting coefficient corresponding to the total interference power; and constructing the fitness function based on the total amount of transmitted data, the first weighting coefficient, the load transmission ratio matching degree, the second weighting coefficient, the total interference power, and the third weighting coefficient.

[0058] Specifically, when constructing the fitness function, the integrated electronic system pre-sets a first weighting coefficient corresponding to the total amount of transmitted data. The second weighting coefficient corresponding to the load transfer ratio The third weighting coefficient corresponding to the total interference power To clarify the importance of each optimization indicator in the evaluation, among which + + =1.

[0059] Then, the integrated electronic system can calculate the sum of the transmitted data volume of the conventional beam and the wandering beam in all hopping beam slots (i.e., the sum of the total transmitted data volume of all positions within the current BHP) according to the following formula, thereby obtaining the total transmitted data volume. for: (9) (10) (11) (12) In the formula, For conventional beam The communication rate at time slot t and wavelength b; For wandering beam The communication rate at time slot t and wavelength b; This represents the total amount of data transmitted by wave position b within the current BHP. For conventional beamforming in a single time slot The amount of data transmitted within; For wandering beams in a single time slot The amount of data transmitted within; B represents the channel allowance for each regular beam and wandering beam; This represents the noise power at the b-th wave position, which can be determined in advance.

[0060] Next, the integrated electronic system can calculate the load transfer ratio matching degree according to the following formula. : (13) in, Let be the load transmission ratio of wave position b, which can be calculated using the following formula: (14) in, The load to be transmitted at the b-th wavelength of the current BHP can be predicted in advance during the current BHP.

[0061] The average load transmission ratio across all wavelengths can be calculated using the following formula: (15) When all wave positions All equal to When the load transmission ratio between wavelengths is perfectly balanced, (Optimal); the larger the ratio deviation, The smaller the value, the more it reflects the imbalance between wave positions.

[0062] Subsequently, the integrated electronic system can calculate the total interference power using the following formula. : (16) (17) Among them, the total interference power This reflects the interference suppression performance; the smaller the interference, the larger the fitness function value. Let be the interference power of the k-th wandering beam at the b-th position in the t-th time slot. The antenna gain for the k-th wandering beam is determined by the antenna design parameters. It is the radiation leakage coefficient of the k-th wandering beam (with a value ranging from 0 to 1), which can be calibrated in advance; The frequency reuse interference coefficient can be calibrated in advance.

[0063] Finally, the integrated electronic system is based on the total amount of data transmitted. First weighting coefficient Load transmission ratio matching degree Second weighting coefficient Total interference power and the third weighting coefficient Construct the following fitness function: F= (18) Optionally, based on the fitness function, the chromosome population is iteratively optimized using a genetic algorithm, including: using the chromosome population as the parent population, performing crossover and mutation operations on multiple chromosome vectors in the parent population to generate multiple chromosome vectors as the child population; calculating the fitness value corresponding to all chromosome vectors in the parent population according to the fitness function; sorting the chromosome vectors of the parent population and the child population together according to their fitness values, and selecting a predetermined number of chromosome vectors with the lowest fitness values ​​as the parent population for the next round of iteration.

[0064] Specifically, the integrated electronic system executes an iterative optimization process using a genetic algorithm based on the fitness function F. First, the integrated electronic system uses an initialized chromosome population as the parent population, with each chromosome vector corresponding to a joint scheduling scheme of wave position and power. During each generation of evolution, crossover and mutation genetic operations are performed on the chromosome vectors within the parent population. Crossover involves exchanging partial gene segments between two chromosomes to generate new scheduling combinations; mutation randomly changes the values ​​of individual genes in the chromosomes with a small probability, introducing new scheduling patterns. This generates entirely new chromosome vectors that constitute the child population.

[0065] Furthermore, the integrated electronic system calculates the fitness value F(x) of all chromosome vectors in the parent population based on a pre-constructed fitness function. )~F( The lower the fitness value, the better the performance of the scheduling scheme.

[0066] Then, the integrated electronic system merges all chromosome vectors of the parent and child populations, sorts them uniformly in order of fitness value from low to high, and selects a predetermined number of chromosome vectors with the lowest fitness value after sorting as the parent population for the next round of iteration optimization.

[0067] Finally, the integrated electronic system repeats the above operations until convergence conditions are met, such as reaching the maximum number of iterations, the fitness value no longer decreasing significantly over multiple generations, or the fitness value of the optimal chromosome being lower than a given threshold, thereby determining the optimal chromosome vector.

[0068] This iterative optimization method effectively preserves high-fitness, high-quality allocation schemes by merging and sorting the parent and child populations and selecting the best one, thereby improving the algorithm's global search capability and convergence stability.

[0069] 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.

[0070] Therefore, according to this embodiment, this application realizes the three-dimensional coordinated allocation of time slot-beam-power for target clusters within a single hop beam cycle under the hybrid hop beam architecture of low-orbit satellites, thus solving the technical problem in the prior art that it is impossible to optimize the scheduling of the wave position and power of wandering beams.

[0071] 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.

[0072] 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.

[0073] Example 2

[0074] Figure 6 A satellite hybrid beam-hopping allocation device according to this embodiment is shown, which corresponds to the method described according to Embodiment 1. (Reference) Figure 6As shown, the device includes: a scanning beam determination module 610, used to determine the scanning beam corresponding to the target cluster within the current hopping beam period, wherein the scanning beam includes a conventional beam and a wandering beam; an allocation variable definition module 620, used to define the wave position allocation variable and power allocation variable corresponding to the wave positions of the wandering beam in different hopping beam slots within the current hopping beam period; and a chromosome vector definition module 630, used to define a chromosome vector based on the wave position allocation variable and the power allocation variable, and initialize the chromosome vector to obtain a chromosome population, wherein the chromosome vector represents the target cluster in each hopping beam slot of the current hopping beam period and each... The system includes: a joint allocation method for the scanning beam's corresponding wave position and power; a fitness function construction module 640, used to construct a fitness function, wherein the fitness function is related to the total transmitted data volume of the target cluster in the current hopping beam cycle, the load transmission ratio of each wave position of the target cluster, and the total interference power of the wandering beam; an iterative optimization module 650, used to iteratively optimize the chromosome population using a genetic algorithm based on the fitness function to determine the optimal chromosome vector; and an optimal joint allocation method determination module 660, used to determine the optimal joint allocation method of the wave position and power of the wandering beam of the target cluster in the current hopping beam cycle based on the optimal chromosome vector.

[0075] Optionally, the operation of defining the wave position allocation variable corresponding to the wave position of different hop beam slots in the current hop beam period includes: defining a subset of wandering beams that have been allocated to the target cluster in the current hop beam period, and defining wave position allocation variables for the wandering beams in the subset of wandering beams. Wherein, if the wandering beam is allocated to the target wave position of the target cluster in one hop beam slot of the current hop beam period, the value of the corresponding wave position allocation variable is 1, and if the wandering beam is not allocated to the target wave position of the target cluster in one hop beam slot of the current hop beam period, the value of the corresponding wave position allocation variable is 0.

[0076] Optionally, after defining a position allocation variable for the wandering beams within the wandering beam subset, a corresponding first constraint condition is set, wherein the first constraint condition includes: within the current hopping beam period, the wandering beams in the wandering beam subset are fixedly assigned to target clusters, scanned only between positions of the target clusters, and the same wandering beam can only be assigned to one position in the same hopping beam time slot; and in the same hopping beam time slot, each position of the target cluster can only be scanned by one scanning beam.

[0077] Optionally, the operation of defining the power allocation variables corresponding to the positions of different hop beam timeslots within the current hop beam period of the wandering beam includes: defining the power allocation variables of the scanning positions of the wandering beams within the target cluster within the current hop beam timeslot, wherein the power allocation variables are the transmit power of each scanning beam in a specified timeslot and a specified position; after defining the power allocation variables for the wandering beams within the wandering beam subset, setting the corresponding second constraint conditions, wherein the second constraint conditions are: the transmit power is a non-negative value, the transmit power cannot be greater than the maximum transmit power of a single wandering beam, and the total transmit power of all scanning beams within the target cluster cannot exceed the total satellite power threshold.

[0078] Optionally, the operation of defining the chromosome vector based on the wavelet allocation variable and the power allocation variable includes: defining the first gene position of the chromosome vector using bit encoding based on the first constraint of the wavelet allocation variable; and defining the second gene position of the chromosome vector using binary numerical encoding based on the second constraint of the power allocation variable.

[0079] Optionally, the operation of constructing the fitness function includes: pre-determining a first weighting coefficient corresponding to the total amount of transmitted data, a second weighting coefficient corresponding to the load transmission ratio, and a third weighting coefficient corresponding to the total interference power; and constructing the fitness function based on the total amount of transmitted data, the first weighting coefficient, the load transmission ratio matching degree, the second weighting coefficient, the total interference power, and the third weighting coefficient.

[0080] Optionally, based on the fitness function, the chromosome population is iteratively optimized using a genetic algorithm, including: using the chromosome population as the parent population, performing crossover and mutation operations on multiple chromosome vectors in the parent population to generate multiple chromosome vectors as the child population; calculating the fitness value corresponding to all chromosome vectors in the parent population according to the fitness function; sorting the chromosome vectors of the parent population and the child population together according to their fitness values, and selecting a predetermined number of chromosome vectors with the lowest fitness values ​​as the parent population for the next round of iteration.

[0081] Therefore, according to this embodiment, this application realizes the three-dimensional coordinated allocation of time slot-beam-power for target clusters within a single hop beam cycle under the hybrid hop beam architecture of low-orbit satellites, thus solving the technical problem in the prior art that it is impossible to optimize the scheduling of the wave position and power of wandering beams.

[0082] Example 3

[0083] Figure 7 A satellite hybrid beam-hopping allocation device according to this embodiment is shown, which corresponds to the method described according to Embodiment 1. (Reference) Figure 7As shown, the device includes: a processor 710; and a memory 720, connected to the processor 710, for providing the processor 710 with instructions to process the following steps: determining the scanning beam corresponding to the target cluster within the current beam-hopping period, wherein the scanning beam includes a regular beam and a wandering beam; defining the wavelet allocation variables and power allocation variables corresponding to the wavelets of the wandering beam in different beam-hopping time slots within the current beam-hopping period; defining a chromosome vector based on the wavelet allocation variables and power allocation variables, and initializing the chromosome vector to obtain a chromosome population, wherein the chromosome population is determined by the wavelet allocation variables and power allocation variables. The quantity represents the joint allocation method of the target cluster with the corresponding wave positions and powers of each hopping beam time slot and each scanning beam in the current hopping beam cycle; a fitness function is constructed, wherein the fitness function is related to the total amount of transmitted data of the target cluster in the current hopping beam cycle, the load transmission ratio of each wave position of the target cluster, and the total interference power of the wandering beam; based on the fitness function, the chromosome population is iteratively optimized using a genetic algorithm to determine the optimal chromosome vector; and based on the optimal chromosome vector, the optimal joint allocation method of the wave positions and powers of the wandering beams of the target cluster in the current hopping beam cycle is determined.

[0084] Optionally, the operation of defining the wave position allocation variable corresponding to the wave position of different hop beam slots in the current hop beam period includes: defining a subset of wandering beams that have been allocated to the target cluster in the current hop beam period, and defining wave position allocation variables for the wandering beams in the subset of wandering beams. Wherein, if the wandering beam is allocated to the target wave position of the target cluster in one hop beam slot of the current hop beam period, the value of the corresponding wave position allocation variable is 1, and if the wandering beam is not allocated to the target wave position of the target cluster in one hop beam slot of the current hop beam period, the value of the corresponding wave position allocation variable is 0.

[0085] Optionally, after defining a position allocation variable for the wandering beams within the wandering beam subset, a corresponding first constraint condition is set, wherein the first constraint condition includes: within the current hopping beam period, the wandering beams in the wandering beam subset are fixedly assigned to target clusters, scanned only between positions of the target clusters, and the same wandering beam can only be assigned to one position in the same hopping beam time slot; and in the same hopping beam time slot, each position of the target cluster can only be scanned by one scanning beam.

[0086] Optionally, the operation of defining the power allocation variables corresponding to the positions of different hop beam timeslots within the current hop beam period of the wandering beam includes: defining the power allocation variables of the scanning positions of the wandering beams within the target cluster within the current hop beam timeslot, wherein the power allocation variables are the transmit power of each scanning beam in a specified timeslot and a specified position; after defining the power allocation variables for the wandering beams within the wandering beam subset, setting the corresponding second constraint conditions, wherein the second constraint conditions are: the transmit power is a non-negative value, the transmit power cannot be greater than the maximum transmit power of a single wandering beam, and the total transmit power of all scanning beams within the target cluster cannot exceed the total satellite power threshold.

[0087] Optionally, the operation of defining the chromosome vector based on the wavelet allocation variable and the power allocation variable includes: defining the first gene position of the chromosome vector using bit encoding based on the first constraint of the wavelet allocation variable; and defining the second gene position of the chromosome vector using binary numerical encoding based on the second constraint of the power allocation variable.

[0088] Optionally, the operation of constructing the fitness function includes: pre-determining a first weighting coefficient corresponding to the total amount of transmitted data, a second weighting coefficient corresponding to the load transmission ratio, and a third weighting coefficient corresponding to the total interference power; and constructing the fitness function based on the total amount of transmitted data, the first weighting coefficient, the load transmission ratio matching degree, the second weighting coefficient, the total interference power, and the third weighting coefficient.

[0089] Optionally, based on the fitness function, the chromosome population is iteratively optimized using a genetic algorithm, including: using the chromosome population as the parent population, performing crossover and mutation operations on multiple chromosome vectors in the parent population to generate multiple chromosome vectors as the child population; calculating the fitness value corresponding to all chromosome vectors in the parent population according to the fitness function; sorting the chromosome vectors of the parent population and the child population together according to their fitness values, and selecting a predetermined number of chromosome vectors with the lowest fitness values ​​as the parent population for the next round of iteration.

[0090] Therefore, according to this embodiment, this application realizes the three-dimensional coordinated allocation of time slot-beam-power for target clusters within a single hop beam cycle under the hybrid hop beam architecture of low-orbit satellites, thus solving the technical problem in the prior art that it is impossible to optimize the scheduling of the wave position and power of wandering beams.

[0091] 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.

[0092] 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.

[0093] 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.

[0094] 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.

[0095] 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.

[0096] 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.

[0097] 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 hybrid beam hopping allocation method, characterized in that, include: Determine the scanning beam corresponding to the target cluster within the current beam-hopping period, wherein the scanning beam includes a conventional beam and a wandering beam; Define the wavelet allocation variables and power allocation variables corresponding to the wavelets of the wandering beam in different hop beam slots within the current hop beam period; A chromosome vector is defined based on the wavelength allocation variable and the power allocation variable, and a chromosome population is obtained by initializing the chromosome vector. The chromosome vector represents the joint allocation method of the target cluster with the corresponding wavelength and power of each hop beam time slot and each scanning beam in the current hop beam cycle. Construct a fitness function, wherein the fitness function is related to the total amount of transmitted data of the target cluster in the current hopping beam period, the load transmission ratio matching degree of each wave position of the target cluster, and the total interference power of the wandering beam; Based on the fitness function, a genetic algorithm is used to iteratively optimize the chromosome population to determine the optimal chromosome vector; and Based on the optimal chromosome vector, the optimal joint allocation method of wave position and power of the wandering beam of the target cluster in the current hopping beam period is determined.

2. The method according to claim 1, characterized in that, The operation of defining the wavefront allocation variables corresponding to the wavefronts of the wandering beam in different hop beam slots within the current hop beam period includes: Define a subset of wandering beams that have been assigned to the target cluster within the current hopping beam period, and define a position allocation variable for the wandering beams within the subset of wandering beams. If the wandering beam is assigned to the target position of the target cluster in one hopping beam slot of the current hopping beam period, the value of the corresponding position allocation variable is 1. If the wandering beam is not assigned to the target position of the target cluster in one hopping beam slot of the current hopping beam period, the value of the corresponding position allocation variable is 0.

3. The method according to claim 2, characterized in that, After defining wave position allocation variables for the wandering beams within the subset of wandering beams, a corresponding first constraint condition is set, wherein the first constraint condition includes: Within the current hopping beam cycle, the wandering beams in the wandering beam subset are fixedly assigned to the target cluster, scanning only between the wave positions of the target cluster, and the same wandering beam can only be assigned to one wave position in the same hopping beam time slot; and Within the same hopping beam slot, each position of the target cluster can only be scanned by one scanning beam.

4. The method according to claim 1, characterized in that, The operation of defining the power allocation variables corresponding to the wavefronts of the wandering beam in different hop beam slots within the current hop beam period includes: Define the power allocation variable for the scanning position of the wandering beam within the target cluster in the current hopping beam time slot, wherein the power allocation variable is the transmit power of each scanning beam in a specified time slot and a specified beam position; After defining power allocation variables for the wandering beams within the wandering beam subset, a corresponding second constraint condition is set, wherein the second constraint condition is: the transmit power is a non-negative value, the transmit power cannot be greater than the maximum transmit power of a single wandering beam, and the total transmit power of all scanning beams within the target cluster cannot exceed the satellite total power threshold.

5. The method according to claim 1, characterized in that, The operation of defining a chromosome vector based on the wavelet allocation variable and the power allocation variable includes: Based on the first constraint condition of the wavelet allocation variable, the first gene position of the chromosome vector is defined using bit-level encoding; and The second gene locus of the chromosome vector is defined using binary numerical encoding based on the second constraint condition of the power allocation variable.

6. The method according to claim 1, characterized in that, The operations for constructing the fitness function include: A first weighting coefficient corresponding to the total transmitted data volume, a second weighting coefficient corresponding to the load transmission ratio matching degree, and a third weighting coefficient corresponding to the total interference power are predetermined; and A fitness function is constructed based on the total amount of transmitted data, the first weighting coefficient, the load transmission ratio matching degree, the second weighting coefficient, the total interference power, and the third weighting coefficient.

7. The method according to claim 1, characterized in that, Based on the fitness function, the operation of iteratively optimizing the chromosome population using a genetic algorithm includes: Using the chromosome population as the parent population, perform crossover and mutation operations on multiple chromosome vectors in the parent population to generate multiple chromosome vectors as the child population. Calculate the fitness value of all chromosome vectors in the parent population based on the fitness function; The chromosome vectors of the parent population and the child population are sorted together according to their fitness values, and a predetermined number of chromosome vectors with the lowest fitness values ​​are selected as the parent population for the next round of iteration.

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

9. A satellite hybrid beam-hopping allocation device, characterized in that, include: The scanning beam determination module is used to determine the scanning beam corresponding to the target cluster within the current hopping beam period, wherein the scanning beam includes a conventional beam and a wandering beam; The allocation variable definition module is used to define the wave position allocation variable and power allocation variable corresponding to the wave position of the wandering beam in different hop beam time slots within the current hop beam period; The chromosome vector definition module is used to define a chromosome vector according to the wave position allocation variable and the power allocation variable, and initialize the chromosome vector to obtain a chromosome population, wherein the chromosome vector represents the joint allocation method of the target cluster with the corresponding wave position and power of each hop beam time slot and each scanning beam in the current hop beam cycle; The fitness function construction module is used to construct a fitness function, wherein the fitness function is related to the total amount of transmitted data of the target cluster in the current beam-hopping period, the load transmission ratio of each wave position of the target cluster, and the total interference power of the wandering beam; The iterative optimization module is used to iteratively optimize the chromosome population using a genetic algorithm based on the fitness function to determine the optimal chromosome vector; and The optimal joint allocation method determination module is used to determine the optimal joint allocation method of the wave position and power of the wandering beam of the target cluster in the current hopping beam period based on the optimal chromosome vector.

10. A satellite hybrid beam-hopping allocation 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: Determine the scanning beam corresponding to the target cluster within the current beam-hopping period, wherein the scanning beam includes a conventional beam and a wandering beam; Define the wavelet allocation variables and power allocation variables corresponding to the wavelets of the wandering beam in different hop beam slots within the current hop beam period; A chromosome vector is defined based on the wavelength allocation variable and the power allocation variable, and a chromosome population is obtained by initializing the chromosome vector. The chromosome vector represents the joint allocation method of the target cluster with the corresponding wavelength and power of each hop beam time slot and each scanning beam in the current hop beam cycle. Construct a fitness function, wherein the fitness function is related to the total amount of transmitted data of the target cluster in the current beam-hopping period, the load transmission ratio of each wave position of the target cluster, and the total interference power of the wandering beam; Based on the fitness function, a genetic algorithm is used to iteratively optimize the chromosome population to determine the optimal chromosome vector; and Based on the optimal chromosome vector, the optimal joint allocation method of wave position and power of the wandering beam of the target cluster in the current hopping beam period is determined.

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