Wave position resource allocation method and device and computer equipment

Abstract

The invention provides a beam position resource allocation method and device and computer equipment, which can be applied to the technical field of wireless communication. Based on the method, a first scheduling weight of each service in M services corresponding to each user in N users can be determined, N * M first scheduling weights are obtained, the first scheduling weights are demand intensities of the services corresponding to the users for time slot resources in wave positions to which the services belong, and N and M are positive integers; according to N * M first scheduling weights corresponding to each beam position in B beam positions in a target adjustment period, a second scheduling weight of each beam position in the B beam positions is determined, the second scheduling weight is the demand intensity of the beam position for time slot resources in a beam, and B is a positive integer; determining an air interface load of each wave position in the B wave positions in the target adjustment period; and according to the second scheduling weight and the air interface load of each beam position in the B beam positions, allocating time slot resources to each beam position in the B beam positions.

Description

Technical Field

[0001] This application belongs to the field of wireless communication technology, and in particular relates to a method, apparatus and computer equipment for allocating wavelet resources. Background Technology

[0002] In satellite wireless communication, satellite payloads often need to receive uplink signals transmitted from the ground terminal through corresponding physical channels. However, due to the inconsistency in stability between the satellite payload and the ground terminal, as well as the relative motion between the two communicating parties, frequency offset occurs during communication, which in turn affects signal demodulation and easily leads to demodulation failure. In low-Earth orbit (LEO) satellite communication, because LEO satellites orbit at a relatively lower altitude and the relative motion speed between the satellite and the ground terminal is faster, the above problems are even more pronounced.

[0003] Current satellite communication non-terrestrial networks (NTNs) typically use beam hopping (BH) as a beam usage mode to dynamically allocate system bandwidth and power, effectively matching available satellite capacity with user service demands. Utilizing beam hopping to achieve on-demand service is also a major solution for current non-geostationary orbit (NGSO) satellite communication systems. For example, Starlink satellites are configured with phased array antennas that simultaneously generate multiple point beams, relaying services to different users in different geographical locations through beam hopping.

[0004] The resource allocation problem in beam-hopping systems can be divided into beam-hopping mode design and dynamic time-division scheduling, thus it can be understood as a scheduling problem in both the time and spatial domains. The first step is beam-hopping mode design, which rationally allocates time slots to each beam position cell through beam-hopping. Time slot allocation is generally based on cell service statistics and Quality of Service (QoS) priority requirements. During the corresponding time slot, the phased array adaptively shapes the beams to point to the corresponding beam position cell. The second step is dynamic time-frequency division scheduling. The beam position cell allocates resources according to current user needs. Generally, based on existing user service statistics and QoS priority requirements, the scheduling order of user services is determined within the time slot, and then bandwidth, time slots, and power resources are allocated to user services sequentially.

[0005] Existing terrestrial networks (TN) have a small coverage area, so beam hopping is unnecessary; therefore, only the second step, dynamic time-frequency division scheduling, is required. The basic idea of ​​the Enhanced Proportional Fair (EPF) algorithm is to consider the ratio of instantaneous rate to long-term average rate when selecting users, while simultaneously using weights to adjust different users, achieving a balance between system performance and user experience. The EPF algorithm assigns a priority to each user within the cell, and at any given time, the system schedules the user with the highest priority. The mathematical expression for the EPF algorithm can be represented as: Where k is the scheduled user, R i (t) represents the maximum rate supported by user i under the channel conditions at time t, and r i (t) represents the cumulative average rate of user i at time t. After scheduling is completed, the user's priority factor needs to be updated. If there are multiple users in the cell, and the system continuously schedules a user with good channel quality, r i (t) will gradually increase, causing the priority to gradually decrease, thus allowing the system to schedule other users with higher priority. If a user has poor channel quality and is not scheduled by the system for a long time, then its average throughput r will be lower. i (t) will decrease, which will increase the priority and give the user a chance to be scheduled.

[0006] Existing TN commercial network algorithms combine service priority requirements and QoS requirements into the EPF algorithm. While ensuring QoS requirements, they achieve fairness and improve the performance of the beam-hopping system. For example, the GBR services allocated to users with Guaranteed Bit Rate (GBR) are sorted according to service priority weights, and parallel channel allocation of subcarriers is performed for each service in turn. For the remaining parallel channels of subcarriers, the EPF algorithm is used to allocate them to Non-GBR services.

[0007] However, in the scenario of beam hopping resource allocation, the existing algorithms mentioned above can only schedule and sort users within a single beam position. The fairness of users between beam positions cannot be guaranteed, and the performance of the beam hopping system will also decrease due to the uneven load between beam positions. Summary of the Invention

[0008] This specification provides a beam hopping resource allocation method, apparatus, and computer equipment that can ensure fairness among users and load balance among beam hopping resources in beam hopping scenarios, thereby improving the performance of the beam hopping system.

[0009] This specification provides a method for allocating wavelet resources, including:

[0010] Determine the first scheduling weight of each service in the M services corresponding to each user among N users, and obtain N*M first scheduling weights. The first scheduling weight is the demand intensity of the service corresponding to the user for the time slot resources in the corresponding wavelength position, where N and M are positive integers, N is the number of users, and M is the number of services.

[0011] Based on the N*M first scheduling weights corresponding to each of the B wave positions within the target adjustment period, the second scheduling weight of each of the B wave positions is determined. The second scheduling weight is the demand intensity of the wave position for the time slot resources within the beam, where B is a positive integer and B is the number of wave positions.

[0012] Determine the air interface load of each of the B wave positions within the target adjustment period;

[0013] Based on the second scheduling weight and air interface load of each of the B wave positions, time slot resources are allocated to each of the B wave positions.

[0014] In some embodiments, based on N*M first scheduling weights corresponding to each of the B wave positions within the target adjustment period, a second scheduling weight for each of the B wave positions is determined. The second scheduling weight represents the wave position's demand intensity for intra-beam time slot resources, where B is a positive integer and represents the number of wave positions.

[0015] Based on the M first scheduling weights of the M services corresponding to each of the N users, determine the first uplink scheduling weight set and the first downlink scheduling weight set of each of the N users within the target adjustment period, and obtain N first uplink scheduling weight sets and N first downlink scheduling weight sets.

[0016] Based on the N first uplink scheduling weight sets and N first downlink scheduling weight sets corresponding to each of the B wave positions, the first uplink scheduling weight and the first downlink scheduling weight of each of the B wave positions are determined respectively.

[0017] Based on the fusion result of the first uplink scheduling weight and the first downlink scheduling weight of each of the B wave positions, the second scheduling weight of each of the B wave positions is determined.

[0018] In some embodiments, based on the M first scheduling weights of the M services corresponding to each of the N users, a first uplink scheduling weight set and a first downlink scheduling weight set for each of the N users within the target adjustment period are determined, resulting in N first uplink scheduling weight sets and N first downlink scheduling weight sets, including:

[0019] Based on the M first scheduling weights of the M services corresponding to each of the N users in each of the Q scheduling cycles, determine the second uplink scheduling weight set and the second downlink scheduling weight set of each of the N users in the target adjustment period, and obtain N second uplink scheduling weight sets and N second downlink scheduling weight sets.

[0020] The second uplink scheduling weight set and the second downlink scheduling weight set of each of the N users are sampled according to a preset sampling period to obtain the first uplink scheduling weight set and the first downlink scheduling weight set of each of the N users within the target adjustment period.

[0021] In some embodiments, the N*M first scheduling weights include M third uplink scheduling weights and M third downlink scheduling weights for the M services corresponding to each of the N users; each of the N sets of second uplink scheduling weights includes Q second uplink scheduling weights; each of the N sets of second downlink scheduling weights includes Q second downlink scheduling weights.

[0022] The method further includes:

[0023] Based on the maximum third uplink scheduling weight among the M third uplink scheduling weights and the maximum third downlink scheduling weight among the M third downlink scheduling weights of the M services corresponding to each of the N users in each of the Q scheduling periods, the second uplink scheduling weight and the second downlink scheduling weight of each of the N users in each of the Q scheduling periods are determined respectively.

[0024] In some embodiments, the first uplink scheduling weight and the first downlink scheduling weight of each of the B wave positions are determined based on the N first uplink scheduling weight sets and the N first downlink scheduling weight sets corresponding to each wave position in the B wave positions, including:

[0025] Based on the average result of each first uplink scheduling weight set in the N first uplink scheduling weight sets of the N users corresponding to each of the B wave positions, and the average result of each first downlink scheduling weight set in the N first downlink scheduling weight sets of the N users corresponding to each of the B wave positions, the fourth uplink scheduling weight and the fourth downlink scheduling weight of each user in the N users corresponding to each of the B wave positions are determined respectively.

[0026] Based on the average results of the N fourth uplink scheduling weights and the average results of the N fourth downlink scheduling weights corresponding to each of the B wave positions, the first uplink scheduling weight and the first downlink scheduling weight of each of the B wave positions within the target adjustment period are determined respectively.

[0027] In some embodiments, determining the air interface load of each of the B waveforms within the target adjustment period includes:

[0028] Obtain the uplink physical resource block utilization rate and downlink physical resource block utilization rate of each of the B wave positions within the target adjustment period;

[0029] The load weight of each of the B wave positions is determined based on the fusion result of the uplink physical resource block utilization rate and the downlink physical resource block utilization rate of each wave position.

[0030] In some embodiments, determining the air interface load of each of the B waveforms within the target adjustment period includes:

[0031] Obtain the uplink physical resource block utilization rate and downlink physical resource block utilization rate of each of the B wave positions within the target adjustment period;

[0032] Based on the comparison results of the uplink physical resource block utilization rate and the downlink physical resource block utilization rate of each of the B wave positions, the load weight of each of the B wave positions is determined.

[0033] In some embodiments, time slot resources are allocated to each of the B wavebands based on the second scheduling weight and air interface load of each waveband, including:

[0034] Based on the coupling result of the second scheduling weight and the load weight of each of the B wave positions, the third scheduling weight of each of the B wave positions is determined.

[0035] Based on the third scheduling weight of each of the B wave positions, time slot resources are allocated to each of the B wave positions.

[0036] In some embodiments, time slot resources are allocated to each of the B wave positions according to the third scheduling weight of each wave position, including:

[0037] Find the first wave position with the largest third scheduling weight among the B wave positions;

[0038] In the B wave positions, find multiple second wave positions where the difference between the third scheduling weight and the maximum third scheduling weight is greater than the difference threshold, and the difference between the time slot resource and the minimum time slot resource threshold is greater than or equal to the time slot resource unit.

[0039] Find the third wave position with the smallest third scheduling weight among the plurality of second wave positions;

[0040] Adjust the time slot resources of the first and third wave positions.

[0041] In some embodiments, adjusting the time slot resources of the first and third wavelengths includes:

[0042] Increase the time slot resources of the first wave position by time slot resource units;

[0043] Reduce the time slot resources of the third wave position by time slot resource units.

[0044] In some embodiments, a first scheduling weight is determined for each of the M services corresponding to each of the N users, resulting in N*M first scheduling weights. The first scheduling weight represents the demand intensity of the service corresponding to the user for the time slot resources within its respective wavelength range. Here, N and M are positive integers, where N is the number of users and M is the number of services, including:

[0045] Based on multiple preset Quality of Service (QoS) parameters, obtain the first scheduling weight of each service among the M services corresponding to each of the N users.

[0046] This specification also provides a wavelet resource allocation device, including:

[0047] The first determining module is used to determine the first scheduling weight of each service in the M services corresponding to each user among N users, and obtain N*M first scheduling weights. The first scheduling weight is the demand intensity of the service corresponding to the user for the time slot resources within the corresponding wavelength. Here, N and M are positive integers, N is the number of users, and M is the number of services.

[0048] The second determining module is used to determine the second scheduling weight of each of the B wave positions based on the N*M first scheduling weights corresponding to each wave position in the target adjustment period. The second scheduling weight is the demand intensity of the wave position for the time slot resources in the beam, where B is a positive integer and B is the number of wave positions.

[0049] The third determining module is used to determine the air interface load of each of the B wave positions within the target adjustment period;

[0050] The allocation module is used to allocate time slot resources to each of the B wave positions according to the second scheduling weight and air interface load of each wave position.

[0051] This specification also provides a computer device, including a processor and a memory for storing processor-executable instructions, wherein the processor, when executing the instructions, implements the relevant steps of the aforementioned wavelet resource allocation method.

[0052] This specification also provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the relevant steps of the wavelet resource allocation method.

[0053] This specification also provides a computer program product comprising a computer program that, when executed by a processor, implements the relevant steps of the aforementioned wavelet resource allocation method.

[0054] Based on the beam hopping resource allocation method, apparatus, and computer equipment provided in this specification, the first scheduling weight of each service among M services corresponding to each of N users can be determined, resulting in N*M first scheduling weights. Each first scheduling weight represents the demand intensity of the service corresponding to a user for time slot resources within its beam, where N and M are positive integers, N is the number of users, and M is the number of services. Based on the N*M first scheduling weights corresponding to each of B beam hopping positions within a target adjustment period, a second scheduling weight is determined for each of the B beam hopping positions. This second scheduling weight represents the demand intensity of the beam hopping position for time slot resources within the beam, where B is a positive integer and B is the number of beam hopping positions. The air interface load of each of the B beam hopping positions within the target adjustment period can be determined. Time slot resources can be allocated to each of the B beam hopping positions based on the second scheduling weight and air interface load of each of the B beam hopping positions. This ensures fairness among users and load balance among beam hopping positions in beam hopping resource allocation scenarios, improving the performance of the beam hopping system. Specifically, by leveraging the first scheduling weights of the N*M user services corresponding to each beam position, the scheduling weights of each beam position within the target adjustment period are determined, successfully transforming the scheduling weights from within a beam position to between beam positions. Furthermore, by clearly defining the air interface load of each beam position within the target adjustment period, time slot resource allocation can be comprehensively considered based on the scheduling weights of each beam position and the air interface load. This process not only achieves precise matching between beam resources and service demands but also improves user satisfaction with service quality and further optimizes load balancing between beam positions. Attached Figure Description

[0055] To more clearly illustrate the embodiments of this specification, the accompanying drawings used in the embodiments will be briefly introduced below. The drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 This is a schematic diagram of a hopping beam system in a scenario example;

[0057] Figure 2 This is a schematic flowchart of a wave position resource allocation method provided in the embodiments of this specification;

[0058] Figure 3 This is a flowchart illustrating a method for determining the second scheduling weight of each of the B wave positions within an adjustment period, as provided in the embodiments of this specification.

[0059] Figure 4 This is a flowchart illustrating a method for determining the air interface load of each of the B waveforms within an adjustment period, as provided in the embodiments of this specification.

[0060] Figure 5 This is a flowchart illustrating a method for determining the air interface load of each of the B waveforms within an adjustment period, as provided in the embodiments of this specification.

[0061] Figure 6 This is a flowchart illustrating a method for allocating wave position resources based on a third scheduling weight of wave position, as provided in an embodiment of this specification.

[0062] Figure 7 This is a flowchart illustrating a sampling method for wave position scheduling weights provided in an embodiment of this specification.

[0063] Figure 8 This is a flowchart illustrating a method for determining uplink and downlink scheduling weights of a waveform, as provided in an embodiment of this specification.

[0064] Figure 9 This is a flowchart illustrating a method for determining the utilization rate of physical resource blocks of a wave position, as provided in an embodiment of this specification.

[0065] Figure 10 This is a flowchart illustrating a method for adjusting time slot resources of a wave position according to an embodiment of this specification.

[0066] Figure 11 This is a flowchart illustrating a method for adjusting time slot resources of a wave position according to an embodiment of this specification.

[0067] Figure 12 This is a schematic diagram illustrating an embodiment of a wave position resource allocation method provided in this specification, applied in a scenario example.

[0068] Figure 13 This is a schematic diagram illustrating the method for determining business scheduling weights in a scenario example;

[0069] Figure 14 This is a schematic diagram illustrating the method for fusing uplink and downlink scheduling weights in a scenario example.

[0070] Figure 15 This is a schematic diagram of wave position resource adjustment in a scenario example;

[0071] Figure 16 This is a schematic diagram illustrating how the time slot resources of waveband 1 and waveband 2 change with different adjustment periods when the sampling period is 16 waveband service times in a scenario example.

[0072] Figure 17 This is a schematic diagram illustrating how the time slot resources of waveband 1 and waveband 2 change with different adjustment periods when the sampling period is 8 or 4 waveband service times in a scenario example.

[0073] Figure 18 This is a schematic diagram of the structural composition of a wave position resource allocation device provided in the embodiments of this specification;

[0074] Figure 19 This is a schematic diagram of the structural composition of the computer device provided in the embodiments of this specification. Detailed Implementation

[0075] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0076] It should be noted that the information and data related to users involved in the embodiments of this specification are all information and data authorized by the user or fully authorized by the relevant parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of the relevant data all comply with relevant laws, regulations, and standards, and necessary confidentiality measures have been taken. They do not violate public order and good morals, and corresponding operation entry points are provided for users or relevant parties to choose to authorize or refuse.

[0077] It should also be noted that in the embodiments of this specification, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0078] refer to Figure 1As shown, in satellite-based communication scenarios, the NTN beam-hopping system establishes a communication link between the satellite and the user terminal, connecting the user terminal to the satellite network to achieve satellite-based wireless communication. Specifically, the satellite can be a low Earth orbit satellite, a medium Earth orbit satellite, an inclined geosynchronous orbit satellite, or a highly elliptical orbit satellite, etc., and the user terminal can be a broadband terminal, a navigation and positioning terminal, a vehicle-mounted / airborne / shipborne terminal, a remote sensing data receiving terminal, or an emergency rescue terminal, etc. The satellite carries phased array antennas, transponders, and other equipment, possessing the ability to generate and control beam hopping. With precise control of the phased array antenna, the NTN beam-hopping system can quickly switch beam directions, thereby achieving dynamic coverage of different areas (i.e., beam positions) on the ground. For each beam position, the NTN beam-hopping system can perform fine-grained allocation of beam resources based on the scheduling information of each user terminal within that beam position. In this beam resource allocation process, the fairness of user resource allocation among beam positions and the balance of load among beam positions are key factors that determine the overall performance of the NTN beam-hopping system, and directly affect the resource utilization efficiency and user communication quality of the NTN beam-hopping system.

[0079] Figure 2 This is a flowchart illustrating a wavelet resource allocation method provided in an embodiment of this specification. In practice, it may include the following steps:

[0080] S10: Determine the first scheduling weight of each service in the M services corresponding to each of the N users, and obtain N*M first scheduling weights. The first scheduling weight is the demand intensity of the service corresponding to the user for the time slot resources in the corresponding wavelength. Here, N and M are positive integers, N is the number of users, and M is the number of services.

[0081] In some embodiments, for N users within the coverage area of ​​any wavelength band (N is a positive integer representing the total number of user terminals actually accessing the band, such as home satellite broadband terminals, vehicle communication terminals, emergency rescue terminals, etc.), the M services initiated by each user (M is a positive integer representing the number of services currently running for a single user, such as a user simultaneously performing satellite voice calls and low-speed file downloads) are analyzed one by one. A corresponding first scheduling weight is calculated for each "user-service" combination, ultimately forming N*M independent first scheduling weights. Each independent first scheduling weight can be considered a quantitative representation of the demand intensity of the user's corresponding service for time slot resources within its wavelength band; that is, the higher the weight value, the more urgent the service's demand for time slot resources in the current scheduling cycle, and the higher its priority should be in resource allocation.

[0082] In some embodiments, step S10 may specifically include: obtaining the first scheduling weight of each of the M services corresponding to each of the N users based on a plurality of preset Quality of Service (QoS) parameters. QoS parameters may include at least user fairness and differentiation requirements, service priority, GBR rate requirements, and Packet Delay Budget (PDB) requirements. Specifically, user fairness requirements ensure that each user has a reasonable opportunity for resource allocation, avoiding excessive resource concentration on a few users; differentiation requirements consider the different service quality expectations of different users, providing more suitable resource support for users with special needs; service priority clarifies the importance of different services, for example, emergency call services usually have a higher priority than ordinary file download services; GBR rate requirements specify the minimum transmission rate that certain services must guarantee to ensure the realization of their basic functions, such as video call services; and PDB delay requirements limit the maximum tolerable delay from data packet transmission to reception, which is crucial for services with high real-time requirements such as online games.

[0083] The NTN beam-hopping system can calculate the first scheduling weight Wg(n,m) of each of the M services corresponding to each user among N users in each of B beam positions using a preset scheduling algorithm. Here, n represents the user ID used to distinguish different users (1≤n≤N), and N is the number of users; m represents the service ID used to identify different services used by the user (1≤m≤M), and M is the number of services. During the calculation, the scheduling algorithm quantifies each QoS parameter and assigns a corresponding weight according to its importance. For example, for high-priority services, the algorithm gives them a higher weight in the calculation; for services with GBR rate requirements, the weight value is adjusted according to the difference between the actual rate and the required rate; for services with strict PDB latency requirements, if the current latency is close to the budget limit, the algorithm increases its scheduling weight to prioritize resource allocation and reduce latency. The preset scheduling algorithm can be the classic EPF scheduling algorithm or other scheduling algorithms that can generate the first scheduling weight of each user for each service.

[0084] The first scheduling weight Wg(n,m) obtained through this calculation method can comprehensively reflect the urgency, importance, and resource demand intensity of user n's service m in the current scheduling cycle, providing a precise priority basis for subsequent resource allocation, ensuring that limited resources can prioritize meeting the service needs of those with higher and more urgent QoS requirements, thereby improving the overall service quality and user satisfaction of the system.

[0085] S20: Based on the N*M first scheduling weights corresponding to each of the B wave positions within the target adjustment period, determine the second scheduling weight of each of the B wave positions. The second scheduling weight is the demand intensity of the wave position for time slot resources within the beam, where B is a positive integer and B is the number of wave positions.

[0086] In some embodiments, the retracement period of a beam-hopping system can represent the time period for a cyclic sweep of all positions, denoted as P. The retracement period P precisely marks the time span during which the beam-hopping system starts from the initial position, sequentially passes through each preset position, and finally returns to the initial position, completing one full coverage cycle. Within each retracement period P, the beam-hopping system can rapidly switch and scan between different positions according to a preset sequence and pattern. Each position receives beam-hopping coverage and service within this period, ensuring that users on each position receive attention and resource support from the beam-hopping system within a certain time interval.

[0087] In some embodiments, the target adjustment period can be expressed as the dynamic adjustment period of hopping beam time slot resource allocation, which can be defined using a multiple of the hopping beam retrace period, denoted as T, i.e., the adjustment period is T*P. This definition allows the adjustment period to match the cyclic hopping scan rhythm of the hopping beam. For example, when T is 1, the target adjustment period is equal to the hopping beam retrace period P, meaning that after each cyclic hopping scan of all positions, the hopping beam system will dynamically adjust the time slot resource allocation once; when T is 2, the target adjustment period is 2*P, meaning that an adjustment is performed only after every two cyclic hopping scans. By defining the target adjustment period as a multiple of the hopping beam retrace period, the dynamic adjustment of time slot resources can be made more in line with the operating rules of the hopping beam system. It ensures the timeliness of the adjustment, preventing excessively frequent adjustments from increasing system overhead, and ensures that after a sufficient number of hopping scans, the hopping beam system has sufficient basis to reasonably optimize resource allocation, thereby further improving the resource utilization efficiency and overall performance of the hopping beam system.

[0088] In some embodiments, step S20 may specifically include, for example: Figure 3 The steps shown are as follows:

[0089] S201: Based on the M first scheduling weights of the M services corresponding to each of the N users, determine the first uplink scheduling weight set and the first downlink scheduling weight set of each of the N users within the target adjustment period, and obtain N first uplink scheduling weight sets and N first downlink scheduling weight sets.

[0090] In some embodiments, the NTN beam-hopping system's communication architecture features bidirectional interaction, specifically encompassing two core communication directions: satellite-to-ground and ground-to-satellite. The satellite-to-ground direction primarily transmits signals, data, or services from the satellite to the ground user terminal, while the ground-to-satellite direction handles the function of the ground user terminal sending signals, data, or services to the satellite. These two communication directions together constitute the complete information transmission link of the NTN beam-hopping system, ensuring smooth communication between space and ground.

[0091] In the NTN beam-hopping system, there are two communication directions. The first scheduling weight Wg(n,m) mentioned above can include the third downlink scheduling weight Wg of user n for service m in the satellite-to-ground direction. DL (n, m), and the third uplink scheduling weight Wg in the ground-to-satellite direction. UL (n, m). These two scheduling weights correspond to the scheduling priority and resource allocation requirements of user services in different communication directions, providing more accurate basic data for subsequent resource adjustments.

[0092] In some embodiments, the third uplink scheduling weight Wg generated for each user n for each service m UL (n, m) and the third downlink scheduling weight Wg DL (n, m) can be used to assign the third uplink scheduling weight Wg to the same user n for M services. UL The (n, m) values ​​are merged, and the first uplink scheduling weight set for the user is obtained by comprehensively considering factors such as the uplink demand and urgency of each service; similarly, the third downlink scheduling weight Wg for each service is calculated. DL The (n,m) sets are fused to obtain the first downlink scheduling weight combination for that user. These sets completely record the changes in the uplink and downlink scheduling weights for each user n throughout the entire target adjustment period, providing a comprehensive and systematic basis for subsequent allocation of bandwidth resources according to business needs, and helping to improve the rationality and accuracy of resource allocation.

[0093] S202: Based on the N sets of first uplink scheduling weights and the N sets of first downlink scheduling weights corresponding to each of the B wave positions, determine the first uplink scheduling weight and the first downlink scheduling weight for each of the B wave positions.

[0094] In some embodiments, for the N first uplink scheduling weight sets corresponding to N users within each wave position in the target adjustment period T*P, the uplink scheduling weights of all users in each first uplink scheduling weight set can be merged to obtain the uplink merged scheduling weight of each user within the target adjustment period T*P. Each user's uplink merged scheduling weight is a concentrated reflection of its uplink scheduling demand within the target adjustment period T*P, incorporating key information such as the user's urgency and allocation priority for uplink resources at different times. After obtaining the uplink merged scheduling weight of each user within the target adjustment period T*P, the uplink merged scheduling weights of all users within the target adjustment period T*P can be further merged to obtain the first uplink scheduling weight BW for each of the B wave positions. ULsch (i, j). Where, B = ∑B i B i B can represent the number of positions under the i-th beam, where B is a positive integer. B can also represent the total number of positions under all beams. ULsch (i, j) can represent the first uplink scheduling weight of the j-th position under the i-th beam. By comprehensively considering factors such as the uplink demand and urgency of each user in each position, the first uplink scheduling weight BW of each position within the target adjustment period T*P is obtained. ULsch (i, j) can intuitively and accurately represent the overall scheduling needs and priorities of the entire wave position for uplink resources within the target adjustment period.

[0095] In some embodiments, for the first downlink scheduling weight set of N users corresponding to each wave position within the target adjustment period T*P, the downlink scheduling weights of all users in each first downlink scheduling weight set can be merged to obtain the downlink merged scheduling weight of each user within the target adjustment period T*P. The downlink merged scheduling weight of each user is a concentrated reflection of their downlink scheduling needs within the target adjustment period T*P, incorporating key information such as the urgency and allocation priority of the user's downlink resources at different times. After obtaining the downlink merged scheduling weight of each user within the target adjustment period T*P, the downlink merged scheduling weights of all users within the target adjustment period T*P can be further merged to obtain the first downlink scheduling weight BW for each of the B wave positions. DLsch (i,j). Where BW DLsch (i,j) can represent the first downlink scheduling weight of the j-th position under the i-th beam. By comprehensively considering factors such as the downlink demand and urgency of each user in each position, the first downlink scheduling weight BW of each position within the target adjustment period T*P is obtained. DLsch (i,j) can intuitively and accurately represent the overall scheduling needs and priorities of downlink resources for the entire wave position within the target adjustment period.

[0096] S203: Determine the second scheduling weight of each of the B wave positions based on the fusion result of the first uplink scheduling weight and the first downlink scheduling weight of each wave position.

[0097] In some embodiments, considering the operating characteristics of NTN beam-hopping systems, uplink and downlink communication are mostly performed synchronously; that is, uplink and downlink data transmissions are coordinated and work together to complete the communication process. This synchronicity means that when calculating the beam position scheduling weights, neither the uplink nor the downlink can be considered in isolation; both must be combined to more comprehensively reflect the overall scheduling requirements of the beam positions. Therefore, the second scheduling weight of each beam position can be determined by combining the uplink and downlink beam position scheduling weights.

[0098] Specifically, in order to obtain the second scheduling weight of each wave position, the first uplink scheduling weight BW of each of the B wave positions within the target adjustment period T*P can be adjusted. ULsch (i, j) and the first downlink scheduling weight BW DLsch (i, j) are fused. This fusion is not arbitrary but aims to balance uplink and downlink communication requirements. One specific fusion method involves calculating the first uplink scheduling weight BW for each frequency position. ULsch (i,j) and the first downlink scheduling weight BW DLsch The sum of (i,j) is used as the second scheduling weight BW for each wave position. sch (i, j). The second scheduling weight obtained in this way can take into account the needs of uplink and downlink communication in a balanced way, and thus better balance the performance of uplink and downlink communication such as quality of service guarantee during resource allocation, ensuring that both can receive reasonable resource support and avoiding the degradation of the communication quality of the other due to favoring one side.

[0099] In some embodiments, when the communication scenario of the NTN beam-hopping system is special and only involves uplink communication, it means that the core task of the system is to ensure the transmission of uplink data. In this case, there is no need to fuse the uplink and downlink scheduling weights; the first uplink scheduling weight BW of each of the B positions within the target adjustment period T*P can be directly applied. ULsch (i, j) is the second scheduling weight BW for each wave position. sch (i, j). At this point, the second scheduling weight can reflect the uplink communication needs of the wave position, thereby prioritizing the QoS and other performance of uplink communication during resource allocation, and ensuring that uplink data can be transmitted efficiently and stably.

[0100] In some embodiments, if the NTN beam-hopping system involves only downlink communication, similar to the case involving only uplink communication, the focus of the beam-hopping system is to ensure the transmission of downlink data. In this case, the first downlink scheduling weight BW of each of the B positions within the target adjustment period T*P can be directly applied. DLsch (i, j) is the second scheduling weight BW for each wave position. sch (i,j). In this way, the second scheduling weight can focus on the downlink communication needs of the wavelet, and prioritize the performance of downlink QoS during resource allocation, so that downlink data such as high-definition video and file downloads can be transmitted to users smoothly.

[0101] In some embodiments, NTN beam-hopping systems may experience either uplink or downlink communication limitations. Uplink communication limitations may manifest as poor uplink channel quality or congestion due to excessive uplink data transmission; downlink communication limitations may be due to severe downlink channel interference or insufficient downlink resources. In such cases, to ensure effective communication for the limited party, the first uplink scheduling weight BW for each of the B positions within the target adjustment period T*P can be adjusted. ULsch (i, j) and the first downlink scheduling weight BW DLsch The larger value in (i, j) is used as the second scheduling weight BW for each wave position. sch (i,j). This approach allows the second scheduling weight to accurately consider whether uplink or downlink communication is restricted first, following the principle of "whoever is restricted first is prioritized," thus ensuring the QoS and other performance of the restricted party and preventing the entire communication system from being affected by the restriction of one party.

[0102] S30: Determine the air interface load of each of the B wave positions within the target adjustment period.

[0103] In some embodiments, the air interface load of a bandpass can refer to the pressure on air interface resources exerted by the current volume of service data and the number of user connections on the air interface channel of a specific bandpass. It directly reflects the usage and busyness of air interface resources for that bandpass. By clearly defining the air interface load of each bandpass, it is possible to clearly understand which bandpasses are under high load and require more time slot resources to alleviate the pressure; and which bandpasses are under low load and resources can be appropriately allocated to other high-load bandpasses. This achieves balanced utilization of beam-hopping resources throughout the system, avoiding situations where some bandpasses are congested and others are idle due to uneven load distribution, and further improves the overall operating efficiency of the system.

[0104] In some embodiments, step S30 may specifically include, for example: Figure 4 The steps shown are as follows:

[0105] S301: Obtain the uplink physical resource block utilization rate and downlink physical resource block utilization rate of each of the B wave positions within the target adjustment period.

[0106] In some embodiments, the uplink physical resource block utilization rate of each waveform position can be represented as the ratio of the number of physical resource blocks actually used in the uplink direction of each waveform position within the target adjustment period T*P to the total number of uplink physical resource blocks. Similarly, the downlink physical resource block utilization rate of each waveform position can be represented as the ratio of the number of physical resource blocks actually used in the downlink direction of each waveform position within the target adjustment period T*P to the total number of downlink physical resource blocks.

[0107] By acquiring the uplink and downlink physical resource block utilization rates of each beacon position within the adjustment period, the NTN beam-hopping system can accurately determine the consumption of physical resources in the uplink and downlink directions for different beacons. For beacons with high uplink or downlink physical resource block utilization rates, it indicates that physical resources in their corresponding directions are relatively scarce, and it may be necessary to appropriately increase resource supply in subsequent resource allocations. Conversely, for beacons with low utilization rates, their idle physical resources can be allocated to other beacons with high demand, thereby achieving efficient flow and rational allocation of physical resources among beacons, further improving the resource utilization efficiency and service quality of the entire communication system.

[0108] S302: Determine the load weight of each of the B wave positions based on the fusion result of the uplink physical resource block utilization rate and the downlink physical resource block utilization rate of each wave position.

[0109] In some embodiments, considering the operating characteristics of NTN beam-hopping systems, uplink and downlink communication are mostly performed synchronously; that is, uplink and downlink data transmissions are coordinated and work together to complete the communication process. This synchronicity means that when calculating the load weight of a beam position, neither the uplink nor the downlink can be considered in isolation; both must be combined to more comprehensively reflect the overall scheduling requirements of the beam position. Therefore, the load weight of each beam position can be determined by comprehensively considering the utilization rates of the uplink and downlink physical resource blocks for each beam position.

[0110] Specifically, to obtain the load weight of each wave position, the utilization rate of the first uplink physical resource block PrbRt of each of the B wave positions within the target adjustment period T*P can be calculated. UL (i, j) and the first downlink physical resource block utilization rate PrbRt DL (i,j) are fused. One specific fusion method is to calculate the first uplink physical resource block utilization PrbRt for each wave position. UL (i,j) and the first downlink physical resource block utilization rate PrbRt DLThe sum of (i, j) is used as the load weight BW for each wave position. prb (i, j).

[0111] This calculation method fully considers the synchronous execution of uplink and downlink communication in NTN beam-hopping systems. Since uplink and downlink communication work together to complete the entire communication process, the sum of their utilization rates is used as the beam-level load weight, comprehensively reflecting the overall load situation of the beam in both uplink and downlink directions. When adjusting the load balancing between beams based on this weight, the beam-hopping system comprehensively considers the sum of the uplink and downlink loads for each beam. For beams with a higher total load, resource allocation is appropriately increased to alleviate overall pressure; for beams with a lower total load, idle resources are rationally allocated. This approach effectively avoids the problem of excessive load concentration in one direction due to focusing solely on uplink or downlink load, ultimately achieving uplink and downlink air interface load balancing for the beam and ensuring stable communication performance for the entire beam in both uplink and downlink directions.

[0112] In some embodiments, when the communication scenario of the NTN beam-hopping system is special and only involves uplink communication, it means that the core task of the system is to ensure the transmission of uplink data. In this case, the utilization rate of the first uplink physical resource block PrbRt of each of the B positions within the target adjustment period T*P can be directly used. UL (i, j) is the load weight BW for each wave position. prb (i, j). After determining the load weight at the wave position level based on the uplink physical resource block utilization rate, the focus of resource allocation during wave position balancing will be on the uplink load. For wave positions with high uplink physical resource block utilization, it indicates that their uplink air interface load is heavy, and more resources need to be allocated to meet uplink service demands. For wave positions with low utilization, their idle uplink resources can be allocated to wave positions with tight downlink load. Thus, this method can accurately adjust the load balance between wave positions according to the downlink air interface load status, ensuring that the service quality of uplink communication is given priority.

[0113] In some embodiments, if the NTN beam-hopping system involves only downlink communication, similar to the case involving only uplink communication, the focus of the beam-hopping system is to ensure the transmission of downlink data. In this case, the first downlink physical resource block utilization rate PrbRt of each of the B positions within the target adjustment period T*P can be directly used. DL (i, j) serves as the load weight BW for each wave position. prb(i, j). Using downlink physical resource block utilization as the beamwidth weight, the NTN hopping beam system focuses on the downlink load of each beamwidth during beamwidth balancing. When the downlink physical resource block utilization of a beamwidth is high, it indicates that its uplink air interface load pressure is high, requiring timely allocation of more resources to support downlink data transmission; while for beamwidths with low downlink utilization, their idle downlink resources will be rationally allocated to beamwidths with heavier downlink loads. In this way, beamwidth balancing can be achieved according to the uplink air interface load, ensuring efficient and stable downlink communication.

[0114] In some embodiments, step S30 may further include, for example: Figure 5 The steps shown are as follows:

[0115] S501: Obtain the uplink physical resource block utilization rate and downlink physical resource block utilization rate of each of the B wave positions within the target adjustment period.

[0116] S502: Based on the comparison results of the uplink physical resource block utilization rate and the downlink physical resource block utilization rate of each of the B wave positions, determine the load weight of each of the B wave positions.

[0117] In some embodiments, considering that NTN hopping beam systems may experience uplink or downlink communication limitations, in order to ensure that communication on the limited side is effectively guaranteed, the utilization rate of the first uplink physical resource block PrbRt for each of the B beam positions can be increased. UL (i,j) and the first downlink physical resource block utilization rate PrbRt DL The larger value in (i,j) is used as the load weight BW for each wave position. prb (i, j). This method, using the larger of the two values ​​as the beamwidth load weight, accurately identifies which direction's load reaches a constrained state first. During beamwidth load balancing, the hopping beam system prioritizes the direction with higher utilization; that is, whichever direction becomes constrained first, resources are allocated to it first to alleviate load pressure. For example, if the uplink physical resource block utilization is greater than the downlink utilization, it indicates that the uplink load is constrained first, and uplink air interface load balancing will be prioritized; conversely, downlink will be prioritized. In this way, load constraining issues can be accurately addressed, ensuring that communication performance in the constrained direction is prioritized, maintaining the stable operation of the entire system.

[0118] S40: Allocate time slot resources to each of the B wave positions according to the second scheduling weight and air interface load of each wave position.

[0119] In some embodiments, time slot resources can represent hopping beam time domain resources. During hopping beam communication, time is divided into continuous, fixed-length time intervals, each of which constitutes a time slot. These time slots collectively form the total time domain resources available for data transmission in the hopping beam system. Hopping beams can switch to different wavelengths in different time slots to communicate with users on the corresponding wavelengths.

[0120] In some embodiments, step S40 may specifically include, for example: Figure 6 The steps shown are as follows:

[0121] S401: Determine the third scheduling weight of each of the B wave positions based on the coupling result of the second scheduling weight and the load weight of each wave position.

[0122] In some embodiments, the second scheduling weight BW of each of the B wave positions within the target adjustment period T*P can be coupled. sch (i,j) and load weight BW prb (i,j), to obtain the third scheduling weight BW(i,j) for each wave position. One specific fusion method is to calculate the second scheduling weight BW for each wave position. sch (i, j) and load weight BW prb The product of (i, j) is used as the third scheduling weight BW(i, j) for each beam position. This coupling process allows the system to consider both the urgency of a beam position's resource demand and its actual load capacity, avoiding extreme situations such as "high demand but full load yet still allocating resources" or "low demand but idle load yet underutilized." The third scheduling weight for each beam position obtained after this coupling process incorporates both the beam position's service scheduling demand information and actual load information, enabling more precise guidance for subsequent time slot resource allocation. This ensures that resources flow to the beam positions that truly need them and match their load capacity, thereby improving resource utilization efficiency and further guaranteeing the stable operation and service quality of the entire beam-hopping system.

[0123] S402: Allocate time slot resources to each of the B wave positions according to the third scheduling weight of each wave position.

[0124] In some embodiments, the third scheduling weight serves as a comprehensive indicator integrating the second scheduling weight (reflecting the overall scheduling needs of the broadcast position) and the load weight (reflecting the pressure on air interface resource usage). Its value directly reflects the urgency of the broadcast position's demand for time slot resources within the target adjustment period and the priority of reasonable allocation. When allocating time slot resources, the third scheduling weight of each broadcast position can be used as the primary basis, following the principle of "priority allocation for those with higher weights," while also considering the total amount of time slot resources within the target adjustment period T*P, to achieve a scientific and reasonable allocation.

[0125] Specifically, for beams with a high third scheduling weight, it means that their need for time slot resources is more urgent after comprehensively considering service demands and load conditions. The beam-hopping system will allocate more time slot resources to them to ensure that user services on that beam have sufficient time resource support and avoid service delays or interruptions due to insufficient resources. For beams with a lower third scheduling weight, the beam-hopping system will allocate fewer time slot resources accordingly. This is not to ignore the needs of that beam, but rather to judge its overall situation and determine that its current urgency for time slot resources is lower. A moderate amount of resources can meet its basic service needs, and the remaining time slot resources can be allocated to beams that need them more, thereby achieving efficient utilization of overall resources.

[0126] This time slot resource allocation method based on the third scheduling weight allows time slot resources to be accurately allocated to the most needed positions, ensuring that the service needs of high-priority positions are met and achieving a balanced allocation of overall time slot resources. This effectively improves the resource utilization efficiency of the beam-hopping system and the service quality of user services, providing a solid resource guarantee for the stable operation of the system.

[0127] In some embodiments, the target adjustment period includes Q scheduling periods, where Q is a positive integer and Q is the number of scheduling periods.

[0128] In some embodiments, each target adjustment period may include Q scheduling periods. A scheduling period can represent the dynamic time-frequency division scheduling period for users within a band position, and can be denoted as t. The scheduling period t clearly defines the time interval for dynamic allocation and scheduling of time and frequency resources among users within a specific band position. Within each scheduling period denoted as t, the beam-hopping system can flexibly divide and allocate time and frequency resources within the band position based on various dynamically changing factors such as the real-time service demands of each user, data transmission volume, and channel quality. The target adjustment period integrates Q such "instantaneous scheduling units," essentially providing the NTN beam-hopping system with an "observation and optimization window." Through data analysis over Q consecutive scheduling periods, the NTN beam-hopping system can avoid resource allocation deviations caused by sudden surges in traffic (such as instantaneous data transmission peaks) within a single scheduling period, and more accurately capture the long-term trends and patterns of user service demands within the band position.

[0129] Based on this, step S201 above may specifically include, for example: Figure 7 The steps shown are as follows:

[0130] S2011: Based on the M first scheduling weights of the M services corresponding to each of the N users in each of the Q scheduling cycles, determine the second uplink scheduling weight set and the second downlink scheduling weight set of each of the N users in the target adjustment period, thereby obtaining N second uplink scheduling weight sets and N second downlink scheduling weight sets.

[0131] In some embodiments, within the target adjustment period T*P, the first scheduling weights related to uplink services for each user within Q scheduling periods can be summarized and organized. These weights, which are scattered across various scheduling periods, are then combined in an orderly manner to form the user's second uplink scheduling weight set, which can be represented as Wg. UL (n,t); Similarly, for downlink services, the first scheduling weights within multiple scheduling periods will be aggregated to form a second downlink scheduling weight set, which can be represented as Wg. DL (n,t). These two sets are like "files" of a user's uplink and downlink scheduling needs within the target adjustment period, fully recording the changes in user n's demand for uplink and downlink resources in different scheduling periods t, providing comprehensive basic data for subsequent sampling and processing.

[0132] S2012: Sample the second uplink scheduling weight set and the second downlink scheduling weight set of each of the N users according to the preset sampling period, to obtain the first uplink scheduling weight set and the first downlink scheduling weight set of each of the N users within the target adjustment period.

[0133] In some embodiments, the preset sampling period can represent the period for sampling user scheduling weights, used to calculate wave position scheduling weights. It can be defined using a multiple of the scheduling period t, denoted as L, where L is a positive integer and represents a multiple of the scheduling period t; that is, the sampling period is L*t. This method of defining the preset sampling period as a multiple of the scheduling period t allows the sampling process to flexibly adapt to different system requirements. When the system has high requirements for data accuracy, a smaller value of L can be selected to increase the sampling frequency; when the system prioritizes processing efficiency, a larger value of L can be selected to reduce the number of samples. Regardless of the value of L, it ensures that the sampled user scheduling weight data matches the time scale of the scheduling period, thereby providing accurate and applicable data support for the calculation of wave position scheduling weights, further improving the scientific rigor and efficiency of the entire wave position resource allocation process.

[0134] In some embodiments, according to a preset sampling period L*t, the second uplink scheduling weight set Wg can be selected. UL The corresponding weight data are extracted from (n,t), and these extracted data together constitute the first uplink scheduling weight set Wg. UL (n,Lt); Similarly, from the second downlink scheduling weight set Wg DL Data is extracted from (n, t) according to a preset sampling period to form the first downlink scheduling weight set Wg. DL (n, Lt). This sampling process reduces the amount of data while ensuring data representativeness, thus improving the system's efficiency in processing scheduling weight data. For example, if the target adjustment period T*P contains 100 scheduling periods t, and the preset sampling period L*t is 10 scheduling periods, then one weight data point will be extracted from the second uplink and downlink scheduling weight set every 10 scheduling periods, ultimately resulting in a first uplink and downlink scheduling weight set containing 10 data points. This sampling method preserves the key change characteristics of user scheduling weights while avoiding the processing pressure on the system due to excessive data volume, making subsequent operations such as wavelet resource allocation based on the first uplink and downlink scheduling weight sets more efficient and accurate.

[0135] Furthermore, the aforementioned N*M first scheduling weights may include M third uplink scheduling weights and M third downlink scheduling weights for the M services corresponding to each of the N users; each of the aforementioned N sets of second uplink scheduling weights may include Q second uplink scheduling weights; each of the aforementioned N sets of second downlink scheduling weights may include Q second downlink scheduling weights.

[0136] In some embodiments, each of the aforementioned second uplink scheduling weight sets can be a set containing Q specific values, each of which represents a second uplink scheduling weight. These weights collectively reflect the changes in the user's uplink scheduling demand over the Q scheduling cycles within the target adjustment period. Correspondingly, the second downlink scheduling weight set also contains multiple second downlink scheduling weights, which present the dynamics of the user's scheduling demand over multiple scheduling cycles from the downlink perspective. Each first scheduling weight can include the third uplink scheduling weight Wg generated by user n for service m within each scheduling cycle t. UL (n,m) and the third downlink scheduling weight Wg DL (n, m). These two weights correspond to the scheduling priority and resource demand of users in the uplink and downlink directions of different services, respectively.

[0137] Based on this, step S201 may further include: determining the second uplink scheduling weight and the second downlink scheduling weight of each of the N users in each of the Q scheduling periods, based on the maximum third uplink scheduling weight among the M third uplink scheduling weights and the maximum third downlink scheduling weight among the M third downlink scheduling weights of the M services corresponding to each user in each of the N users in each of the Q scheduling periods.

[0138] In some embodiments, for each user n within each scheduling period t of Q scheduling periods, the third uplink scheduling weight Wg of user n on multiple services m can be determined. UL We analyze (n, m) and select the largest third uplink scheduling weight. This largest third uplink scheduling weight best reflects the user's most urgent business needs in the uplink direction within the current scheduling period. This largest third uplink scheduling weight can be used as the second uplink scheduling weight Wg for user n within this scheduling period t. UL (n), thereby precisely focusing on the core needs of users in the upward direction.

[0139] Similarly, for each user n within a scheduling period t, a third downlink scheduling weight Wg can be assigned to them across multiple services m. DL We analyze the data in (n, m) to identify the largest third downlink scheduling weight. This largest weight represents the user's most prioritized business demand in the downlink direction within the current scheduling period. Based on this, we determine the second downlink scheduling weight Wg for user n within this scheduling period t. DL (n), thereby accurately capturing the key needs of users in the downstream direction.

[0140] Determining the second uplink scheduling weight and the second downlink scheduling weight in this way can highlight the user's main needs in the uplink and downlink directions in each scheduling cycle while integrating the scheduling weights of multiple user services. This provides targeted basic data for the subsequent formation of the second uplink scheduling weight set and the second downlink scheduling weight set, thereby making the subsequent processing based on these sets more in line with the user's actual business needs.

[0141] In some embodiments, step S202 may specifically include, for example: Figure 8 The steps shown are as follows:

[0142] S2021: Based on the average result of each first uplink scheduling weight set in the N first uplink scheduling weight sets of the N users corresponding to each of the B wave positions, and the average result of each first downlink scheduling weight set in the N first downlink scheduling weight sets of the N users, determine the fourth uplink scheduling weight and the fourth downlink scheduling weight of each user in the N users corresponding to each of the B wave positions.

[0143] In some embodiments, the first uplink scheduling weight set Wg UL (n, Lt) contains the uplink scheduling weights of a user at multiple sampling times within the target adjustment period. These weights reflect the fluctuations in the user's demand for uplink resources at different points in time. By calculating the average of this set, the impact of short-term fluctuations can be effectively smoothed out, resulting in a relatively stable and representative value. This value is the user's fourth uplink scheduling weight within the target adjustment period. For example, if a user's first uplink scheduling weight set contains five values: 0.3, 0.5, 0.4, 0.6, and 0.2, and their average is 0.4, then 0.4 is the user's fourth uplink scheduling weight within the target adjustment period. It comprehensively reflects the user's average scheduling demand intensity in the uplink direction throughout the entire target adjustment period, providing concise and effective data support for subsequent weight calculations from the user dimension to the wave position dimension.

[0144] Similarly, the first downlink scheduling weight set Wg DL (n, Lt) encompasses the downlink scheduling weights of a user at multiple sampling times within the target adjustment period. These data intuitively demonstrate the fluctuations in the user's downlink resource demand at different points in time. By calculating the average result of this set, the interference caused by short-term fluctuations can be effectively smoothed out, yielding a stable and representative value. This value is the user's fourth downlink scheduling weight within the target adjustment period. The fourth downlink scheduling weight comprehensively reflects the average scheduling demand intensity in the downlink direction for the user throughout the entire target adjustment period, providing a concise and reliable data foundation for subsequent downlink weight calculations from the user dimension to the wave position dimension.

[0145] S2022: Based on the average results of the N fourth uplink scheduling weights and the average results of the N fourth downlink scheduling weights corresponding to each of the B wave positions, determine the first uplink scheduling weight and the first downlink scheduling weight for each of the B wave positions within the target adjustment period.

[0146] In some embodiments, each waveband covers N users, and the fourth uplink scheduling weights of these users reflect their average uplink demand within the target adjustment period. The average of the fourth uplink scheduling weights for all users within that waveband is calculated, and the result is the first uplink scheduling weight BW for that waveband within the target adjustment period. ULsch (i,j). For example, if a waveband contains 3 users with fourth uplink scheduling weights of 0.4, 0.5, and 0.6 respectively, and their average is 0.5, then 0.5 is the first uplink scheduling weight for that waveband. This value comprehensively reflects the uplink demand of all users within the waveband, fully reflecting the overall uplink resource demand level of that waveband within the target adjustment period. It provides an important decision-making basis for subsequent resource allocation between wavebands, ensuring that resource allocation matches the overall uplink demand of the waveband.

[0147] Similarly, the average of the fourth downlink scheduling weights for N users within each wavelength position is calculated, and the result is the first downlink scheduling weight BW for that wavelength position within the target adjustment period. DLsch (i,j). The first downlink scheduling weight integrates the downlink demand of all users within the wavelet, and can comprehensively reflect the overall demand level of downlink resources for the wavelet within the target adjustment period. It provides a key decision basis for subsequent resource allocation between waveslet, ensuring that resource allocation can be adapted to the overall downlink demand of the wavelet.

[0148] In some embodiments, step S301 may specifically include, for example: Figure 9 The steps shown are as follows:

[0149] S3011: Calculate the number of uplink physical resource blocks used and the number of downlink physical resource blocks used for each of the B wave positions within the target adjustment period.

[0150] In some embodiments, within the target adjustment period T*P, each wave position encompasses N users. These users utilize physical resource blocks due to uplink and downlink services within each scheduling period t. To count the uplink physical resource block usage, the number of physical resource blocks occupied by the uplink services of all users in that wave position within each scheduling period is recorded individually. The results from Q scheduling periods are then summed to obtain the total number of uplink physical resource blocks used by that wave position within the entire target adjustment period. Similarly, to count the downlink physical resource block usage, the number of physical resource blocks occupied by the downlink services of all users in that wave position within each scheduling period is recorded and summed to obtain the total number of downlink physical resource blocks used within the target adjustment period.

[0151] S3012: Based on the comparison results of the number of uplink physical resource blocks used and the uplink time slot resources of each of the B wave positions within the target adjustment period, determine the uplink physical resource block utilization rate of each of the B wave positions.

[0152] In some embodiments, the uplink time slot resources of each frequency band within the target adjustment period T*P can be the total number of physical resource blocks available for uplink services within that frequency band during the target adjustment period. This is determined by the number of uplink time slots and the number of physical resource blocks contained in each time slot. The uplink physical resource block utilization rate is obtained by comparing the number of uplink physical resource blocks used with the total number of uplink time slot resources, for example, by expressing it as a ratio. The uplink physical resource block utilization rate directly reflects the efficiency of uplink physical resource utilization for that frequency band. A higher utilization rate indicates a tighter supply of uplink resources; conversely, a lower utilization rate indicates more idle uplink resources.

[0153] S3013: Based on the comparison results of the downlink physical resource block usage number and the downlink time slot resources of each of the B wave positions within the target adjustment period, determine the downlink physical resource block utilization rate of each of the B wave positions.

[0154] In some embodiments, the downlink time slot resources of each frequency band within the target adjustment period T*P can be the total number of physical resource blocks available for downlink services within that frequency band during the target adjustment period. The number of downlink physical resource blocks used can be compared with the total number of downlink time slot resources, for example, by calculating their ratio, to obtain the downlink physical resource block utilization rate. The downlink physical resource block utilization rate reflects the efficiency of downlink physical resource utilization for that frequency band, providing an important basis for determining whether downlink resources are sufficient and whether resource adjustments are needed.

[0155] In some embodiments, step S402 may specifically include, for example: Figure 10 The steps shown are as follows:

[0156] S4021: Find the first wave position with the largest third scheduling weight among the B wave positions.

[0157] In some embodiments, the first wave position with the highest third scheduling weight can be found among B wave positions. Since the third scheduling weight comprehensively reflects the service demand and load status of a wave position, the highest third scheduling weight means that the wave position has the largest resource gap or the highest service priority during the target adjustment period. For example, if a wave position has a significantly higher third scheduling weight than other wave positions due to a sudden surge in high-priority services, it will be marked as the first wave position and become the focus of resource adjustment.

[0158] S4022: Among the B wave positions, find multiple second wave positions where the difference between the third scheduling weight and the maximum third scheduling weight is greater than the difference threshold, and the difference between the time slot resource and the minimum time slot resource threshold is greater than or equal to the time slot resource unit.

[0159] In some embodiments, the time slot resource unit can be either the smallest divisible time slot resource unit of the beam hopping system (i.e., one minimum time slot resource unit) or an aggregate unit formed by combining multiple minimum time slot resource units. Here, "one minimum time slot resource unit" represents the smallest granularity of resource scheduling in the beam hopping system. Its duration matches the switching cycle of the satellite beam hopping and the service latency requirements of the user terminal, for example, set to 1ms or 2ms based on the low latency characteristics of low Earth orbit satellites. The advantage of this minimum unit is its ability to accurately respond to low-rate, sudden service demands, such as emergency short message transmission from satellite communication mobile phones or location information feedback from emergency rescue terminals. These services have small data volumes per transmission and low resource consumption requirements; allocating one minimum time slot resource unit is sufficient to meet transmission needs, avoiding resource waste. Simultaneously, for scenarios with a large number of users and scattered service types within a beam, using one minimum time slot resource unit as the scheduling unit enables "on-demand allocation," improving the overall utilization rate of resources within the beam. "Multiple minimum time slot resource units" aggregates the smallest units based on business needs, such as combining 2, 4, or 8 minimum time slot resource units into a single scheduling unit. This aggregation method is more suitable for high-speed, continuous business scenarios, such as high-definition video streaming services provided by airborne satellite communication systems for passenger planes, and large file transfer needs of ocean-going cargo ship terminals. These types of services require stable bandwidth support, and the transmission capacity of a single minimum time slot resource unit cannot meet the rate requirements. By aggregating multiple minimum units, continuous resource blocks can be formed, ensuring the smoothness of business transmission. In addition, when satellite payload base station computing resources are limited, using multiple minimum time slot resource units as scheduling units can reduce the number of calculations per scheduling and reduce on-board resource consumption.

[0160] In some embodiments, multiple second wave positions that meet specific conditions can be selected from B wave positions. These conditions include: the difference between the third scheduling weight and the maximum third scheduling weight is greater than a preset difference threshold, and the difference between the time slot resources currently allocated to the wave position and the minimum time slot resource threshold set by the system is greater than or equal to time slot resource units. The former ensures that the resource demand urgency of the second wave position is much lower than that of the first wave position, avoiding new imbalances caused by allocating resources from wave positions with closer demand; the latter ensures that these wave positions have available "redundant resources," that is, there are still remaining time slot resources after the current time slot resources meet their basic needs, and the remaining amount reaches the available time slot resource units, which can support the effective transfer of resources. For example, if the third scheduling weight of a certain wave position is only half of the maximum weight (exceeding the difference threshold), and its current time slot resources are 2 more time slot resource units than the minimum time slot threshold (meeting the resource splitting condition), it will be included in the list of second wave positions.

[0161] S4023: Find the third wave position with the smallest third scheduling weight among the plurality of second wave positions.

[0162] In some embodiments, among the selected multiple second wave positions, the third wave position with the lowest third scheduling weight can be identified. The lowest third scheduling weight means that the resource demand of that wave position is the least urgent, and allocating its remaining resources will have the least impact on its own business. For example, among multiple second wave positions, if a certain wave position has the lowest third scheduling weight, it indicates that its current business pressure is the lowest. Allocating resources from this wave position can both meet the needs of the first wave position and minimize the impact on its own service quality.

[0163] S4024: Adjust the time slot resources of the first wave position and the third wave position.

[0164] In some embodiments, based on the search results described above, the time slot resources of the first and third wave positions can be adjusted.

[0165] In some embodiments, step S4024 may specifically include, for example: Figure 11 The steps shown are as follows:

[0166] S40241: Increase the time slot resources of the first wave position by time slot resource units.

[0167] S40242: Reduce the time slot resources of the third wave position by time slot resource units.

[0168] Because the first wave slot has the highest third scheduling weight, its demand for time slot resources is the strongest during the current adjustment cycle, potentially leading to risks such as service congestion and data transmission delays. Increasing its time slot resources in increments of one time slot resource unit can gradually and precisely alleviate the resource pressure on this wave slot. For example, if the time slot resource unit is one time slot block, adding one time slot block of resources to the first wave slot each time avoids the waste caused by adding too many resources at once and allows for flexible adjustments based on the actual changes in the wave slot's demand. As time slot resources gradually increase, high-priority services on the first wave slot can receive more sufficient time resource support, effectively ensuring the smoothness and timeliness of data transmission, thereby improving user satisfaction with service delivery.

[0169] The third wave slot is selected from multiple second wave slots, possessing the lowest third scheduling weight. Its resource demand is the least urgent, and its currently allocated time slot resources have some redundancy after meeting its basic needs. Reducing its time slot resources by unit ensures that the third wave slot's own operations are not significantly affected, while achieving a reasonable resource transfer. For example, if the third wave slot's time slot resources exceed the minimum time slot resource threshold by two units, reducing its resources by one unit will still meet its basic business needs, preventing service interruptions or delays due to insufficient resources. This gradual reduction method ensures the stability of the third wave slot's operations while efficiently allocating its idle resources to the more needed first wave slots, achieving optimized allocation of time slot resources across the entire system and improving overall resource utilization efficiency.

[0170] As can be seen from the above, based on the beam-hopping resource allocation method provided in the embodiments of this specification, the first scheduling weight of each service in the M services corresponding to each of N users can be determined, resulting in N*M first scheduling weights. The first scheduling weight represents the demand intensity of the service corresponding to the user for time slot resources within its beam, where N and M are positive integers, N is the number of users, and M is the number of services. Based on the N*M first scheduling weights corresponding to each of the B beams within the target adjustment period, a second scheduling weight is determined for each of the B beams. The second scheduling weight represents the demand intensity of the beam for time slot resources within the beam, where B is a positive integer and B is the number of beams. The air interface load of each of the B beams within the target adjustment period can be determined. Time slot resources can be allocated to each of the B beams based on the second scheduling weight and air interface load of each of the B beams. This ensures fairness among users and load balance among beams in beam-hopping resource allocation scenarios, improving the performance of the beam-hopping system. Specifically, by leveraging the first scheduling weights of the N*M user services corresponding to each beam position, the scheduling weights of each beam position within the target adjustment period are determined, successfully transforming the scheduling weights from within a beam position to between beam positions. Furthermore, by clearly defining the air interface load of each beam position within the target adjustment period, time slot resource allocation can be comprehensively considered based on the scheduling weights of each beam position and the air interface load. This process not only achieves precise matching between beam resources and service demands but also improves user satisfaction with service quality and further optimizes load balancing between beam positions.

[0171] In a specific scenario example, refer to Figure 1 The hopping beam system shown can utilize a beam slot resource allocation method provided in this specification to match the time slot resources and service demands of hopping beam service beam slots, balancing the load between beam slots and improving QoS satisfaction. For detailed implementation procedures, please refer to [link / reference needed]. Figure 12 As shown, it includes the following steps:

[0172] When the scheduling period arrives, based on user fairness and differentiation requirements, service priority, GBR rate requirements, PDB latency requirements, etc., the scheduling weight Wg(n,m) for each user and each service is calculated according to the classic EPF scheduling algorithm, where n is the user ID and m is the service ID. This can be expressed as the formula:

[0173] Wg(n,m)=F(α n ,β n,m γ n，m δ n，m );

[0174] In the formula, α n This refers to the user differentiation factor (fair-time configuration 1), α of user x. xα relative to other users y y The larger the value of β, the larger the Wg of user x; n，m It is the priority factor of the business, the β of business x n，x β relative to other business y n，y The larger the value of x, the larger the Wg of the business x; γ n,m This refers to the GBR rate requirement of the service, and the actual service rate r. n,m With γ n,m The greater the gap, the larger the business's Wg; δ n，m This refers to the PDB latency requirement of the service, and the actual latency d of the service. n,m With δ n,m The larger the gap, the greater the QoS requirement (Wg). F(*) is the fair weight for calculating the enhancement ratio of these QoS requirements; a concrete example can be found here. Figure 13 .

[0175] In addition, other QoS requirements such as Multi-Band-Radio (MBR) restrictions can be added to the above process to control MBR. These are not listed here.

[0176] The larger the user's first scheduling weight Wg(n,m) for each service, the more priority the resources can be obtained within the scheduling period. This ensures that the services with the most urgent and important QoS requirements can obtain the most resources first. Furthermore, an enhanced proportional fair weight calculation formula is used to reflect fairness among users, while also taking into account the user's channel conditions to improve the capacity of the beam hopping system.

[0177] NTN beam-hopping systems typically calculate user scheduling weights for both satellite-to-ground and ground-to-satellite communication directions, denoted as Wg in the downlink direction. DL (n, m) and the upward direction Wg UL (n, m).

[0178] First, the sorting result Wg of the scheduling weights for multiple user services. DL (n,m) and Wg UL For each user (n, m), the user with the largest service weight is selected as the uplink / downlink scheduling weight Wg. DL (n) and Wg UL (n).

[0179] Then, for the user scheduling weight time-domain sequence Wg DL (n, t) and Wg UL Periodic sampling of (n,t) yields Wg DL (n, Lt) and Wg UL (n, Lt), where L is the sampling period.

[0180] Finally, within the hopping beam resource allocation adjustment period T*P, for Wg DL (n, Lt) and Wg UL (n,Lt), the average value BW is obtained by averaging by user and by unit service duration within the beam position j of beam i. DLsch (i,j) and BW ULsch (i,j).

[0181] Considering that NTN beam hopping is generally performed synchronously for uplink and downlink, it is necessary to comprehensively consider the uplink and downlink bandwidth scheduling weights:

[0182] 1. If using BW DLsch (i,j) and BW ULsch The sum of (i, j) yields the wave position level scheduling weight BW. sch (i,j) will ultimately balance the performance of uplink and downlink QoS guarantees.

[0183] 2. If only BW is used DLsch (i, j) is the wave position level scheduling weight BW sch (i,j) This method only considers downlink and prioritizes downlink QoS and other performance.

[0184] 3. If only BW is used ULsch (i, j) is the wave position level scheduling weight BW sch (i, j) This method only considers the uplink and prioritizes uplink QoS and other performance.

[0185] 4. If using BW DLsch (i,j) and BW ULsch The larger value of (i, j) is used as the wave position level scheduling weight BW sch (i,j) This method considers whether uplink or downlink is restricted first, prioritizing the QoS and performance of the affected segment. A concrete example of comprehensive uplink and downlink bandwidth scheduling weights can be found in [reference needed]. Figure 14 .

[0186] Within the hopping beam resource allocation adjustment period T*P, the downlink PRB utilization rate PrbRt is calculated separately. DL (i, j) and uplink PRB utilization PrbRt UL (i, j). Within the hopping beam resource allocation adjustment cycle, the number of downlink PRBs used by user n at scheduling time t and the number of uplink PRBs used by user n at scheduling time t are counted. Then, they are divided by the number of available uplink and downlink PRBs calculated based on the service time D to obtain the PRB utilization rate.

[0187] The wave level load weight is calculated as follows:

[0188] 1. If using PrbRtDL (i,j) and PrbRt UL The sum of (i, j) yields the wave level load weight BW. prb (i, j) will eventually balance the uplink and downlink air interface load.

[0189] 2. If only PrbRt is used DL (i, j) is the wave position level load weight BW prb (i,j), this method performs inter-wavelength equalization on the downlink air interface load.

[0190] 3. If only PrbRt is used UL (i, j) is the wave position level load weight BW prb (i, j), this method performs inter-wavelength equalization based on uplink air interface load.

[0191] 4. If using PrbRt dL (i,j) and PrbRt UL The larger value of (i, j) is used as the wave level load weight BW prb (i, j) This method considers whether the uplink load or the downlink load is limited first, and prioritizes the air interface load balancing of the one that is limited first.

[0192] The final wave weight is obtained by combining the two scheduling weights and the load weight:

[0193] BW(i,j)=BW sch (i, j)*BW prb (i,j);

[0194] After completing the statistical wavelet level weighting, the maximum weight BW is found by sorting within the beam. max (i) and its corresponding wave position ID (Jmax(i)).

[0195] Then, according to the weight from smallest to largest, search for wave positions (Jx(i)) that meet the following two conditions.

[0196] First, the weight difference has exceeded the given difference threshold (BWDiffTHd, to prevent ping-pong adjustment).

[0197] Second, the current service duration of the current wave position is greater than or equal to the minimum service duration of the minimum wave position plus the adjustment time granularity (to ensure that the wave position with a small weight can meet the minimum requirements after reducing the service time).

[0198] Once all the above conditions are met, the service time D of wave position i is adjusted according to the following formula:

[0199]

[0200] Exit the adjustment process after each execution to ensure that only one group is adjusted at a time. For specific adjustment details, please refer to [link / reference]. Figure 15 .

[0201] The above scenario example verifies the waveband resource allocation method provided in this specification. It determines the first scheduling weight of each of the M services corresponding to each of the N users, resulting in N*M first scheduling weights. Each first scheduling weight represents the demand intensity of the service corresponding to a user for time slot resources within its respective waveband, where N and M are positive integers, N is the number of users, and M is the number of services. Based on the N*M first scheduling weights corresponding to each of the B wavebands within the target adjustment period, a second scheduling weight is determined for each of the B wavebands. This second scheduling weight represents the demand intensity of the waveband for time slot resources within the beam, where B is a positive integer and B is the number of wavebands. The air interface load of each of the B wavebands within the target adjustment period can be determined. Time slot resources can be allocated to each of the B wavebands based on the second scheduling weight and air interface load. Specifically, by leveraging the first scheduling weights of the N*M user services corresponding to each beam position, the scheduling weights of each beam position within the target adjustment period are determined, successfully transforming the scheduling weights from within a beam position to between beam positions. Furthermore, by clearly defining the air interface load of each beam position within the target adjustment period, time slot resource allocation can be comprehensively considered based on the scheduling weights of each beam position and the air interface load. This process not only achieves precise matching between beam resources and service demands but also improves user satisfaction with service quality and further optimizes load balancing between beam positions.

[0202] The following are simulation results of the wavelet resource allocation method proposed in this specification in a single-beam, two-wavelet user scenario:

[0203] The allocation of single-beam two-position users is shown in Table 1 below:

[0204] Table 1

[0205] Wave position 1 user id list 1，3，5，6 Wave position 2 user id list 2，4

[0206] Configure a single GBR service, with GFBR 30Mbps and MFBR 240Mbps.

[0207] From the perspective of ideal balance, the desired final beam position service time ratio is 2:1. However, due to the 20ms beam backflip period, a 1ms adjustment granularity cannot achieve the ideal ratio; in practice, only 14:6 or 13:7 can be configured. Simulation results show... Figure 16 and Figure 17 The adjustment process.

[0208] from Figure 16 and Figure 17The adjustment process shows that after configuring the sampling period to 16 Transmission Time Intervals (TTIs) (i.e., a transmission time interval can be regarded as a time slot resource unit of transmission time interval) (L=16), the adjustment process will be ping-pong within a reasonable range due to larger weight fluctuations. Shortening the sampling period to 8 TTIs and 4 TTIs has the same effect, and it stops adjusting after reaching a ratio of 13:7.

[0209] The rate results of the wavelet resource allocation method under the three scheduling weight sampling period configurations are shown in Table 2:

[0210] Table 2

[0211]

[0212]

[0213] As can be seen, after using the wavelet resource allocation method in this manual, the downlink system capacity is sufficient, the GBR guarantee balance and user fairness are improved, and the overall GBR guarantee satisfaction is significantly improved.

[0214] See Figure 18 As shown in the embodiments of this specification, a wave position resource allocation device is also provided, which may specifically include the following structural modules:

[0215] The first determining module 1801 is specifically used to determine the first scheduling weight of each service in the M services corresponding to each of the N users, and obtain N*M first scheduling weights. The first scheduling weight is the demand intensity of the service corresponding to the user for the time slot resources within its respective wavelength, where N and M are positive integers, N is the number of users, and M is the number of services.

[0216] The second determining module 1802 is specifically used to determine the second scheduling weight of each of the B wave positions based on the N*M first scheduling weights corresponding to each wave position in the B wave positions within the target adjustment period. The second scheduling weight is the demand intensity of the wave position for time slot resources within the beam, where B is a positive integer and B is the number of wave positions.

[0217] The third determining module 1803 is specifically used to determine the air interface load of each of the B wave positions within the target adjustment period.

[0218] The allocation module 1804 is specifically used to allocate time slot resources to each of the B wave positions according to the second scheduling weight and air interface load of each wave position.

[0219] In some embodiments, the second determining module 1802 can specifically determine the second scheduling weight of each of the B wave positions according to the N*M first scheduling weights corresponding to each wave position in the target adjustment period, wherein the second scheduling weight is the demand intensity of the wave position for the time slot resources within the beam, and B is a positive integer, where B is the number of wave positions:

[0220] Based on the M first scheduling weights of the M services corresponding to each of the N users, determine the first uplink scheduling weight set and the first downlink scheduling weight set of each of the N users within the target adjustment period, and obtain N first uplink scheduling weight sets and N first downlink scheduling weight sets.

[0221] Based on the N first uplink scheduling weight sets and N first downlink scheduling weight sets corresponding to each of the B wave positions, the first uplink scheduling weight and the first downlink scheduling weight of each of the B wave positions are determined respectively.

[0222] Based on the fusion result of the first uplink scheduling weight and the first downlink scheduling weight of each of the B wave positions, the second scheduling weight of each of the B wave positions is determined.

[0223] In some embodiments, the second determining module 1802 can specifically determine the first uplink scheduling weight set and the first downlink scheduling weight set for each of the N users within the target adjustment period based on the M first scheduling weights of the M services corresponding to each of the N users, thereby obtaining N first uplink scheduling weight sets and N first downlink scheduling weight sets:

[0224] Based on the M first scheduling weights of the M services corresponding to each of the N users in each of the Q scheduling cycles, determine the second uplink scheduling weight set and the second downlink scheduling weight set of each of the N users in the target adjustment period, and obtain N second uplink scheduling weight sets and N second downlink scheduling weight sets.

[0225] The second uplink scheduling weight set and the second downlink scheduling weight set of each of the N users are sampled according to a preset sampling period to obtain the first uplink scheduling weight set and the first downlink scheduling weight set of each of the N users within the target adjustment period.

[0226] In some embodiments, the N*M first scheduling weights include M third uplink scheduling weights and M third downlink scheduling weights for the M services corresponding to each of the N users; each of the N sets of second uplink scheduling weights includes Q second uplink scheduling weights; each of the N sets of second downlink scheduling weights includes Q second downlink scheduling weights.

[0227] The second determining module 1802 mentioned above can also be used for:

[0228] Based on the maximum third uplink scheduling weight among the M third uplink scheduling weights and the maximum third downlink scheduling weight among the M third downlink scheduling weights of the M services corresponding to each of the N users in each of the Q scheduling periods, the second uplink scheduling weight and the second downlink scheduling weight of each of the N users in each of the Q scheduling periods are determined respectively.

[0229] In some embodiments, the second determining module 1802 can specifically determine the first uplink scheduling weight and the first downlink scheduling weight for each of the B wave positions according to the N first uplink scheduling weight sets and N first downlink scheduling weight sets corresponding to each of the B wave positions in the following manner:

[0230] Based on the average result of each first uplink scheduling weight set in the N first uplink scheduling weight sets of the N users corresponding to each of the B wave positions, and the average result of each first downlink scheduling weight set in the N first downlink scheduling weight sets of the N users corresponding to each of the B wave positions, the fourth uplink scheduling weight and the fourth downlink scheduling weight of each user in the N users corresponding to each of the B wave positions are determined respectively.

[0231] Based on the average results of the N fourth uplink scheduling weights and the average results of the N fourth downlink scheduling weights corresponding to each of the B wave positions, the first uplink scheduling weight and the first downlink scheduling weight of each of the B wave positions within the target adjustment period are determined respectively.

[0232] In some embodiments, the third determining module 1803 described above can specifically determine the air interface load of each of the B waveforms within the target adjustment period in the following manner:

[0233] Obtain the uplink physical resource block utilization rate and downlink physical resource block utilization rate of each of the B wave positions within the target adjustment period;

[0234] The load weight of each of the B wave positions is determined based on the fusion result of the uplink physical resource block utilization rate and the downlink physical resource block utilization rate of each wave position.

[0235] In some embodiments, the third determining module 1803 described above can specifically determine the air interface load of each of the B waveforms within the target adjustment period in the following manner:

[0236] Obtain the uplink physical resource block utilization rate and downlink physical resource block utilization rate of each of the B wave positions within the target adjustment period;

[0237] Based on the comparison results of the uplink physical resource block utilization rate and the downlink physical resource block utilization rate of each of the B wave positions, the load weight of each of the B wave positions is determined.

[0238] In some embodiments, the third determining module 1803 can specifically obtain the uplink physical resource block utilization rate and downlink physical resource block utilization rate of each of the B wave positions within the target adjustment period in the following manner:

[0239] The number of uplink physical resource blocks used and the number of downlink physical resource blocks used for each of the B wave positions within the target adjustment period are counted.

[0240] Based on the comparison results of the number of uplink physical resource blocks used and the uplink time slot resources of each of the B wave positions within the target adjustment period, the uplink physical resource block utilization rate of each of the B wave positions is determined.

[0241] Based on the comparison results of the downlink physical resource block usage and the downlink time slot resources of each of the B wave positions within the target adjustment period, the downlink physical resource block utilization rate of each of the B wave positions is determined.

[0242] In some embodiments, the allocation module 1804 may allocate time slot resources to each of the B wave positions according to the second scheduling weight and air interface load of each of the B wave positions in the following manner:

[0243] Based on the coupling result of the second scheduling weight and the load weight of each of the B wave positions, the third scheduling weight of each of the B wave positions is determined.

[0244] Based on the third scheduling weight of each of the B wave positions, time slot resources are allocated to each of the B wave positions.

[0245] In some embodiments, the allocation module 1804 may allocate time slot resources to each of the B wave positions according to the third scheduling weight of each wave position in the B wave positions in the following manner:

[0246] Find the first wave position with the largest third scheduling weight among the B wave positions;

[0247] In the B wave positions, find multiple second wave positions where the difference between the third scheduling weight and the maximum third scheduling weight is greater than the difference threshold, and the difference between the time slot resource and the minimum time slot resource threshold is greater than or equal to the time slot resource unit.

[0248] Find the third wave position with the smallest third scheduling weight among the plurality of second wave positions;

[0249] Adjust the time slot resources of the first and third wave positions.

[0250] In some embodiments, the allocation module 1804 can specifically adjust the time slot resources of the first wave position and the third wave position in the following manner:

[0251] Increase the time slot resources of the first wave position by time slot resource units;

[0252] Reduce the time slot resources of the third wave position by time slot resource units.

[0253] In some embodiments, the first determining module 1805 can specifically determine the first scheduling weight of each service among the M services corresponding to each of the N users in the following manner:

[0254] Based on multiple preset Quality of Service (QoS) parameters, obtain the first scheduling weight of each service among the M services corresponding to each of the N users.

[0255] It should be noted that the units, devices, or modules described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. For ease of description, the above devices are described by dividing them into various modules according to their functions. Of course, in implementing this specification, the functions of each module can be implemented in one or more software and / or hardware, or the module that implements the same function can be implemented by a combination of multiple sub-modules or sub-units, etc. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and 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. Furthermore, the coupling or direct coupling or communication connection between the devices or units shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0256] As can be seen from the above, based on the waveband resource allocation device provided in the embodiments of this specification, the first scheduling weight of each service in the M services corresponding to each of N users can be determined, resulting in N*M first scheduling weights. The first scheduling weight represents the demand intensity of the service corresponding to the user for time slot resources within its respective waveband, where N and M are positive integers, N is the number of users, and M is the number of services. Based on the N*M first scheduling weights corresponding to each of the B wavebands within the target adjustment period, the second scheduling weight of each of the B wavebands is determined. The second scheduling weight represents the demand intensity of the waveband for time slot resources within the beam, where B is a positive integer and B is the number of wavebands. The air interface load of each of the B wavebands within the target adjustment period can be determined. Time slot resources can be allocated to each of the B wavebands based on the second scheduling weight and air interface load of each of the B wavebands. Specifically, by leveraging the first scheduling weights of the N*M user services corresponding to each beam position, the scheduling weights of each beam position within the target adjustment period are determined, successfully transforming the scheduling weights from within a beam position to between beam positions. Furthermore, by clearly defining the air interface load of each beam position within the target adjustment period, time slot resource allocation can be comprehensively considered based on the scheduling weights of each beam position and the air interface load. This process not only achieves precise matching between beam resources and service demands but also improves user satisfaction with service quality and further optimizes load balancing between beam positions.

[0257] This specification provides an embodiment of a computer device, see below. Figure 19 As shown. The computer device includes a network communication port 1901, a processor 1902, and a memory 1903. These structures are connected by internal cables so that they can perform specific data interaction.

[0258] The processor 1902 can specifically be used to determine the first scheduling weight of each service among the M services corresponding to each of the N users, obtaining N*M first scheduling weights. The first scheduling weight is the demand intensity of the service corresponding to the user for the time slot resources within its respective band, where N and M are positive integers, N is the number of users, and M is the number of services. Based on the N*M first scheduling weights corresponding to each of the B bands within the target adjustment period, a second scheduling weight is determined for each of the B bands. The second scheduling weight is the demand intensity of the band for the time slot resources within the band, where B is a positive integer and B is the number of bands. The air interface load of each of the B bands within the target adjustment period is determined. Based on the second scheduling weight and air interface load of each of the B bands, time slot resources are allocated to each of the B bands.

[0259] The memory 1903 can be used to store corresponding instruction programs, as well as related data such as target data.

[0260] Based on the above method, the relevant structural performance of computer equipment can be effectively utilized to improve the data processing speed of electronic equipment and efficiently realize data processing for wavelet resource allocation.

[0261] In this embodiment, the network communication port 1901 can be a virtual port bound to different communication protocols, thereby enabling the sending or receiving of different data. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. Furthermore, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM or CDMA; it can also be a Wi-Fi chip; or it can be a Bluetooth chip.

[0262] In this embodiment, the processor 1902 can be implemented in any suitable manner. For example, the processor can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc. This specification is not limiting.

[0263] In this embodiment, the memory 1903 may include multiple layers. In a digital system, anything that can store binary data can be a memory. In an integrated circuit, a circuit with storage function but no physical form is also called a memory, such as RAM, FIFO, etc. In a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0264] This specification also provides a computer-readable storage medium based on the above-described method for allocating wavelength slot resources. The computer-readable storage medium stores computer program instructions that, when executed, implement the following: determining the first scheduling weight of each of the M services corresponding to each of the N users, resulting in N*M first scheduling weights, where each first scheduling weight represents the demand intensity of the service corresponding to the user for time slot resources within its respective wavelength slot, where N and M are positive integers, N is the number of users, and M is the number of services; determining the second scheduling weight of each of the B wavelength slots based on the N*M first scheduling weights corresponding to each wavelength slot within the target adjustment period, where the second scheduling weight represents the demand intensity of the wavelength slot for time slot resources within the beam, where B is a positive integer and B is the number of wavelength slots; determining the air interface load of each of the B wavelength slots within the target adjustment period; and allocating time slot resources to each of the B wavelength slots based on the second scheduling weight and air interface load.

[0265] In this embodiment, the storage medium includes, but is not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), cache, hard disk drive (HDD), or memory card. The memory can be used to store computer program instructions. The network communication unit can be an interface configured according to standards specified in the communication protocol for network connection communication.

[0266] In this embodiment, the specific functions and effects implemented by the program instructions stored in the computer-readable storage medium can be explained in comparison with other embodiments, and will not be repeated here.

[0267] This specification also provides a computer program product, comprising at least a computer program, which, when executed by a processor, implements the following method steps: determining the first scheduling weight of each of the M services corresponding to each of the N users, obtaining N*M first scheduling weights, where the first scheduling weight is the demand intensity of the service corresponding to the user for the time slot resources within its respective band, where N and M are positive integers, N is the number of users, and M is the number of services; determining the second scheduling weight of each of the B bands based on the N*M first scheduling weights corresponding to each band within the target adjustment period, where the second scheduling weight is the demand intensity of the band for the time slot resources within the band, where B is a positive integer, and B is the number of bands; determining the air interface load of each of the B bands within the target adjustment period; and allocating time slot resources to each of the B bands based on the second scheduling weight and air interface load of each band.

[0268] While this specification provides the steps of operation for the methods described in the embodiments or flowcharts, more or fewer steps may be included based on conventional or non-inventive means. The order of steps listed in the embodiments is merely one possible order of execution among many steps and does not represent the only possible order. In actual device or client product execution, the methods shown in the embodiments or drawings may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment, or even a distributed data processing environment). The terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitations, the presence of other identical or equivalent elements in a process, method, product, or apparatus that includes said elements is not excluded. The terms "first," "second," etc., are used to denote names and do not indicate any particular order.

[0269] Those skilled in the art will also know that, besides implementing the controller using purely computer-readable program code, the same functions can be achieved by logically programming the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0270] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, classes, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer-readable storage media, including storage devices.

[0271] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this specification can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of this specification can essentially be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, mobile terminal, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments of this specification.

[0272] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. This specification can be used in numerous general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable electronic devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices, etc.

[0273] Although this specification has been described by way of examples, those skilled in the art will recognize that many variations and modifications are possible without departing from the spirit of this specification, and it is intended that the appended claims cover such variations and modifications without departing from the spirit of this specification.

Claims

1. A method for allocating wave position resources, characterized in that, The method includes: Determine the first scheduling weight of each service in the M services corresponding to each user among N users, and obtain N*M first scheduling weights. The first scheduling weight is the demand intensity of the service corresponding to the user for the time slot resources in the corresponding wavelength position, where N and M are positive integers, N is the number of users, and M is the number of services. Based on the N*M first scheduling weights corresponding to each of the B wave positions within the target adjustment period, the second scheduling weight of each of the B wave positions is determined. The second scheduling weight is the demand intensity of the wave position for the time slot resources within the beam, where B is a positive integer and B is the number of wave positions. Determine the air interface load of each of the B wave positions within the target adjustment period; Based on the second scheduling weight and air interface load of each of the B wave positions, time slot resources are allocated to each of the B wave positions.

2. The method according to claim 1, characterized in that, The step of determining the second scheduling weight for each of the B wave positions based on the N*M first scheduling weights corresponding to each wave position within the target adjustment period includes: Based on the M first scheduling weights of the M services corresponding to each of the N users, determine the first uplink scheduling weight set and the first downlink scheduling weight set of each of the N users within the target adjustment period, and obtain N first uplink scheduling weight sets and N first downlink scheduling weight sets. Based on the N first uplink scheduling weight sets and N first downlink scheduling weight sets corresponding to each of the B wave positions, the first uplink scheduling weight and the first downlink scheduling weight of each of the B wave positions are determined respectively. Based on the fusion result of the first uplink scheduling weight and the first downlink scheduling weight of each of the B wave positions, the second scheduling weight of each of the B wave positions is determined.

3. The method according to claim 2, characterized in that, The target adjustment period includes Q scheduling periods, where Q is a positive integer and Q is the number of scheduling periods; The step of determining the first uplink scheduling weight set and the first downlink scheduling weight set for each of the N users within the target adjustment period, based on the M first scheduling weights of the M services corresponding to each of the N users, includes: Based on the M first scheduling weights of the M services corresponding to each of the N users in each of the Q scheduling cycles, determine the second uplink scheduling weight set and the second downlink scheduling weight set of each of the N users in the target adjustment period, and obtain N second uplink scheduling weight sets and N second downlink scheduling weight sets. The second uplink scheduling weight set and the second downlink scheduling weight set of each of the N users are sampled according to a preset sampling period to obtain the first uplink scheduling weight set and the first downlink scheduling weight set of each of the N users within the target adjustment period.

4. The method according to claim 3, characterized in that, The N*M first scheduling weights include M third uplink scheduling weights and M third downlink scheduling weights for the M services corresponding to each of the N users; each of the N sets of second uplink scheduling weights includes Q second uplink scheduling weights. Each of the N sets of second downlink scheduling weights includes Q second downlink scheduling weights; The method further includes: Based on the maximum third uplink scheduling weight among the M third uplink scheduling weights and the maximum third downlink scheduling weight among the M third downlink scheduling weights of the M services corresponding to each of the N users in each of the Q scheduling periods, the second uplink scheduling weight and the second downlink scheduling weight of each of the N users in each of the Q scheduling periods are determined respectively.

5. The method according to claim 2, characterized in that, The step of determining the first uplink scheduling weight and the first downlink scheduling weight for each of the B wave positions based on the N first uplink scheduling weight sets and the N first downlink scheduling weight sets corresponding to each wave position includes: Based on the average result of each first uplink scheduling weight set in the N first uplink scheduling weight sets of the N users corresponding to each of the B wave positions, and the average result of each first downlink scheduling weight set in the N first downlink scheduling weight sets of the N users corresponding to each of the B wave positions, the fourth uplink scheduling weight and the fourth downlink scheduling weight of each user in the N users corresponding to each of the B wave positions are determined respectively. Based on the average results of the N fourth uplink scheduling weights and the average results of the N fourth downlink scheduling weights corresponding to each of the B wave positions, the first uplink scheduling weight and the first downlink scheduling weight of each of the B wave positions within the target adjustment period are determined respectively.

6. The method according to claim 1, characterized in that, Determining the air interface load of each of the B wave positions within the target adjustment period includes: Obtain the uplink physical resource block utilization rate and downlink physical resource block utilization rate of each of the B wave positions within the target adjustment period; The load weight of each of the B wave positions is determined based on the fusion result of the uplink physical resource block utilization rate and the downlink physical resource block utilization rate of each wave position.

7. The method according to claim 1, characterized in that, Determining the air interface load of each of the B wave positions within the target adjustment period includes: Obtain the uplink physical resource block utilization rate and downlink physical resource block utilization rate of each of the B wave positions within the target adjustment period; Based on the comparison results of the uplink physical resource block utilization rate and the downlink physical resource block utilization rate of each of the B wave positions, the load weight of each of the B wave positions is determined.

8. The method according to claim 6 or 7, characterized in that, The step of allocating time slot resources to each of the B wave positions based on the second scheduling weight and air interface load of each wave position includes: Based on the coupling result of the second scheduling weight and the load weight of each of the B wave positions, the third scheduling weight of each of the B wave positions is determined. Based on the third scheduling weight of each of the B wave positions, time slot resources are allocated to each of the B wave positions.

9. The method according to claim 8, characterized in that, The step of allocating time slot resources to each of the B wave positions according to the third scheduling weight of each wave position includes: Find the first wave position with the largest third scheduling weight among the B wave positions; In the B wave positions, find multiple second wave positions where the difference between the third scheduling weight and the maximum third scheduling weight is greater than the difference threshold, and the difference between the time slot resource and the minimum time slot resource threshold is greater than or equal to the time slot resource unit. Find the third wave position with the smallest third scheduling weight among the plurality of second wave positions; Adjust the time slot resources of the first and third wave positions.

10. The method according to claim 9, characterized in that, The adjustment of the time slot resources of the first and third wavelengths includes: Increase the time slot resources of the first wave position by time slot resource units; Reduce the time slot resources of the third wave position by time slot resource units.

11. The method according to claim 1, characterized in that, The determination of the first scheduling weight of each service among the M services corresponding to each of the N users includes: Based on multiple preset Quality of Service (QoS) parameters, obtain the first scheduling weight of each service among the M services corresponding to each of the N users.

12. A wave position resource allocation device, characterized in that, The device includes: The first determining module is used to determine the first scheduling weight of each service in the M services corresponding to each user among N users, and obtain N*M first scheduling weights. The first scheduling weight is the demand intensity of the service corresponding to the user for the time slot resources within the corresponding wavelength. Here, N and M are positive integers, N is the number of users, and M is the number of services. The second determining module is used to determine the second scheduling weight of each of the B wave positions based on the N*M first scheduling weights corresponding to each wave position in the target adjustment period. The second scheduling weight is the demand intensity of the wave position for the time slot resources in the beam, where B is a positive integer and B is the number of wave positions. The third determining module is used to determine the air interface load of each of the B wave positions within the target adjustment period; The allocation module is used to allocate time slot resources to each of the B wave positions according to the second scheduling weight and air interface load of each wave position.

13. A computer device, characterized in that, include: The system includes a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to implement the wavelet resource allocation method according to any one of claims 1 to 11.

14. A computer storage medium, characterized in that, The computer storage medium stores computer program instructions, which, when executed, implement the steps of the wavelet resource allocation method according to any one of claims 1 to 11.

15. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the steps of the wavelet resource allocation method according to any one of claims 1 to 11.

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