CN112994778B - High-throughput satellite beam adaptive scheduling method based on service priority - Google Patents
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Abstract
The invention discloses a high-throughput satellite beam on-demand scheduling method based on service priority and rate self-adaptation, which comprises the following steps: measuring the service flow and channel capacity of each beam cell in a downlink scene of the low-orbit high-throughput satellite system; establishing a nested optimization problem of a maximized adaptive rate adjustment factor and a maximized system throughput according to the obtained data, and dynamically allocating the adaptive rate adjustment factor and the beam service time of each cell by taking average residence time and the number of beams as constraints; and finally, when spare beams exist, selecting the cell with co-frequency interference to provide service according to the minimum co-frequency interference cost function. The method solves the problem of resource waste of a preset full coverage mode in a downlink scene of a low-orbit high-throughput satellite system, and can cover a plurality of cells by using a small amount of wave beams in a time division multiplexing mode.
Description
Technical Field
The invention relates to the technical field of satellite communication, in particular to a high-throughput satellite beam on-demand scheduling method based on service priority and rate self-adaption.
Background
In recent years, the traditional communication satellite cannot meet the increasing demands of terrestrial broadband high-speed data service flow and all-weather seamless access, and the development of high-throughput satellites is promoted by the demand of high-speed satellite communication. Different from the larger single beam coverage of the traditional communication satellite, the high-throughput satellite simply and efficiently generates a plurality of small-coverage-range high-gain spot beams by using a hybrid precoding technology, and greatly enhances the channel capacity and the service quality of a satellite-to-spot communication link. In addition, the high-flux multi-beam satellite also introduces a frequency multiplexing and polarization multiplexing technology between point beams, and service beams with different frequencies and polarizations are provided for adjacent beam cells, so that the co-frequency interference between the beams is reduced, and the received signal-to-interference-and-noise ratio and the service quality are improved while the full coverage of the beams is completed. At present, a high-flux multi-beam satellite is already applied to a high-orbit satellite to a certain extent, and under the trend that the satellite and 5G are fused, the high-flux satellite is further combined with a low-orbit satellite, so that all-weather seamless ultra-wideband communication service is provided for users.
However, in the low orbit satellite scenario, the existing predefined full coverage mode of the high flux satellite has a series of problems:
problem 1: the ground service flow distribution has large tailing and quick change, which leads to the reduction of the energy efficiency of the system.
In a traditional high-orbit high-flux satellite scene, the coverage area of each beam cell under the satellite is large, the change is small, the service flow of each beam cell can be approximately regarded as poisson distribution, and in a low-orbit satellite scene, the coverage area of each beam cell is small, the service flow fluctuation is more severe, and the service flow distribution tailing is more serious. In addition, the low-orbit satellite has a high overhead speed of about 7.9km/s, the effective service time is not more than 10 minutes, and the low-orbit high-throughput satellite needs to rapidly serve a plurality of cells with different service flow requirements. If the conventional predetermined full coverage mode is applied to uniformly distribute the beams, it will result in the energy of the beams in some low traffic cells being wasted or some high traffic cells being not adequately served.
Problem 2: the use of frequency reuse techniques for the intended full coverage reduces the spectral efficiency of the system.
In a conventional predetermined full coverage mode, co-channel interference between beams is reduced by using a frequency reuse technology, but frequency reuse is equivalent to dividing the whole bandwidth of a satellite into a plurality of sub-frequency bands for reuse, and generally uses 'several-color reuse' to represent how many frequency bands are divided in a system, such as 'three-color reuse' and 'four-color reuse', and the larger the reused 'color number' is, the farther the cell interval of the same frequency is, the smaller the co-channel interference is. However, once frequency multiplexed, this means that the bandwidth of the beam must be limited, and the larger the "number of colors" multiplexed, the smaller the bandwidth allocated to the beam, thereby reducing the spectral efficiency and throughput of the system.
Problem 3: the ground service types are different, and the problems of service sequence and priority exist.
There are many service types in 5G communication, taking live broadcast service and broadband data transmission service as examples, the key of live broadcast service is uninterrupted, and data transmission can tolerate a certain interruption through edge cache. The traditional predetermined full coverage mode cannot dynamically allocate service time according to the service priority and the current channel state, which may cause interruption of live broadcast service due to failure of priority service or serious shortage of data transmission service rate.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the related art.
Therefore, the invention aims to provide a high-throughput satellite beam on-demand scheduling method based on service priority and rate self-adaptation.
In order to achieve the above object, an embodiment of the present invention provides a high throughput satellite beam on-demand scheduling method based on service priority and rate adaptation, including the following steps: step S1, measuring the service distribution of each cell on the ground of the current time slot in the downlink scene of the low-orbit high-flux satellite system and the downlink channel capacity of the satellite of the current time slot; step S2, establishing a nested optimization problem of maximized adaptive rate adjustment factor and maximized system throughput according to the service distribution of each cell on the ground of the current time slot and the downlink channel capacity of the satellite of the current time slot, and dynamically allocating the adaptive rate adjustment factor and the beam service time of each cell by taking average residence time and the number of beams as constraints; and step S3, according to the beam service time, preferentially distributing high priority service, secondly distributing beam cells without co-frequency interference based on the longest queue principle, and finally selecting the cells with co-frequency interference to provide service according to the minimum co-frequency interference cost function when there is spare beams.
The high-throughput satellite beam on-demand scheduling method based on service priority and rate adaptation of the embodiment of the invention dynamically allocates adaptive rate adjustment factors and beam service time of each cell with the aim of maximizing system throughput according to service flow and channel capacity of each beam cell of a satellite; further, according to the determined beam service time of each cell, a beam scheduling mode at each moment is selected by taking a minimum same frequency interference cost function as a target, and beam allocation as required is completed; therefore, the problem of resource waste of a preset full coverage mode in a downlink scene of a low-orbit high-throughput satellite system is solved, and a plurality of cells can be covered by a small number of beams in a time division multiplexing mode.
In addition, the service priority and rate adaptation-based high-throughput satellite beam on-demand scheduling method according to the above embodiment of the present invention may further have the following additional technical features:
further, in an embodiment of the present invention, the step S2 specifically includes: step S201, respectively establishing a first optimization problem of a maximized adaptive rate adjustment factor and a second optimization problem of a maximized system throughput according to the service distribution of each cell on the ground of the current time slot and the downlink channel capacity of the satellite of the current time slot; step S202, the first optimization problem is restrained according to the average lingering time and the number of the wave beams, and the minimum value of the maximized self-adaptive rate adjustment factor is solved; step S203, constraining the second optimization problem by the minimum value of the average dwell time, the number of beams, and the maximized adaptive rate adjustment factor, and solving an optimal beam service time.
Further, in one embodiment of the invention, the average dwell time W of the n beam cells s n Comprises the following steps:
wherein, G n Serving time of beam for n cells, C n Is the channel capacity of n cells, A rn Adaptive rate adjustment factor, T, for n cells n And tau is the specified minimum average linger time for the n cell service distributions on the ground of the current time slot.
Further, in an embodiment of the present invention, an expression for constraining by using the number of beams is as follows:
where K is the number of beams, G i Serving time for the beam of the ith cell.
Further, in one embodiment of the present invention, the first optimization problem is expressed in the form of:
max η
s.t.(1)，(2)
A rn ≤η，n＝1，…，N
where η is the maximized adaptive rate adjustment factor A r Minimum value of (A) rn Is the adaptive rate adjustment factor for n cells.
Further, in an embodiment of the present invention, when constraining the second optimization problem, first, according to an adaptive rate adjustment factor and the service distribution of each cell on the ground of the current timeslot, a maximized system equivalent throughput is obtained as
Further, in one embodiment of the present invention, the second optimization problem is expressed in the form of:
max TP
s.t.(1)，(2)
A rn ≤η，m＝1，…，N
Wherein TP is the maximized system equivalent throughput, A rn Is the adaptive rate adjustment factor for n cells.
Further, in an embodiment of the present invention, the step S3 specifically includes:
step S301, determining a service sequence, wherein cells needing uninterrupted service, such as a live broadcast service cell, are set as high-priority beam cells, and other beam cells are set as secondary-priority beam cells;
step S302, adding the high priority beam cell into a beam mode for service;
step S303, adding the co-frequency interference cells in the allocated beam cells into an interference cell list for updating;
step S304, eliminating the beam cells in the same frequency interference cell list, adding the secondary priority beam cell into a beam mode for service, and iteratively executing step S303 until all the remaining beam cells are the same frequency interference cells;
step S305, if there are still vacant beams, the same frequency interference cost function will be used
Serving the beam cell with the least system influence, and iteratively executing the steps S303 to S304 until no idle beam exists.
Further, in an embodiment of the present invention, the co-channel interference cost function f c n The calculation formula of (2) is as follows:
wherein the content of the first and second substances,
for the frequency of cell n in the co-channel interfering cell list,
the service time remains for cell n.
Further, in an embodiment of the present invention, the method further includes:
and when the residual service is less than the number of spot beams, pointing the idle beam to the satellite with the highest current service sequence, and expanding the channel capacity of the beam through multiple coverage.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic diagram of a low-orbit high-throughput satellite beam on-demand scheduling scenario;
FIG. 2 is a flow chart of a method for high throughput satellite beam on-demand scheduling based on service priority and rate adaptation according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating the result of adaptive rate adjustment factor assignment according to one embodiment of the present invention;
FIG. 4 is a diagram illustrating the result of beam service time allocation according to one embodiment of the present invention;
fig. 5 is a schematic diagram of the 15 th beam allocation pattern of the 28 beam patterns according to an embodiment of the present invention;
Fig. 6 is a flow chart of beam allocation based on traffic priority and inter-beam interference according to an embodiment of the present invention;
fig. 7 is a diagram illustrating throughput gain and inter-beam interference suppression obtained by comparing the present application with the conventional beam allocation scheme.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The proposed service priority and rate adaptation based high-throughput satellite beam on-demand scheduling method according to the embodiments of the present invention is described below with reference to the accompanying drawings.
First, parameters used in the embodiment of the present invention are defined and explained, as shown in fig. 1, a low-orbit high-throughput satellite beam on-demand scheduling scenario is considered, the number of beam cells is denoted as N, and the number of satellite downlink service beams is denoted as K. The service distribution T of each cell on the ground of the current time slot is known by the control channel of the satellite 1×N ＝{T 1 ,T 2 ,…T n ,…T N In units of Mbit s -1 Current time slot satellite downlink channel capacity C 1×N ＝{C 1 ,C 2 ,…C n ,…C N In Mbit s -1 . In order to solve the problem of transmission interruption caused by the fact that the service flow of the ground cell is larger than the channel capacity, an adaptive rate adjustment factor is introduced
A rn ∈(0,1]Such as A rn If 1, it means that the service can be served at full rate, if a rn <A 1 indicates that the channel condition is not good or the traffic flow is too large. The beam scheduling result of the current time slot is G 1×N ＝{G 1 ,G 2 ,…G n ,…G N In which G is n ∈(0,1]The physical meaning is the ratio of the beam occupied by the cell n to the current time slot length, if G n 1 means that cell n always occupies a beam in the current timeslot, and if G is equal to 1 n <A 1 then indicates that cell n has not been served during the current time slot.
Further, as shown in fig. 2, the method for scheduling high-throughput satellite beams on demand based on service priority and rate adaptation includes the following steps:
in step S1, the traffic distribution of the terrestrial cells of the current time slot and the capacity of the satellite downlink channel of the current time slot in the downlink scenario of the low-earth high-throughput satellite system are measured.
That is, the service distribution T of each cell on the ground of the current time slot in the downlink scene of the low-orbit high-throughput satellite system and the downlink channel capacity C of the satellite of the current time slot are measured.
In step S2, a nested optimization problem of the maximized adaptive rate adjustment factor and the maximized system throughput is established according to the service distribution of each cell on the ground of the current time slot and the downlink channel capacity of the satellite of the current time slot, and the adaptive rate adjustment factor and the beam service time of each cell are dynamically allocated with the average residence time and the number of beams as constraints.
Further, in an embodiment of the present invention, step S2 specifically includes:
step S201, respectively establishing a first optimization problem of a maximized self-adaptive rate adjustment factor and a second optimization problem of a maximized system throughput according to the service distribution of each cell on the ground of the current time slot and the downlink channel capacity of a satellite of the current time slot;
step S202, constraining the first optimization problem by the average lingering time and the number of beams, and solving the minimum value of the maximized adaptive rate adjustment factor;
step S203, the second optimization problem is constrained by the minimum value of the average dwell time, the number of beams and the maximized adaptive rate adjustment factor, and the optimal beam service time is solved.
Specifically, a first optimization problem is first established: maximizing adaptive rate adjustment factor a r To ensure cell fairness.
In the embodiment of the invention, the adaptive rate adjustment factor A of the system r Between 0 and 1, the adaptive rate adjustment factor A is clearly present r The larger the system throughput. But for the cell n with better channel state, the adaptive rate adjustment factor A rn Larger, for the cell with poor channel state, its A rn Smaller, even 0. Therefore, the adaptive rate adjustment factor A is needed to be considered for the fairness of each beam cell r Is constrained so that in the first optimization problem, the goal is to maximize the adaptation rate adjustment factor a r Is measured.
In the first optimization problem, another key index of the system, the average residence time W, is required s Constrained, average dwell time W for n beam cells s n Comprises the following steps:
wherein G is n Serving time of beam for n cells, C n Is the channel capacity of n cells, A rn Is self of n cellsAdaptation rate adjustment factor, T n And tau is the specified minimum average linger time for the n cell service distributions on the ground of the current time slot.
In addition, the expression that the number of beams is used for constraint is as follows:
where K is the number of beams, G i Serving time for the beam of the ith cell.
The first optimization problem is then expressed in the form of:
max η
s.t.(1)，(2)
A rn ，≤η，n＝1，…，N
where η is the maximized adaptive rate adjustment factor A r The result of the first optimization problem, as shown in fig. 3 and 4, can solve the adaptive rate adjustment factor a of the maximized system throughput r And beam service time G, A rn Is the adaptive rate adjustment factor for n cells.
Second, a second optimization problem is established: maximized system throughput.
The factor A may be adjusted according to the adaptation rate while constraining the second optimization problem r The service distribution T of each cell on the ground of the current time slot is obtained, and the maximized system equivalent throughput is obtained as
Wherein the content of the first and second substances,
is the hadamard product of the vectors.
The second optimization problem is then expressed in the form of:
max TP
s.t.(1)，(2)
A rn ≤η，n＝1，…，N
wherein TP is the maximized systemUnified equivalent throughput, A rn Is the adaptive rate adjustment factor for n cells.
In step S3, according to the beam service time, a high priority service is preferentially allocated, then a beam cell without co-channel interference is allocated based on the longest queue principle, and finally, when there is a spare beam, a cell with co-channel interference is selected according to the minimum co-channel interference cost function to provide service.
In other words, each cell occupies the beam time according to the next time slot determined in step S2, and then the beam allocation pattern of each sub-slot needs to be selected according to the service optimization level, the queuing length, and the inter-beam interference.
Further, in an embodiment of the present invention, step S3 specifically includes:
step S301, determining a service sequence, wherein a cell requiring uninterrupted service is set as a high priority beam cell, and other beam cells are set as secondary priority beam cells.
Specifically, in a low-orbit high-throughput satellite scene, different priorities are allocated for different services, such as a live broadcast service and a broadband data transmission service, and the priority of the live broadcast service is higher. And then, aiming at a plurality of tasks with low priority, the cells without co-channel interference and long service time are preferentially distributed.
Step S302, adding the high priority beam cell into the beam mode for service to prevent the burst service from interrupting the high priority service, wherein the main objective is to ensure the continuous service of the service, so the co-frequency interference between the high priority beam cells can be temporarily disregarded.
Step S303, adding the co-channel interference cells in the allocated beam cells to the interference cell list for updating.
And step S304, eliminating the beam cells in the co-frequency interference cell list, adding the sub-priority beam cells into a beam mode for service, and iteratively executing the step S303 until all the remaining beam cells are the co-frequency interference cells.
Step S305, if there are still vacant beams, the vacant beams will be selected according to the same frequency interference cost function f c n Serving the beam cell with the minimum system influence, and iteratively executing the steps S303 to S304 until no idle beam exists, wherein the same frequency interference cost function f c n The calculation formula of (c) is:
wherein the content of the first and second substances,
for the frequency of cell n in the co-channel interfering cell list,
the service time remains for cell n.
Further, as shown in fig. 5, the method further includes: and when the residual service is less than the number of spot beams, pointing the idle beam to the satellite with the highest current service sequence, and expanding the channel capacity of the beam through multiple coverage.
As shown in fig. 6, the specific work flow of step S3 in the embodiment of the present invention is:
firstly, judging whether a beam to be distributed of the rest service exists, if so, adding a high-priority beam cell into a beam mode for service, if so, adding the high-priority beam cell into the beam mode, updating an interference cell list and the service to be distributed, iterating the process until the high-priority service does not exist in the service to be distributed, and then starting to distribute the low-priority service;
when entering low-priority service distribution, judging whether cells without same frequency interference and with long service time in the service to be distributed are not in an interference cell list or not, if not, adding the cells without same frequency interference and with long service time into a beam mode, updating the interference cell list and the service to be distributed again, iterating the process until the cells without same frequency interference and with long service time are in the interference cell list, and starting to distribute the same frequency interference cells;
When the same frequency interference cell distribution is entered, firstly judging whether an idle beam exists or a service to be distributed exists, if so, selecting a cell with the minimum same frequency interference cost function, adding the cell into a beam mode, meanwhile, updating an interference cell list and the service to be distributed, iterating the process until no idle beam exists or no service to be distributed exists, and entering a beam distribution generation mode;
when entering a beam generation distribution mode, judging whether the number of service cells is smaller than the number of spot beams, if not, a plurality of beams serve one cell, preferentially serve the cell with large service volume, if the number of the cells is less than half of the number of the beams, service of all the rest cells is completed in the mode, and the beam occupation time minus the minimum service volume in the beam mode is updated to be used as new beam occupation time; if not, directly updating the beam occupation time minus the minimum service volume in the beam mode as the new beam occupation time;
and after the occupied time of the wave beam is updated, distributing the finally updated service to be distributed, and iterating the process until all the distributed services complete the service.
The service priority and rate adaptation-based high-throughput satellite beam on-demand scheduling method proposed by the present invention is further described below by a specific embodiment.
In order to verify the performance advantage of the proposed beam splitting scheme, the Monte Carlo simulation results of the beam splitting scheme and the traditional beam splitting scheme are compared and analyzed under different ground flow intensity coefficients M. The parameters in the computational simulation process are shown in the following table:
the method used by the Monte Carlo simulation is to randomly generate the traffic distribution of the ground service and the capacity distribution of the ground channel of the satellite, then to count the throughput gain and the interference suppression between beams obtained by the proposed beam distribution scheme compared with the traditional beam distribution scheme in each simulation, and to average the statistical results, the result in the simulation figure 7 can be obtained.
The results of fig. 7 demonstrate that the proposed beam allocation scheme works well under different ground traffic loads, and is superior to the conventional beam allocation scheme in terms of both throughput and inter-beam interference.
To sum up, the high-throughput satellite beam on-demand scheduling method based on service priority and rate adaptation provided by the embodiment of the present invention can adaptively adjust the ground service rate with a goal of maximizing system throughput based on variable ground service traffic and satellite-ground channel capacity, and allocate the time of each beam cell occupying a beam, thereby improving the energy efficiency of the system, for example, when the ground traffic intensity coefficient M is 2, the throughput of the beam on-demand scheduling method of the present invention is improved by 17.91% compared with the existing predetermined full coverage method; under the condition that the frequency reuse factor is 1, compared with the opportunity beam scheduling without the minimum co-frequency interference beam distribution, the co-frequency interference is reduced by 25.55 percent; meanwhile, the priority service of high-priority services such as live broadcast and switching is ensured, which cannot be realized by a preset full-coverage mode.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (6)
1. A high-throughput satellite beam on-demand scheduling method based on service priority and rate adaptation is characterized by comprising the following steps:
step S1, measuring the service distribution of each cell on the ground of the current time slot in the downlink scene of the low-orbit high-flux satellite system and the downlink channel capacity of the satellite of the current time slot;
step S2, establishing a nested optimization problem of maximized adaptive rate adjustment factor and maximized system throughput according to the service distribution of each cell on the ground of the current time slot and the downlink channel capacity of the satellite of the current time slot, and dynamically allocating the adaptive rate adjustment factor and the beam service time of each cell by taking average residence time and the number of beams as constraints;
and step S3, according to the beam service time, preferentially distributing high priority service, secondly distributing beam cells without co-frequency interference based on the longest queue principle, and finally selecting the cells with co-frequency interference to provide service according to the minimum co-frequency interference cost function when there is spare beams.
2. The method for on-demand scheduling of high-throughput satellite beams based on service priority and rate adaptation according to claim 1, wherein the step S2 specifically includes:
step S201, respectively establishing a first optimization problem of a maximized adaptive rate adjustment factor and a second optimization problem of a maximized system throughput according to the service distribution of each cell on the ground of the current time slot and the downlink channel capacity of the satellite of the current time slot;
step S202, the first optimization problem is restrained according to the average lingering time and the number of the wave beams, and the minimum value of the maximized self-adaptive rate adjustment factor is solved;
step S203, constraining the second optimization problem by the minimum value of the average dwell time, the number of beams, and the maximized adaptive rate adjustment factor, and solving an optimal beam service time.
3. The method of on-demand scheduling for high throughput satellite beams based on service priority and rate adaptation of claim 2 wherein the average dwell time of n beam cells
Comprises the following steps:
wherein G is n Serving time of beam for n cells, C n Is the channel capacity of n cells, A rn Adaptive rate adjustment factor, T, for n cells n And tau is the specified minimum average linger time for the n cell service distributions on the ground of the current time slot.
4. The method of claim 2, wherein the second optimization problem is constrained by first obtaining a maximum system equivalent throughput as follows according to adaptive rate adjustment factors and the traffic distribution of each cell on the ground during the current timeslot
Wherein, A r For the adaptive rate adjustment factor vector for each cell on the ground,
is the Hadamard product of the vector, and T is the service distribution of each cell on the ground at the current time slot.
5. The method for on-demand scheduling of high-throughput satellite beams based on service priority and rate adaptation according to claim 1, wherein the step S3 specifically includes:
step S301, determining a service sequence, wherein a cell needing uninterrupted service is set as a high-priority beam cell, and other beam cells are set as secondary-priority beam cells;
step S302, adding the high priority beam cell into a beam mode for service;
step S303, adding the co-frequency interference cells in the allocated beam cells into an interference cell list for updating;
Step S304, eliminating the beam cells in the same frequency interference cell list, adding the secondary priority beam cell into a beam mode for service, and iteratively executing step S303 until all the remaining beam cells are the same frequency interference cells;
step S305, if there are still vacant beams, the same frequency interference cost function will be used
Serving the beam cell with the minimum system influence, and iteratively executing the steps S303 to S304 until no idle beam exists, wherein the co-channel interference cost function
The calculation formula of (2) is as follows:
wherein the content of the first and second substances,
for the frequency of cell n in the co-channel interfering cell list,
the service time remains for cell n.
6. The method for on-demand scheduling of high-throughput satellite beams based on service priority and rate adaptation according to claim 5, further comprising:
and when the residual service is less than the number of spot beams, pointing the idle beam to the satellite with the highest current service sequence, and expanding the channel capacity of the beam through multiple coverage.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN111555799A (en) * | 2020-05-20 | 2020-08-18 | 清华大学 | Double-layer resource allocation method and system for broadband phased array satellite |
| CN111769865A (en) * | 2020-05-08 | 2020-10-13 | 中国科学院计算技术研究所 | Resource management method based on satellite-ground cooperative processing |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| US8805275B2 (en) * | 2012-06-11 | 2014-08-12 | Viasat Inc. | Robust beam switch scheduling |
| CN105245265B (en) * | 2014-06-20 | 2021-01-01 | 中兴通讯股份有限公司 | User service mode selection method under 3D wave beam, pilot frequency information sending method and device |
| CN107124726B (en) * | 2017-04-28 | 2020-04-10 | 北京邮电大学 | Multi-beam GEO system access control method based on maximized throughput |
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| CN110278024B (en) * | 2019-08-07 | 2020-07-24 | 清华大学 | System capacity optimization method and device for satellite communication constellation |
| CN110996394B (en) * | 2019-12-12 | 2022-07-29 | 南京邮电大学 | Satellite communication system resource scheduling method combining beam hopping and precoding |
| CN111163520A (en) * | 2019-12-27 | 2020-05-15 | 东方红卫星移动通信有限公司 | Dynamic resource allocation method of low-earth-orbit satellite communication system |
| CN112243254B (en) * | 2020-10-08 | 2021-04-30 | 军事科学院***工程研究院网络信息研究所 | Adaptive access control method for satellite-ground integrated communication |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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| CN111769865A (en) * | 2020-05-08 | 2020-10-13 | 中国科学院计算技术研究所 | Resource management method based on satellite-ground cooperative processing |
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