CN111641450B - Satellite-ground integrated network communication and cache resource joint scheduling method - Google Patents
Satellite-ground integrated network communication and cache resource joint scheduling method Download PDFInfo
- Publication number
- CN111641450B CN111641450B CN202010487336.0A CN202010487336A CN111641450B CN 111641450 B CN111641450 B CN 111641450B CN 202010487336 A CN202010487336 A CN 202010487336A CN 111641450 B CN111641450 B CN 111641450B
- Authority
- CN
- China
- Prior art keywords
- ground
- satellite
- base station
- user
- optimization scheme
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/1853—Satellite systems for providing telephony service to a mobile station, i.e. mobile satellite service
- H04B7/18539—Arrangements for managing radio, resources, i.e. for establishing or releasing a connection
- H04B7/18543—Arrangements for managing radio, resources, i.e. for establishing or releasing a connection for adaptation of transmission parameters, e.g. power control
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/1853—Satellite systems for providing telephony service to a mobile station, i.e. mobile satellite service
- H04B7/18539—Arrangements for managing radio, resources, i.e. for establishing or releasing a connection
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/1853—Satellite systems for providing telephony service to a mobile station, i.e. mobile satellite service
- H04B7/18569—Arrangements for system physical machines management, i.e. for construction operations control, administration, maintenance
- H04B7/18573—Arrangements for system physical machines management, i.e. for construction operations control, administration, maintenance for operations control, administration or maintenance
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/535—Allocation or scheduling criteria for wireless resources based on resource usage policies
Abstract
The invention discloses a satellite-ground integrated network communication and cache resource joint scheduling method, which mainly solves the problems of low system combining rate and low user capacity in the prior art. The scheme is as follows: constructing a satellite-ground integrated network communication and cache resource joint scheduling optimization scheme; decoupling the joint scheduling optimization scheme into an independent ground network resource scheduling optimization scheme and a satellite network resource scheduling optimization scheme by utilizing Lagrange relaxation; and in each discrete time slot, respectively carrying out optimal resource scheduling on the ground network resource scheduling optimization scheme and the satellite network resource scheduling optimization scheme according to the current link state and the wireless access link transmission content information. The method solves the non-convexity and satellite-ground return capacity coupling constraint of satellite-ground integrated network communication and cache resource joint scheduling under the condition of cache limitation, has low complexity and flexible network demand target adjustment, and can be used for a ground network with cache limitation and heterogeneous systems of different satellite constellation networks.
Description
Technical Field
The invention belongs to the technical field of communication, and particularly relates to a resource scheduling method which can be used for radio resource management and control under a satellite-ground integrated network with limited cache.
Background
In recent years, the demand for wireless mobile data traffic has shown an exponential growth trend, and conventional terrestrial communication networks cannot guarantee wide coverage of the network due to limitation to scarce land resources, while considering that it is impractical to equip each cell with an optical fiber or a stable wireless backhaul link, and thus the limited terrestrial backhaul capacity greatly affects network performance. Fortunately, the breakthrough advances made in low earth orbit satellite network systems in recent years have provided an effective alternative to communication coverage extension and stable backhaul connections by deploying ultra-dense constellations and cooperating with legacy networks to support seamless and high capacity communication services. Particularly, when a satellite terrestrial integrated network STIN comes into sight of people, the whole network can effectively merge ultra-dense low-earth orbit satellites with a traditional terrestrial network. The ultra-dense low-earth orbit satellite provides a high-capacity satellite backhaul for a ground base station by utilizing a high-frequency Ka/Ku frequency band, so that more ground users can access a network to enjoy high-quality communication service.
Although the capacity of the backhaul can be greatly increased by introducing the satellite technology, the network performance is still limited by the backhaul link and network congestion is easily generated as the number of users increases, and the satellite backhaul still has difficulty in supporting future huge service demands. Research has shown that most of people's service requests tend to focus on a small portion of the content, and these service requests reuse scarce backhaul resources. Based on this phenomenon, the caching mechanism is considered as an effective technology for solving the requirement of huge flow. By storing the content with high popularity in the local base station, a plurality of user requests are directly satisfied in the associated base station without passing through backhaul resources, so that the pressure of a backhaul link can be effectively relieved, the transmission delay of the user is greatly reduced, and the user experience is improved. Since user association and resource allocation in the cache network have great significance for saving backhaul resources, many scholars have been devoted to research on resource scheduling methods in the ground cache network in recent years, and have had many mature research results. Much research is devoted to maximizing network throughput and saving backhaul resources as much as possible by finding the best resource scheduling method under the limited resource constraint. The advantages of the comprehensive caching mechanism and the satellite ground comprehensive network are combined into a whole, and the comprehensive caching mechanism and the satellite ground comprehensive network become a new research enthusiasm. On one hand, a high-capacity satellite backhaul link is introduced to provide more stable wireless access for ground users; on the other hand, the cache is added in the ground network, so that the pressure of the return resources of the satellite can be effectively relieved, and the access amount is further increased to realize wide-area coverage.
Current research on this new architecture focuses mainly on how to improve the caching mechanism to maximize the gain that the architecture brings. However, in the satellite-terrestrial integrated network allowing caching, because of the different idealized or fixed backhaul capacity considered by the terrestrial network, the user association and resource allocation relationship in this scenario have an important impact on improving the network performance, but related research has not fully characterized the same. Due to the multiple connectivity between terrestrial base stations and satellites, researchers are no longer considering idealized or fixed backhaul capacity in terrestrial networks, but rather select different satellites for association by a terrestrial base station to obtain dynamically changing satellite backhaul capacity. This approach greatly increases the capacity of the satellite backhaul, but also brings new challenges to the design of the resource scheduling method: (1) the problem of user association in the current network is not only the problem of association between a ground base station and a user, but also the problem of association between a ground base station and a satellite coupled with the ground base station. (2) The design of the resource scheduling method in the current network also needs to fully consider the characteristics of satellite communication, for example, the satellite communication is affected by propagation delay caused by long-distance transmission while having a high-capacity backhaul link; the angular spacing that exists between different satellite-to-ground links can have an effect on the interference between the links.
In view of the above difficulties in the above scenario, the conventional resource scheduling method of the ground network cannot be directly used for resource scheduling in the scenario, and meanwhile, research related to the resource scheduling problem in the scenario is also deficient. Therefore, how to design the resource scheduling method efficiently under the satellite terrestrial integrated network with limited cache is very important.
Disclosure of Invention
The invention aims to provide a satellite-ground integrated network communication and cache resource joint scheduling method aiming at the characteristics of the scene and the limitations of the traditional technology, so as to give full play to the potential gains brought by the fusion of a ground cache mechanism and a satellite-ground integrated network and further improve the resultant rate and the user capacity of the system.
The technical idea of the invention is as follows: decoupling a communication and cache resource combined scheduling optimization scheme under a satellite-ground integrated network with limited cache by using a Lagrange relaxation method, and decomposing the scheme into resource scheduling optimization schemes of two independent networks; and iteratively updating the Lagrangian operator to realize the optimal network resource scheduling of the two network resource scheduling optimization schemes. The method comprises the following specific steps:
(1) constructing a satellite-ground integrated network communication and cache resource joint scheduling optimization scheme by taking the maximum system resultant rate and user capacity as targets under the constraint of cache limited conditions and satellite-ground backhaul capacity coupling; two different optimization objectives are used in this scheme: the system synthesis rate and the user capacity are used for balancing the user service quality and the network coverage demand under the satellite-ground integrated network, the tendency of the current scheme to two targets is represented by a discount factor, and a larger discount factor indicates that the current scheme is more inclined to maximize the system user capacity;
(2) decoupling the joint scheduling optimization scheme in the step (1) into an independent ground network resource scheduling optimization scheme and a satellite network resource scheduling optimization scheme by using a Lagrange relaxation method;
(3) in each discrete time slot, respectively carrying out optimal resource scheduling on the ground network resource scheduling optimization scheme and the satellite network resource scheduling optimization scheme according to the current link state and the wireless access link transmission content information:
3a) initializing a Lagrangian operator at the beginning of each discrete time slot;
3b) based on a given Lagrange operator, realizing an optimal wireless resource allocation decision for a ground network resource scheduling optimization scheme according to a ground link state and wireless access link transmission content information;
3c) realizing an optimal wireless resource allocation decision for the satellite network resource scheduling optimization scheme according to the satellite-ground link state;
3d) if the resource allocation results of the two networks cannot guarantee the satellite-ground return capacity coupling constraint after decision, removing the users one by one according to the ascending sequence of the ground user rate until the constraint is met;
3e) and iteratively updating the Lagrangian operator after decision making, so that the resource scheduling result after decision making continuously approaches to the real optimal result.
Compared with the prior art, the invention has the following advantages:
firstly, two optimization targets of system resultant rate and user capacity are comprehensively considered in the construction of a satellite-ground integrated network communication and cache resource joint scheduling optimization scheme, so that the user service quality and the network coverage requirement under a satellite-ground integrated network are balanced; simultaneously using a discount factor to represent the tendency of the current scheme to two different targets, wherein a larger discount factor indicates that the current scheme is more inclined to maximize the capacity of a system user; in the process of realizing the resource scheduling optimization scheme, the network requirement of the satellite-ground integrated network dynamic change can be met by flexibly adjusting the discount factor.
Secondly, the joint scheduling optimization scheme is decoupled into the independent ground network resource scheduling optimization scheme and the satellite network resource scheduling optimization scheme by adopting the Lagrange relaxation method, so that the non-convexity of the communication and cache resource joint scheduling optimization scheme under the satellite-ground integrated network with limited cache and satellite-ground backhaul capacity coupling constraint which is difficult to process are effectively solved, and meanwhile, compared with the optimal result, the system performance loss is only less than 1%.
Thirdly, the invention can simply and flexibly divide the ground users with different target requirements for the wireless resource allocation decision of the ground network resource scheduling optimization scheme, and ensures that the requirements of each type of users are met as much as possible through a high-efficiency resource allocation algorithm. Experimental results show that the resource scheduling decision can bring better system performance especially when the cache condition is severely limited.
Fourthly, the wireless resource allocation decision of the satellite network resource scheduling optimization scheme vividly describes the multi-connection relationship between satellite-ground links and the off-axis antenna gain in satellite communication as a many-to-one matching model with external conditions, and combines a matching theory and a classical Galer-Shapril matching algorithm to realize the maximum gain of the satellite return capacity under the satellite-ground integrated network. Experimental results show that the resource scheduling decision can provide stable satellite backhaul capacity under different satellite constellations, and can give full play to huge gains brought by multiple connectivity.
Drawings
FIG. 1 is a flow chart of an implementation of the present invention;
FIG. 2 is a diagram of a network scenario used in the present invention;
FIG. 3 is a flow chart of a radio resource allocation decision making sub-process performed in the present invention for a ground network resource scheduling optimization scheme;
FIG. 4 is a flow chart of a radio resource allocation decision making sub-process performed in the present invention for a satellite network resource scheduling optimization scheme;
FIG. 5 is a diagram of simulation results of system aggregate rate and user capacity under different cache constraints according to the present invention;
FIG. 6 is a diagram showing simulation results of the total capacity of the satellite backhaul varying with the number of satellites in different multi-connection relationships of the satellite-ground link according to the present invention; wherein fig. 6(a) is a graph showing the simulation results of the total capacity of the return trip of the satellite as a function of the number of satellites in the case where the base station allows access to only one satellite; FIG. 6(b) is a diagram showing the simulation results of the total capacity of the satellite backhaul varying with the number of satellites in the case where the base station allows access to two satellites;
FIG. 7 is a graph of simulation results for two objectives in an optimization scheme of the present invention under different discounting factors.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The following detailed description of the principles of the invention is provided in connection with the accompanying drawings.
The satellite-ground integrated network scenario considered by the present invention is as shown in fig. 2: the low earth orbit satellite provides high-capacity satellite return for the ground base station through the high-frequency Ka frequency band to realize the demand of more ground users, wherein:
the low earth orbit satellite set is S { (SAT)s),s＝1,...,NSAT}，SATsRepresenting the s-th low-earth orbit satellite, s being taken from 1 to NSAT，NSATFor low earth orbitThe number of stars;
the set of base stations is M { (SBS)m),m＝1,...,NSBS}，SBSmDenotes the mth base station, m is taken from 1 to NSBS，NSBSIs the number of base stations;
the set of ground users is J { (user)j),j＝1,...,Nuser}，userjRepresenting the jth terrestrial user, j taking N from 1user，NuserThe number of users on the ground;
the set of ground link sub-channels is K { (C-sub {)k),k＝1,...,NK}，C-subkRepresenting the kth terrestrial link subchannel, k being taken from 1 to NK，NKThe number of sub-channels of the ground link;
the set of satellite-to-ground link sub-channels is C { (Ka-sub)c),c＝1,...,NC}，Ka-subcRepresenting the c-th satellite-to-ground link subchannel, c taking from 1 to NC，NCIs the number of satellite-to-ground link sub-channels.
Each base station allowing simultaneous access to NrThe satellite return capacity is further improved by the satellite, and an equivalent formula of the satellite return capacity is represented as follows:
wherein, CmAs a base station SBSmSatellite backhaul capacity of Cm,sIs a base station SBSmAnd satellite SATsThe link rate between the satellite and the ground, and T is the satellite-ground link propagation delay; dm,sAs a base station SBSmAnd satellite SATsThe amount of link data in between.
All base stations are limited to buffer limited conditions: it means that the total amount of the cache contents of each base station does not exceed the cache capacity of the base station and the cache capacity of the base station is far smaller than the total amount of the contents of the whole network. The concrete expression is as follows: suppose there are N files of different popularity in the entire network, denoted as F { (F)n),n＝1,...,N}，fnRepresenting the nth file content; each base station is provided with certain caching capacity which can cache N at mostmaxA content, wherein Nmax＜＜N。
All base stations are limited by the satellite-to-ground backhaul capacity coupling constraint: means that the backhaul resource consumed by each base station to meet the user requirement is not greater than the satellite backhaul capacity of the base station in each discrete time slot. The specific formula is expressed as:
wherein x ism,j,kIs an indicator variable of the terrestrial link assignment sub-channel,
the condition of the content cached by the base station is recorded,
representation base station SBSmIn which the file f is cachednOtherwise
Remembering the indoor content request case and obeying to the Zipf distribution,
representing ground users userjRequested the file fnOtherwise
Representing ground users userjWhether the request can be in the SBSmIs satisfied in the above-mentioned step (a),
representing ground users userjRequested file caching in base station SBSmIn, otherwise
CmAs a base station SBSmOf the satellite backhaul capacity, UbackRepresenting the backhaul resources consumed by the base station, which portion is mainly satisfied by users whose needs cannot be satisfied at the local base station
And (4) generating.
Referring to fig. 1, the implementation steps of this example are as follows:
1.1) setting resource scheduling decision variables of a ground link and a satellite-ground link as X and B respectively:
wherein x ism,j,kIs an indication variable of the sub-channel allocated by the ground link, if the ground userjDistribution to base station SBSmTerrestrial link sub-channel C-subkThen xm,j,k1, otherwise xm,j,k0; in the same way, bm,s,cIs an indicator variable of the satellite-to-ground link assignment subchannel, if the base station SBSmAllocation to satellite SATsSatellite-to-ground link sub-channel Ka-subcThen b ism,s,c1, otherwise bm,s,c＝0；
1.2) establishing the following optimization target calculation formula by taking the maximum system resultant rate and the user capacity as targets, wherein the optimization target calculation formula comprises six constraint conditions, and the optimization target calculation formula specifically comprises the following steps:
limited by:
wherein, { xm,j,k,bm,s,cRepresents resource scheduling decision variables of the ground link and the satellite-ground link,
the sum of the rates of the system is represented,
represents the system user capacity, mu is a discount factor;
constraint (1) indicates that the base station can only associate terrestrial users within its coverage area, where the coverage matrix between the base station and the terrestrial users is expressed as
am,jExpressed as a ground user 1jAnd base station SBSmAssociation, otherwise am,j＝0；
Constraint (2) represents the satellite-to-ground backhaul capacity coupling constraints that each base station is subjected to;
constraint (3) indicates that the ground link sub-channel can only be allocated to one ground user at most in the same time slot;
constraint (4) and constraint (6) indicate that each terrestrial user or base station can be allocated to at most one channel resource in the same time slot;
constraint (5) indicates that the satellite link subchannel can only be allocated to N at most in the same time slotrA base station, NrThe maximum number of satellites allowed to be accessed by the base station.
And 2, decoupling the combined scheduling optimization scheme in the step 1 into an independent ground network resource scheduling optimization scheme and a satellite network resource scheduling optimization scheme by using a Lagrange relaxation method.
2.1) introducing a set of lagrange operators λ ═ λi|i＝1,2,...,NSBSIs ≧ 0, where λiRepresenting Lagrangian operators associated with base station i, i being taken from 1 to NSBS，NSBSRepresenting the number of ground base stations;
2.2) relaxing the satellite-ground backhaul capacity coupling constraint into an optimization target calculation formula by using an operator in the step 2.1), and converting the satellite-ground integrated network resource scheduling optimization scheme into an unconstrained optimization scheme:
wherein λ is lagrangian operator, { X, B } is resource scheduling decision variable of ground link and satellite-ground link, L (X, B, λ) is lagrangian function, and the specific formula is:
wherein, { xm,j,k,bm,s,cRepresents resource scheduling decision variables of the ground link and the satellite-ground link,
the sum of the rates of the system is represented,
represents the system user capacity, mu is the discount factor, lambdamRepresentation and base station SBSmThe associated lagrangian operator is used,
which represents the total consumption of the satellite backhaul,
is an indication variable, U, of whether the contents of the ground user request are buffered in the base stationbackIndicating the backhaul resource consumed by the terrestrial base station, CmRepresentation base station SBSmOf the satellite backhaul capacity, Nuser、NSBS、NKThe number of the ground user, the base station and the ground link sub-channel.
Node of resource allocation after given decisionFruit { X*,B*In the case of the optimization scheme, the satellite-ground integrated network communication and cache resource joint scheduling scheme can be converted into an unconstrained convex optimization scheme, wherein X is*Optimal results for ground network resource allocation; b is*Optimal results for satellite network resource allocation;
2.3) decoupling the unconstrained optimization scheme in 2.2) into a mutually independent ground network resource scheduling optimization scheme and satellite network resource scheduling optimization scheme:
2.3.1) optimization scheme of scheduling resources of the terrestrial network aims to maximize the resultant rate and the user capacity of the terrestrial network while saving backhaul resource consumption as much as possible, and comprises three constraints, the formula of which is as follows:
limited by: (1)(3)(4)
Where X denotes a ground network resource scheduling optimization variable,
the sum of the rates of the system is represented,
which represents the capacity of the users of the system,
representing the total satellite backhaul consumption, Nuser、NSBS、NKRespectively the number of the ground user, the base station and the ground link sub-channel, mu is a discount factor, lambdamRepresentation and base station SBSmThe associated lagrangian operator is used,
is an indication variable, U, of whether the contents of the ground user request are buffered in the base stationbackRepresents backhaul resources consumed by a ground base station;
constraint (1) indicates that the base station can only associate with terrestrial users within its coverage;
constraint (3) indicates that the ground link sub-channel can only be allocated to one ground user at most in the same time slot;
constraint (4) indicates that each terrestrial user can be allocated to at most one channel resource in the same time slot;
2.3.2) optimization scheme for scheduling resources of satellite network aiming at maximizing total capacity of satellite backhaul, comprising two constraints, the formula of which is as follows:
limited by: (5)(6)
Wherein { B } represents a satellite network resource scheduling optimization variable, NSBSIs the number of base stations, λmRepresentation and base station SBSmAssociated Lagrangian, CmRepresenting terrestrial base stations SBSmThe satellite backhaul capacity of;
constraint (5) indicates that the satellite link subchannel can only be allocated to N at most in the same time slotrA base station, wherein NrThe number of satellites allowed to access each base station;
constraint (6) indicates that each base station can be allocated to at most one channel resource in the same time slot.
And 3, in each discrete time slot, respectively carrying out optimal resource scheduling on the ground network resource scheduling optimization scheme and the satellite network resource scheduling optimization scheme according to the current link state and the wireless access link transmission content information.
3.1) initializing a Lagrangian operator at the beginning of each discrete time slot;
3.2) based on a given Lagrange operator, realizing the optimal wireless resource allocation decision for the ground network resource scheduling optimization scheme according to the ground link state and the wireless access link transmission content information:
referring to fig. 3, the specific implementation of this step is as follows:
3.2.1) according to service user mode
All users are divided into: local hit group:
and backhaul acquisition group
3.2.2) initializing a ground network resource scheduling decision variable X;
3.2.3) ground-link sub-channel C-subkGreedy de-matching a set of terrestrial users with best channel quality in a local hit set
And base station
Wherein, JunIs the set of all unmatched users, NSBSIs the number of base stations, hm,j,kFor users on the groundjAnd base station SBSmTerrestrial link channel C-sub betweenkIf a plurality of sub-channels send requests to the same user, the user selects the sub-channel with the best quality to match;
3.2.4) selecting the best matching object according to the tendency for each pair of successfully matched base station-channel pairs, and adding the best matching object into the alternative set; for each successfully matched user and base station-channel pair (j, (m, k)), the trend function is:
wherein h ist,i,kFor users on the groundiAnd base station SBStTerrestrial link channel C-sub betweenkGain of ht,j,kFor users on the groundjAnd base station SBStTerrestrial link channel C-sub betweenkA gain of (d);
3.2.5) selecting the best matching pair from the candidate set for each ground subchannel according to the utility function, the ground link subchannel C-subkThe utility function of (a) is:
wherein N isuserAnd NSBSNumber of terrestrial users and base stations, R, respectivelym,j,kFor users on the groundjAnd base station SBSmTerrestrial link between at channel C-subkEffective rate of (c), xm,j,kRepresenting a ground link resource scheduling decision variable, mu is a discount factor;
3.2.6) repeat 3.2.4) and 3.2.5) until all users have been assigned a terrestrial channel or the utility function of all terrestrial subchannels is no longer valid;
3.2.7) user defining backhaul acquisition groupjThe gain function using the remaining unmatched channel resources (m, k) is:
Gainj,(m,k)＝R'm,j,k-Rsub+μ-λmUback；
wherein R'm,j,kIs the user rate, R, of the backhaul acquisition groupsubIs the influence of the user using the channel resource on the network complexing rate, mu is the discount factor, lambdamIs SBS with base stationmRelated Lagrangian, UbackRepresents backhaul resources consumed by a ground base station; based on the occupied Gain of users in each backhaul acquisition group, an infinite search method is used to allocate unused channel resources to the best user until the Gain is no longer valid, i.e. Gainj,(m,k)Not less than 0, obtaining the optimal result X of the ground network resource allocation*；
3.3) realizing the optimal wireless resource allocation decision for the satellite network resource scheduling optimization scheme according to the satellite-ground link state;
referring to fig. 4, this step is implemented as follows:
3.3.1) initializing a satellite network resource scheduling decision variable B;
3.3.2) Each satellite Link sub-channel Ka-subcGreedy de-matching a set of terrestrial base stations with best channel quality
And satellite
Wherein M isunIs the set of all unmatched ground base stations, NSATAs to the number of satellites,
as a base station SBSmAnd satellite SATsSatellite-to-ground link channel Ka-sub betweencA gain of (d); if the ground base station receives the request of a plurality of satellite sub-channels, N with the best channel quality is selectedrA plurality of channels;
3.3.3) selecting the best matching object according to the tendency for each pair of successfully matched satellite-channel pairs, and adding the best matching object into the alternative set; for each matched base station and satellite-channel pair (m, (s, c)), its dip function is:
wherein the content of the first and second substances,
and
respectively the antenna gain of the satellite-to-ground link and the off-axis antenna gain,
and
channel gain for the satellite-to-ground link;
3.3.4) selecting the best matching pair from the alternative set according to the utility function by each satellite subchannel, the satellite-ground link subchannel Ka-subcThe utility function of (a) is:
wherein N isSBSAnd NSATIs the number of base stations and satellites, λmRepresentation and base station SBSmRelated Lagrange operator, Rm,s,cAs a base station SBSmAnd satellite SATsThe satellite-ground link between them is in the channel Ka-subcEffective rate of (a), bm,s,cRepresenting a satellite-ground link resource scheduling decision variable;
3.3.5) repeat 3.3.3) and 3.3.4) until the gain function of all base stations allocated channels or all satellite subchannels is no longer valid, yielding the best result B of the satellite network resource allocation*。
3.4) if the resource allocation results of the two networks after decision making can not guarantee the satellite-ground return capacity coupling constraint, removing one user by one according to the ascending sequence of the ground user rate until the constraint is met;
3.5) iteratively updating the Lagrangian operator after decision making the resource scheduling result after decision continuously approximate to the real optimal result:
the implementation of this step is as follows:
3.5.1) obtaining resource allocation result { X) after decision of ground network resource scheduling optimization scheme and satellite network resource scheduling optimization scheme*,B*In which X is*Optimal results for ground network resource allocation; b is*Optimal results for satellite network resource allocation;
3.5.2) updating Lagrangian operators by using a descending gradient method, wherein the specific formula is as follows:
wherein λ is(t+1)And λ(t)Lagrangian operators at the iteration step t +1 and time t, respectively, theta(t)Is a monotonically decreasing exponential function with respect to t, L (X)*,B*And, lambda) is a lagrange function,
represents the gradient with respect to λ, λ being the lagrangian operator;
3.5.3) whether the convergence condition is satisfied: [ theta ](t+1)-θ(t)| ≦ ε, where ε is a Lagrangian iteration convergence parameter;
if not, repeating 3.5.1) and 3.5.2) and carrying out the next iteration; and if the convergence condition is met, obtaining the optimal resource scheduling scheme.
The application effect of the present invention will be described in detail with reference to the simulation.
1. Simulation conditions are as follows:
in a simulation scene, a satellite-ground integrated network with limited downlink buffer is considered, ground users and base stations are respectively randomly distributed and uniformly distributed in a network scene of 1000m multiplied by 1000m, and the power spectrum density of Gaussian white noise is-174 dBm/Hz. Number of base stations N SBS25, the ground user density is 500/km2Number of terrestrial link subchannels NKAt 15, each terrestrial link subchannel is a subcarrier with a bandwidth of 1 MHz; number of low earth orbit satellites NSATTo 8, the number of satellite-to-ground link sub-channels NCEach satellite-to-ground link subchannel is a subcarrier of 20MHz bandwidth, 10. Respectively depicting small-scale fading under a C frequency band and a Ka frequency band by Rayleigh fading and Rice fading; UMi path loss model is considered in the ground network, and free space path loss model is considered in the satellite network. The Lagrangian iteration parameter ε is set to 10-7. There are 50 files in the network, and the ground base station cache uses the optimal popularity cache strategy MPC. Three baseline algorithms were used to evaluate the performance of the invention, respectively: an explicit search algorithm (ES), a greedy algorithm, and a random algorithm.
2. Simulation content and result analysis:
simulation 1: under the small-scale test, the system performance and the calculation time length obtained by the invention and the poor search algorithm are compared.
The poor search algorithm can find all possible results in a specific scene, and then the optimal result is obtained through the poor search. In the small scale test, the number of base stations NSBSThe calculation time length of the two schemes and the solved system performance index are respectively calculated by the invention and the existing poor search algorithm by changing the number of the ground users and the number of the ground link sub-channels. The results are shown in Table 1.
TABLE 1
As can be seen from table 1, when the number of users exceeds the available spectrum resources, i.e. Nuser≥NSBS×NKThe invention can effectively reduce the calculation time, and compared with the optimal result, the invention only has the system performance loss of less than 1 percent. In addition, as the number of users and the number of channels increase, the calculation time of the poor search algorithm will increase dramatically, but the present invention can greatly save the calculation time.
Simulation 2: along with the change of the buffer limited condition of the base station, the comparison and the change trend of the system performance obtained by the radio resource allocation decision used by the ground network resource scheduling optimization scheme and the greedy algorithm and the random algorithm are shown, and the result is shown in fig. 5.
The experimental results of fig. 5 show that: under the same condition, the system resultant rate obtained by the wireless resource allocation decision used by the ground network resource scheduling optimization scheme is higher than the simulation results of the greedy algorithm and the random algorithm. In particular, when the base station only allows buffering 2 files, i.e. 4% of the total files, the resulting system aggregate rate increases by 28.5% and 120.7% compared to the greedy algorithm and the random algorithm, respectively. However, as the buffer capacity of the ground base station is increased, the advantages of the invention compared with the other two methods are gradually reduced. This fully shows that the radio resource allocation decision used in the ground network resource scheduling optimization scheme of the present invention can bring better performance especially under the condition that the buffer condition is severely limited.
Simulation 3: adopting different satellite-ground links to realize multiple connection relations NrThe number of low-earth orbit satellites is changed, the comparison and the change trend of the total return capacity of the satellite obtained by the radio resource allocation decision used by the satellite network resource scheduling optimization scheme and the greedy algorithm and the random algorithm are shown, and the result is shown in fig. 6.
Fig. 6(a) is a graph showing the simulation results of the total capacity of the return trip of the satellite as a function of the number of satellites in the case where the base station allows access to only one satellite; fig. 6(b) is a diagram showing a simulation result of the total capacity of the satellite backhaul depending on the number of satellites in a case where the base station allows access to two satellites. The experimental results of fig. 6 show that: under the same condition, the total return capacity of the satellite obtained by the wireless resource allocation decision used by the satellite network resource scheduling optimization scheme is far higher than the results of a greedy algorithm and a random algorithm. When the number of the low-earth orbit satellites is 3, the total return capacity of the satellite obtained by the method can be increased by 121.4% and 280.2% at most respectively compared with a greedy algorithm and a random algorithm. With the increase of the number of satellites, the results obtained by the greedy algorithm and the random algorithm are reduced at the inflection point, and the total capacity of the satellite return trip obtained by the method is stably improved, which shows that the wireless resource allocation decision used by the satellite network resource scheduling optimization scheme can obtain stable satellite return trip capacity under different satellite constellations and has universality. Furthermore, with NrThe method can fully play the huge gain brought by multiple connectivity by using the wireless resource allocation decision used by the satellite network resource scheduling optimization scheme, thereby correspondingly improving the total capacity of the satellite backhaul。
And (4) simulation: the resource scheduling optimization scheme of the present invention is used to favor two objectives with different discounting factors, and the result is shown in fig. 7.
The experimental results of fig. 7 show that: the discount factor μ has an important role in the target tendency of the resource scheduling optimization scheme. When mu is smaller, the resource scheduling optimization scheme pursues a larger system integration rate; as μ increases, resource scheduling optimization schemes start to gradually strive for more user access.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (9)
1. A satellite-ground integrated network communication and cache resource joint scheduling method is characterized by comprising the following steps:
(1) constructing a satellite-ground integrated network communication and cache resource joint scheduling optimization scheme by taking the maximum system resultant rate and user capacity as targets under the constraint of cache limited conditions and satellite-ground backhaul capacity coupling; two different optimization objectives are used in this scheme: the system synthesis rate and the user capacity are used for balancing the user service quality and the network coverage demand under the satellite-ground integrated network, and the discount factors are used for representing the tendencies of the current scheme to the two targets;
the satellite-ground integrated network communication and cache resource joint scheduling optimization scheme constructed by taking the maximized system resultant rate and the user capacity as the targets is realized as follows:
1a) setting resource scheduling decision variables of a ground link and a satellite-ground link as X and B respectively; wherein x ism,j,kIs an indicator variable for the assignment of sub-channels to terrestrial links, x if a terrestrial user j is assigned to a sub-channel k of a base station mm,j,k1, otherwise xm,j,k0; in the same way, bm,s,cIs an indicator variable of the satellite-to-ground link assignment subchannel, if base station m is assigned to subchannel c of satellite s, then bm,s,c1, otherwise bm,s,c＝0；
1b) Establishing an optimization target calculation formula by taking the maximum system resultant rate and the user capacity as targets, wherein the optimization target calculation formula comprises six constraint conditions, and specifically comprises the following steps:
limited by:
wherein, { xm,j,k,bm,s,cRepresents resource scheduling decision variables of the ground link and the satellite-ground link,
the sum of the rates of the system is represented,
represents the system user capacity, mu is a discount factor; J. m, S, K and C represent the ground user, base station, satellite, ground link sub-channel and satellite-ground link sub-channel sets, respectively; n is a radical ofuser、NSBS、NSAT、NKAnd NCThe number of the ground users, the base station, the satellite, the ground link sub-channel and the satellite-ground link sub-channel; cmSatellite backhaul capacity for ground base station m;
constraint (1) indicates that the base station can only associate terrestrial users within its coverage area, where am,j,kIs the coverage variable between the base station and the ground user;
constraint (2) represents the satellite-to-ground backhaul capacity coupling constraints to which each base station is subjected, wherein
Is an indication variable for determining whether the request content of the ground user is cached in the base station, if the base station m caches the request content of the user j, the base station m determines that the request content of the user j is cached in the base station m
Otherwise
UbackRepresents backhaul resources consumed by a ground base station;
constraint (3) indicates that the ground link sub-channel can only be allocated to one ground user at most in the same time slot;
constraint (4) indicates that each terrestrial user can be allocated to at most one channel resource in the same time slot;
constraint (5) indicates that the satellite link subchannel can only be allocated to N at most in the same time slotrA base station, wherein NrThe number of satellites allowed to access each base station;
constraint (6) indicates that each base station can be allocated to at most one channel resource in the same time slot;
(2) decoupling the joint scheduling optimization scheme in the step (1) into an independent ground network resource scheduling optimization scheme and a satellite network resource scheduling optimization scheme by using a Lagrange relaxation method;
(3) in each discrete time slot, respectively carrying out optimal resource scheduling on the ground network resource scheduling optimization scheme and the satellite network resource scheduling optimization scheme according to the current link state and the wireless access link transmission content information:
3a) initializing a Lagrangian operator at the beginning of each discrete time slot;
3b) based on a given Lagrange operator, realizing an optimal wireless resource allocation decision for a ground network resource scheduling optimization scheme according to a ground link state and wireless access link transmission content information;
3c) realizing an optimal wireless resource allocation decision for the satellite network resource scheduling optimization scheme according to the satellite-ground link state;
3d) if the resource allocation results of the two networks cannot guarantee the satellite-ground return capacity coupling constraint after decision, removing the users one by one according to the ascending sequence of the ground user rate until the constraint is met;
3e) and iteratively updating the Lagrangian operator after decision making, so that the resource scheduling result after decision making continuously approaches to the real optimal result.
2. The method of claim 1, wherein the buffer-bound condition and the satellite-to-ground backhaul capacity coupling constraint in (1) are respectively set as follows:
the cache limitation condition is as follows: the total content of each ground base station cache does not exceed the cache capacity of the ground base station and the cache capacity of the ground base station cache is far smaller than the total content of the whole network;
the satellite-to-ground backhaul capacity coupling constraint is: ensuring that in each discrete time slot, the backhaul resource consumed by each ground base station to meet the user requirement is not greater than the satellite backhaul capacity of the base station, wherein the backhaul resource consumed by the ground base station is mainly generated by users whose requirements cannot be met at the local base station; the constraint enables a resource scheduling model under the satellite-ground integrated network to be composed of ground network resource scheduling and satellite network resource scheduling which are coupled.
3. The method of claim 1, wherein the satellite-to-ground integrated network in (1) is: the ultra-dense low-earth orbit satellite provides a high-capacity satellite return for a ground base station by utilizing a high-frequency Ka frequency band so as to realize more user access, and the ground base station allows a plurality of satellites to be accessed simultaneously so as to further improve the return capacity; the ground base station has a cache capability, so that the user's requirements can be directly satisfied in the associated base station.
4. The method of claim 3, wherein the high capacity satellite backhaul has an equivalent formula of:
wherein, CmSatellite backhaul capacity, C, for ground base station mm,sIs the link rate between the ground base station m and the associated satellite s, and T is the satellite-ground link propagation delay; dm,sIs the amount of link data between the ground base station m and the satellite s.
5. The method of claim 1, wherein the decoupling of the satellite-ground integrated network communication and cache resource joint scheduling optimization scheme into an independent ground network resource scheduling optimization scheme and a satellite network resource scheduling optimization scheme by using a Lagrangian relaxation method in (2) is implemented as follows:
2a) introducing a set of Lagrangian operators lambda ═ lambda { [ lambda ]i|i＝1,2,…,NSBSIs ≧ 0, where λiRepresenting Lagrangian operators associated with base station i, i being taken from 1 to NSBS，NSBSRepresenting the number of ground base stations;
2b) relaxing satellite-ground return capacity coupling constraint in the satellite-ground integrated network communication and cache resource joint scheduling optimization scheme by using an operator in 2a), so that the scheme is converted into an unconstrained optimization scheme;
2c) decoupling the unconstrained optimization scheme in 2b) into a ground network resource scheduling optimization scheme and a satellite network resource scheduling optimization scheme which are independent of each other.
6. The method of claim 5, wherein the optimization scheme for scheduling the terrestrial network resources and the optimization scheme for scheduling the satellite network resources in 2c) are as follows:
2c1) the ground network resource scheduling optimization scheme aims to maximize the resultant rate and the user capacity of the ground network while saving the backhaul resource consumption, and comprises three constraint conditions, wherein the formula is expressed as follows:
limited by: constraints (1), (3) and (4);
where X denotes a ground network resource scheduling optimization variable,
the sum of the rates of the system is represented,
which represents the capacity of the users of the system,
representing the total satellite backhaul consumption, Nuser、NSBS、NKRespectively the number of the ground user, the base station and the ground link sub-channel, mu is a discount factor, lambdamRepresenting the lagrangian associated with base station m,
is an indication variable, U, of whether the contents of the ground user request are buffered in the base stationbackRepresents backhaul resources consumed by a ground base station;
2c2) the optimization scheme of the satellite network resource scheduling aims at maximizing the total capacity of the satellite backhaul, and comprises two constraint conditions, wherein the formula is expressed as follows:
limited by: the constraint (5) (6),
wherein { B } represents a satellite network resource scheduling optimization variable, NSBSIs the number of base stations, λmRepresenting the Lagrangian, C, associated with the base station mmRepresenting the satellite backhaul capacity of the terrestrial base station m.
7. The method of claim 1, wherein the optimal radio resource allocation decision for the ground network resource scheduling optimization scheme in 3b) is implemented as follows:
3b1) according to
All users are divided into: local hit group
And backhaul acquisition group
3b2) Initializing a ground network resource scheduling decision variable X;
3b3) each ground link sub-channel is greedy matched with a group of ground users and base stations with the best channel quality in the local hit group; if a plurality of sub-channels send requests to the same user, the user selects the sub-channel with the best quality to match;
3b4) selecting the best matching object according to the tendency of each pair of successfully matched base station-channel pairs, and adding the best matching object into the alternative set;
3b5) selecting the best matching pair from the alternative set by each ground subchannel according to the utility function; the utility function of the ground sub-channel is the equivalent sum of the user sum rate and the user capacity on the channel;
3b6) repeat 3b4) and 3b5) until all users have been assigned a terrestrial channel or the utility function of all terrestrial subchannels is no longer valid;
3b7) based on the occupation gain of users in each backhaul acquisition group, unused channel resources are allocated to the optimal user by using a poor search method until the gain is no longer effective, and the optimal result X of the ground network resource allocation is obtained*(ii) a The user occupation gain is the difference between the user rate and the influence value of the used channel resources on the overall network complexing rate.
8. The method of claim 1, wherein the optimal radio resource allocation decision for the satellite network resource scheduling optimization scheme in 3c) is implemented as follows:
3c1) initializing a satellite network resource scheduling decision variable B;
3c2) each satellite link subchannel greedy matches a set of ground base stations and satellites with the best channel quality, if the ground base stations receive requests for multiple satellite subchannelsSelecting N where the channel quality is bestrA plurality of channels;
3c3) selecting the best matching object according to the tendency of each pair of successfully matched satellite-channel pairs, and adding the best matching object into the alternative set;
3c4) each satellite subchannel selects the best matching pair from the alternative set according to the utility function;
3c5) repeat 3c3) and 3c4) until the gain function for all base stations allocated channels or all satellite subchannels is no longer valid, yielding the best result B for satellite network resource allocation*。
9. The method as claimed in claim 1 wherein said iteratively updating the post-decision lagrangian operator in 3e) is performed as follows:
3e1) obtaining resource allocation result { X after decision of ground network resource scheduling optimization scheme and satellite network resource scheduling optimization scheme*,B*In which X is*Optimal results for ground network resource allocation; b is*Optimal results for satellite network resource allocation;
3e2) and updating the Lagrangian operator by using a descending gradient method, wherein the specific formula is as follows:
wherein λ is(t+1)And λ(t)Lagrangian operators at the iteration step t +1 and time t, respectively, theta(t)Is a monotonically decreasing exponential function with respect to t, L (X)*,B*And, lambda) is a lagrange function,
represents the gradient with respect to λ, λ being the lagrangian operator;
3e3) judging whether a convergence condition is met: [ theta ](t+1)-θ(t)| ≦ ε, where ε is a Lagrangian iteration convergence parameter;
if not, repeating 3e1) and 3e2) and carrying out the next iteration;
and if the convergence condition is met, obtaining the optimal resource scheduling scheme.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010487336.0A CN111641450B (en) | 2020-06-02 | 2020-06-02 | Satellite-ground integrated network communication and cache resource joint scheduling method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010487336.0A CN111641450B (en) | 2020-06-02 | 2020-06-02 | Satellite-ground integrated network communication and cache resource joint scheduling method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111641450A CN111641450A (en) | 2020-09-08 |
| CN111641450B true CN111641450B (en) | 2021-07-27 |
Family
ID=72330672
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010487336.0A Active CN111641450B (en) | 2020-06-02 | 2020-06-02 | Satellite-ground integrated network communication and cache resource joint scheduling method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111641450B (en) |
Families Citing this family (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112633334B (en) * | 2020-12-09 | 2023-08-11 | 西安电子科技大学 | Modeling method based on satellite measurement operation control resource planning and scheduling |
| WO2022170446A1 (en) * | 2021-02-09 | 2022-08-18 | 北京小米移动软件有限公司 | Method and apparatus for determining satellite link information |
| CN112702443B (en) * | 2021-02-26 | 2021-06-18 | 之江实验室 | Multi-satellite multi-level cache allocation method and device for satellite-ground cooperative communication system |
| CN113015105B (en) * | 2021-03-08 | 2022-06-03 | 哈尔滨工业大学（深圳） | Method for jointly optimizing code cache content placement and resources of air-space-ground integrated network |
| CN113055489B (en) * | 2021-03-23 | 2022-09-06 | 北京计算机技术及应用研究所 | Implementation method of satellite-ground converged network resource allocation strategy based on Q learning |
| CN113115461B (en) * | 2021-04-23 | 2023-04-07 | 北京科技大学 | QMIX-based wireless resource allocation optimization method and device |
| CN113316196B (en) * | 2021-05-10 | 2022-07-01 | 北京科技大学 | Resource allocation method and device in satellite-ground cooperative network based on edge cache |
| CN114374742B (en) * | 2021-05-18 | 2023-06-27 | 北京邮电大学 | Dynamic cache updating and cooperative transmission method for low-orbit satellite network |
| CN113382426B (en) * | 2021-05-26 | 2022-08-23 | 重庆邮电大学 | Distributed user association method for guaranteeing user mobility and time delay requirements |
| CN113395103B (en) * | 2021-06-11 | 2022-05-24 | 中国人民解放军国防科技大学 | Navigation system inter-satellite route planning method and device considering capacity limitation |
| CN113472420B (en) * | 2021-06-29 | 2022-05-24 | 大连大学 | Satellite network cache placement method based on regional user interest perception |
| CN113691598B (en) * | 2021-08-15 | 2022-11-25 | 南京理工大学 | Cooperative caching method for satellite-ground converged network |
| CN113766661B (en) * | 2021-08-30 | 2023-12-26 | 北京邮电大学 | Interference control method and system for wireless network environment |
| CN115133972B (en) * | 2022-03-14 | 2023-06-27 | 重庆邮电大学 | Satellite system task scheduling and unloading method |
| CN115021793B (en) * | 2022-04-27 | 2023-04-18 | 哈尔滨工业大学（威海） | Network coding-based satellite network inter-satellite link planning and power distribution method |
| CN116567762A (en) * | 2023-07-12 | 2023-08-08 | 成都本原星通科技有限公司 | Satellite-ground cooperative selection access control method based on multi-QoS optimization |
| CN116865842B (en) * | 2023-09-05 | 2023-11-28 | 武汉能钠智能装备技术股份有限公司 | Resource allocation system and method for communication multiple access edge computing server |
Family Cites Families (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102780523B (en) * | 2012-07-31 | 2014-10-29 | 中国电子科技集团公司第五十四研究所 | Multi-satellite cooperative observation business scheduling method |
| CN103632053B (en) * | 2013-11-26 | 2016-08-17 | 中国西安卫星测控中心 | Based on low rail constellation star ground TT&C Resources combined scheduling method in orbit determination constraint satisfaction |
| US10348394B1 (en) * | 2014-03-14 | 2019-07-09 | Tarana Wireless, Inc. | System architecture and method for enhancing wireless networks with mini-satellites and pseudollites and adaptive antenna processing |
| CN106507366B (en) * | 2016-11-25 | 2019-11-05 | 中国航空无线电电子研究所 | The repeater satellite sky time-frequency domain resources dynamic dispatching method of facing multiple users |
| CN108495332B (en) * | 2018-03-28 | 2020-10-13 | 山东大学 | Combined resource fair distribution method based on cellular D2D communication system |
| CN108900237B (en) * | 2018-06-21 | 2020-10-16 | 重庆邮电大学 | Resource allocation method for multi-beam satellite communication system |
| US10771147B2 (en) * | 2018-08-17 | 2020-09-08 | Hughes Network Systems Llc | Satellite communication system for diversity gateway switching and satellite communication method for diversity gateway switching |
| CN109714097B (en) * | 2018-11-07 | 2021-04-13 | 长沙天仪空间科技研究院有限公司 | Cross-domain cooperative scheduling system for satellite resources |
| CN109951335B (en) * | 2019-03-24 | 2022-03-04 | 西安电子科技大学 | Satellite network delay and rate combined guarantee routing method based on time aggregation graph |
-
2020
- 2020-06-02 CN CN202010487336.0A patent/CN111641450B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN111641450A (en) | 2020-09-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111641450B (en) | Satellite-ground integrated network communication and cache resource joint scheduling method | |
| Na et al. | UAV-supported clustered NOMA for 6G-enabled Internet of Things: Trajectory planning and resource allocation | |
| CN111769865B (en) | Resource management method based on satellite-ground cooperative processing | |
| CN108738151B (en) | Wireless prediction resource allocation method based on rough information | |
| CN111865398B (en) | Satellite-ground transmission method under large-scale LEO satellite deployment | |
| Zhang et al. | Resource allocation in beam hopping communication system | |
| CN111093213B (en) | Hot content superposition pushing and distributing method and system and wireless communication system | |
| CN112994776B (en) | Gateway station rain attenuation resisting switching method and device suitable for high-throughput satellite communication | |
| CN115801091A (en) | Large-scale constellation network resource scheduling method for satellite-ground cooperative computing | |
| CN112583566A (en) | Network resource allocation method based on air-space-ground integrated system | |
| Wang et al. | Admission control and power allocation for NOMA-based satellite multi-beam network | |
| Ni et al. | Joint optimization of user association and resource allocation in cache-enabled terrestrial-satellite integrating network | |
| CN110602722B (en) | Design method for joint content pushing and transmission based on NOMA | |
| CN113873658B (en) | Method for allocating beam hopping resources by taking user service weight gain as objective function | |
| Zhu et al. | Energy efficient resource allocation in cloud based integrated terrestrial-satellite networks | |
| Zeng et al. | Networked satellite telemetry resource allocation for mega constellations | |
| Liu et al. | A successive deep Q-learning based distributed handover scheme for large-scale LEO satellite networks | |
| CN109831759B (en) | Three-dimensional D2D matching algorithm based on software defined wireless network | |
| Zhang et al. | Exploiting collaborative computing to improve downlink sum rate in satellite integrated terrestrial networks | |
| CN113382426B (en) | Distributed user association method for guaranteeing user mobility and time delay requirements | |
| CN114793126B (en) | Multi-beam low-orbit satellite user grouping and resource allocation method | |
| Cai et al. | Research on beam hopping technology of satellite resource management | |
| CN116156421A (en) | Differentiated service transmission method based on double-layer satellite heterogeneous network | |
| CN115833886A (en) | Power control method of non-cellular large-scale MIMO system | |
| CN109104768A (en) | A kind of non-orthogonal multiple access joint bandwidth and method of rate allocation based on simulated annealing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |