CN102256260B - Method for configuring independent resources based on resource flow - Google Patents

Method for configuring independent resources based on resource flow Download PDF

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CN102256260B
CN102256260B CN 201110179932 CN201110179932A CN102256260B CN 102256260 B CN102256260 B CN 102256260B CN 201110179932 CN201110179932 CN 201110179932 CN 201110179932 A CN201110179932 A CN 201110179932A CN 102256260 B CN102256260 B CN 102256260B
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base station
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杨春刚
李建东
刘勤
盛敏
李红艳
李维英
闫继磊
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Xidian University
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Abstract

The invention discloses a method for configuring independent resources based on s resource flow in the field of wireless communication resource management control. Regarding the problems of low convergence speed and various resource treating unsuitability in the prior art, a resource configuring method with higher convergence speed of various resources, suitable for treating a wireless communication system, is provided. In the method, a concept based on the resource flow in the wireless communication system is adopted, requests of multiple users to resources are planned to be changes of spatial intensity of a resource field, and the resource configuration realized based on the resource flow does not require interaction. Meanwhile, a closed-form solution of an optimal resource configuration strategy is deduced, so that high-efficiency independent resource configuration is realized to ensure the existence and the optimality of an optimal solution. The problem of more interaction times and the problems that the existence, the optimality and the like of the optimal solution cannot be ensured in the prior art are solved, and the high-efficiency independent resource configuration is realized to ensure the existence and the optimality of the optimal solution.

Description

Autonomous resource allocation method based on resource flow
Technical field
The invention belongs to communication technical field, further relate to the autonomous resource allocation method based on resource flow in a kind of wireless communication resources management control field.The method can realize the dynamic autonomous configuration of multiple multidimensional resource high-efficiency in the wireless communication system, effectively promotes the resource utilization in the wireless communication system.
Background technology
The management of resource and control have become one of key technology that determines the current wireless communication system performance, and it is by effectively guaranteeing multi-user's QoS requirement for the high-efficient disposition of resource, and effectively improve the level of resources utilization.Under the environment of current heterogeneous network height fusion development, no matter the efficient utilization that how to realize various resources is further to reduce the operation and maintenance expense for operator, thereby improve the economic well-being of workers and staff of operator's resource, or satisfying more and more much higher kind of transmission rate service demand all has serious challenge.
Prior wireless network is just experiencing great development, and various forms of networks emerge in an endless stream, and the scene that multiple network covers occurs in same geographic area, and the user experiences and performance in wireless communication systems has conclusive effect for promoting in effective configuration of resource.Aspect dynamic resource management and distribution technique, substantially comprise following several technology at present: based on the dynamic resource management technology of optimisation technique, adopt the resource-adaptive distribution technique of learning algorithm and the non-cooperation resource allocation methods that proposes based on game theory.In current heterogeneous network environment and under the diversified background of resource height, above-mentioned three kinds of technical methods are respectively based on optimization, and study and game theory are realized resource distribution.
The patent application document of Tsing-Hua University " combined optimization method of power division, channel allocation and trunk node selection " (publication number CN 101483911A, application number 200910077817.8, a kind of realization power is disclosed applying date 2009.1.22), the combined optimization method of the resources such as channeling and trunking node.The method adopts the method for power division and channel allocation iteration to realize the combined optimization of power division and channel allocation.The deficiency that the method exists be convergence rate slow, be not suitable for processing more different resources and distribute.The demand that simultaneously, can not adapt to present net environment dynamic resource allocation and autonomous configuration based on resource management and the distribution method of optimisation technique.
The patent application document of Beijing University of Post ﹠ Telecommunication " based on free associating wireless resource management system and the method for intensified learning " (publication number CN 101132363A, application number 200710120182.6, applying date 2007.8.10) a kind of free associating wireless resource management system based on intensified learning and method are disclosed in.The reconfigurable portable terminal of the method is initiated channel request, the wireless support function module of reshuffling is collected the local wireless sources manager information, adopt the intensified learning method to carry out " trial and error " alternately according to diverse network performance parameter index, according to corresponding decision criteria, determine whether to admit immediately new session.The resource allocation proposal based on optimization that the method is relatively traditional, intensified learning is a kind of on-line study technology with independent learning ability " trial and error ".The learner is by obtaining learning experience with environment is constantly mutual, and then progressively improves its behavioral strategy.Intensified learning has certain flexibility and adaptivity.But the deficiency that the method exists is, the interaction times between intensified learning technology General Requirements learner and the environment is more, therefore, and the requirement of the real-time under the scenes such as the wireless data service that becomes in the time of can not guaranteeing and dynamic wireless channel decline.
The patent application document of the Nanjing Univ. of Posts and Telecommunications Poewr control method of normalized betting model " in the cognitive radio technology based on " (publication number CN 101359941A, application number 200810195893.4, applying date 2008.9.12) disclose a kind of discussing based on non-cooperative game in and proposed Poewr control method, the method is a kind of implementation that is used in particular for transmitting terminal power control in the cognitive radio.The deficiency that the method exists is that in based on game theoretic design process, the utility function design is to affect one of key factor of Poewr control method design and final performance, has for the balanced existence of solution that proposes betting model and optimality etc. to have a strong impact on.In addition, in concrete game power control process, need to find the solution the single order partial derivative, calculation of complex.Can not satisfy equally the requirement of autonomous configuration.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, propose a kind of method of the autonomous resource distribution based on resource flow, the method is portrayed autonomous configuration and the self-management and control that multidimensional resource under the multiple communication scenes realizes resource by resource flow.
The present invention realizes that the concrete thought of above-mentioned purpose is, at first according to the total resources computational resource space initial strength of base station; Then, realize based on the resource flow allocation optimum.Consider the isomery communication network environment, resource flow is responsible for making up, administering and maintaining to realize high-efficient disposition and the utilization of resource in the base station that is installed in the isomery communication network.Do not consider that the resource of resource flow in the operational management process dissipates, and user's resource request causes the amplitude fading of resource flow and does not affect its direction.
The present invention realizes that the concrete steps of above-mentioned purpose are as follows:
(1) neighbor list is upgraded in the base station
After the start of base station, according to the initialization base station distribution, determine resource flow supply tabulation and resource flow request list;
(2) determine total resources
2a) resource supply and resource expenditure total amount is determined respectively by resource flow supply and request list in the base station;
2b) active user's resource request total amount is calculated in the base station by the service-user sum;
2c) base station is by resource supply, expenditure and user resources request total amount, the clean total resources of three's read group total current base station;
(3) according to total resources with apart from information such as base station locations, computational resource space each point initial strength.
(4) judge whether the base station moves, if the base station motion is arranged, go to step (1), otherwise, the following step carried out;
(5) judge whether to exist new user to arrive, if there is new user to arrive, go to step 2c), otherwise, the following step carried out;
(6) experience average resource field intensity in the small area, computational resource spatial point overall strength according to resource space point place;
(7) according to the resource field overall strength at the base station resource upper limit, resource space point place and with respect to one party to partial derivative function etc., calculate the optimal weights function;
(8) total resources that has according to optimal weights function and current base station calculates optimum resource field intensity;
(9) according to optimum resource field intensity, realize the resource flow allocation optimum;
(10) finish.
The present invention compared with prior art has the following advantages:
The first, the present invention is directed in the prior art convergence rate slow, be not suitable for processing the multiple resources assignment problem, faster resource allocation method of a kind of multiple resources convergence rate that is suitable for processing wireless communication system is provided.
Second, the present invention is directed to the more problem of interaction times in the prior art, adopt the concept based on resource flow in the wireless communication system, the multi-user is planned to the variation of resource field spatial-intensity itself for the request of resource, realize resource distribution based on resource flow, need not mutual.
The 3rd, the present invention for not guaranteeing existence of optimal solution and optimality problem in the prior art, derives the closed solutions of optimum resource allocation strategy from global system, realizes that the resource high-efficiency autonomous configuration guarantees optimal solution existence and optimality.
Description of drawings
Fig. 1 is flow chart of the present invention;
Fig. 2 is that the present invention finishes the design sketch that space, resource field makes up;
Fig. 3 is the design sketch that the present invention realizes the autonomous high-efficient disposition of resource.
Embodiment:
The present invention considers the isomery communication network environment, and resource flow is responsible for making up, administering and maintaining to realize high-efficient disposition and the utilization of resource in the base station that is installed in the isomery communication network.Do not consider that the resource of resource flow in the operational management process dissipates, and user's resource request causes the amplitude fading of resource flow and does not affect its direction.
The present invention will be further described below in conjunction with accompanying drawing 1.
Step 1, neighbor list is upgraded in the base station
After the start of base station, according to the initialization base station distribution, determine resource flow supply tabulation and resource flow request list.
Step 2, total resources is determined in the base station
2a) corresponding resource supply and resource expenditure total amount is determined by resource flow supply and request list in the base station.
2b) active user's resource request total amount is calculated by the service-user sum in the base station.
2c) base station is by the resource supply, and resource is paid and user resources request total amount, calculates the clean total resources of current base station.
Step 3, computational resource space initial strength
The base station is according to the initial strength of following formula computational resource spatial point
E i = - ▿ { M / κ d i }
Wherein, E iTo be d apart from base station distance iResource space point intensity,
Figure BSA00000526807000042
Expression gradient operator number, M is the clean resource vector of current base station, κ is constant.
Step 4 judges whether the base station moves.If the base station motion is arranged, go to step (1), otherwise, carry out the following step;
Step 5 judges whether to exist new user to arrive.If have new user to arrive, go to step 2c), otherwise, the following step carried out;
Step 6, computational resource spatial point overall strength
According to following formula computational resource spatial point resource field overall strength
Figure BSA00000526807000043
Wherein,
Figure BSA00000526807000044
Resource space point d iThe resource field overall strength at place, E ' iThe resource field mean intensity from different base station that spatial point i experiences,
Figure BSA00000526807000045
It is small area.
Step 7 is calculated the optimal weights function
The optimal weights function is calculated according to following formula in the base station
ω d i = ∂ S d i ∂ E i 1 ( λ i κ d i S d i 2 + S d i )
Wherein,
Figure BSA00000526807000052
The optimal weights function,
Figure BSA00000526807000053
It is resource field overall strength
Figure BSA00000526807000054
With respect to E iPartial derivative, λ iTo satisfy λ i(M-M MaxThe variable of)=o, M MaxBe the base station resource amount upper limit,
Figure BSA00000526807000055
Resource space point d iThe resource field overall strength at place, κ is constant.
Step 8 is calculated optimum resource field intensity
Calculate at resource space point d according to following formula the base station iThe optimum resource field intensity at place
Figure BSA00000526807000056
Wherein,
Figure BSA00000526807000057
Resource space point d iThe optimum resource field intensity at place,
Figure BSA00000526807000058
Optimal weights function, M are that the base station has total resources.
Step 9, the resource flow allocation optimum
The base station is according to following formula computational resource stream allocation optimum strategy
Figure BSA00000526807000059
Wherein,
Figure BSA000005268070000510
Resource flow allocation optimum strategy,
Figure BSA000005268070000511
Resource space point d iThe optimum resource field intensity at place, more space, new resources field.
Step 10 finishes.
Be further described below in conjunction with accompanying drawing 2 and 3 pairs of effects of the present invention of accompanying drawing.
Fig. 2 is that the present invention finishes the design sketch that space, resource field makes up, and provides the radio communication scene of simple three base stations here, and supposes that multi-user resource total demand from resource request to three base stations that send is respectively: 50,25,100 units.Adopt the front five steps of method of the present invention to realize the structure in space, resource field, i.e. the resource field field intensity of each point in the space, calculating place resource field.On the basis of Fig. 2, Fig. 3 is the design sketch that the present invention realizes the autonomous high-efficient disposition of resource, supposes when the multi-user resource total demand of three base stations of forward direction changes the autonomous control procedure schematic diagram of the inventive method.For example, be changed to respectively to the multi-user resource total demand of three base stations: 10, during 8,200 units, namely to the base station 3 resource request of sending in space, initial resource field, such as the more resource of request on the basis of Fig. 2.At this moment, adopt rear five steps of the present invention to calculate the optimization field intensity in space, resource field this moment.In theory, base station 1 and 2 resource can be towards the base station 3 direction flow, to satisfy current multi-user for the excessive request of base station 3.Comparison diagram 2 and Fig. 3 find, when the resource request to base station 3 has increase, with respect to Fig. 2, the best deflection base station 3 that flows to of each point resource in the space, resource field among Fig. 3, even generation resource flow direction reverses, therefore, base station 1 and base station 2 realize that in the control of method of the present invention resource flow constantly flows to the more base station 3 of stock number, therefore realizes based on the autonomous high-efficient disposition of the resource of resource flow.

Claims (1)

1. based on the autonomous resource allocation method of resource flow, its step comprises as follows:
(1) neighbor list is upgraded in the base station
After the start of base station, according to the initialization base station distribution, determine resource flow supply tabulation and resource flow request list;
(2) determine total resources
2a) resource supply and resource expenditure total amount is determined respectively by resource flow supply and request list in the base station;
2b) active user's resource request total amount is calculated in the base station by the service-user sum;
2c) base station is by the clean total resources of resource supply, expenditure and user resources request total amount three read group total current base station;
(3) according to total resources with apart from base station position information, according to following formula computational resource space each point initial strength:
Figure FSB00001121160400011
Wherein, E iTo be d apart from the base station iResource space point intensity,
Figure FSB00001121160400012
Expression gradient operator number, M is the clean resource vector of current base station, κ is constant;
(4) judge whether the base station moves, if the base station motion is arranged, go to step (1); Otherwise, carry out the following step;
(5) judge whether to exist new user to arrive, if there is new user to arrive, go to step 2c); Otherwise, carry out the following step;
(6) experience average resource field intensity in the small area according to resource space point place, according to following formula computational resource spatial point overall strength:
Wherein,
Figure FSB00001121160400014
Resource space point d iThe resource field overall strength at place, E ' iThe resource field mean intensity from different base station that spatial point i experiences,
Figure FSB00001121160400015
It is small area;
(7) according to the resource field overall strength at the base station resource upper limit, resource space point place and with respect to one party to the partial derivative function, calculate the optimal weights function according to following formula:
Figure FSB00001121160400021
Wherein,
Figure FSB00001121160400022
The optimal weights function, It is resource field overall strength
Figure FSB00001121160400024
With respect to E iPartial derivative, E iTo be d apart from the base station iResource space point intensity, λ iTo satisfy λ i(M-M MaxThe variable of)=o, M MaxBe the base station resource amount upper limit,
Figure FSB00001121160400025
Resource space point d iThe resource field overall strength at place, κ is constant;
(8) total resources that has according to optimal weights function and current base station calculates at resource space point d according to following formula iThe optimum resource field intensity at place:
Figure FSB00001121160400026
Wherein,
Figure FSB00001121160400027
Resource space point d iThe optimum resource field intensity at place,
Figure FSB00001121160400028
Optimal weights function, ln are the natural logrithm symbols, and M is that the base station has total resources;
(9) according to optimum resource field intensity, flow the allocation optimum strategy according to following formula computational resource:
Figure FSB00001121160400029
Wherein,
Figure FSB000011211604000210
Resource flow allocation optimum strategy,
Figure FSB000011211604000211
Resource space point d iThe optimum resource field intensity at place;
(10) finish.
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