CN106455078B - A kind of resource allocation methods in the wireless dummy network of combination balance policy - Google Patents
A kind of resource allocation methods in the wireless dummy network of combination balance policy Download PDFInfo
- Publication number
- CN106455078B CN106455078B CN201610927943.8A CN201610927943A CN106455078B CN 106455078 B CN106455078 B CN 106455078B CN 201610927943 A CN201610927943 A CN 201610927943A CN 106455078 B CN106455078 B CN 106455078B
- Authority
- CN
- China
- Prior art keywords
- user
- service provider
- resource allocation
- function
- base station
- 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
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/50—Allocation or scheduling criteria for wireless resources
- H04W72/52—Allocation or scheduling criteria for wireless resources based on load
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The invention discloses the resource allocation methods in a kind of wireless dummy network of combination balance policy, consider the income of infrastructure provider and service provider, by being user's connection and resource allocation two sub-problems by PROBLEM DECOMPOSITION, simplifies the solution of problem, maximize global income.The present invention is based on a kind of strategies of equilibrium, it can be by the connection scheme and Resource Allocation Formula of user come price determination, the price will affect the connection scheme and Resource Allocation Formula of user again simultaneously, pricing function involved in the present invention, demand function, contract of supply, operator can be selected according to their own needs, it ensure that the different demands that operator is able to satisfy under different situations, simultaneously, have benefited from Lagrange duality method, Resource Allocation Formula is distributed scheme, it can be in each base station isolated operation, and fast convergence rate, efficiently solve how the scheme between designing system handling capacity and user resources fairness in distribution.
Description
Technical field
The invention belongs to the radio resource management techniques fields in mobile communication, and in particular to a kind of in wireless communication system
The resource of resource allocation methods and user in wireless dummy network based on balance policy between multiple service providers point
With being connected with base station.
Background technique
Wireless network virtualizes (Wireless NetworkVirtualization, WNV) by by a physical network
Multiple virtual networks are abstracted into, enable multiple operators or user group to share the resource of same physical network, and can be in void
Meet certain isolation between quasi- network.Due to can reduce the infrastructure construction expense and network operation expense of operator
With, reduce operator access threshold, and be conducive to accelerate wireless technology research and deployment process, wireless network virtualization
Have become the hot spot of research.
Wireless network virtualization needs to realize that multiple virtual networks share bottom physical resource, among these just includes nothing
Line resource (power, frequency spectrum etc.) needs suitable wireless resource allocation methods to realize to the reasonable shared of radio resource.Cause
This, one of the research emphasis in radio resource allocation wireless network virtualization always.A kind of effective resource allocation techniques are logical
The radio resource allocation between adjustment service provider (Service Provider, SP) is crossed, and then improves the handling capacity of system.
In the assignment procedure, it is also contemplated that the problem of user selects base station, this is a nondeterministic polynomial difficulty (Non-
Deterministic Polynomial hard, NP hard) problem.Existing two kinds of classical wireless resource allocation methods,
Radio resource allocation i.e. based on maximize handling capacity criterion and the radio resource allocation based on ratio equity criterion.But this point
Have apparent defect with mode: resource can be assigned to the good user of channel condition, and the user of bad channel conditions would become hard to
Fairness to resource, therefore this method of salary distribution is very poor.And absolutely fair distribution will obviously seriously reduce system
Handling capacity, therefore should have a kind of scheme balanced between throughput of system and user resources fairness in distribution.
Summary of the invention
Goal of the invention: in order to overcome the deficiencies in the prior art, provide one kind to maximize infrastructure provider,
The benefit of service provider is target, and in the case where guaranteeing QoS of customer demand, selects optimal user connection side
Case and Resource Allocation Formula.The present invention is based on a kind of strategies of equilibrium, can pass through the connection scheme of user and resource allocation side
Case carrys out price determination, while the price will affect the connection scheme and Resource Allocation Formula of user again, determine involved in the present invention
Valence function, demand function, contract of supply, operator can be selected according to their own needs, ensure that under different situations
The different demands of operator are able to satisfy, meanwhile, have benefited from Lagrange duality method, Resource Allocation Formula is distributed side
Case, can be in each base station isolated operation, and fast convergence rate, efficiently solve how designing system handling capacity and use
Scheme between the resource allocation fairness of family.
Technical solution: to achieve the above object, the present invention is provided in a kind of wireless dummy network of combination balance policy
Resource allocation methods, comprising the following specific steps
Step 1): the acquisition network information, initiation parameter: service provider's number N, number of base stations M in acquisition network
And number of users K, Website Hosting is denoted as { J0,J1...,Ji, wherein macro station J0It indicates, small station { J1,J2,...,JMTable
Show；
Step 2): at the resource allocation moment, user information is acquired by common channel estimation methods and obtains user's
Information calculates the SINR of user by these information:
WhereinIt is channel gain, comprising path loss, shade is weak, antenna gain, and j indicates base station number, n and k points
Not Biao Shi service provider number and Customs Assigned Number, each time execute resource allocation methods when,One can be regarded as often
Number, PjRepresent the transmission power for the base station j that user present position receives, σ2Indicate the power of noise；
Step 3): the unit price and pay off function of user are determined: when executing each time, needs to select unit price and the user of user
Pay off function indicate cost consumed by user, in order to realize the balance between network performance and user fairness, user
Pay off function to have a continuously differentiable, monotonic increase, stringent recessed property；On the other hand, the unit price of user is then a constant,
The unit price of each user is possible to identical, it is also possible to and it is different, the unit price of user is denoted as { α1,α2...αK, wherein αkIt indicates
The unit price of user k, the unit price of user and the pay off function of user are preset by operator, are configured i.e. in method operation
It can；
Step 4): determining the unit price of service provider and the pay off function of service provider, and wireless dummy resource can be seen
Doing is commodity, and infrastructure provider provides wireless dummy resource, is considered the supplier of these commodity, and service provides
Quotient pays certain cost and obtains wireless dummy resource, is considered consumer, to first confirm that before method operation
The pricing strategy of virtual resource, for different service providers, infrastructure provider takes different charge method and list
The unit price of service provider is denoted as { β by valence1,β2...βI, βiIndicate the unit price for the service provider that number is i, service provides
The pay off function of quotient is formulated by service provider and infrastructure provider joint consultation, is pre-entered into system, is being carried out
When resource allocation, different service providers selects corresponding pay off function to execute, and has obtained the unit price of service provider
After the pay off function of service provider, system-computed goes out service provider's price to be paid；
Step 5): determine objective function: system determines different objective functions, according to different demands by adjusting mesh
Scalar functions adjust the scheme of the connection of user and the distribution of resource, by step 3) and step 4), obtain user and service provides
After the unit price and pay off function of quotient, the income of service provider, which is subtracted equal to the income obtained from user to infrastructure, to be mentioned
For the expenditure of quotient's payment, with { π1,...,πNIndicate, πnThe income that number obtains as n service provider is represented, infrastructure mentions
The income obtained for quotient is equal to the expenditure that service provider is paid to it, uses π0It indicates；From economic angle, Ke Yixuan
Pareto optimality is selected as a kind of objective function, Pareto optimality (Pareto Optimality), also referred to as Pareto efficiency
(Pareto efficiency) refers to a kind of perfect condition of resource allocation, it is assumed that intrinsic group and assignable money
Source, from a kind of distribution state into the variation of another state, under the premise of not making anyone circumstances degenerate, so that at least
One people becomes more preferably, and Pareto-optimality is exactly can not have the leeway of more Pareto improvements, in other words, pa again
It is path and the method for reaching Pareto optimality that tired support, which is improved, and Pareto optimality is fair and efficiency " ideal kingdom ".
According to Pareto optimality theory, problem can be indicated are as follows:
In formulaIndicate the coefficient of connection of user and base station and the resource ratio that base station is distributed to the user, item
Part C1 illustrates each user at most and can only connect to a base station, and condition C 2 illustrates that the use being connected with him is distributed in each base station
The resource at family is no more than the resource that base station is possessed, if condition C 3 illustrates that a user is connected to some base station, this
A base station has to distribute resource for this user, and C4 illustrates the case where user connects base station, if user is connected to some
Base station is then that value is 1, otherwise, value 0；
Step 6): according to problem 2) the characteristics of, by problem 2) decompose it is problematic 3) and problem 5) two parts, problem 3) be base
The income of Infrastructure provider, problem 5) be service provider income: first by resource allocation improve infrastructure provide
The income of quotient, this some are expressed as:
Wherein n indicates the number of service provider, βnIndicate the unit price of service provider, VnThe service for indicating that number is n mentions
For the resource quantity that quotient obtains, U () indicates the pay off function of service provider, obtains problem 3) a subproblem:
This is the subproblem of infrastructure provider part, and above-mentioned formula (4) is meant that through user-association and resource
Distribution maximizes the income of infrastructure provider, according to problem 4) the characteristics of, this some is expressed as:
Here ln (Rn,k) and CnTwo specific pays off function, in addition, problem 2) another subproblem be clothes
The income of business provider:
This is the subproblem of Service Provider part, and above-mentioned formula (5) is meant that through user-association and resource allocation
Maximize the income of service provider；
Step 7): Solve problems 4): in problem 4) inWithIt interdepends, intercouples, it is difficult to which direct solution leads to
Cross problem 4) it resolves into two sub-problems and solves, it is if user-association scheme determines, i.e., allIt is known that so
Problem reform into aboutA subproblem, so assuming initially thatAll it has been determined that the payment of service provider simultaneously
Function and unit price (assuming that only there are two types of the unit prices of service provider) also all determine, then problem is just to solve for
It is exactly the V of above-mentioned formulan,k, whereinIndicate the rate of user, WjIndicate the money that the base station is possessed
Source number can prove problem 6) it is stringent convex problem, according to convex optimum theory, use KKT (Karush-Kuhn-
Tucker) condition solves to obtain
Wherein μjIt is a Lagrange coefficient, passes through μj=max { β1|κn,k|-β2Wj, 0 } and it obtains, wherein | κn,k| it indicates
The number of user after obtaining resource allocation policy, can determine user-association strategy, by what is obtained according to Resource Allocation FormulaGeneration return problem 4) in obtain
Solve problems 7), obtain the connection scheme of user
Step 8): after infrastructure provider part subproblem is solved, Service Provider part is next solved
Subproblem: according to Pareto optimality theory
With
Max Ω (α), Ω (α)=ΣnπnProblem 9)
Wherein Ω (α) indicates the sum of the income of all service providers.
Problem 9) with problem 4) it is similar, by solving the problems, such as method 4), by problem 9) be decomposed into user-association and resource
Two sub-problems are distributed, resource allocation subproblem is solved using method of Lagrange multipliers, resource allocation is obtained by KKT condition
As a result, in generation, returns problem 9 again after obtaining Resource Allocation Formula), obtain the association scheme of user；
Step 9): after Resource Allocation Formula and user-association scheme are determined by step 8), determine that reasonable service mentions
For the price of quotient, the specific method is as follows:
According to the result of Resource Allocation Formula above, it can be seen that if some βnIt is bigger, infrastructure provider
It can be more willing to resource allocation to the partial service provider, if instead βnSmaller, infrastructure provider is then more willing to
Other service providers are given resource allocation.So can be by adjusting βn, provide to adjust infrastructure in service offer
The ratio of resource allocation between quotient can obtain the price of optimal service provider, the process of iteration by way of iteration
In need to be arranged demand function and contract of supply, use Φ respectivelyD(t) and ΦS(t) demand function when the t times iteration of expression and confession
Function is answered, the two functions can be arranged in infrastructure provider according to the actual needs；
Step 10): initialization β=βinitAnd t=0, βinitIt is the initial value of price β, initializes iteration step length λ, it can be by transporting
Seek quotient's setting, after the price that step 4) is used is set as price β (t), operating procedure 9) method can obtain it is optimal
Resource Allocation Formula and user-association scheme recalculate Φ after obtaining resource scheme and user-association schemeD(t) and ΦS
(t), formula (10) is recycled to calculate the Φ of the t times iterationD(t)-ΦS(t) and β (t+1):
β (t+1)=β (t)+λ (ΦD(t)-ΦS(t)) problem 10)
Price is updated, until | ΦD(t)-ΦS(t) | < ε, ε > 0, ε is the positive number of a very little, can be set by operator,
Price is stable at this time, which is exactly required most reasonable service provider unit price；
Step 11): terminate: service provider's needed for setting method for the unit price of finally obtained service provider
Unit price carries out the calculating of user's connection and resource allocation.
Further, the β in the step 4)iIt is preset by operator.
The utility model has the advantages that compared with prior art, the present invention considering infrastructure provider and the receipts of service provider simultaneously
Benefit, be finally reached Pareto optimality in economics as a result, by being user's connection and two sons of resource allocation by PROBLEM DECOMPOSITION
Problem simplifies the solution of problem, maximizes global income；The resource allocation methods based on balance policy proposed pass through true
After determining resource allocation and user's connection method, the unit price of adjustment service provider can be removed dynamically to ensure that infrastructure provides
Quotient's charge is more reasonable, and using this unit price feedback into Resource Allocation Formula；Meanwhile this method is provided in the service of determination
Quotient unit price after, determine user connection and resource allocation method be it is distributed, can the isolated operation on each base station,
And algorithm the convergence speed is fast, can obtain higher system effectiveness with lower computation complexity；Have benefited from balance policy, mentions
Method out can effectively calculate unit price, obtain reasonable Resource Allocation Formula and user's connection scheme, have benefited from each step
Customization, the method for proposition can effectively be carried out according to practical situation while guaranteeing service quality it is customized, can
To meet the unique demand of different operators, operator can select different pays off function according to their own needs, supply letter
Several and demand function to carry out algorithm customized in conjunction with oneself demand.
Detailed description of the invention
Fig. 1 is flow diagram of the invention.
Specific embodiment
In the following with reference to the drawings and specific embodiments, the present invention is furture elucidated, it should be understood that these embodiments are merely to illustrate
It the present invention rather than limits the scope of the invention, after the present invention has been read, those skilled in the art are to of the invention each
The modification of kind equivalent form falls within the application range as defined in the appended claims.
As shown in Figure 1, the present invention provides the resource allocation methods in a kind of wireless dummy network of combination balance policy, packet
Include step in detail below:
Step 1): the acquisition network information, initiation parameter: service provider's number N, number of base stations M in acquisition network
And number of users K, Website Hosting is denoted as { J0,J1...,Ji, wherein macro station J0It indicates, small station { J1,J2,...,JMTable
Show；
Step 2): at the resource allocation moment, user information is acquired by common channel estimation methods and obtains user's
Information calculates the SINR of user by these information:
WhereinIt is channel gain, comprising path loss, shade is weak, antenna gain, and j indicates base station number, n and k points
Not Biao Shi service provider number and Customs Assigned Number, each time execute resource allocation methods when,One can be regarded as often
Number, PjRepresent the transmission power for the base station j that user present position receives, σ2Indicate the power of noise；
Step 3): the unit price and pay off function of user are determined: when executing each time, needs to select unit price and the user of user
Pay off function indicate cost consumed by user, in order to realize the balance between network performance and user fairness, user
Pay off function to have a continuously differentiable, monotonic increase, stringent recessed property；On the other hand, the unit price of user is then a constant,
The unit price of each user is possible to identical, it is also possible to and it is different, the unit price of user is denoted as { α1,α2...αK, wherein αkIt indicates
The unit price of user k, the unit price of user and the pay off function of user are preset by operator, are configured i.e. in method operation
It can；
Step 4): determining the unit price of service provider and the pay off function of service provider, and wireless dummy resource can be seen
Doing is commodity, and infrastructure provider provides wireless dummy resource, is considered the supplier of these commodity, and service provides
Quotient pays certain cost and obtains wireless dummy resource, is considered consumer, to first confirm that before method operation
The pricing strategy of virtual resource, for different service providers, infrastructure provider takes different charge method and list
The unit price of service provider is denoted as { β by valence1,β2...βI, βiIndicate the unit price for the service provider that number is i, βiBy runing
Quotient presets or sets again after being calculated the step of passing through below, and the pay off function of service provider is by servicing
Provider and infrastructure provider joint consultation are formulated, and are pre-entered into system, when carrying out resource allocation, different clothes
Business provider selects corresponding pay off function to execute, and has obtained the unit price of service provider and the payment letter of service provider
After number, system-computed goes out service provider's price to be paid；
Step 5): determine objective function: system determines different objective functions, according to different demands by adjusting mesh
Scalar functions adjust the scheme of the connection of user and the distribution of resource, by step 3) and step 4), obtain user and service provides
After the unit price and pay off function of quotient, the income of service provider, which is subtracted equal to the income obtained from user to infrastructure, to be mentioned
For the expenditure of quotient's payment, with { π1,...,πNIndicate, πnThe income that number obtains as n service provider is represented, infrastructure mentions
The income obtained for quotient is equal to the expenditure that service provider is paid to it, uses π0It indicates；From economic angle, Ke Yixuan
Pareto optimality is selected as a kind of objective function, Pareto optimality (Pareto Optimality), also referred to as Pareto efficiency
(Pareto efficiency) refers to a kind of perfect condition of resource allocation, it is assumed that intrinsic group and assignable money
Source, from a kind of distribution state into the variation of another state, under the premise of not making anyone circumstances degenerate, so that at least
One people becomes more preferably, and Pareto-optimality is exactly can not have the leeway of more Pareto improvements, in other words, pa again
It is path and the method for reaching Pareto optimality that tired support, which is improved, and Pareto optimality is fair and efficiency " ideal kingdom ", according to
Pareto optimality is theoretical, and problem can indicate are as follows:
In formulaIndicate the coefficient of connection of user and base station and the resource ratio that base station is distributed to the user, item
Part C1 illustrates each user at most and can only connect to a base station, and condition C 2 illustrates that the use being connected with him is distributed in each base station
The resource at family is no more than the resource that base station is possessed, if condition C 3 illustrates that a user is connected to some base station, this
A base station has to distribute resource for this user, and C4 illustrates the case where user connects base station, if user is connected to some
Base station is then that value is 1, otherwise, value 0；
Step 6): according to problem 2) the characteristics of, by problem 2) decompose it is problematic 3) and problem 5) two parts, problem 3) be base
The income of Infrastructure provider, problem 5) be service provider income: first by resource allocation improve infrastructure provide
The income of quotient, this some are expressed as:
Wherein n indicates the number of service provider, βnIndicate the unit price of service provider, VnThe service for indicating that number is n mentions
For the resource quantity that quotient obtains, U () indicates the pay off function of service provider, obtains problem 3) a subproblem:
This is the subproblem of infrastructure provider part, and above-mentioned formula (4) is meant that through user-association and resource
Distribution maximizes the income of infrastructure provider, according to problem 4) the characteristics of, this some is expressed as:
Here ln (Rn,k) and CnTwo specific pays off function, in addition, problem 2) another subproblem be clothes
The income of business provider:
This is the subproblem of Service Provider part, and above-mentioned formula (5) is meant that through user-association and resource allocation
Maximize the income of service provider；
Step 7): Solve problems 4): in problem 4) inWithIt interdepends, intercouples, it is difficult to which direct solution leads to
Cross problem 4) it resolves into two sub-problems and solves, it is if user-association scheme determines, i.e., allIt is known that so
Problem reform into aboutA subproblem, so assuming initially thatAll it has been determined that the payment of service provider simultaneously
Function and unit price (assuming that only there are two types of the unit prices of service provider) also all determine, then problem is just to solve for
It is exactly the V of above-mentioned formulan,k, whereinIndicate the rate of user, WjIndicate the money that the base station is possessed
Source number can prove problem 6) it is stringent convex problem, according to convex optimum theory, use KKT (Karush-Kuhn-
Tucker) condition solves to obtain
Wherein μjIt is a Lagrange coefficient, passes through μj=max { β1|κn,k|-β2Wj, 0 } and it obtains, wherein | κn,k| it indicates
The number of user after obtaining resource allocation policy, can determine user-association strategy, by what is obtained according to Resource Allocation FormulaGeneration return problem 4) in obtain
Solve problems 7), obtain the connection scheme of user
Step 8): after infrastructure provider part subproblem is solved, Service Provider part is next solved
Subproblem: according to Pareto optimality theory
With
Max Ω (α), Ω (α)=ΣnπnProblem 9)
Wherein Ω (α) indicates the sum of the income of all service providers.
Problem 9) with problem 4) it is similar, by solving the problems, such as method 4), by problem 9) be decomposed into user-association and resource
Two sub-problems are distributed, resource allocation subproblem is solved using method of Lagrange multipliers, resource allocation is obtained by KKT condition
As a result, in generation, returns problem 9 again after obtaining Resource Allocation Formula), obtain the association scheme of user；
Step 9): after Resource Allocation Formula and user-association scheme are determined by step 8), determine that reasonable service mentions
For the price of quotient, the specific method is as follows:
According to the result of Resource Allocation Formula above, it can be seen that if some βnIt is bigger, infrastructure provider
It can be more willing to resource allocation to the partial service provider, if instead βnSmaller, infrastructure provider is then more willing to
Other service providers are given resource allocation.So can be by adjusting βn, provide to adjust infrastructure in service offer
The ratio of resource allocation between quotient can obtain the price of optimal service provider, the process of iteration by way of iteration
In need to be arranged demand function and contract of supply, use Φ respectivelyD(t) and ΦS(t) demand function when the t times iteration of expression and confession
Function is answered, the two functions can be arranged in infrastructure provider according to the actual needs；
Step 10): initialization β=βinitAnd t=0, βinitIt is the initial value of price β, initializes iteration step length λ, it can be by transporting
Seek quotient's setting, after the price that step 4) is used is set as price β (t), operating procedure 9) method can obtain it is optimal
Resource Allocation Formula and user-association scheme recalculate Φ after obtaining resource scheme and user-association schemeD(t) and ΦS
(t), formula (10) is recycled to calculate the Φ of the t times iterationD(t)-ΦS(t) and β (t+1):
β (t+1)=β (t)+λ (ΦD(t)-ΦS(t)) problem 10)
Price is updated, until | ΦD(t)-ΦS(t) | < ε, ε > 0, ε is the positive number of a very little, can be set by operator,
Price is stable at this time, which is exactly required most reasonable service provider unit price；
Step 11): terminate: service provider's needed for setting method for the unit price of finally obtained service provider
Unit price carries out the calculating of user's connection and resource allocation.
Claims (2)
1. the resource allocation methods in a kind of wireless dummy network of combination balance policy, it is characterised in that: including in detail below
Step:
Step 1): the acquisition network information, initiation parameter: service provider's number N, number of base stations M and use in acquisition network
Amount mesh K, is denoted as { J for Website Hosting0,J1...,Ji, wherein macro station J0It indicates, small station { J1,J2,...,JMIndicate；
Step 2): at the resource allocation moment, acquiring user information by common channel estimation methods and obtain the information of user,
By these information, the SINR of user is calculated:
WhereinIt is channel gain, comprising path loss, shade is weak, antenna gain, and j indicates base station number, and n and k distinguish table
Show service provider's number and Customs Assigned Number, when executing resource allocation methods each time,A constant, P can be regarded asj
Represent the transmission power for the base station j that user present position receives, σ2Indicate the power of noise；
Step 3): the unit price and pay off function of user are determined: when executing each time, needs to select the unit price of user and the branch of user
Function is paid to indicate cost consumed by user, the unit price of user is denoted as { α1,α2...αK, wherein αkIndicate the list of user k
Valence, the unit price of user and the pay off function of user are preset by operator, are configured in method operation；
Step 4): determining the unit price of service provider and the pay off function of service provider, will first really before method operation
The pricing strategy for recognizing virtual resource, for different service providers, infrastructure provider take different charge method and
The unit price of service provider is denoted as { β by unit price1,β2...βI, βiIndicate the unit price for the service provider that number is i, service mentions
Formulated, be pre-entered into system by service provider and infrastructure provider joint consultation for the pay off function of quotient, into
When row resource allocation, different service providers selects corresponding pay off function to execute, and has obtained the list of service provider
After valence and the pay off function of service provider, system-computed goes out service provider's price to be paid；
Step 5): determine objective function: system determines different objective functions according to different demands, by adjusting target letter
Number, adjusts the scheme of the connection of user and the distribution of resource, by step 3) and step 4), obtains user and service provider
After unit price and pay off function, the income of service provider is equal to the income obtained from user and subtracts to infrastructure provider
The expenditure of payment, with { π1,...,πNIndicate, πnRepresent the income that number obtains as n service provider, infrastructure provider
Obtained income is equal to the expenditure that service provider is paid to it, uses π0It indicates；
According to Pareto optimality theory, problem can be indicated are as follows:
In formulaIndicate the coefficient of connection of user and base station and the resource ratio that base station is distributed to the user, condition C 1
Illustrate each user at most and can only connect to a base station, condition C 2 illustrates that the user's being connected with him distributed in each base station
Resource is no more than the resource that base station is possessed, if condition C 3 illustrates that a user is connected to some base station, this base
Station has to distribute resource for this user, and C4 illustrates the case where user connects base station, if user is connected to some base station
It is then value is 1, otherwise, value 0；
Step 6): according to problem 2) the characteristics of, by problem 2) decompose it is problematic 3) and problem 5) two parts, problem 3) be that basis is set
Apply the income of provider, problem 5) be service provider income: first by resource allocation improve infrastructure provider
Income, this some are expressed as:
Wherein n indicates the number of service provider, βnIndicate the unit price of service provider, VnIndicate the service provider that number is n
Obtained resource quantity, U () indicate service provider pay off function, obtain problem 3) a subproblem:
This is the subproblem of infrastructure provider part, and above-mentioned formula (4) is meant that through user-association and resource allocation
The income for maximizing infrastructure provider, according to problem 4) the characteristics of, this some is expressed as:
Here ln (Rn,k) and CnTwo specific pays off function, in addition, problem 2) another subproblem be that service mentions
For the income of quotient:
This is the subproblem of Service Provider part, and above-mentioned formula (5) is meant that maximum by user-association and resource allocation
Change the income of service provider；
Step 7): Solve problems 4): by by problem 4) resolve into two sub-problems and solve, it is assumed thatAll it has been determined that
The pay off function of service provider and unit price also all determine simultaneously, then problem is just to solve for
It is exactly the V of above-mentioned formulan,k, whereinIndicate the rate of user, WjIndicate the number of resources that the base station is possessed
Mesh solves to obtain using KKT condition
Wherein μjIt is a Lagrange coefficient, passes through μj=max { β1|κn,k|-β2Wj, 0 } and it obtains, wherein | κn,k| indicate user
Number, after obtaining resource allocation policy, user-association strategy can be determined according to Resource Allocation Formula, by what is obtained
Generation return problem 4) in obtain
Solve problems 7), obtain the connection scheme of user
Step 8): after infrastructure provider part subproblem is solved, the son for next solving Service Provider part is asked
Topic: according to Pareto optimality theory
With
Max Ω (α), Ω (α)=ΣnπnProblem 9)
Wherein Ω (α) indicates the sum of the income of all service providers；
By problem 9) it is decomposed into user-association and resource allocation two sub-problems, resource allocation is solved using method of Lagrange multipliers
Subproblem, by KKT condition obtain resource allocation as a result, in generation, returns problem 9 again after obtaining Resource Allocation Formula), obtain
The association scheme of user；
Step 9): after Resource Allocation Formula and user-association scheme are determined by step 8), reasonable service provider is determined
Price, the specific method is as follows:
By adjusting βn, the ratio of resource allocation among service providers is provided to adjust infrastructure, iteration can be passed through
Mode obtains the price of optimal service provider, needs that demand function and contract of supply is arranged during iteration, uses respectively
ΦD(t) and ΦS(t) demand function when the t times iteration of expression and contract of supply, infrastructure provider can be according to actual
Need to be arranged the two functions；
Step 10): initialization β=βinitAnd t=0, βinitIt is the initial value of price β, initializes iteration step length λ, it can be by operator
Setting, after the price that step 4) is used is set as price β (t), operating procedure 9) method can obtain optimal resource
Allocation plan and user-association scheme recalculate Φ after obtaining resource scheme and user-association schemeD(t) and ΦS(t),
Formula (10) are recycled to calculate the Φ of the t times iterationD(t)-ΦS(t) and β (t+1):
β (t+1)=β (t)+λ (ΦD(t)-ΦS(t)) problem 10)
Price is updated, until | ΦD(t)-ΦS(t) | < ε, ε > 0, ε is the positive number of a very little, can be set by operator, at this time
Price is stable, which is exactly required most reasonable service provider unit price；
Step 11): terminate: the list of service provider needed for setting method for the unit price of finally obtained service provider
Valence carries out the calculating of user's connection and resource allocation.
2. the resource allocation methods in a kind of wireless dummy network of combination balance policy according to claim 1, special
Sign is: the β in the step 4)iIt is preset by operator.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610927943.8A CN106455078B (en) | 2016-10-31 | 2016-10-31 | A kind of resource allocation methods in the wireless dummy network of combination balance policy |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610927943.8A CN106455078B (en) | 2016-10-31 | 2016-10-31 | A kind of resource allocation methods in the wireless dummy network of combination balance policy |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106455078A CN106455078A (en) | 2017-02-22 |
| CN106455078B true CN106455078B (en) | 2019-07-12 |
Family
ID=58179014
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610927943.8A Active CN106455078B (en) | 2016-10-31 | 2016-10-31 | A kind of resource allocation methods in the wireless dummy network of combination balance policy |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106455078B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107018528B (en) * | 2017-04-23 | 2020-04-03 | 西安电子科技大学 | Equivalent capacity-based wireless network virtualization method in single-cell LTE-A system |
| CN107172710B (en) * | 2017-04-23 | 2019-12-06 | 西安电子科技大学 | resource allocation and service access control method based on virtual subnet |
| CN107172606B (en) * | 2017-06-29 | 2021-02-23 | 南京邮电大学 | Method for distributing sharable green energy combined spectrum in wireless network |
| CN107708214B (en) * | 2017-09-30 | 2021-02-02 | 重庆邮电大学 | Network utility maximization virtual resource allocation method based on Lyapunov |
| CN108365991B (en) * | 2018-02-26 | 2021-09-07 | 重庆邮电大学 | Downlink power resource allocation method facing wireless network virtualization environment |
| CN109272405B (en) * | 2018-09-30 | 2020-09-29 | 大唐碳资产有限公司 | Carbon asset transaction method and system |
| CN111356141B (en) * | 2020-03-06 | 2022-08-30 | 深圳清华大学研究院 | Distributed resource allocation method for inter-operator spectrum sharing based on network slice |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102333362A (en) * | 2011-10-26 | 2012-01-25 | 北京交通大学 | Distributed-price-algorithm-based cognitive radio power control method |
| CN102917362A (en) * | 2012-10-12 | 2013-02-06 | 南京邮电大学 | Multi-domain resource allocation method based on collaborative optimization in ubiquitous wireless network |
| CN103313251A (en) * | 2013-06-04 | 2013-09-18 | 北京邮电大学 | Multi-cell cooperative resource allocation method based on potential game theory |
| CN103781118A (en) * | 2014-01-14 | 2014-05-07 | 西安电子科技大学 | Heterogeneous wireless network access control and resource distribution joint method based on multiple services |
| CN104660394A (en) * | 2015-03-23 | 2015-05-27 | 中国矿业大学 | Spectrum resource allocation method based on utility function and price mechanism |
| CN105959234A (en) * | 2016-06-30 | 2016-09-21 | 南京理工大学 | Load balance resource optimization method under safety perceptive cloud radio access network |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040267897A1 (en) * | 2003-06-24 | 2004-12-30 | Sychron Inc. | Distributed System Providing Scalable Methodology for Real-Time Control of Server Pools and Data Centers |
| US8897828B2 (en) * | 2004-08-12 | 2014-11-25 | Intellectual Ventures Holding 81 Llc | Power control in a wireless communication system |
| US20110130150A1 (en) * | 2009-12-01 | 2011-06-02 | Nokia Corporation | Methods and apparatus for service-aware energy saving and load balancing operations |
-
2016
- 2016-10-31 CN CN201610927943.8A patent/CN106455078B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102333362A (en) * | 2011-10-26 | 2012-01-25 | 北京交通大学 | Distributed-price-algorithm-based cognitive radio power control method |
| CN102917362A (en) * | 2012-10-12 | 2013-02-06 | 南京邮电大学 | Multi-domain resource allocation method based on collaborative optimization in ubiquitous wireless network |
| CN103313251A (en) * | 2013-06-04 | 2013-09-18 | 北京邮电大学 | Multi-cell cooperative resource allocation method based on potential game theory |
| CN103781118A (en) * | 2014-01-14 | 2014-05-07 | 西安电子科技大学 | Heterogeneous wireless network access control and resource distribution joint method based on multiple services |
| CN104660394A (en) * | 2015-03-23 | 2015-05-27 | 中国矿业大学 | Spectrum resource allocation method based on utility function and price mechanism |
| CN105959234A (en) * | 2016-06-30 | 2016-09-21 | 南京理工大学 | Load balance resource optimization method under safety perceptive cloud radio access network |
Non-Patent Citations (2)
| Title |
|---|
| "基于博弈论的无线资源分配研究";曾令康;《中国优秀博士学位论文全文数据库信息科技辑》;20100505;全文 |
| "异构无线网络中用户分配和资源分配研究";方彬;《中国优秀博士学位论文全文数据库信息科技辑》;20150401;全文 |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106455078A (en) | 2017-02-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106455078B (en) | A kind of resource allocation methods in the wireless dummy network of combination balance policy | |
| Luong et al. | Applications of economic and pricing models for resource management in 5G wireless networks: A survey | |
| Du et al. | Contract design for traffic offloading and resource allocation in heterogeneous ultra-dense networks | |
| Zhu et al. | Overview of demand management in smart grid and enabling wireless communication technologies | |
| Li et al. | Coalitional game theoretic approach for secondary spectrum access in cooperative cognitive radio networks | |
| Tsaousoglou et al. | Personalized real time pricing for efficient and fair demand response in energy cooperatives and highly competitive flexibility markets | |
| CN103687023B (en) | Optimization Radio Resource method based on time delay differentiated service and proportionality rate constraint | |
| CN108990067B (en) | Energy efficiency control method applied to ultra-dense heterogeneous network | |
| Huang | Market mechanisms for cooperative spectrum trading with incomplete network information | |
| Le et al. | Joint cache allocation with incentive and user association in cloud radio access networks using hierarchical game | |
| Tsaousoglou et al. | Demand response as a service: Clearing multiple distribution-level markets | |
| Kim | An adaptive smart grid management scheme based on the coopetition game model | |
| Wu et al. | Distributed reinforcement learning algorithm of operator service slice competition prediction based on zero-sum markov game | |
| Jia et al. | Social-aware learning-based online energy scheduling for 5G integrated smart distribution power grid | |
| Kim et al. | Profitable and energy-efficient resource optimization for heterogeneous cloud-based radio access networks | |
| CN109729526B (en) | Dynamic spectrum allocation method based on matching theory in heterogeneous network | |
| Kim | A new triple bargaining game-based energy management scheme for hierarchical smart grids | |
| Wang et al. | User oriented resource management with virtualization: A hierarchical game approach | |
| Debbabi et al. | Game theory for B5G upper-tier resource allocation using network slicing | |
| Reyhanian et al. | Double-auction-based energy trading for small cell networks with energy harvesting | |
| Reyhanian et al. | A matching-game-based energy trading for small cell networks with energy harvesting | |
| Le et al. | On a new incentive and market based framework for multi-tier shared spectrum access systems | |
| Alrabaee et al. | A game theory approach: Dynamic behaviours for spectrum management in cognitive radio network | |
| Jiang et al. | Research on Resource Allocation Algorithm of 5G Network in Multi-Business Smart Grid | |
| CN109219069B (en) | Energy distribution and pricing method of green backhaul network based on cooperation of multiple operators |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20210326 Address after: 201306 building C, No. 888, Huanhu West 2nd Road, Lingang New Area, Pudong New Area, Shanghai Patentee after: Shanghai Hanxin Industrial Development Partnership (L.P.) Address before: No.6, Dongda Road, Taishan new village, Pukou District, Nanjing City, Jiangsu Province, 210096 Patentee before: SOUTHEAST University |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20230920 Address after: 201615 room 301-6, building 6, no.1158, Jiuting Central Road, Jiuting Town, Songjiang District, Shanghai Patentee after: White box (Shanghai) Microelectronics Technology Co.,Ltd. Address before: 201306 building C, No. 888, Huanhu West 2nd Road, Lingang New Area, Pudong New Area, Shanghai Patentee before: Shanghai Hanxin Industrial Development Partnership (L.P.) |
|
| TR01 | Transfer of patent right |