CN103856996B - A kind of joint Power control and connection control method - Google Patents
A kind of joint Power control and connection control method Download PDFInfo
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- CN103856996B CN103856996B CN201410048818.0A CN201410048818A CN103856996B CN 103856996 B CN103856996 B CN 103856996B CN 201410048818 A CN201410048818 A CN 201410048818A CN 103856996 B CN103856996 B CN 103856996B
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Abstract
It is an object of the invention to provide a kind of joint Power control and connection control method.The present invention is based on stackelberg betting model, and using Home eNodeB as leader, used as subordinate, after Home eNodeB carries out the decision-making of transmission power, grand user can correspondingly make the decision-making for accessing selection to grand user.Power system capacity is maximized as target, carry out game, be finally reached equilibrium state, determine the transmission power strategy of Home eNodeB and the access strategy of grand user between leadership and subordinate layer.The method is directed to deficiency of the game method of general Power Control in home base station network in terms of the interference that grand user is subject to is reduced, the game method of joint Power control and Access Control is proposed, and allows grand user more positive effect to be played in terms of systematic entirety energy is improved.
Description
Technical field
The present invention relates to a kind of joint Power control and connection control method, and in particular to provide in a kind of home base station network
In the scheme of source distribution, the method for the Access Control of the transmission power control of Home eNodeB and grand user belongs to communication technology neck
Domain.
Background technology
Future there will be over 50% speech business and the data service more than 70% all will occur in interior, therefore provide high
The indoor voice-and-data business of quality is very necessary.And with the development of radio communication, in network, more adopt higher frequency
Section deployment wireless coverage.From electromagnetic theory, the penetration capacity of the higher radio wave of frequency is poorer, therefore, high-frequency signal
Decay after through walls is larger, causes in-door covering quality relatively poor.If strengthened using the traditional approach of deployment macro base station
In-door covering, one side coverage effect are limited, and face the difficult problems such as base station selection；On the other hand, strengthen indoor using macro base station
What is covered is relatively costly, is unfavorable for large scale deployment.Home eNodeB can solve above-mentioned two problems simultaneously, effectively be lifted indoor
Radio signal quality.
Home eNodeB coverage is little, transmission power is low, as effective supplement of macro base station, can improve regional area and cover
Lid is not enough, capacity and frequency spectrum resource are using limited problem.Household base station technology be a kind of application indoors environment or other
Base station equipment under small range overlay environment, can avoid penetrating the decay that building brings, support 2G, 2.5G, 3G or even 4G
Product, is matched with outdoor macro base station, is arranged using identical wireless communication system, supports the switching of indoor and outdoor base station.Family
Base station passes through digital subscriber line（DSL）Or fiber bandwidth is connected to internet, then internet is connected to telecommunication carrier
Network.
However, with Home eNodeB dispose it is more dense, the interference of the cross-layer that exists between macro base station and Home eNodeB and
Co-layer interference between neighboring home base station becomes the problem of urgent need to resolve.Therefore, the interference pipe in Home eNodeB double-layer network
Reason becomes new challenge.In recent years, many researchs reduce interference from the angle of reasonable management Radio Resource.In macrocellular and family
Under the scene that front yard base station coexists, efficient radio resource allocation algorithm is used in combination, systematic function can be greatly improved.
Game Theory is widely used in the resource management in Home eNodeB.Because game theory is one kind by setting up mathematics
Model, carrys out the effective tool of aid decision making person's analysis and trade-off decision, and the resource management in Home eNodeB is mainly concerned with money
How source is distributed in double-layer network, and the assigning process of the resource such as power, frequency spectrum is exactly a kind of decision-making.
Although many methods carry out Power Control based on game theory, throughput of system is improve to a certain extent.But it is right
In some grand users from macro base station farther out and near Home eNodeB, Power Control is only carried out still it cannot be guaranteed that this grand user
Performance, and influence whether the performance of domestic consumer.
The content of the invention
Technical problem：It is an object of the invention to provide a kind of based on the control of game theoretic joint Power and Access Control side
Method, the method can solve the problem that the co-layer between the cross-layer interference existed between macro base station and Home eNodeB and neighboring home base station is done
Problem is disturbed, even for some grand users from macro base station farther out and near Home eNodeB, the method also can guarantee that this grand use
The performance at family, and the performance of domestic consumer will not also be greatly affected.The present invention is based on stackelberg betting model, family
Front yard base station is leader, and grand user is subordinate.On the one hand, Home eNodeB carries out Power Control；On the other hand, grand user according to
Itself geographical position residing in a network and the transmission power information of different base station, selection can make the base station of its throughput-optimal
To access.By joint Power control and Access Control, throughput of system can be optimized, especially largely improve grand use
The handling capacity at family, what the grand user of reduction was subject to are disturbed.
Technical scheme：The present invention sets up model by Game Theory, the resource being applied in Home eNodeB double-layer network
Distribution.The invention establishes the stackelberg betting model of a kind of Home eNodeB and grand user's combined optimization system performance,
Home eNodeB first carries out power decision as leader；Grand user is believed according to the transmission power of Home eNodeB as subordinate
Result with carrying out access trade-off decision later, and is fed back to Home eNodeB by breath.
Specifically method is：
1）Initialization system parameter：
In each base station, number of users destination aggregation (mda) initial value is User_Collect=[M, T ..., T], gives macro base station
Transmission power is P0, Home eNodeB Initial Trans { Pj}(0), j={ 1,2 ... N }, wherein M are random distribution in macrocell
Grand number of users, N are the number of Home eNodeB in the macrocell, and T is the number of domestic consumer in each Home eNodeB；
2）The decision process of subordinate layer can be modeled as Access Control subgame：
In known leadership（Home eNodeB）Initial power { Pj}(0)Under conditions of, subordinate layer（Grand user）It is rich by many wheels
Play chess and find out maximum utility UMUEi(Si) access balance policyEach wheel gambling process is each grand user by poor
Lift the possible strategy of limited kind to determine the optimal policy of this wheel；
Build subordinate layer utility function UMUEi(Si) expression be：
In formula, tactful SiRepresent that grand user i accesses SiIndividual base station, i={ 1,2 ..., M }, B_total are each base stations
Total bandwidth, bandwidth are averagely allocated to all users in base station,It is SiThe number of users of individual base station,Refer to base station SiArrive
The Signal to Interference plus Noise Ratio of grand user i,It is SiThe transmission power of individual base station, PkIt is the transmission power of other base stations,It is SiIndividual base
Stand the channel gain of grand user i, hk,iIt is channel gain of other base stations to user i；
3）The decision process of leadership can be modeled as Power Control subgame:
According to subordinate layer（Grand user）FeedbackInformation updating User_Collect, leadership（Each Home eNodeB）
Feed back according to this again, game draws the transmission power of newest adjustment
Subordinate layer utility function U is built firstFAPj(Pj) expression be：
In formula, tactful PjRepresent the transmission power of j-th Home eNodeB, NjIt is the number of users of j-th base station,It is j-th
The Signal to Interference plus Noise Ratio of n-th domestic consumer in Home eNodeB（No matter why n is worth,Can all make and be
Wherein, hj,jIt is channel gains of the Home eNodeB j to its user, h0,jIt is channel gain of the macro base station to the user of Home eNodeB j,
hk,jBe other Home eNodeB and Home eNodeB j user between channel gain）, w is the weight factor of cost item, hj,mIt is
Channel gain of the j Home eNodeB to the user of remaining non-this base station, LmIt is number of users that base station that user m is accessed includes
Mesh,Total Q base station（That is Q=N+1）, there is N i-th base stationiIndividual user；
The Section 1 of effectiveness represents the total capacity of Home eNodeB j, Section 2Represent to each in other base stations
The interference sum of individual user；
Then adjustment is iterated to the transmission power of each Home eNodeB in system, by power policy of effectiveness when maximum
As the power decision of final leadership, comprise the following steps that：
a）The transmission power strategy of each Home eNodeB is initialized：Initial time n=0 is made, each Home eNodeB
In the transmission power strategy of initial time it is
b）The transmission power strategy of each Home eNodeB of subsequent time is calculated respectively according to following formula, n=n+1 is then made：
c）In judging whether system, all Home eNodeB are satisfied by following condition：
The power policy of each Home eNodeB meets conditionWherein ε is the mistake that power policy is allowed
Difference scope；
In this way, then into step d）, otherwise return to step b）；
d）The transmission power strategy of each Home eNodeB that final updating is obtained, as leadership in current network state
Under optimal power strategy
4）Grand user proceeds to respond to the power decision in Home eNodeBMake the decision-making for accessing selection
5）Repeat step 3）、4）, according to feedback informationHome eNodeB adjusts power policyThen it is grand
User responds, and obtains access strategyLeadership and subordinate layer carry out stackelberg game, until last
To stable solution, power policy and access strategy all no longer change,The as equilibrium value of stackelberg game.
The present invention is applied to game theory principle in the Power Control and Access Control of home base station network, and Home eNodeB is made
For leader, grand user influences each other as subordinate, the strategy between leadership and subordinate layer, in constantly adjustment iteration
User finally determines transmission power decision-making and accesses decision-making.So combining carries out Power Control and Access Control, can be preferably
Optimization systematic function.And consideration to user and base station relative position relation during Power Control, is also added, more accurately
The transmission power of ground control Home eNodeB.
Beneficial effect：The present invention compared with prior art, with advantages below：
1., in the effectiveness of Power Control subgame, cost function considers the transmission power of Home eNodeB to diverse location
And the customer impact degree of different base station is different, and more accurately power is controlled.
2. couple grand user carries out Access Control, and grand user more can be actively participating in the optimization of system, so as to subtract
Little cross-layer interference.
3. macro base station and Home eNodeB optimize throughput of system jointly, build stackelberg game and are connect to combine
Enter control and Power Control.
The present invention considers joint Power control and Access Control, in addition to the transmission power to Home eNodeB is controlled,
Access Control is carried out to grand user also, grand user selects the base station for making own throughput optimum to access.The present invention is by game theory
Principle is applied in the double-layer network that Home eNodeB and macro base station are constituted, based on stackelberg betting model, by family's base
Stand as leader, grand user builds the problem model of two sublayers respectively as subordinate, and found a family base station and grand user
Utility function, then joint Power control and Access Control, optimize power system capacity.
Stackelberg game is the expansion of non-cooperative game, preferentially can be adopted as a group game participant of leader
Action is taken, and decision-making is then made as the game participants of subordinate.Therefore, there is grade difference between game participant,
Leadership can predict and oneself once take certain to take action, the ensuing reaction of subordinates；And subordinates do not have this
Forecast function, is only capable of responding the action of leader.
Description of the drawings
Fig. 1 is the SNA figure of the present invention.
Schematic flow sheets of the Fig. 2 for the inventive method.
Fig. 3 is the average throughput of initial grand user（Setting M=10）Analogous diagram.
Average throughputs of the Fig. 4 for initial home user（Setting T=3）Analogous diagram.
Fig. 5 is the average throughput analogous diagram of all users in two-layer system.
Specific embodiment
The present invention is described in further detail below in conjunction with accompanying drawing.
Fig. 1 is the SNA figure of the present invention.In the coverage of 1 macro base station, the grand user of random distribution M, covers
There is N number of Home eNodeB in a certain region in the range of lid, in each Home eNodeB, have T domestic consumer.Macro base station and all of
Home eNodeB adopts same frequency range.
The basic ideas of the present invention are that game theory principle is applied to the interference management solved in Home eNodeB double-layer network,
Cross-layer interference and co-layer interference, optimization system resource configuration, lift system throughput performance are reduced as far as possible.It is family's base first
The power decision stood and the relation accessed between decision-making of grand user are modeled, and set up joint Power control and Access Control
Stackelberg betting model.Then respectively to leadership and the rational utility function of subordinate layer building, analyze Home eNodeB
Power decision process and grand user access decision process.The strategy of the strategy and subordinate layer of leadership iteration back and forth, until
Stable solution is finally obtained, power policy and access strategy all no longer change.
As shown in the schematic flow sheet of Fig. 2 the inventive method, specific implementation process of the present invention is as follows：
1）Starter system parameter：
The double-layer network model that 1 macrocell and N number of home cell collectively form is set up, random distribution M in macro base station
Grand user, has N number of Home eNodeB in a certain region in macro base station coverage, has T domestic consumer in each Home eNodeB.
Macro base station and all of Home eNodeB adopt same frequency range.In each base station, number of users destination aggregation (mda) initial value is User_
Collect=[M, T ..., T], the transmission power for giving macro base station are P0, the Initial Trans of each Home eNodeB are { Pj
}(0), j={ 1,2 ... N }；
2）The decision process of subordinate layer can be modeled as Access Control subgame：
Access Control subgame is<I,(Si)i∈I,(UMUEi)i∈I>.In double-deck home base station network, Access Control game master
It is directed to grand user（Non-family safe base station subscriber）, because the original domestic consumer in Home eNodeB（Home eNodeB is ordered
The person of readding）It is close with a distance from the Home eNodeB for serving it, it is ensured that its Qos is good, therefore the set of game person is I=here
{1,2,...,M}。(Si)i∈IIt is the strategy set of game person, SiIt is the strategy of i-th game person, represents and access which base station, Si
={ 0,1 ..., N }, " 0 " represent that grand user continues to access macro base station, do not switch, and " 1 ..., N " represents that switching is accessed to
Which Home eNodeB.(UMUEi)i∈IThe effectiveness set of game person is represented, the concrete utility function form of i-th game person is such as
Under：
In formula, tactful SiRepresent that grand user i accesses SiIndividual base station；B_total is the total bandwidth of each base station, and bandwidth is put down
All users in base station are distributed to；It is SiThe number of users of individual base station；Refer to base station SiTo the letter of grand user i
Dry ratio of making an uproar, because SiBoth it had been probably macro base station, it is also possible to Home eNodeB, therefore Signal to Interference plus Noise Ratio had not been adopted above with " M " or " F "
Lower target expression way；It is SiThe transmission power of individual base station, PkIt is the transmission power of other base stations；It is SiIndividual base station
To the channel gain of grand user i, hk,iIt is channel gain of other base stations to user i；
In known leadership（Home eNodeB）Initial power { Pj}(0)Under conditions of, subordinate layer（Grand user）It is rich by many wheels
Play chess and find out maximum utility UMUEi(Si) access balance policy
In each wheel gambling process, all grand users carry out decision-making simultaneously, select under current network scene, optimum plan
Slightly, game person i does not know the strategy of other game persons.And in fact, after epicycle gambling process terminates, the selection of game person i
It is not optimal immediately, because may be in epicycle decision-making, many users and game person i have selected same strategy, switches
Access same base station Si, the bandwidth resources for so distributing to game person i are just more expected few than before, so a wheel decision-making terminates
Afterwards, the result of game person i must be dominant strategy.The game of many wheels is also needed, when reaching stable situation, is only
The stable strategy of game processed.
The set of strategies S of this gamei={ 0,1 ..., N } is limited, so the existence of game equilibrium can be equal by Nash
The existence result explanation of weighing apparatus.
Theorem 1：At least there is a Nash equilibrium in each limited strategic formula game（Including pure strategy and mixed strategy
Nash is balanced）.
3）The decision process of leadership can be modeled as Power Control subgame
Here set up the non-cooperative game model of a Power Control, it is considered to our target --- optimization handling capacity is made
For the income item of utility function, punishment of the interference caused to other users by the transmission power of Home eNodeB as utility function
.
Power Control subgame is<J,(Pj)j∈J,(UFAPj)j∈J>, wherein J={ 1,2 ..., N } is for game participant's
Set（That is the set of Home eNodeB）, (Pj)j∈JIt is the strategy set of game person, PjIt is the strategy of j-th game person, represents house
The transmission power level of front yard base station j, P_min≤Pj≤P_max（P_min, P_max represent the minimum of a value of Home eNodeB transmission power
And maximum）.(UFAPj)j∈JIt is the utility function set of game person, expression is as follows：
In formula, B_total is the total bandwidth of each base station, and bandwidth is averagely allocated to all users in base station；NjIt is jth
The number of users of individual base station；It is the Signal to Interference plus Noise Ratio of n-th domestic consumer in j-th Home eNodeB, as it was noted above, one
User's signal to noise ratio approximately equal in Home eNodeB, therefore no matter why n is worth,All make and beW is the weight factor of cost item,
W is bigger, represents that the punishment for producing interference to power is bigger；hj,mIt is letter of j-th Home eNodeB to the user of remaining non-this base station
Road gain, LmIt is number of users that base station that user m is accessed includes.Total Q base station（That is Q
=N+1）, there is N i-th base stationiIndividual user.
The Section 1 of effectiveness represents the total capacity of Home eNodeB j, Section 2Represent to each in other base stations
The interference sum of individual user.Because PjThere is interference in whole frequency range that can be to user m places base station, and user m only occupies frequency
Spectral coverageTherefore interference is expressed asCost function in Section 2 has taken into full account the geographical position for being disturbed user
And own base station, the actual size of distracter is more accurately expressed, Power Control is carried out and also more accurately can be only had better than general
Weight coefficient is multiplied by the cost function of power form.
IfThen gatherIt is the Nash Equilibrium Solution of this betting model.
Here, the betting model existence and uniqueness in a balanced way, then the form for providing its equilibrium solution are first proved.
Theorem 2：For a set of strategies（G={ S1,…,SN;u1,…,uN}）, policy space SiIt is one of theorem in Euclid space
Non-NULL compact convex set.If utility function uiIn S (S={ S1,…,SN) on it is continuous, and in SiIt is upper to intend recessed, then to there is one
The Nash Equilibrium of individual pure strategy.
Theorem 3：If a function is concave function, then it is quasiconcave function certainly.
Policy space (P hereinj)j∈JIt is the compact convex set of a non-NULL.From formula（2）It is also seen that utility function UFAPj
(Pj) it is in (Pj)j∈JOn be continuous.
By formula（3）Understand,Therefore U (Pj) in (Pj)j∈JOn be concave function.According to theorem 3, U
(Pj) in (Pj)j∈JIt is to intend recessed.Therefore the several conditions in theorem 2 all meet, the betting model has Nash Equilibrium Solution.According to number
Gain knowledge and understand, work as satisfactionWhen, Nash Equilibrium Solution is unique.
OrderCan solve
Make againHave
Then the iterative formula of power is as follows：
Adjustment is iterated to the transmission power of each Home eNodeB in system, using power policy of effectiveness when maximum as
The power decision of final leadership, comprises the following steps that：
a）The transmission power strategy of each Home eNodeB is initialized：Initial time n=0 is made, each Home eNodeB
In the transmission power strategy of initial time it is
b）The transmission power strategy of each Home eNodeB of subsequent time is calculated respectively according to following formula, n=n+1 is then made：
c）In judging whether system, all Home eNodeB are satisfied by following condition：
The power policy of each Home eNodeB meets conditionWherein ε is the mistake that power policy is allowed
Difference scope；
In this way, then into step d）, otherwise return to step b）；
d）The transmission power strategy of each Home eNodeB that final updating is obtained, as leadership in current network state
Under optimal power strategy
According to subordinate layer（Grand user）FeedbackInformation updating User_Collect, then leadership（Each family's base
Stand）Power alternative manner recited above is performed, game draws the transmission power of newest adjustment
4）Grand user proceeds to respond to the power decision in Home eNodeBMake the decision-making for accessing selection
5）Repeat step 3）、4）, according to feedback informationHome eNodeB adjusts power policyThen it is grand
User responds, and obtains access strategyLeadership and subordinate layer carry out stackelberg game, until last
To stable solution, power policy and access strategy all no longer change,The as equilibrium value of stackelberg game.
Joint Power is controlled and the method final goal of Access Control is to find the equilibrium solution of stackelberg game
（Stackelberg Equilibrium）.SE's is defined as follows：
Then (P*,S*) be the game SE.
Because the optimal response function of leadership's subgame model, formula（6）It is continuous, so this this tank that primary
There is a SE to I haven't seen you for ages in lattice game.
In sum, the present invention is based on stackelberg betting model, collectively forms in macrocell and home cell
Joint Power control and Access Control in double-layer network, Home eNodeB and grand user optimize systematic function jointly.Power control
The corresponding utility function of target design of maximize handling capacity is directed in game, iteration goes out power equalization solution；Access Control is rich
In playing chess, grand user selects the base station that makes own throughput optimum to access.
Fig. 3 is the average throughput of initial grand user（Setting M=10）Analogous diagram, simulation result can be illustrated, compared to general
Power Control game method, method proposed by the present invention can largely improve the throughput performance of grand user.
Average throughputs of the Fig. 4 for initial home user（Setting T=3）Analogous diagram, simulation result show, the present invention's
Under method, the average throughput of domestic consumer starts to be slightly less than general Power Control game method（This is because of the invention
Method in add Access Control scheme, grand user's access to family base station is certain to share the bandwidth of original domestic consumer
Resource, the average throughput of original domestic consumer can be reduced）.But, in view of Home eNodeB resource is sufficient, can carry for domestic consumer
For service well, even if number of users becomes many, service quality still can ensure that, will not improve interruption rate, domestic consumer
Handling capacity still has high value.And, as Home eNodeB number increases, under the method for the present invention, the handling capacity meeting of domestic consumer
It is higher than the handling capacity under general Power Control game method.This is because, after Home eNodeB is densely distributed, change in the present invention
The superiority of the Power Control game method for entering can be embodied, and the income that Power Control is brought in the inventive method is than grand use
The impact that family switching brings is bigger.
Fig. 5 is the average throughput analogous diagram of all users in two-layer system, and in expression whole system, all users' is flat
Handling capacity can be higher under the inventive method.
Claims (1)
1. it is a kind of to be controlled based on game theoretic joint Power and connection control method, it is characterised in that the method establishes a kind of family
Front yard base station and the stackelberg betting model of grand user's combined optimization system performance, Home eNodeB are as leader, advanced
Row power decision；Grand user, determines with access selection was carried out later according to the transmission power information of Home eNodeB as subordinate
Plan, and result fed back to Home eNodeB, the method are comprised the following steps that：
1) initialization system parameter：
In each base station, number of users destination aggregation (mda) initial value is User_Collect=[M, T ..., T], gives the transmitting of macro base station
Power is P0, Home eNodeB Initial Trans { Pj}(0), j={ 1,2 ... N }, wherein M are the grand use of random distribution in macrocell
Amount mesh, N are the number of Home eNodeB in the macrocell, and T is the number of domestic consumer in each Home eNodeB；
2) decision process of subordinate layer can be modeled as Access Control subgame：
It is Home eNodeB initial power { P in known leadershipj}(0)Under conditions of, subordinate layer is that grand user is looked for by the game of many wheels
Go out maximum utility UMUEi(Si) access balance policy { Si *}(0), each wheel gambling process is that each grand user has by exhaustion
Limit plants possible strategy to determine the optimal policy of this wheel；
Build subordinate layer utility function UMUEi(Si) expression be：
In formula, tactful SiRepresent that grand user i accesses SiIndividual base station, i={ 1,2 ..., M }, B_total are total bands of each base station
Width, bandwidth are averagely allocated to all users in base station,It is SiThe number of users of individual base station,Refer to base station SiTo grand use
The Signal to Interference plus Noise Ratio of family i,It is SiThe transmission power of individual base station, PkIt is the transmission power of other base stations,It is SiIndividual base station is arrived
The channel gain of grand user i, hk,iIt is channel gain of other base stations to user i；
3) decision process of leadership can be modeled as Power Control subgame:
It is { the S of grand user feedback according to subordinate layeri *}(0)Information updating User_Collect, leadership be each Home eNodeB again according to
Feed back accordingly, game draws the transmission power { P of newest adjustmentj*}(1)；
Leadership's utility function U is built firstFAPj(Pj) expression be：
In formula, tactful PjRepresent the transmission power of j-th Home eNodeB, NjIt is the number of users of j-th base station,It is j-th family
The Signal to Interference plus Noise Ratio of n-th domestic consumer in base station, no matter why n is worth,All make and be
Wherein, hj,jIt is channel gains of the Home eNodeB j to its user, h0,jIt is channel gain of the macro base station to the user of Home eNodeB j,
hk,jBe other Home eNodeB and Home eNodeB j user between channel gain, w is the weight factor of cost item, hj,mIt is jth
Channel gain of the individual Home eNodeB to the user of remaining non-this base station, LmIt is number of users that base station that user m is accessed includes,Total Q base station, Q=N+1, i-th base station have NiIndividual user；
The Section 1 of effectiveness represents the total capacity of Home eNodeB j, Section 2Represent to each use in other base stations
The interference sum at family；
Then adjustment is iterated to the transmission power of each Home eNodeB in system, using power policy of effectiveness when maximum as
The power decision of final leadership, comprises the following steps that：
A) the transmission power strategy of each Home eNodeB is initialized：Initial time n=0 is made, each Home eNodeB is first
The transmission power strategy at moment beginning is Pj (0)；
B) calculate the transmission power strategy of each Home eNodeB of subsequent time according to following formula respectively, then make n=n+1：
C) in judging whether system, all Home eNodeB are satisfied by following condition：
The power policy of each Home eNodeB meets conditionWherein ε is the error model that power policy is allowed
Enclose；
In this way, then into step d), otherwise return to step b)；
The transmission power strategy of each Home eNodeB that d) final updating is obtained, as leadership under current network state
Optimal power strategy { Pj *}；
4) grand user proceeds to respond to the power decision { P in Home eNodeBj*}(1), make the decision-making { S for accessing selectioni *}(1)；
5) repeat step 3), 4), according to feedback information { Si *}(k), Home eNodeB adjustment power policy is { Pj *}(k+1), Ran Houhong
User responds, and obtains access strategy { Si*}(k+1), leadership and subordinate layer carry out stackelberg game, until last
Stable solution is obtained, power policy and access strategy all no longer change,The as equilibrium value of stackelberg game.
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| CN104796975B (en) * | 2015-04-15 | 2019-02-19 | 北京邮电大学 | One of dense deployment scene descending self-adapting power regulation mode |
| CN106714268B (en) * | 2015-07-22 | 2019-11-19 | 上海诺基亚贝尔股份有限公司 | A method of for realizing access and power control combined optimization |
| CN106060906B (en) * | 2016-05-24 | 2019-06-25 | 东南大学 | The Poewr control method of high spectrum effect low-power consumption in a kind of two layers of heterogeneous network |
| CN105848296B (en) * | 2016-06-01 | 2019-04-16 | 南京邮电大学 | A kind of resource allocation methods based on stackelberg game |
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