CN107708156A - Heterogeneous cellular network load balancing method with prejudgment - Google Patents
Heterogeneous cellular network load balancing method with prejudgment Download PDFInfo
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- H—ELECTRICITY
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- H04W28/08—Load balancing or load distribution
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Abstract
The invention discloses a heterogeneous cellular network load balancing method with prejudgment. The method comprises the following steps: firstly, constructing a Stainberg game model with a pre-unloading decision, wherein an upper-layer leader is a macro cell, and a lower-layer follower is a micro cell; then dividing the load balancing process into two stages, wherein in the first stage, the macro base station determines whether to unload the macro user, if so, the second stage enters a mutual help part, namely, the load balancing is carried out; otherwise, the second stage enters a self-dry-alive part, namely, load balancing is not carried out; if the second phase of the Stackelberg game model enters a mutual help section, the macro base station encourages the small base station to serve macro users by adopting an incentive mechanism. The method provides theoretical support for load balancing between the macro cell and the micro cell when and under what conditions in the heterogeneous cellular network scene.
Description
Technical field
The invention belongs to wireless communication technology field, particularly a kind of isomery cellular network load balancing side with anticipation
Method.
Background technology
In isomery cellular network, because macro base station transmission power is big, and user tends to access and receives prominent base
Stand, the problem of macrocellular network often faces overload.Now, if cellulor is ready to service grand user, can make full use of
The resource of cellulor, mitigate the load of macrocellular network, so as to lift overall performance of network.Some existing documents are in Staenberg
(Stackelberg) under the framework of betting model, encourage small base station to receive by designing different incentive mechanisms and service grand
User, bibliography H.Soumaya, Z.Monia, T.Sami, " Win-win relationship between macrocell
and femtocells for spectrum sharing in LTE-A,”IET Commun.,vol.8,no.7,pp.1109–
1116,2014；K.Zhu,E.Hossain and D.Niyato,“Pricing,spectrum sharing,and service
selection in two-tier small cell networks:A hierarchical dynamic game
Approach, " IEEE Trans.Mobile Comput., vol.13, no.8, pp.1843-1856, in 2014. two documents,
Macro base station encourages small base station to access grand user to sell frequency spectrum and pay the method for subsidy respectively.
However, existing research there is problems：First, whether the strategy grand user unloaded is to macrocellular and small
Honeycomb both sides are favourable；Secondly, under what circumstances, it is more favourable than without unloading to carry out unloading.Existing research always assumes that
Macro base station needs to be unloaded grand user, but in fact, the service being subject to as macrocellular network light load or grand user
When being all satisfied with, macrocellular need not be unloaded.In addition, work as small cell network heavier loads or cellulor channel quality not
When good, macrocellular unloads the tactful satisfaction that can not only lift grand user of grand user, can also aggravate small cell network
Burden, i.e. macrocellular and cellulor both sides are not made a profit.
The content of the invention
It is an object of the invention to provide a kind of isomery cellular network load-balancing method with anticipation, can prejudge grand
When honeycomb carries out unloading grand user, to realize more reasonably isomery cellular network load balancing.
The technical solution for realizing the object of the invention is：A kind of isomery cellular network load balancing side with anticipation
Method, comprise the following steps：
Step 1, by isomery cellular network problem of load balancing, it is modeled as a two stage Stackelberg games mould
Type, senior level leader person are the macro base stations in network, and lower floor follower is the small base station in network；
Step 2, whether Stackelberg betting models first stage, macro base station anticipation will unload grand user：It is then second
Stage enters part of helping each other, that is, carries out load balancing；Otherwise second stage is into part of oneself working, i.e., without load
It is balanced；
Step 3, if Stackelberg betting models second stage enters part of helping each other, macro base station is using sharp
Encouraging mechanism encourages small base station to service grand user.
Further, described in step 1 by isomery cellular network problem of load balancing, be modeled as one it is two stage
Stackelberg betting models, the betting model are：
Wherein, B=Bs∪S0For the set of all base stations, S0For macro base station, Bs=[S1,Sk,…,SK] be small base station collection
Close, β=[0,1] is that macro base station rewards ratio strategy set, and α=[0,1] is small base station open hour ratio strategy set, U0For
The utility function of macro base station, U1For the utility function of small base station.
Further, whether the macro base station anticipation described in step 2 will unload grand user, specific as follows：
When grand user q speedLess than threshold value RτWhen, the user is unloaded, wherein,
Wherein, c0The price of per unit speed is paid to macro base station for grand user,Small base station is discharged into for grand user q
Speed afterwards,For cellulor user k speed, c1The price of per unit speed is paid to small base station for cellulor user, f is
On the overhead factor of macro base station transmit power, h characterizes cellulor user k importance, P0For the transmission power of macro base station, T
For frame length.
Further, the macro base station described in step 3 encourages small base station to service grand user using incentive mechanism, is specially：
Macro base station realizes the maximization of utility function by adjusting reward ratio, and small base station is realized each by adjusting open hour ratio
The maximization of utility function；
The utility function of macro base station includes income and expense two parts, and the utility function of macro base station is in a certain frame：
Wherein, α is the time scale of small base station grand user of open service in this frame, and β is that macro base station is drawn from income
The reward ratio of small base station is given, to encourage it to access grand user；
The utility function of small base station is in a certain frame：
Wherein, ζ (α) is nondecreasing function on α, and ζ (α)=h α2, (h ＞ 0).
Compared with prior art, its remarkable advantage is the present invention：(1) problem of load balancing is configured to have pre- unloading
The Stackelberg betting models of decision-making, and prejudge when to carry out grand user's unloading more favourable；(2) by the effectiveness letter of macro base station
Number is designed as a piecewise function for corresponding to different decision-makings, can intuitively embody influence of the different decision-makings to macro base station.
Brief description of the drawings
Fig. 1 is the isomery cellular network model signal for the isomery cellular network load-balancing method that the present invention has anticipation
Figure.
Fig. 2 is macrocellular of the present invention and cellulor working mechanism schematic diagram.
Fig. 3 is load balancing process flow schematic diagram in the present invention.
Fig. 4 is that grand user moves schematic diagram in the present invention.
Fig. 5 is the schematic diagram that the distance of the grand user of macro base station in the present invention influences on macro base station effectiveness.
Fig. 6 is the schematic diagram that the wall penetration loss in the present invention between the grand user of macro base station influences on macro base station effectiveness.
Fig. 7 is the schematic diagram that the wall penetration loss between the medium and small grand user in base station of the present invention influences on macro base station effectiveness.
Fig. 8 is the schematic diagram that the medium and small phone user's importance of the present invention influences on macro base station effectiveness.
Embodiment
Fig. 1 is the model of isomery cellular network in the present invention.In the model, K cellulor cloth is arranged on a macrocellular
Coverage in, and with macro base station with frequency work.Information transfer is divided in units of frame, and each frame is further drawn again
It is divided into time slot.A user can only be dispatched in a time slot by setting each base station, and different time slot services is distributed not in small base station
Same user, and using mixing access control mechanism.
The use environment of the present invention is the network scenarios of sparse distribution, and interfering between cellulor can be ignored not
Meter, and a grand user can only fall in the coverage of a small base station, can also be ignored by the interference of other small base station
Disregard.Present networks scene can be reduced to a macrocellular and cover a cellulor.Fig. 2 is macrocellular and chalcid fly in the present invention
Schematic diagram of mechanism is made in the work holdup.Scheme medium and small base station grand user accessed in latter two time slot to be serviced, therefore macro base station is rear two
Do not worked in individual time slot.
The present invention has the isomery cellular network load-balancing method of anticipation, idiographic flow such as Fig. 3, comprises the following steps：
Step 1, by isomery cellular network problem of load balancing, it is modeled as a two stage Stackelberg games mould
Type, the senior level leader person of game are the macro base stations in network, and lower floor follower is the small base station in network；
Step 2, the Stackelberg betting models first stage, whether macro base station anticipation will unload grand user, if unloading
Grand user is more favourable, then second stage enters " helping each other " part, that is, carries out load balancing；If macro base station oneself service is grand
User is more favourable, then second stage enters " oneself is worked " part, i.e., without load balancing；
Step 3, in " helping each other " part of Stackelberg betting models second stage, macro base station uses excitation set
System encourages small base station to service grand user, and specifically, macro base station realizes the maximization of utility function, small base by adjusting reward ratio
Stand and the maximization of respective utility function is realized by adjusting open hour ratio.
The specific implementation of the present invention is as follows：
First, described in step 1 by isomery cellular network problem of load balancing, be modeled as one it is two stage
Stackelberg betting models, the betting model are：
The betting modelIn include four parts, wherein, B=Bs∪S0For the set of all base stations, S0For grand base
Stand, Bs=[S1,Sk,…,SK] be small base station set, β=[0,1] be macro base station reward ratio strategy set, α=[0,1] is
Small base station open hour ratio strategy set, U0For the utility function of macro base station, U1For the utility function of small base station.
2nd, described in step 2 in the first phase, whether macro base station anticipation will unload grand user, specific as follows：
When grand user q speedLess than threshold value RτWhen, the user is unloaded, wherein,
Wherein, c0The price of per unit speed is paid to macro base station for grand user,Small base station is discharged into for grand user q
Speed afterwards,For cellulor user k speed, c1The price of per unit speed is paid to small base station for cellulor user, f is
On the overhead factor of transmit power, h characterizes cellulor user k importance, and cellulor user k is more important, and h is bigger, P0For
The transmission power of macro base station, T are frame length.
3rd, macro base station described in step 3 realizes the maximization of utility function by adjusting reward ratio, and small base station passes through adjustment
Open hour ratio realizes the maximization of respective utility function, specific as follows：
The utility function of macro base station includes two parts：Income and expense.The utility function of macro base station is in a certain frame：
Wherein, α is the time scale of small base station grand user of open service in this frame, and β is that macro base station is drawn from income
The reward ratio of small base station is given, to encourage it to access grand user.
The utility function of small base station is in a certain frame：
Wherein, ζ (α) is a nondecreasing function on α, and the function is by cellulor user different in real system model
Performance is determined, ζ (α)=h α are set in the present invention2, (h ＞ 0).
4th, the optimization aim of game：Macro base station realizes the maximization of effectiveness by adjusting reward ratio, and majorized function is：
P1:
Small base station realizes the maximization of respective effectiveness by adjusting open hour ratio, and majorized function is：
P2:
Embodiment 1
The specific embodiment of the present invention is as follows, and system emulation uses Matlab softwares, and parameter setting does not influence typically
Property.Simulating scenes are a two-level network comprising a macrocellular and a cellulor, and the covering of macrocellular and cellulor is partly
Footpath is respectively 300m and 30m, and transmission power is respectively 800mW and 100mW, and ambient noise is assumed to be 10-7MW, bandwidth are set to
3MHz.Without loss of generality, it is assumed that path-loss factor λ=3, it is respectively c that user, which pays small base station and the unit price of macro base station,1=
0.1 and c0=5, parameter f=2 × 106。
Influence of the distance of the grand user of macro base station to effectiveness is probed into first, it is assumed that grand user moves in small base station range
Dynamic situation.Fig. 4 is that grand user moves schematic diagram.As seen from Figure 5, when the grand user distance of macro base station is less than certain thresholding,
Macro base station oneself, which services grand user, can obtain very high effectiveness.In this case, it is unnecessary and can not to carry out unloading
Make a profit.After both distances exceed thresholding, macro base station effectiveness increases with the increase of distance, grand user and small base station away from
From reducing, therefore grand user is discharged into the speed behind small base station and can uprised.
Then probe into influence of the channel quality to effectiveness.As seen from Figure 6, when coverage of the grand user in small base station
When inside is mobile, regardless of the channel quality between the grand user of macro base station, macro base station always unloads the grand user.And if
Grand user is in small base station range edge, when the channel quality between the grand user of macro base station is not very poor, oneself
It is more favourable selection for macro base station to service the grand user.That is, it is to have that macro base station carries out anticipation before unloading
It is necessary.As seen from Figure 7, when grand user is in small base station range edge, due to the grand user in small base station it
Between channel quality be deteriorated, what grand user was subject to carrys out the interference reduction of base station from childhood, therefore macro base station can obtain higher speed
Rate.If grand user is located within the coverage of small base station, when the bad channel quality between the grand user in small base station to a certain journey
When spending, macro base station oneself services grand user also can advantageously, and now the first step of institute's extracting method seems highly significant.
Then influence of the cellulor user importance to effectiveness is probed into.As seen from Figure 8 when the weight of the grand user in small base station
When the property wanted is very low, the small base station meeting grand user of full-range service, macro base station, which can prejudge, to carry out unloading grand user.With the grand user in small base station
The increase of importance, the time that small base station services grand user can tail off.When the importance of the grand user in small base station reaches particular value,
In order to obtain best effectiveness, macro base station anticipation is without unloading grand user.In this case, whether anticipation needs to unload grand
User is a process being necessary.
To sum up, it is proposed by the present invention have anticipation isomery cellular network load-balancing method, can be directed to different situations,
The network scenarios of varying environment, make to macrocellular and the favourable decision-making of microcellulor, be macrocellular in isomery cellular network scene
Problem of load balancing between microcellulor provides theory support.
Claims (4)
1. a kind of isomery cellular network load-balancing method with anticipation, it is characterised in that comprise the following steps：
Step 1, by isomery cellular network problem of load balancing, a two stage Stackelberg betting model is modeled as, on
Layer leader is the macro base station in network, and lower floor follower is the small base station in network；
Step 2, whether Stackelberg betting models first stage, macro base station anticipation will unload grand user：It is then second stage
Into part of helping each other, that is, carry out load balancing；Otherwise second stage is into part of oneself working, i.e., equal without loading
Weighing apparatus；
Step 3, if Stackelberg betting models second stage enters part of helping each other, macro base station uses excitation set
System encourages small base station to service grand user.
2. the isomery cellular network load-balancing method with anticipation according to claim 1, it is characterised in that step 1
It is described by isomery cellular network problem of load balancing, be modeled as a two stage Stackelberg betting model, the game
Model is：
Wherein, B=Bs∪S0For the set of all base stations, S0For macro base station, Bs=[S1,Sk,…,SK] be small base station set, β
=[0,1] is that macro base station rewards ratio strategy set, and α=[0,1] is small base station open hour ratio strategy set, U0For grand base
The utility function stood, U1For the utility function of small base station.
3. the isomery cellular network load-balancing method with anticipation according to claim 1, it is characterised in that step 2
Described in macro base station anticipation whether to unload grand user, it is specific as follows：
When grand user q speedLess than threshold value RτWhen, the user is unloaded, wherein,
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Speed,For cellulor user k speed, c1For cellulor user to small base station pay per unit speed price, f be on
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It is long.
4. the isomery cellular network load-balancing method with anticipation according to claim 1, it is characterised in that step 3
Described in macro base station encourage small base station to service grand user using incentive mechanism, be specially：Macro base station is by adjusting reward ratio
The maximization of utility function is realized, small base station realizes the maximization of respective utility function by adjusting open hour ratio；
The utility function of macro base station includes income and expense two parts, and the utility function of macro base station is in a certain frame：
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The utility function of small base station is in a certain frame：
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108616916A (en) * | 2018-04-28 | 2018-10-02 | 中国人民解放军陆军工程大学 | Cooperative anti-interference layered game model and anti-interference learning algorithm |
| CN109104743A (en) * | 2018-07-09 | 2018-12-28 | 南京邮电大学 | Data unloading method based on price in a kind of heterogeneous wireless network |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103327535A (en) * | 2013-07-18 | 2013-09-25 | 西安电子科技大学 | Load transferring method for disturbance compensation in hierarchical cellular network |
| CN103906246A (en) * | 2014-02-25 | 2014-07-02 | 北京邮电大学 | Wireless backhaul resource scheduling method under honeycomb heterogeneous network |
| CN105007583A (en) * | 2015-07-28 | 2015-10-28 | 华中科技大学 | Energy efficiency improving method based on game playing in heterogeneous cellular network |
| CN105554829A (en) * | 2016-01-29 | 2016-05-04 | 华中科技大学 | Base station selection method used in switching process of micro base station and home base stations |
-
2017
- 2017-10-27 CN CN201711029669.3A patent/CN107708156A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103327535A (en) * | 2013-07-18 | 2013-09-25 | 西安电子科技大学 | Load transferring method for disturbance compensation in hierarchical cellular network |
| CN103906246A (en) * | 2014-02-25 | 2014-07-02 | 北京邮电大学 | Wireless backhaul resource scheduling method under honeycomb heterogeneous network |
| CN105007583A (en) * | 2015-07-28 | 2015-10-28 | 华中科技大学 | Energy efficiency improving method based on game playing in heterogeneous cellular network |
| CN105554829A (en) * | 2016-01-29 | 2016-05-04 | 华中科技大学 | Base station selection method used in switching process of micro base station and home base stations |
Non-Patent Citations (1)
| Title |
|---|
| SOUMAYA HAMOUDA等: "Win–win relationship between macrocell and femtocells for spectrum sharing in LTE-A", 《IET COMMUN.2014》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108616916A (en) * | 2018-04-28 | 2018-10-02 | 中国人民解放军陆军工程大学 | Cooperative anti-interference layered game model and anti-interference learning algorithm |
| CN109104743A (en) * | 2018-07-09 | 2018-12-28 | 南京邮电大学 | Data unloading method based on price in a kind of heterogeneous wireless network |
| CN109104743B (en) * | 2018-07-09 | 2021-08-03 | 南京邮电大学 | Pricing-based data unloading method in heterogeneous wireless network |
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