CN107172674A - Relay selection and power distribution method based on game theory in a kind of intelligent grid - Google Patents
Relay selection and power distribution method based on game theory in a kind of intelligent grid Download PDFInfo
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- CN107172674A CN107172674A CN201710521830.2A CN201710521830A CN107172674A CN 107172674 A CN107172674 A CN 107172674A CN 201710521830 A CN201710521830 A CN 201710521830A CN 107172674 A CN107172674 A CN 107172674A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
- H04L5/003—Arrangements for allocating sub-channels of the transmission path
- H04L5/0032—Distributed allocation, i.e. involving a plurality of allocating devices, each making partial allocation
- H04L5/0035—Resource allocation in a cooperative multipoint environment
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
- H04W40/08—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on transmission power
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W40/00—Communication routing or communication path finding
- H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
- H04W40/22—Communication route or path selection, e.g. power-based or shortest path routing using selective relaying for reaching a BTS [Base Transceiver Station] or an access point
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/04—Wireless resource allocation
- H04W72/044—Wireless resource allocation based on the type of the allocated resource
- H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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- Signal Processing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The invention discloses relay selection and power distribution method based on game theory in a kind of intelligent grid, suitable for relay network system, the system includes source node, destination node and via node, under conditions of each relaying quotation, user modeling is that buyer selects optimal relaying and optimal purchase power by criterion of maximum utility, relaying be modeled as seller by intelligent grid provide different cost prices determine commercial value strategy obtain maximum profit, selection of the end user to relaying after continuous game iteration, the quotation of optimal power allocation and relaying, which no longer changes, has reached Nash Equilibrium point.The present invention effectively improves transmission rate while can taking into account the interests of user and via node, amount of calculation is less and fast convergence rate.
Description
Technical field
The present invention relates to wireless communication technology field, and in particular to the relay selection based on game theory in a kind of intelligent grid
And power distribution method.
Background technology
Following cordless communication network can realize the covering of gamut signal by relay transmission, reduce communication blind district
Influence, improves communication transmission quality.By the cooperation transmission of relaying, the broadcast characteristic of wireless network can be effectively utilized, is realized
Space diversity.Relay selection in cooperative relay network and the power distribution on different via nodes can greatly influence net
The performance of network.
In following cooperative relay network, via node may be provided by different service providers or individual, with selfishness
Characteristic, while the demand to resource has heterogeneous binding feature, these cause the association that node is realized by mechanism of effective incentive
Making transmission turns into inevitable.Another aspect intelligent grid has very big difference as electric energy network of future generation and the traditional power network of present situation
Different, this influence produced to wireless network communication technique field also will be different.It is renewable in following intelligent grid
The energy plays very crucial effect in power network, because the different therefore power networks of the Production conditions of different regenerative resources are being carried out
The price that energy is provided when transmitting is also different, therefore carries out examining when relay selection and power distribution in a communication network
The factor of worry.It is most of during relay selection and power distribution in research at present only to consider optimal power selection and relaying choosing
Select, have ignored power network and the influence that energy cost difference is brought to final decision is provided.
The content of the invention
In order to overcome the shortcoming and deficiency that prior art is present, the present invention is provided in a kind of intelligent grid based on game theory
Relay selection and power distribution method.
The present invention is adopted the following technical scheme that：
Relay selection and power distribution method based on game theory in a kind of intelligent grid, it is adaptable to half-duplex relay network
System, including a source node S, a destination node D and K via node, comprise the following steps：
S1 user is before each transmission of data blocks, and relay cooperative pattern may be selected in user, is specially：User is according to itself
Utility function selects most suitable relaying to set up collaboration communication link from K via node.The quotation of each via node
For ηk(t), all relayings constitute quotation collection and are combined into Ψ (t)={ η1(t),η2(t),…ηK(t)}；
S2 user is U to each via node k utility functionS,k(ηk(t)), each relaying quotation set Ψ is being learnt
(t) under conditions of, user purchase power p optimal to each trunk node selectionkTo cause the utility function of itself to reach maximum
It is worth and isThe maximum value set of utility function that user constitutes to K via node
User chooses maximum from set Θ (Ψ (t)) again, and its corresponding via node is optimal via node k*=argmax (Θ
(Ψ(t)))；
The optimal relaying k of S3*Profit functionIf selected after k*Price reduction can be passed through
Sell more power to obtain more profits, then update quotation set Ψ (t)={ η1(t),η2(t),…ηK(t) }, if not making a price reduction
Then quotation set Ψ (t) is constant；
Other relayings not being easily selected by a user will carry out attracting user, i.e. η (t+1)=max (η by making a price reductionmin,η
(t)-△ η), then obtain new quotation collection and be combined into Ψ (t+1)={ η1(t+1),η2(t+1),…ηK(t+1) }, if Ψ (t)
=Ψ (t+1) then illustrates relaying no longer modification quotation, and user and the strategy relayed no longer change and reach Nash Equilibrium point,
Otherwise return in S1.
The transmission means relayed in the S1 uses time division multiplexing mode, and number is sent to base station in first time slot user
According to while each via node receives the data block of broadcast, second time slot is interior to carry out relay selection and power distribution, chooses
Relay k*With power pkData are sent to base station.
Utility function of the user itself to via node in the S2WhereinFor
The reachable outage capacity of user.
The profit function of via node itself is in the S3：Uk(pk,ηk)=(ηk-ck)pk, wherein ckFor relaying into
This price, that is, relay the price bought from intelligent grid.
η in the S3minFor the lowest price that can be dropped to of via node, i.e.,
Beneficial effects of the present invention：
The method that the present invention introduces economics game theory under relay selection and power distribution method, is to buy by user modeling
Person selects optimal relaying and optimal purchase power by criterion of maximum utility, and relaying is modeled as into seller is provided not by intelligent grid
Same cost price determines that commercial value strategy obtains maximum profit, and the present invention can take into account the interests of user and via node
Effectively improve transmission rate simultaneously, amount of calculation is less and fast convergence rate.
Brief description of the drawings
Fig. 1 is the workflow diagram of the present invention；
Fig. 2 is the flow chart of relay selection of the present invention and power distribution method；
Fig. 3 is user utility change curve in user and relaying gambling process in this example；
Fig. 4 is relaying price change curve in user and relaying gambling process in this example；
Fig. 5 is selected in this example optimal to relay the variation diagram changed with customer location；
Fig. 6 is the change curve that selected optimal relaying price changes with customer location in this example.
Embodiment
With reference to embodiment and accompanying drawing, the present invention is described in further detail, but embodiments of the present invention are not
It is limited to this.
Embodiment
Relay selection and power distribution method based on game theory in a kind of intelligent grid, for relay network system, institute
The relay network system stated under intelligent grid includes a source node S, a destination node D and K via node R, core
Step is user as buyer and optimal relaying and optimal purchase power is selected by criterion of maximum utility, and relaying is as seller by intelligence
Energy power network provides different cost prices and determines that commercial value strategy obtains maximum profit, and both carry out game, relays in market
In be at war with, it is final that both carry out games and reach balance, user and via node all according to itself maximization of utility no longer
It is to have reached Nash Equilibrium point to change decision-making.
As shown in figure 1, relay selection and power distribution method based on game theory in a kind of intelligent grid, it is adaptable to half pair
Work relay network system, comprises the following steps：
S1 user is before each transmission of data blocks, and relay cooperative pattern may be selected in user, is specially：User is according to itself
Utility function selects most suitable relaying to set up collaboration communication link from K via node.The quotation of each via node
For ηk(t), all relayings constitute quotation collection and are combined into Ψ (t)={ η1(t),η2(t),…ηK(t)}；
In relay network system model, user has two kinds of transmission modes：Direct transmission mode and relay cooperative pattern, are used
Family is determined selecting which kind of mode of operation to be the utility function value size by itself.
S2 user is U to each via node k utility functionS,k(ηk(t)), each relaying quotation set Ψ is being learnt
(t) under conditions of, user purchase power p optimal to each trunk node selectionkTo cause the utility function of itself to reach maximum
It is worth and isThe maximum value set of utility function that user constitutes to K via node
User chooses maximum from set Θ (Ψ (t)) again, and its corresponding via node is optimal via node k*=argmax (Θ
(Ψ(t)))；
The optimal relaying k of S3*Profit functionIf selected after k*Price reduction can be passed throughGo out
Sell more power to obtain more profits, then update quotation set Ψ (t)={ η1(t),η2(t),…ηK(t) }, if not making a price reduction
The set Ψ (t) that offers is constant；
Other relayings not being easily selected by a user will carry out attracting user, i.e. η (t+1)=max (η by making a price reductionmin,η
(t)-△ η), then obtain new quotation collection and be combined into Ψ (t+1)={ η1(t+1),η2(t+1),…ηK(t+1) }, if Ψ (t)
=Ψ (t+1) then illustrates relaying no longer modification quotation, and user and the strategy relayed no longer change and reach Nash Equilibrium point,
Otherwise return in S1.
The S3 is specifically that via node is taken action, if selected relaying price reduction sells more power and makes oneself profit letter
Number increase is then made a price reduction, and is not made a price reduction if it can not increase oneself profit；Selected relaying is not made a price reduction and then obtained newly
Quotation set Ψ (t+1), without iteration if Ψ (t)=Ψ (t+1), otherwise continue iteration.
After continuous game iteration end user to the quotation of the selection of relaying, optimal power allocation and relaying no longer
After changing, you can think that user and via node no longer change decision-making and reached Nash Equilibrium point.The embodiment of the present invention
Relay selection and power distribution method flow chart it is as shown in Figure 2.
The basic scene that the present embodiment is used is as follows：
Have in cooperative communication network a destination node D be located at (0m, 0m), have four via node Ω=1,2,3,
4 }, respectively positioned at (- 150m, 0m), (- 150m, 50m), (- 100m, 0m), (100m, 0m), have a source node S from (- 300m,
0m) it is moved to (+300m, 0m).Noise powerFor 10-8W, channel gain is Rayleigh fadingWherein dij
For the distance between node, channel fading factor-alpha is 2, and outage probability ε is 0.001, and four via nodes divide from intelligent grid
The price do not bought is respectively { 3,1.5,2,2 }, and it is 0.2 to relay the amplitude △ η made a price reduction every time.
The simulation result of this example is obtained using software Matlab.
Fig. 3 and Fig. 4 reflect user at (+130m, 0m) user and relaying between game, just at first due to
Itself effectiveness in the case of 1 is maximum in selecting therefore optimal relay selection is relaying 1 at family, and other do not have selected relaying all
Start price reduction and attract user, as the decline user of price has found during selection relaying 3 itself effectiveness than larger thus start choosing
Select relaying 3, and relay 1,2 and 4 and continue to make a price reduction, after final constantly iteration about 75 times, price of each relaying no longer becomes
Change and start to have reached Nash Equilibrium point to select optimal relaying, now also iteration goes out optimal purchase power.
Fig. 5 and Fig. 6 reacted user's source node S from (- 300m, 0m) be moved to (+300m, 0m) when selection relaying and
The situation of price change.While user is selecting direct transmission mode and relay cooperative pattern during continuous movement
The optimal relaying and optimal purchase power at diverse location moment are selected according to different situations, wherein price is also because between relaying
Competition with the intelligent grid different cost prices of offer and it is different.
Above-described embodiment is preferably embodiment, but embodiments of the present invention are not by the embodiment of the invention
Limitation, other any Spirit Essences without departing from the present invention and the change made under principle, modification, replacement, combine, simplification,
Equivalent substitute mode is should be, is included within protection scope of the present invention.
Claims (5)
1. relay selection and power distribution method based on game theory in a kind of intelligent grid, it is adaptable to half-duplex relay network system
System, including a source node S, a destination node D and K via node, it is characterised in that comprise the following steps：
S1 user is before each transmission of data blocks, and relay cooperative pattern may be selected in user, is specially：User is according to itself effectiveness
Function selects most suitable relaying to set up collaboration communication link from K via node.The quotation of each via node is ηk
(t), all relayings constitute quotation collection and are combined into Ψ (t)={ η1(t),η2(t),…ηK(t)}；
S2 user is U to each via node k utility functionS,k(ηk(t)), each relaying quotation set Ψ (t) is being learnt
Under the conditions of, user purchase power p optimal to each trunk node selectionkTo cause the utility function of itself to reach, maximum isThe maximum value set of utility function that user constitutes to K via nodeWith
Maximum is chosen in family from set Θ (Ψ (t)) again, and its corresponding via node is optimal via node k*=argmax (Θ (Ψ
(t)))；
The optimal relaying k of S3*Profit functionIf selected after k*Price reduction can be passed throughSell
More power obtain more profits, then update quotation set Ψ (t)={ η1(t),η2(t),…ηK(t) }, reported if not making a price reduction
Valency set Ψ (t) is constant；
Other relayings not being easily selected by a user will carry out attracting user, i.e. η (t+1)=max (η by making a price reductionmin,η(t)-
Δ η), then obtain new quotation collection and be combined into Ψ (t+1)={ η1(t+1),η2(t+1),…ηK(t+1) }, if Ψ (t)=Ψ
(t+1) strategy of then explanation relaying no longer modification quotation, user and relaying, which no longer changes, reaches Nash Equilibrium point, otherwise
Return in S1.
2. relay selection according to claim 1 and power distribution method, it is characterised in that the transmission relayed in the S1
Mode uses time division multiplexing mode, data is sent to base station in first time slot user, while each via node receives broadcast
Data block, carry out relay selection and power distribution, the relaying k chosen in second time slot*With power pkNumber is sent to base station
According to.
3. relay selection according to claim 1 and power distribution method, it is characterised in that user itself is right in the S2
The utility function of via nodeWhereinFor the reachable outage capacity of user.
4. relay selection according to claim 1 and power distribution method, it is characterised in that in the S3 via node from
The profit function of body is：Uk(pk,ηk)=(ηk-ck)pk, wherein ckFor the cost price of relaying, that is, relay and purchased from intelligent grid
The price entered.
5. relay selection according to claim 4 and power distribution method, it is characterised in that η in the S3minFor relaying
The lowest price that can be dropped to of node, i.e.,
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| CN201710521830.2A CN107172674A (en) | 2017-06-30 | 2017-06-30 | Relay selection and power distribution method based on game theory in a kind of intelligent grid |
| PCT/CN2017/116133 WO2019000851A1 (en) | 2017-06-30 | 2017-12-14 | Game theory-based relay selection and power distribution method in smart power grid |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019000851A1 (en) * | 2017-06-30 | 2019-01-03 | 华南理工大学 | Game theory-based relay selection and power distribution method in smart power grid |
| CN110290575A (en) * | 2019-06-06 | 2019-09-27 | 华南理工大学 | Matched relay selection and power distribution method are based in a kind of cordless communication network |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110856232B (en) * | 2019-11-12 | 2022-02-08 | 全球能源互联网研究院有限公司 | Relay selection and frequency distribution method and device for electric power wireless private network |
| KR102391458B1 (en) * | 2020-05-11 | 2022-04-26 | 서강대학교 산학협력단 | Microgrid-to-microgrid power distribution system and power distribution method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101868030A (en) * | 2010-05-25 | 2010-10-20 | 华南理工大学 | Distributed wireless network wireless resource distribution method |
| CN102065481A (en) * | 2010-11-26 | 2011-05-18 | 西安电子科技大学 | Auction theory-based power distribution method in relay communication |
| US20130114500A1 (en) * | 2010-07-27 | 2013-05-09 | Thomson Licensing | Method and apparatus for cooperation in cognitive radio networks |
| CN104640141A (en) * | 2015-01-30 | 2015-05-20 | 南京邮电大学 | Multi-relay-node cooperative game motivating method |
| US20150281907A1 (en) * | 2008-05-13 | 2015-10-01 | At&T Mobility Ii Llc | Location-based services in a femtocell network |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104023370A (en) * | 2014-06-12 | 2014-09-03 | 国家电网公司 | Cooperative transmission method based on game theory in smart power grid |
| CN104021429A (en) * | 2014-06-12 | 2014-09-03 | 国家电网公司 | Management method of intelligent power grid demand side |
| CN104301985B (en) * | 2014-09-19 | 2018-09-11 | 华北电力大学（保定） | Energy distribution method between power grid and cognitive base station in a kind of mobile communication |
| CN107172674A (en) * | 2017-06-30 | 2017-09-15 | 华南理工大学 | Relay selection and power distribution method based on game theory in a kind of intelligent grid |
-
2017
- 2017-06-30 CN CN201710521830.2A patent/CN107172674A/en active Pending
- 2017-12-14 WO PCT/CN2017/116133 patent/WO2019000851A1/en active Application Filing
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150281907A1 (en) * | 2008-05-13 | 2015-10-01 | At&T Mobility Ii Llc | Location-based services in a femtocell network |
| CN101868030A (en) * | 2010-05-25 | 2010-10-20 | 华南理工大学 | Distributed wireless network wireless resource distribution method |
| US20130114500A1 (en) * | 2010-07-27 | 2013-05-09 | Thomson Licensing | Method and apparatus for cooperation in cognitive radio networks |
| CN102065481A (en) * | 2010-11-26 | 2011-05-18 | 西安电子科技大学 | Auction theory-based power distribution method in relay communication |
| CN104640141A (en) * | 2015-01-30 | 2015-05-20 | 南京邮电大学 | Multi-relay-node cooperative game motivating method |
Non-Patent Citations (3)
| Title |
|---|
| 夏展望: ""基于博弈论的协作通信中继节点的功率分配"", 《南京工程学院学报(自然科学版)》 * |
| 柯峰: ""DF协作中继网络基于买者_卖者博弈的中继选择和功率分配策略"", 《电子与信息学报》 * |
| 高龙年: ""基于博弈论的协作通信网络中继选择和功率分配算法研究"", 《信息科技辑》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2019000851A1 (en) * | 2017-06-30 | 2019-01-03 | 华南理工大学 | Game theory-based relay selection and power distribution method in smart power grid |
| CN110290575A (en) * | 2019-06-06 | 2019-09-27 | 华南理工大学 | Matched relay selection and power distribution method are based in a kind of cordless communication network |
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Application publication date: 20170915 |