CN103796211A - Distribution method of united power and channels in cognitive wireless network - Google Patents

Distribution method of united power and channels in cognitive wireless network Download PDF

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CN103796211A
CN103796211A CN201410081327.6A CN201410081327A CN103796211A CN 103796211 A CN103796211 A CN 103796211A CN 201410081327 A CN201410081327 A CN 201410081327A CN 103796211 A CN103796211 A CN 103796211A
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cognitive user
channel
user
cognitive
node
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CN103796211B (en
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李洪兵
应腾达
余华兴
黄天聪
张电
陈刚
廖玉祥
唐夲
徐菁
周鼎
冯彬
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Chongqing University
State Grid Corp of China SGCC
Jiangbei Power Supply Co of State Grid Chongqing Electric Power Co Ltd
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Chongqing University
State Grid Corp of China SGCC
Jiangbei Power Supply Co of State Grid Chongqing Electric Power Co Ltd
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Abstract

The invention discloses a distribution method of united power and channels in a cognitive wireless network. The distribution method of the united power and the channels in the cognitive wireless network comprises the steps that (1) interference between a primary user and a cognitive user on each channel in the multi-channel cognitive wireless network and among cognitive users is quantized and limited; (2) a utility function defining the behavior that each cognitive user is accessed to a frequency spectrum serves as a handling capacity, and the optimal solution of the utility function of the cognitive users is solved in a distributed mode by constructing a non-cooperative game frame so that the performance of the entire network can be optimal; (3) a corresponding price function is introduced to price resource occupation behaviors of the cognitive users, and selfishness of the cognitive users is limited; (4) a potential game model is built by utilizing a non-cooperative game, and astringency of the potential game model is guaranteed. The distribution method of the united power and the channels in the cognitive wireless network has the advantages of solving the problem of distribution of the united power and the channels in a distributed mode by utilizing the price function and the potential game model, and improving distribution fairness of network resources and the utilization efficiency of the frequency spectrum.

Description

Joint Power and method for channel allocation in a kind of cognition wireless network
Technical field
The invention belongs to wireless communication technology field, particularly joint Power and the method for channel allocation in a kind of cognitive radio system.
Background technology
Cognitive radio (CR:Cognitive Radio) is a kind of new technology that improves frequency spectrum resource utilization rate.Its as a kind of can perception the intelligent communication system of extraneous communication environment, allow on time domain, frequency domain and spatial domain, carry out the spectrum reuse of multidimensional and share.The core concept of CR is: by regulating networks running parameter, quantizing and limiting under the prerequisite that primary user (PUs:Primary Users) is disturbed, allow the inferior user (SU:Secondary User) based on cognitive radio function, also referred to as cognitive user, be referred to as cognitive user herein, be CR) chance formula dynamic access mandate frequency range, thus improve the availability of frequency spectrum.Mitola is the scholar who proposes the earliest cognitive radio concept, and he emphasizes that cognitive radio is a kind of radio that obtains appointed function based on model demonstration in radio association area.In other words, cognitive radio is based on frequency spectrum limited network, needs and corresponding primary user consults and select a good opportunity to access corresponding channel and realize a kind of technology of resource-sharing mutually.Up to the present, some government departments and radio standard are organized and are launched respectively corresponding policy and standard.As having proposed corresponding unauthorized device in succession in 2002,2003, FCC (FCC:Federal Communications Commission) need to possess the ability of the vacant frequency range of perception and the frequency spectrum share mode based on interference temperature; In the Britain TVWS frequency range service regeulations that communication office of Britain (Ofcom:Office of Commnications) issues, emphasize to set up TVWS frequency range database all over Britain, consider equipment cost, the equipment of not requiring possesses frequency spectrum perception ability.
Game theory is a kind of mathematical tool of research strategy form, for decision-making and the equalization problem of prediction and optimization imperfect competition making policy decision main body.Due to behavior and the income of rationality user in can analysis and prediction competitive environment, game theory is more and more used in wireless network resource configuration and power control.On the one hand, in many cognition wireless networks of isomery coexisted environment, the finiteness of usable spectrum resource makes user's competitive behavior become selfish.User can not consider the interests of other users or whole network, and the one-side number one of pursuing maximizes.On the other hand, cognitive radio is autonomous in essence, by academic environment, regulates self running parameter, thus improve, optimized network performance.For interaction and the impact of multi-user in single cognition wireless network scene, can study by game modeling.In theory of games framework, defined cognitive wireless network user is participant, corresponding new transformation parameter (frequency, power etc.) to select be behavior collection, the corresponding network performance obtaining is policymaker's effectiveness collection, determines the betting model that special scenes is corresponding, the behavior of many-sided research cognition wireless network: first, share betting model by the dynamic spectrum building between the network user, analysis user behavior under the game framework of standard, and definite running parameter is adjusted strategy; Secondly, the various optimization criterions of game theory energy design frequency spectrum share problem, generally speaking, frequency spectrum optimization utilization is a multi-objective optimization question, be difficult to obtain its optimal solution, and game theory is by seeking the balanced criterion under different game strategies, can obtain best solution of game; Moreover non-cooperative game only utilizes local information just can obtain the shared optimal resource allocation scheme of dynamic spectrum, be specially adapted to the dynamic resource configuration of distributed cognition wireless network.
Non-cooperative game is the important branch of theory of games, has been widely used in cognitive radio networks resource and has distributed.As for ad-hoc network application scene, the people such as N.Nie have proposed the distributed self-adaption channel allocation algorithm based on dive game and irrepentant study, set up the betting model of diving and have solved well adaptive channel allocation convergence problem; And in order to make cognition network user can not produce because of selfishness the skew problem of utility function, the people such as N.Nie have also proposed the distributed self-adaption channel allocation algorithm based on irrepentant study.Although this algorithm has taken into full account the fairness problem of cognitive user in the time of competitive resource, does not consider the interference that primary user is subject to; In addition, the optimization selection problem of power is not also well solved.A.Mostaani and M.F.Sabahi propose the design of a kind of new utility function on the people's such as N.Nie Research foundation, and result shows, the game process under price mechanism is a kind of game of diving, and can converge on Nash Equilibrium.In addition, first the people such as Goodman have proposed the power control algorithm based on non-cooperative game, this algorithm points out that NPG (Non-cooperative Power control Game) has and only have a Nash Equilibrium point, shows but study, and this Nash Equilibrium point is pareto ineffective.For this reason, the people such as Goodman introduce cost mechanism, set up a kind of non-cooperative power control betting model (NPGP:Non-cooperative Power control Game of Pricing) based on linear price, its cost function design is the selfishness in order to suppress user's competition, and each user is paid a price to the resource using.Result shows, NPGP can improve the Pareto efficiency of Nash Equilibrium point, but is not optimum, and its deficiency is utility function at power degeneration and produce degenerate solution at zero point.For this reason, C.W.Sung and W.S.Wong introduce to user and produce the non-linear price mechanism of disturbing proportion to be directly proportional, and have built user's utility function from information theory view.What above researcher considered conventionally is to utilize non-cooperative game model to carry out the iterative of a metamessage (power or channel), and its weak point is not have joint Power control and channel to select.
Channel allocation and power control techniques are the primary study contents that resource is distributed.The people such as Song Wuhua propose a kind of combined channel based on non-cooperative game and the PIWF algorithm of power division, improve Pareto efficiency by pricing mechanism.Although pricing mechanism can be selected cost function, the seeking of best price function needs central entity control, is not suitable for distributed network.Hao He, the people such as Jie Chen have built that a combined channel is selected and the latent betting model of power division, and under interference-limited prerequisite, abstract is a nonlinear optimal problem that can improve cognitive radio networks throughput and consideration user fairness.In addition, define the special target function of each transmission node, and the latent betting model substep of structure is sought the optimal solution of problem.Result of study shows, the game of substep orderliness can converge to Nash Equilibrium point, and meets interference constraints restriction.Wherein, Hao He, the nonlinear optimal problem that the people such as Jie Chen propose is as follows:
Will be from node
Figure 2014100813276100002DEST_PATH_IMAGE001
to node
Figure 398876DEST_PATH_IMAGE002
transmitting-receiving node to being defined as
Figure 2014100813276100002DEST_PATH_IMAGE003
.If channel
Figure 253700DEST_PATH_IMAGE004
,
Figure 2014100813276100002DEST_PATH_IMAGE005
be illustrated in
Figure 971120DEST_PATH_IMAGE006
upper all nodes pair of transmission simultaneously, receiver reception signal and interference ratio (
Figure 2014100813276100002DEST_PATH_IMAGE007
) can be expressed as:
Wherein,
Figure 2014100813276100002DEST_PATH_IMAGE009
it is node arrive
Figure 145564DEST_PATH_IMAGE002
transmission gain,
Figure 344464DEST_PATH_IMAGE010
it is receiver
Figure 951026DEST_PATH_IMAGE002
the thermal noise at place, is generally constant,
Figure 2014100813276100002DEST_PATH_IMAGE011
it is channel
Figure 879143DEST_PATH_IMAGE006
in
Figure 633472DEST_PATH_IMAGE001
the transmitting power of node.
Definition transmitting-receiving node pair
Figure 370484DEST_PATH_IMAGE003
throughput be:
Figure 831552DEST_PATH_IMAGE012
From expression formula can find out, if
Figure 199080DEST_PATH_IMAGE014
be less than 1, the numerical value obtaining is so negative.This means now signal to noise ratio (
Figure 2014100813276100002DEST_PATH_IMAGE015
) too lowly can not continue transmitting and even can have a negative impact to the total throughout of whole network, this is because extra interference always has influence on other link.
Based on above-mentioned analysis, by combined channel select and power division with optimize the problems referred to above:
Maximize
Figure 440705DEST_PATH_IMAGE016
Subject to
Figure 2014100813276100002DEST_PATH_IMAGE017
Figure 2014100813276100002DEST_PATH_IMAGE019
Figure 234666DEST_PATH_IMAGE020
Figure 2014100813276100002DEST_PATH_IMAGE021
Figure 507516DEST_PATH_IMAGE018
Figure 236437DEST_PATH_IMAGE022
Figure 2014100813276100002DEST_PATH_IMAGE023
Wherein
Figure 252935DEST_PATH_IMAGE024
it is the right set of transmitting-receiving node.
Figure 2014100813276100002DEST_PATH_IMAGE025
to be operated in channel on primary user. a two-valued variable, if channel
Figure 410881DEST_PATH_IMAGE006
on link
Figure 251577DEST_PATH_IMAGE003
enliven, it is 1; Otherwise be 0.Constraints
Figure 604061DEST_PATH_IMAGE019
mean
Figure 484292DEST_PATH_IMAGE003
have and can only be in channel group in a channel.
This nonlinear optimal problem is intended to maximize total throughout
Figure 922227DEST_PATH_IMAGE028
.All transmitting nodes are intended to maximize target function, thereby, not only need to consider in target function
Figure 2014100813276100002DEST_PATH_IMAGE029
, also to consider the interference that primary users bear.Thus, definition is operated in channel
Figure 280527DEST_PATH_IMAGE006
on primary user
Figure 690780DEST_PATH_IMAGE025
as follows:
Figure 804229DEST_PATH_IMAGE030
Wherein
Figure 2014100813276100002DEST_PATH_IMAGE031
that the cognition wireless network that primary user y is subject to disturbs,
Figure 667143DEST_PATH_IMAGE032
be
Figure 2014100813276100002DEST_PATH_IMAGE033
the maximum interference that middle primary user is subject to, it is the summation of all channel maximum interference.Exceed threshold value for the interference on channel , further definition:
Figure 828314DEST_PATH_IMAGE036
Wherein
Figure 2014100813276100002DEST_PATH_IMAGE037
represent the total interference on these channels.Then, the definition providing before utilizing, can objective definition function be:
Figure 112665DEST_PATH_IMAGE038
The weak point that above method exists is: the first, really do not realize the co-allocation of distributed power ratio control and channel; The second, do not take into full account the phase mutual interference between cognitive user.But, for realizing distributed associating power and channel allocation, between each cognitive user, needing mutual bulk information, this has just increased the complexity of each cognitive user, is also a technical barrier in realization.
Summary of the invention
Technical problem to be solved by this invention is just to provide joint Power and method for channel allocation in a kind of cognition wireless network, the interference that it can fully take into account (CR-to-CR) between (CR-to-PU) between primary user and cognitive user, each cognitive user suppresses, utilize the distributed solution joint Power of cost function and latent betting model and Channel Assignment Problems, improve fairness and the spectrum utilization efficiency of Resource Allocation in Networks.
In order to solve the problems of the technologies described above, technical scheme of the present invention comprises the following steps:
1, interference suffered between primary user and cognitive user on each channel in multichannel cognition wireless network, between each cognitive user is realized and quantizes and limit;
2, the utility function that defines the behavior of each cognitive user access frequency spectrum is throughput
Figure 2014100813276100002DEST_PATH_IMAGE039
, carry out the distributed utility function optimal solution that solves cognitive user to reach the optimum of overall network performance by building non-cooperative game framework;
3, introduce corresponding cost function the resource occupation behavior of cognitive user is fixed a price, the selfishness of restriction cognitive user;
4, utilize non-cooperative game to be built into a latent betting model, guarantee its convergence.
Step 1 has guaranteed that cognitive user can not exceed to primary user's interference the interference range that primary user can bear, and has taken into full account again the co-channel interference problem between cognitive user; Step 3 lead-in sexual valence lattice mechanism limits the selfish sexual behaviour of cognitive user, has guaranteed the fairness of the competitive resource between user; Step 4 utilizes non-cooperative game theory to be built into a latent betting model, guarantees in theory its convergence; Problem loaded down with trivial details in centralized control is distributed to each cognitive user by step 2, each cognitive user adopts distributed behavioral strategy orderly to maximize self effectiveness, select own optimum channel and corresponding transmitting power, thereby reduce the expense of spectrum allocation may, improve network throughput and performance thereof.
Accompanying drawing explanation
Accompanying drawing of the present invention is described as follows:
Fig. 1 is the network (WSN) emulation system of one embodiment of the invention;
Fig. 2 is resource allocation flow figure of the present invention;
Fig. 3 is the flow chart of single cognitive user joint Power of the present invention and channel iteration;
Fig. 4 is the function convergence schematic diagram of diving in the present invention.
In Fig. 1,1. primary user base station; 2. primary user; 3. cognitive user.
Embodiment
Below in conjunction with drawings and Examples, the invention will be further described:
The present invention includes following steps:
1, between primary user and cognitive user on each channel in multichannel cognition wireless network between (CR-to-PU), each cognitive user (CR-to-CR) suffered interference realize and quantize and limit.
Suppose an ad-hoc cognitive radio networks being formed by multiple cognitive user, have primary user to exist around, scope in random distribution
Figure 2014100813276100002DEST_PATH_IMAGE041
individual cognitive user pair, a cognitive user is to comprising a transmitting node and a receiving node; Frequency spectrum by kindividual orthogonal channel composition, k< n, have simultaneously
Figure 425627DEST_PATH_IMAGE042
individual primary user's node, each primary user can be operated on one or more channels; Defined cognitive user
Figure 607210DEST_PATH_IMAGE044
transmitting power vector
Figure 2014100813276100002DEST_PATH_IMAGE045
,
Figure 734566DEST_PATH_IMAGE046
for cognitive user
Figure 572072DEST_PATH_IMAGE044
at channel
Figure 138182DEST_PATH_IMAGE006
on transmitting power; Channel
Figure 439851DEST_PATH_IMAGE004
, receiver
Figure 738108DEST_PATH_IMAGE002
reception
Figure 125227DEST_PATH_IMAGE007
can be expressed as:
Figure 2014100813276100002DEST_PATH_IMAGE047
Wherein,
Figure 432711DEST_PATH_IMAGE048
it is cognitive user
Figure 323307DEST_PATH_IMAGE044
channel
Figure 2014100813276100002DEST_PATH_IMAGE049
transmission exists
Figure 58045DEST_PATH_IMAGE050
place receive signal interference ratio (
Figure 604564DEST_PATH_IMAGE007
),
Figure 778056DEST_PATH_IMAGE009
it is node
Figure 788737DEST_PATH_IMAGE001
arrive
Figure 694377DEST_PATH_IMAGE002
transmission gain; it is receiver the thermal noise at place, is generally constant;
Figure 302054DEST_PATH_IMAGE011
it is channel
Figure 440911DEST_PATH_IMAGE006
in the transmitting power of node; jamming equation,
Figure 149421DEST_PATH_IMAGE052
for removing
Figure 134695DEST_PATH_IMAGE044
other cognitive user in addition:
Figure 2014100813276100002DEST_PATH_IMAGE053
Set
Figure 382136DEST_PATH_IMAGE035
for the maximum interference power of primary user (PU).So, channel
Figure 452861DEST_PATH_IMAGE006
in all cognitive user (CR) must meet total interference of each primary user (PU):
Figure 443950DEST_PATH_IMAGE054
Wherein
Figure 2014100813276100002DEST_PATH_IMAGE055
it is channel
Figure 283730DEST_PATH_IMAGE006
middle transmitting node
Figure 702073DEST_PATH_IMAGE044
to primary user obstacle gain,
Figure 2014100813276100002DEST_PATH_IMAGE057
similar
Figure 789295DEST_PATH_IMAGE058
jamming equation.Set thresholding far below the actual patient maximum interference of primary users, so just can fine realization for primary user's protection problem.
For certain cognitive user in network, on certain particular channel, except receiving the interference of people having a common goal's neighbor node, self also produces and disturbs people having a common goal's neighbor node.Quantize the co-channel interference that certain cognitive user is born
Figure 2014100813276100002DEST_PATH_IMAGE059
as follows:
Figure 72826DEST_PATH_IMAGE060
Wherein,
Figure 2014100813276100002DEST_PATH_IMAGE061
represent that other cognitive user is to present node
Figure 52896DEST_PATH_IMAGE044
transmitting power, that other cognitive user is to present node
Figure 934581DEST_PATH_IMAGE044
link gain,
Figure 2014100813276100002DEST_PATH_IMAGE063
similar
Figure 960306DEST_PATH_IMAGE058
jamming equation.
Similarly, the interference that this cognitive user produces other people having a common goal's neighbor node
Figure 227339DEST_PATH_IMAGE064
as follows:
Figure 2014100813276100002DEST_PATH_IMAGE065
Cognitive user
Figure 363923DEST_PATH_IMAGE044
the interference summation producing from the interference of other cognitive user and to other cognitive user of bearing can be expressed as:
Figure 767222DEST_PATH_IMAGE066
2, the utility function that defines the behavior of each cognitive user access frequency spectrum is throughput
Figure 963848DEST_PATH_IMAGE039
, carry out the distributed utility function optimal solution that solves cognitive user to reach the optimum of overall network performance, i.e. Nash Equilibrium by building non-cooperative game framework.
First, a game of definition is
Figure 2014100813276100002DEST_PATH_IMAGE067
.In betting model,
Figure 655861DEST_PATH_IMAGE068
it is the set of all transmitting nodes of cognition network; about transmitting node
Figure 330556DEST_PATH_IMAGE044
behavioral strategy; target function, transmitting node expectation maximization target function.
Secondly, define each cognitive user nodes utility function
Figure 2014100813276100002DEST_PATH_IMAGE071
for the throughput of transmitting-receiving node
Figure 221468DEST_PATH_IMAGE072
, throughput equation is as follows:
Figure 2014100813276100002DEST_PATH_IMAGE073
Consider the co-channel interference between unauthorized user, should guarantee that the interference between each cognitive user can not cause the signal interference ratio at receiver place
Figure 132268DEST_PATH_IMAGE048
lower than minimum signal interference ratio that can demodulation
Figure 610654DEST_PATH_IMAGE074
, correspond in the design of cognitive user utility function, if we find
Figure 254125DEST_PATH_IMAGE048
be less than 1, the numerical value obtaining is for negative.This means now
Figure 589291DEST_PATH_IMAGE007
the too low transmitting node that causes of value can not be launched, and the throughput of whole network is contributed to negative growth.
Again, quantize the interference of CR-to-PU, CR-to-CR, it is as follows as interference constraints condition:
Figure DEST_PATH_IMAGE075
Figure 255896DEST_PATH_IMAGE076
Figure DEST_PATH_IMAGE077
Figure 272393DEST_PATH_IMAGE004
Figure 770371DEST_PATH_IMAGE078
Figure DEST_PATH_IMAGE079
Wherein,
Figure 214122DEST_PATH_IMAGE025
to be operated in channel
Figure 368023DEST_PATH_IMAGE006
on primary user; it is jamming equation.Constraints
Figure DEST_PATH_IMAGE081
mean transmitting node to corresponding receiving node
Figure 483243DEST_PATH_IMAGE002
have and can only be in channel group
Figure 858861DEST_PATH_IMAGE082
in a channel, but multiple cognitive user can share same channel; This constraints is embodied in signal interference ratio
Figure 279478DEST_PATH_IMAGE007
computing formula in.
3, lead-in cost function is punished the utility function behavior of fleeing from of cognitive user, suppresses the selfish sexual behaviour of cognitive user;
Consider the interference that primary user is suffered, definition is operated in channel
Figure 752047DEST_PATH_IMAGE006
on primary user as follows:
Figure DEST_PATH_IMAGE083
Figure 621893DEST_PATH_IMAGE004
Figure DEST_PATH_IMAGE085
Wherein
Figure 886652DEST_PATH_IMAGE031
primary user
Figure 171003DEST_PATH_IMAGE056
the cognition wireless network being subject to disturbs,
Figure 521213DEST_PATH_IMAGE032
be
Figure 283633DEST_PATH_IMAGE033
the maximum interference that middle primary user is subject to.
For certain cognitive user in network, on certain particular channel, except being subject to the interference of people having a common goal's neighbor node, self also produces and disturbs people having a common goal's neighbor node.Defined cognitive user
Figure 465215DEST_PATH_IMAGE044
co-channel interference sum be
Figure 858150DEST_PATH_IMAGE086
:
For ad-hoc network, distributed network architecture makes the cognitive user in network can freely determine the messaging parameter of oneself and correspondingly improves communication link (the higher message transmission rate of self, lower error rate etc.), the resource but the restricted gender of usable spectrum resource and maximum transmitted gross power can cause vying each other between cognitive user, one of its negative effect is exactly that the Pareto efficiency of network equilibrium is low.In the environment that does not have mandatory constraints to reach, cognitive user even can be fled from original utility function according to the benefit of self.For this reason, consider above two kinds of interference, set it as the foundation of the selfish sexual behaviour of restriction cognitive user, user obtains corresponding network throughput by bidding.Lead-in cost function is punished the utility function behavior of fleeing from of cognitive user, suppresses the selfish sexual behaviour of cognitive user.Defined cognitive user
Figure 695656DEST_PATH_IMAGE044
cost function and total utility function as follows:
Figure 261767DEST_PATH_IMAGE088
Figure DEST_PATH_IMAGE089
Wherein
Figure 235539DEST_PATH_IMAGE090
,
Figure DEST_PATH_IMAGE091
constant, as the coefficient of linear cost function.
4, utilize non-cooperative game to be built into a latent betting model, guarantee its convergence.
The object of game is to reach balanced, and namely all participants' strategy can reach a kind of stable state.Nash Equilibrium is the one equilibrium of static game of complete information, is defined as follows:
Game
Figure 799376DEST_PATH_IMAGE092
in, wherein strategy combination a Nash Equilibrium, if with respect to participant
Figure 186495DEST_PATH_IMAGE044
,
Figure 225470DEST_PATH_IMAGE094
to select in given all the other participant's optimal policies participant in situation
Figure 319328DEST_PATH_IMAGE044
optimal policy, that is:
Figure 116383DEST_PATH_IMAGE096
Figure DEST_PATH_IMAGE097
Can find out that from definition Nash Equilibrium is a kind of stable state of game, when participant reaches Nash Equilibrium point, can unilaterally deviate from existing state without any a participant.
Solving Nash Equilibrium is more difficult thing, and distributed solving increased difficulty especially.Do not let on person conventionally along with the expansion of game, and iteration is accumulated observation, and wishes that process can converge to equilibrium point.Although this situation is not to have simulated to greatest extent a game process, in the time that scene is modeled as latent game, can guarantee the convergence of game process, guarantee that it converges to Nash Equilibrium.
Latent game is a kind of betting model that utility function meets specific condition.
Definition: game
Figure 662902DEST_PATH_IMAGE092
in, there is the function of diving
Figure 836394DEST_PATH_IMAGE098
meet following some conditions, this game is the game of diving.
i)
Figure DEST_PATH_IMAGE099
ii)
Figure 752715DEST_PATH_IMAGE099
Figure DEST_PATH_IMAGE101
Wherein
Figure 786530DEST_PATH_IMAGE102
is-symbol function.Satisfy condition is i) game of accurately diving; Ii satisfies condition) be the latent game of order.
The feature of latent game is: when all participants make decisions in order, latent game can guarantee that game process converges to Nash Equilibrium point in limited step.The searching of latent function is the precondition of game modeling of diving, represent that game overall interests in convergence process promote, in other words, any one participant makes better decision-making and can make latent functional value further promote in convergence process, this point is apparent from definition, and in the game of diving, individual interest is consistent with entire system interests.
Figure DEST_PATH_IMAGE103
as latent function, the utility function of each cognitive user is:
Figure 170238DEST_PATH_IMAGE104
If each user from
Figure DEST_PATH_IMAGE105
strategy change over
Figure 238688DEST_PATH_IMAGE106
time,
Figure DEST_PATH_IMAGE107
variation be greater than
Figure 315228DEST_PATH_IMAGE108
corresponding variation, so our just network modelling one-tenth order can be dived game and then existence of assurance Nash Equilibrium point.
Prove as follows:
If
Figure 898656DEST_PATH_IMAGE103
be the function of diving, have a definite function of diving
Figure DEST_PATH_IMAGE109
meet following formula:
Figure 83126DEST_PATH_IMAGE110
Work as existence
Figure DEST_PATH_IMAGE111
time, sign function meets:
Figure 6082DEST_PATH_IMAGE112
If right , hypothesis is below set up:
Figure 315841DEST_PATH_IMAGE114
There is following expression:
Defined from latent game, as long as meet above-mentioned inequality assumed condition, be
Figure 315338DEST_PATH_IMAGE116
latent function, meet dive game definition of order, network can be modeled as latent betting model.
The game process of diving is the process of cognitive user continuous renewal self channel selection and transmission power information.Effectiveness when first each cognitive user calculates it and use other channel according to the channel selection strategies of current other cognitive user; Then utility function value when each cognitive user is by other channel of more current use is selected current optimum utility channel in order; And then each cognitive user is selected suitable power by the effectiveness of calculating under different transmission power; By cycle calculations, obtain a kind of equilibrium state.
Like this obtain with
Figure 155118DEST_PATH_IMAGE088
as the utility function expression formula of the function of diving, illustrate that the utility function value of game or latent functional value are along with the accumulation of iterative process is constantly to promote, in other words, each participant (cognitive user) in game constantly updates and optimizes channel selection and the power distribution strategies of self by comparison procedure repeatedly, distributed contribution is improved overall network effectiveness, and tend towards stability (Nash Equilibrium).
Between cognition network and primary user's network based on temperature interference model share spectrum resources; Total utility function is channel
Figure 635778DEST_PATH_IMAGE006
middle cognitive user
Figure 865902DEST_PATH_IMAGE044
the throughput obtaining deducts to disturb the cost function as cost.For the protection to primary user, cognitive network resource is nowhere near.If there is not the condition that suppresses transmitting node, so each cognitive user can be from the one-sided effectiveness that increases of number one in the time of access channel
Figure 723000DEST_PATH_IMAGE029
, some inappropriate transmitting nodes can unilaterally be selected maximum transmitting power transmitting and not consider other situation, will certainly cause like this other suitable transmitting node because total interference of primary user is approached threshold value and can not be launched.Therefore introduce
Figure DEST_PATH_IMAGE117
as the restriction to cognitive user (
Figure 354969DEST_PATH_IMAGE090
,
Figure 6530DEST_PATH_IMAGE091
constant, as the coefficient of linear cost function).Cognitive user, selecting most suitable power and channel when maximizing the throughput self obtaining, must be considered the various interference that corresponding transmitting power produces, and therefrom obtain the cost after frequency spectrum resource with this as it.
Introduce
Figure 989530DEST_PATH_IMAGE118
, correspondingly cognitive user can tend to select most suitable channel, and this cognitive user is when the work of this channel
Figure DEST_PATH_IMAGE119
can be less than its value in other channel work.Obviously, the throughput of cognition wireless network and fairness can be improved thus.
Figure 322422DEST_PATH_IMAGE090
the selected of value will be a practical problems; too small, may cause so interference to suppress too small and network performance is reduced; excessive, may cause so disturbing and suppress by force and make to promote network throughput and become very difficult;
Figure 996981DEST_PATH_IMAGE090
numerical value may affect convergence rate.From point of theory, as embodying the factor of primary user being disturbed to inhibition, larger value should be got, excessively interference can be reduced rapidly, protection primary user while even exceeding primary user's thresholding to guarantee to disturb.
Introduce
Figure 536864DEST_PATH_IMAGE120
.If
Figure 795807DEST_PATH_IMAGE090
a kind of to the rigid macro adjustments and controls of cognitive user nodes, so
Figure 284557DEST_PATH_IMAGE091
can be that one regulates and controls soft ground of cognitive user microcosmic.Cognitive user is weighed effectiveness and cost, and the messaging parameter of oneself is suitably adjusted.If the Internet resources of self asking for are more, its cost of paying is just higher so; If lacking of resource occupying, so corresponding paying is also just lower.
Figure 224831DEST_PATH_IMAGE091
value will be also a practical problems,
Figure 748217DEST_PATH_IMAGE120
the value throughput order of magnitude or less that coexists that should obtain with cognitive user, to regulate the effectiveness of each cognitive user when the Nash Equilibrium, improve Pareto efficiency.
Thereby each cognitive user increases the target function of self continuously, in this accurate game, to reach Nash Equilibrium point be a kind of method of practicality.In order to realize the Continuous behavior of each cognitive user, we introduce a kind of simple random access mechanism: each cognitive user with
Figure DEST_PATH_IMAGE121
probability upgrade self strategy.In particular, each cognitive user incipient stage of each time slot with
Figure 850165DEST_PATH_IMAGE122
probability determines whether in Common Control Channel, carry out transfer of data, whether does according to the value of utility of current utility function the decision-making making new advances.If success, corresponding cognitive user access network, carries out transfer of data; Otherwise continue to intercept channel.Suppose that cognitive user all can correct perception to all channels, in the Common Control Channel that the resource request of other cognitive user and Signalling exchange information all can reach at the whole network, broadcast.Cognitive user can be known channel selection information separately each other.This scheme has guaranteed that an average time point only has a cognitive user to take action, and meanwhile exceeding the probability that a cognitive user takes action is non-zero.Take action when two or multiple cognitive user, latent function may temporarily decline simultaneously, but this can not destroy the trend of the overall monotone increasing of potential function.
Select joint Power to distribute and these two uncertain factors of channel, by distributed algorithm, resource is effectively distributed, as shown in Figure 2 and Figure 3.Wherein Fig. 2 is overall flow figure, and Fig. 3 is supplementing of Fig. 2, take the channel of determining optimum utility as cutting point, provides the concrete operations flow process of each cognitive user.Algorithm is as follows:
Step1: set ad-hoc network topology, produce at random cognitive user pair, calculate communication node link gain
Figure DEST_PATH_IMAGE123
, initialization cognitive user effectiveness
Figure 29473DEST_PATH_IMAGE124
, channel is selected
Figure DEST_PATH_IMAGE125
, power , the coefficient of bidding
Figure 885751DEST_PATH_IMAGE090
,
Figure 424180DEST_PATH_IMAGE091
, given cognitive user nodes target throughput
Figure DEST_PATH_IMAGE127
; Initialization random access procedure;
Step2: each cognitive user is calculated successively respectively current power and selected
Figure 825205DEST_PATH_IMAGE126
, channel is selected
Figure 169599DEST_PATH_IMAGE125
under effectiveness
Figure 667576DEST_PATH_IMAGE124
and throughput
Figure 108397DEST_PATH_IMAGE039
;
Step3: judge all cognitive user nodes
Figure 324615DEST_PATH_IMAGE128
, if so, finish algorithm; Otherwise, carry out step4;
Step4: judge whether that all cognitive user nodes all reach maximum transmission power, if so, finish algorithm; Otherwise, carry out step5;
Step5: judge whether to reach maximum iteration time, if so, finish algorithm; Otherwise, carry out step6;
Step6: present cognitive user node calculates current power successively
Figure 144804DEST_PATH_IMAGE126
under, use the effectiveness of other available channel
Figure 497287DEST_PATH_IMAGE124
, and throughput
Figure 174256DEST_PATH_IMAGE039
;
Step7: present cognitive user node compares the effectiveness under different channels selection
Figure 549874DEST_PATH_IMAGE124
, select and there is the channel of maximum utility and upgrade, calculate corresponding throughput simultaneously
Figure 236070DEST_PATH_IMAGE039
; Otherwise, return to step3;
Step8: judge the throughput that present cognitive user node obtains
Figure 380744DEST_PATH_IMAGE128
if reduce node transmitting power, and enter step2; Otherwise, increase node transmitting power, and enter step2.
Comparing with the scheme for combining of original power and channel allocation, there is following advantage in this programme:
1, utilize non-cooperative game model effectively to solve distributed cognition network joint Power and Channel Assignment Problems, change the Nonlinear Optimization Problem of general objective function (aggregate network throughput) into distributed cognition user's target function.
2, build the convergence of the corresponding betting model assurance network of diving, guarantee the existence of Nash Equilibrium.
3, will disturb the cost function suppressing as cognitive user, user obtains corresponding Internet resources (throughput) by bidding.
4, take into full account the interference of CR-to-PU, CR-to-CR, realize and disturb the quantification and the restriction that suppress, and as cost function.
Embodiment
The present invention is directed to ad-hoc network model, ascending resource (power and channel) assignment problem in the single multichannel cognition wireless network of distributed solution.The type of cognitive user can be mobile phone, vehicle radio station, PDA or other.A network (WSN) emulation system is as shown in Figure 1: cognitive user
Figure DEST_PATH_IMAGE129
be randomly dispersed in the region of 100m*100m, available orthogonal number of channel K=4, maximum iteration time is 1000 times.All cognitive user select transmitting power and available channel as init state at random.Suppose that all cognitive user all can correct perception to all channels, in the Common Control Channel that the resource request of other cognitive user and Signalling exchange information all can reach at the whole network, broadcast.Cognitive user can be known transmitting power and corresponding channel selection information separately each other.Between not existing center to control, the enforcement of this method information interaction between each cognitive user that places one's entire reliance upon, each cognitive user makes a policy in strict accordance with algorithm.The flow process of concrete steps as shown in above-mentioned Fig. 2, Fig. 3.
Fig. 4 is the function (cost function of diving
Figure 431877DEST_PATH_IMAGE088
) convergence schematic diagram, the convergence process of function of diving is consistent with whole network convergence process, because the betting model of diving all can make overall network performance further be promoted while making any one participant make better decision-making in convergence process.The utility function design of introducing price mechanism has fully demonstrated the interference inhibition between interference inhibition and the cognitive user to primary user, improves the utilance of resource distributional equity and frequency spectrum.
The foregoing is only better embodiment of the present invention; be not limited to the present invention; technical staff under any the present invention; do not departing under the prerequisite of the disclosed spirit and scope of the present invention; can do any modification and variation what implement in form and in details; but scope of patent protection of the present invention, still must be as the criterion with the scope that appending claims was defined.

Claims (7)

1. joint Power and a method for channel allocation in cognition wireless network, is characterized in that, comprises the following steps:
(1) interference suffered between primary user and cognitive user on each channel in multichannel cognition wireless network, between each cognitive user is realized and quantizes and limit;
(2) utility function that defines the behavior of each cognitive user access frequency spectrum is throughput
Figure 2014100813276100001DEST_PATH_IMAGE001
, carry out the distributed utility function optimal solution that solves cognitive user to reach the optimum of overall network performance by building non-cooperative game framework;
(3) introduce corresponding cost function the resource occupation behavior of cognitive user is fixed a price, the selfishness of restriction cognitive user;
(4) utilize non-cooperative game to be built into a latent betting model, guarantee its convergence.
2. joint Power and method for channel allocation in a kind of cognition wireless network according to claim 1, is characterized in that, in step (1):
Suppose an ad-hoc cognitive radio networks being formed by multiple cognitive user, have primary user to exist around,
Figure 2014100813276100001DEST_PATH_IMAGE002
scope in random distribution
Figure 2014100813276100001DEST_PATH_IMAGE003
individual cognitive user pair, a cognitive user is to comprising a transmitting node and a receiving node; Frequency spectrum by kindividual orthogonal channel composition, k< n, have simultaneously
Figure 2014100813276100001DEST_PATH_IMAGE004
individual primary user's node, each primary user can be operated on one or more channels; Defined cognitive user
Figure 888662DEST_PATH_IMAGE005
transmitting power vector
Figure 2014100813276100001DEST_PATH_IMAGE006
,
Figure 2014100813276100001DEST_PATH_IMAGE007
for cognitive user
Figure 50653DEST_PATH_IMAGE005
at channel
Figure 2014100813276100001DEST_PATH_IMAGE008
on transmitting power; Channel
Figure 2014100813276100001DEST_PATH_IMAGE009
, receiver reception
Figure 2014100813276100001DEST_PATH_IMAGE011
can be expressed as:
Figure 2014100813276100001DEST_PATH_IMAGE012
Wherein,
Figure 2014100813276100001DEST_PATH_IMAGE013
it is cognitive user
Figure 190779DEST_PATH_IMAGE005
channel
Figure 2014100813276100001DEST_PATH_IMAGE014
transmission exists place receive signal interference ratio ( ),
Figure 2014100813276100001DEST_PATH_IMAGE016
it is node
Figure 2014100813276100001DEST_PATH_IMAGE017
arrive
Figure 494514DEST_PATH_IMAGE010
transmission gain;
Figure 2014100813276100001DEST_PATH_IMAGE018
it is receiver
Figure 460196DEST_PATH_IMAGE010
the thermal noise at place, is generally constant;
Figure 2014100813276100001DEST_PATH_IMAGE019
it is channel
Figure 579462DEST_PATH_IMAGE008
in the transmitting power of node;
Figure DEST_PATH_IMAGE020
jamming equation,
Figure 2014100813276100001DEST_PATH_IMAGE021
for removing
Figure 872220DEST_PATH_IMAGE005
other cognitive user in addition:
Figure DEST_PATH_IMAGE022
Set
Figure 376013DEST_PATH_IMAGE023
for primary user's maximum interference power, so, channel
Figure 412102DEST_PATH_IMAGE008
in all cognitive user must meet total interference of each primary user:
Figure DEST_PATH_IMAGE024
Wherein
Figure 2014100813276100001DEST_PATH_IMAGE025
it is channel middle transmitting node
Figure 35162DEST_PATH_IMAGE005
to primary user obstacle gain, similar
Figure DEST_PATH_IMAGE028
jamming equation;
For certain cognitive user in network, on certain particular channel, except receiving the interference of people having a common goal's neighbor node, self also produces and disturbs people having a common goal's neighbor node; Quantize the co-channel interference that certain cognitive user is born
Figure 2014100813276100001DEST_PATH_IMAGE029
as follows:
Figure DEST_PATH_IMAGE030
Wherein, represent that other cognitive user nodes is to present node
Figure 238520DEST_PATH_IMAGE005
transmitting power,
Figure DEST_PATH_IMAGE032
that other cognitive user nodes is to present node
Figure 332378DEST_PATH_IMAGE005
link gain,
Figure 2014100813276100001DEST_PATH_IMAGE033
similar jamming equation;
The interference that this cognitive user produces other people having a common goal's neighbor node
Figure DEST_PATH_IMAGE034
as follows:
Cognitive user
Figure 613635DEST_PATH_IMAGE005
the interference summation producing from the interference of other cognitive user and to other cognitive user of bearing can be expressed as:
Figure DEST_PATH_IMAGE036
。
3. joint Power and method for channel allocation in a kind of cognition wireless network according to claim 2, is characterized in that, in step (2):
First, a game of definition is
Figure 2014100813276100001DEST_PATH_IMAGE037
; In betting model,
Figure DEST_PATH_IMAGE038
the set of all transmitting nodes of cognition wireless network,
Figure 2014100813276100001DEST_PATH_IMAGE039
about transmitting node
Figure 396914DEST_PATH_IMAGE005
behavioral strategy;
Figure DEST_PATH_IMAGE040
target function, transmitting node expectation maximization target function;
Secondly, define each cognitive user nodes utility function for the throughput of transmitting-receiving node
Figure DEST_PATH_IMAGE042
, throughput equation is as follows:
Figure DEST_PATH_IMAGE043
Moreover, quantizing the interference of CR-to-PU, CR-to-CR, it is as follows as interference constraints condition:
Figure DEST_PATH_IMAGE044
Figure DEST_PATH_IMAGE045
Figure DEST_PATH_IMAGE046
Figure 155399DEST_PATH_IMAGE009
Figure 123355DEST_PATH_IMAGE024
Wherein, to be operated in channel
Figure 94853DEST_PATH_IMAGE008
on primary user,
Figure DEST_PATH_IMAGE049
jamming equation, constraints
Figure 806457DEST_PATH_IMAGE045
mean transmitting node
Figure 874907DEST_PATH_IMAGE005
to corresponding receiving node
Figure 13764DEST_PATH_IMAGE010
have and can only be in channel group in a channel, but multiple cognitive user can share same channel.
4. joint Power and method for channel allocation in a kind of cognition wireless network according to claim 3, is characterized in that, in step (3):
Definition is operated in channel on primary user as follows:
Figure DEST_PATH_IMAGE051
Figure DEST_PATH_IMAGE052
Figure 642301DEST_PATH_IMAGE009
Wherein
Figure DEST_PATH_IMAGE054
primary user
Figure 889743DEST_PATH_IMAGE026
the cognition wireless network being subject to disturbs, be
Figure DEST_PATH_IMAGE056
the maximum interference that middle primary user is subject to;
Defined cognitive user cost function with total utility function
Figure DEST_PATH_IMAGE058
as follows:
Figure DEST_PATH_IMAGE059
Wherein
Figure DEST_PATH_IMAGE061
,
Figure DEST_PATH_IMAGE062
constant, as the coefficient of linear cost function.
5. joint Power and method for channel allocation in a kind of cognition wireless network according to claim 4, is characterized in that, in step (4):
as cost function, each user's total utility function is:
Figure DEST_PATH_IMAGE063
If each user from
Figure DEST_PATH_IMAGE064
strategy change over time,
Figure DEST_PATH_IMAGE066
variation be greater than
Figure DEST_PATH_IMAGE067
corresponding variation, the game of network modelling one-tenth order being dived.
6. joint Power and method for channel allocation in a kind of cognition wireless network according to claim 5, is characterized in that: with
Figure 211244DEST_PATH_IMAGE059
as latent function, α, βfor coefficient undetermined; Network struction is become to the order betting model of diving, can converge to Nash Equilibrium point and also meet rapidly the restriction of interference constraints by distributed game orderly, guaranteed the convergence of network.
7. joint Power and method for channel allocation in a kind of cognition wireless network according to claim 6, is characterized in that, selects joint Power to distribute and these two uncertain factors of channel, by distributed algorithm, resource effectively distributed; Its algorithm is as follows:
Step1: set ad-hoc network topology, produce at random cognitive user pair, calculate communication node link gain
Figure DEST_PATH_IMAGE068
, initialization cognitive user effectiveness , channel is selected
Figure DEST_PATH_IMAGE070
, power
Figure DEST_PATH_IMAGE071
, the coefficient of bidding
Figure 567270DEST_PATH_IMAGE061
,
Figure 62973DEST_PATH_IMAGE062
, given cognitive user nodes target throughput
Figure DEST_PATH_IMAGE072
; Initialization random access procedure;
Step2: each cognitive user is calculated successively respectively current power and selected
Figure 654491DEST_PATH_IMAGE071
, channel is selected
Figure 552040DEST_PATH_IMAGE070
under effectiveness
Figure 203601DEST_PATH_IMAGE069
and throughput
Figure 921022DEST_PATH_IMAGE001
;
Step3: judge all cognitive user nodes
Figure DEST_PATH_IMAGE073
, if so, finish algorithm; Otherwise, carry out step4;
Step4: judge whether that all cognitive user nodes all reach maximum transmission power, if so, finish algorithm; Otherwise, carry out step5;
Step5: judge whether to reach maximum iteration time, if so, finish algorithm; Otherwise, carry out step6;
Step6: present cognitive user node calculates current power successively
Figure 316231DEST_PATH_IMAGE071
under, use the effectiveness of other available channel
Figure 68286DEST_PATH_IMAGE069
, and throughput
Figure 890749DEST_PATH_IMAGE001
;
Step7: present cognitive user node compares the effectiveness under different channels selection , select and there is the channel of maximum utility and upgrade, calculate corresponding throughput simultaneously
Figure 294365DEST_PATH_IMAGE001
; Otherwise, return to step3;
Step8: judge the throughput that present cognitive user node obtains
Figure 963244DEST_PATH_IMAGE073
if reduce node transmitting power, and enter step2; Otherwise, increase node transmitting power, and enter step2.
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