CN101820665B - Admission control method and system in heterogeneous wireless network environment - Google Patents

Abstract

The invention discloses an admission control method and an admission control system in a heterogeneous wireless network environment. The method comprises the following steps of: when an access request is received, collecting the multi-domain information of each network and acquiring a target quality of experience (QoE) vector of a user in the access request by using an admission control entity; performing granularity partition on the information of each attribute domain in the multi-domain information according to a predefined performance index to form information granularity vectors of each attribute domain; according to the target QoE vector of a user terminal and a predefined fuzzy membership function, establishing fuzzy membership grade vectors of resource grains in each attribute domain; based on fuzzy evaluation vectors and inference rules of the resource grains in each attribute domain, establishing mapping relationships between the fuzzy evaluation vectors of the resource grains in each attribute domain and a network comprehensive evaluation index so as to acquire a comprehensive evaluation vector; and according to comprehensive evaluation, selecting the network having the highest network grade of service as an access network. Through the method and the system, an effective admission control strategy is designed for the heterogeneous wireless network and the overall performance of the heterogeneous wireless network is improved.

Description

Acceptance controlling method under the heterogeneous wireless network environment and system

Technical field

The present invention relates to communication technical field, relate in particular to acceptance controlling method and system under a kind of heterogeneous wireless network environment.

Background technology

Be accompanied by the multifarious development of various wireless access technologys and business demand, following B3G and 4G network will be complex network environments with the characteristics of tautomerizing to.Simultaneously, because the development of digital signal decision-making technic, chip integrated technology and radio-frequency technique possesses the important trend that many network accessibilities also become following intelligent terminal development.How rationally utilizing the network isomerism with the optimization system overall performance, experience for the user provides seamless best service, is the hot issue of current heterogeneous network research.

In order to realize the right sex change to multi-domain environment, system need carry out cognition to multiple domain information in wireless, network complicated and changeable, service environment.Different with admittance control in the conventional cellular network; In heterogeneous network, not only need consider available network, also will take multiple domain multidimensional information such as situation, channel situation, available service resource, QoS of survice, the abstract method of the attribute dimensions of research multiple domain information according to heterogeneous networks communication pattern, frequency spectrum; Make up the resource space of many granularities; Thereby back-up system is made optimizing decision, selects optimal network, makes the heterogeneous network overall performance maximize.

Existing research of admitting control for heterogeneous network; Mainly be to the combination admission control between single professional two networks; Under the prerequisite that guarantees QoS of survice; Make system utility value maximization, Fei Yu for example, Vikram Krishnamurthy delivers is entitled as " Optimal JointSession Admission Control in Integrated WLAN and CDMA CellularNetworks with Vertical Handoff " and Ben Ali.R; The article that is entitled as " Optimal Voice Admission Control Performance under Soft VerticalHandoff in Loosely Coupled 3G/WLAN Networks " that Pierre.S delivers; The existing algorithm of considering two network multi-services, but the algorithm autgmentability is bad, complexity is bigger, is unfavorable for practical application; The representative index of minority (SNR, delay etc.) is also just chosen in the consideration of QoS of survice in the existing algorithm; And business tine is rich and varied in the following heterogeneous network; Needs assessment user is for the comprehensive experience of heterogeneous-network service, i.e. QoE (Quality ofExperience); Therefore, the algorithm that guarantees of existing QoS and be not suitable for many networks, multidimensional, multiple domain information scene and use.

In addition, between resource space that makes up many granularities and resources for research grain during incidence relation, the equivalence between often can not the precise definition Internet resources, but approximation between the research Internet resources; Simultaneously, the user has fuzzy characteristic for the perception of QoE, and confirm and uncertain, the clear and fuzzy of notion of information also all are relative.

Summary of the invention

The technical problem that (one) will solve

To defective that exists in the prior art and deficiency; The purpose of this invention is to provide the admittance controlling schemes under a kind of heterogeneous wireless network environment; It can be estimated the resource of heterogeneous wireless network multidimensional multiple domain; And can utilize reasoning from logic to set up the relation between wireless network resource space and the different business QoE demand, select only network, thereby promote the overall performance of heterogeneous wireless network system as access network.

(2) technical scheme

For achieving the above object, the invention provides the acceptance controlling method under a kind of heterogeneous wireless network environment, may further comprise the steps:

S1, when the access request of receiving from user terminal, the multiple domain information of collecting each network is obtained the target QoE vector of user terminal simultaneously;

S2 divides according to the information that predefined evaluation index is carried out the multiattribute territory to said multiple domain information, forms the resource information vector of each Attribute domain;

S3 according to the target QoE vector and the predefined fuzzy member function of said user terminal, sets up the fuzzy membership vector of resource grains in each Attribute domain;

S4; Fuzzy membership vector and fuzzy inference rule based on resource grains in each Attribute domain; Set up the fuzzy membership vector of resource grains in each Attribute domain and the mapping relations between the network synthesis performance evaluation index, thereby obtain the comprehensive performance evaluation of each alternative network;

S5 selects the highest network of comprehensive performance evaluation as best access network, carries out acceptance judging.

Wherein, said target QoE vector comprises the component of availability, quality of the conversation, service delay and four aspects of fail safe.

Wherein, when the information of in step S2, carrying out is divided, said multiple domain information is divided into the information of availability, quality of the conversation, service delay and four Attribute domains of fail safe.

The present invention also provides the acceptance control system under a kind of heterogeneous wireless network environment, comprising:

The information gathering module is used for when the access request of receiving from user terminal, and the multiple domain information of collecting each network is obtained the target QoE vector of user terminal simultaneously; And be used for dividing, form the resource information vector of each Attribute domain according to the information that predefined evaluation index is carried out four Attribute domains to said multiple domain information;

The information inference module is used for target QoE vector and predefined fuzzy member function according to said user terminal, sets up the fuzzy membership vector of resource grains in each Attribute domain; And based on the fuzzy membership vector and the inference rule of resource grains in each Attribute domain, set up the fuzzy membership of resource grains in each Attribute domain and the mapping relations between the network synthesis performance evaluation index, thereby obtain the comprehensive performance evaluation of each alternative network;

Admit the control decision module, select the highest network of comprehensive performance evaluation, carry out acceptance judging as best access network.

(3) beneficial effect

Compared with prior art; The present invention can produce following beneficial effect: to the multiple domain information scene of DYNAMIC COMPLEX; It is abstract that the multiple domain information space is carried out modelling; From the angle of user experience (QoE) multiple domain information is carried out the decomposition of different attribute dimension respectively, and make up its incidence relation, realized the modelling of multiple domain information space abstract; Based on multiattribute domain information space; Utilize fuzzy logic system that the resource information grain is described and carry out reasoning, realized that knowledge converges, reached the purpose of the abstract of complex information; Final formation effective admission control strategy, thereby the utilance of elevator system resource.

Description of drawings

Fig. 1 is the many networks hot spot coverage scene sketch map in the isomerous environment of the embodiment of the invention;

Fig. 2 is the structural representation of acceptance control system under the heterogeneous wireless scene of the embodiment of the invention;

Fig. 3 is the schematic flow sheet of acceptance controlling method under the heterogeneous wireless scene of the embodiment of the invention;

Fig. 4 is the illustraton of model of resource granularity division of the present invention and fuzzy granularity reasoning;

Fig. 5 selects (RN-AC) and tradition not to support single Attribute domain admission control algorithm (SD-AC) of the guaranteed qos of granularity division to compare with random network the scheme of the embodiment of the invention, the admittance request rejection probability comparison diagram that obtains;

Fig. 6 selects the method for inventive embodiments (RN-AC) and does not support single Attribute domain admission control algorithm (SD-AC) of granularity division to compare the comparison diagram of resource utilization ratio with random network.

Embodiment

Below in conjunction with accompanying drawing and embodiment, specific embodiments of the invention describes in further detail.Following examples are used to explain the present invention, but are not used for limiting scope of the present invention.

The present invention has used for reference popular research field in the computer science---and the grain computation model has proposed a kind ofly can consider effectively that isomerous environment strides layer admission control mechanism of multiple domain resource information.In order to understand the bright principle of we better, describe in the face of the grain computation model and to enlightenment of the present invention down.

Human when handling large amount of complex information because human cognitive is limited in one's ability, tend to a large amount of complex information by its separately characteristic with performance it is divided into some comparatively simple pieces, piece that each quilt is branched away just is regarded as a grain.Goods like the market is varied, so people are divided into some and arrange shelf with this by the kind of goods that shelf are put, volume, grade etc. with the market, said here is exactly the notion of grain, and the process of dividing grain is called the information granulation.

In fact, grain just is meant that some individualities (element, point etc.) are through formed of fuzzy relation, similarity relation, proximity relations or functional relationship etc.Grain calculates (granularcomputing) this term and is proposed by T.Y.Lin at first, and it is a kind of new intelligence computation theory and method of dividing based on the problem concept space that grain calculates.The basic problem of Granular Computing comprises two main aspects, the one, and tectonic information granularity how, the 2nd, how to utilize granularity to remove to calculate (problem solving).The former emphasis is considered form, thickness, expression and the explanation of granularity, and the latter considers that the what use is made of granularity goes to find the solution problem.Utilizing the calculating of granularity to comprise two aspects, is the relation of explaining between the various granularities on the one hand, like the degree of approach, dependency degree, the degree of association, thus the operator on definite and the explanation granularity; Be the algorithm of design Granular Computing on the other hand, as approach, reasoning etc.The basic theories framework of Granular Computing comprises: the decomposition and the merging of local grain, the granulation and the grain in domain space that how to define the building method of grain, grain, the computation rule of grain, whole grain approach the Algebraic Structure of compatible operator in the Granular Computing and operator of equal value and grain etc.The present invention mainly adopts fuzzy logic system to carry out the reasoning decision-making of resource grains.

In heterogeneous wireless communication system, the characteristics such as otherness of the heterogeneite of the otherness of network configuration, network optimization strategy, the diversity of class of business and terminal unit ability will make traditional admission control scheme can not be suitable for to a great extent.A angle of calculating based on fuzzy logic from effective evaluation user QoE; Wireless resource information is divided into availability, quality of the conversation, service delay and four attribute dimensions of fail safe (the performance performance of network on each attribute dimensions is called " resource grains "), can characterizes user's QoE demand comparatively all sidedly; On the basis that the information dimension is divided; Utilize fuzzy logic system to carry out reasoning and meet the uncertainty, user of resource assessment fuzzy behaviour for the QoE perception; Help forming the effective mapping between wireless network resource grain and the different business user QoE demand, thereby form effective admission control strategy.

As shown in Figure 1, be the sketch map of the many networks hot spot coverage scene in the isomerous environment of the embodiment of the invention.In this hot spot coverage, a plurality of Radio Access Networks (the for example WiMAX shown in Fig. 1, UMSS, WLAN_1 and WLAN_2) are arranged, be without loss of generality, alternative access network set is expressed as Ω={ AN ₁, AN ₂..., AN _S.The present invention estimates Radio Resource from availability, quality of the conversation, service delay and four attribute dimensions of fail safe, and (considering the resource granularity of four Attribute domains), and be the representative evaluation index of each Attribute domain selection; Simultaneously, on the basis of resource division, the fuzzy logic system carries out reasoning to each Attribute domain resource grains, to coarseness, forms comprehensive evaluation index by fine granularity then.

As shown in Figure 3, admit the method flow sketch map of control down for the heterogeneous wireless network of the embodiment of the invention, specifically may further comprise the steps:

S1, user terminal send the request of access and give the information gathering functional module, trigger the multiple domain information gathering of each network, and this module also can be received the QoE target vector that is included in the request of access simultaneously;

S2, many networks multiple domain information that the information gathering module of overlapping covered each network will be collected is carried out the information division, forms multiattribute territory vector, and with vector quantization data passes to information inference module;

Wherein, the user QoE target vector information that the information preliminary treatment submodule in the information gathering module inserts request comes with the information that obtains and accompanying terminal changes into the form of resource vector, and is specific as follows said:

For the arbitrary network A N in the current alternative collection of network _k∈ Ω, the information that we explain wireless network resource with multidimensional vector,

Be the information vector of k network in i Resource Properties territory, i=1,2,3,4 represent availability, quality of the conversation, service delay and fail safe respectively.Network is divided in the evaluation index of different attribute dimension can be slightly different by different needs.As shown in table 1, what this programme provided is the representative evaluation index of each Attribute domain, and is example with evaluation index shown in this table, and the specific embodiment of scheme is described.

Table 1

Availability	Mobility	Expense	MTBF
				Quality of the conversation	Delay variation	Propagation delay time	The error rate
The service promptness	Propagation delay time	Delay variation	MTBF
				Fail safe	Retransmission probability	Subscription authentication	Access interference

Wherein, MTBF (Mean time between failure) representes the time interval (promptly losing efficacy at interval) that the user can not effectively be served.

S3; The information inference module is according to user QoE target vector and predefined fuzzy member function, sets up the fuzzy membership vector of resource grains in each Attribute domain, and for example (0.5; 0.3; 0.2), wherein each element representes that respectively this resource grains is under the jurisdiction of the probability of H, M, L, wherein L, M and H represent " poor-performing ", " performance is general " and " better performances " respectively; Then based on the fuzzy evaluation vector and the inference rule (Inference Rules) of each Attribute domain; Can set up the mapping relations between fuzzy membership vector and the network synthesis performance evaluation index, thereby thereby obtain the comprehensive performance evaluation that the alternative network set obtains each alternative network.Wherein vectorial about the degree of membership of TB, NS, JA, S, five types of integrated service grades of VS.

S4, according to the degree of membership vector, can be according to admitting control criterion to obtain optimum network; This admittance control criterion is: if best network classes of service (Grade of Service; GoS) meet consumers' demand,, insert accordingly with this optimum network then with the result notification corresponding user terminal; Otherwise, refuse the access request of this business.

For being divided the information vector that obtains, information estimates, and might as well be with the normalization dope vector

As the description i=1 of k network on the i Attribute domain, 2,3,4 refer to availability, quality of the conversation, service delay and fail safe, N respectively _iIt is evaluation index number at Attribute domain i; For user terminal QoE target resource vector, be appreciated that to be base vector that therefore, terminal QoE target resource is to the normalization of resource vector:

Therefore, the present invention can be divided into following two steps to the evaluation of resource grains in each Attribute domain:

The definition of a, fuzzy resembling relation.

Definition-1: among the present invention, the similarity about target resource of any resource grains is represented as follows in the i Attribute domain:

$r_i^k=\left|\right|G_i^k|{|}_w$

Wherein || || _wExpression cum rights norm, to n n dimensional vector n G arbitrarily, || G|| _wCan be defined as

w _iBe the weights of i parameter,

Finding the solution of b, fuzzy membership vector.

Definition-2: the present invention defines member function on each resource domains following:

${\mathrm{\&mu;}}_i^k\left(H\right)=\left\{\begin{array}{cc}1,& r_i^k\&GreaterEqual;h_i\\ \exp [-\frac{{(r_i^k-h_i)}^2}{{2\mathrm{\&sigma;}}^2}],& m_i<r_i^k<h_i\\ 0& r_i^k\&le;m_i\end{array}\right.---\left(1\right)$

${\mathrm{\&mu;}}_i^k\left(M\right)=\left\{\begin{array}{cc}\exp [-\frac{{(r_i^k-m_i)}^2}{2{\mathrm{\&sigma;}}^2}],& l_i<r_i^k<h_i\\ 0,& \mathrm{else}\end{array}\right.---\left(2\right)$

${\mathrm{\&mu;}}_i^k\left(L\right)=\left\{\begin{array}{cc}1,& r_i^k\&le;l_i\\ \exp [-\frac{{(r_i^k-l_i)}^2}{2{\mathrm{\&sigma;}}^2}],& l_i<r_i^k<m_i\\ 0& r_i^k\&GreaterEqual;m_i\end{array}---\left(3\right)\right.$

Wherein, l _i, m _i, h _i(i=1,2,3,4) are represented the center of 3 member functions respectively, are used for characterizing the degree of membership requirement of different fuzzy opinion ratings, σ ²Be the width of member function, in the present invention, σ ²=m _i-l _i=h _i-m _i, i.e. the center distance of each member function.

The information parameter that provides with table-1 is an example, according to the fuzzy resembling relation of definition-1 fuzzy similarity of alternative resource and target resource is calculated, and by fuzzy similarity, can obtain the fuzzy membership vector of each Attribute domain according to the member function in the definition-2

And for network k, can obtain the fuzzy membership matrix, H _k=[μ ₁, μ ₂, μ ₃, μ ₄] '

$H_k=\left[\begin{array}{ccc}{\mathrm{\&mu;}}_1^k\left(H\right)& {\mathrm{\&mu;}}_1^k\left(M\right)& {\mathrm{\&mu;}}_1^k\left(L\right)\\ M& M& M\\ {\mathrm{\&mu;}}_4^k\left(H\right)& {\mathrm{\&mu;}}_4^k\left(M\right)& {\mathrm{\&mu;}}_4^k\left(L\right)\end{array}\right]---\left(4\right)$

Wherein, μ _i ^k(x) expression is that the k network is under the jurisdiction of performance class x (x ∈ { H, M, probable value L}) in the i Attribute domain.

Set up fuzzy evaluation vector and reasoning process and specifically comprise following content:

The fuzzy membership evaluation only is that alternative network is integrated into the evaluation on each Attribute domain; In order to obtain the overall merit performance of Internet resources; Calculating based on each Attribute domain fuzzy membership evaluation; Fuzzy reasoning is carried out in the degree of membership evaluation, thereby obtain the overall merit of network k by the fuzzy membership matrix.An important part of fuzzy reasoning mechanism be fuzzy rule base (Inference Rules Base) shown in table-2, be an example of Inference Rules in the fuzzy reasoning mechanism of the present invention (VoIP is professional).Set up the mapping relations of fuzzy evaluation vector and network synthesis performance evaluation below through the fuzzy reasoning criterion.The reasoning criterion is predefined language rule expression formula in the information inference module (Linguistic Rule Expression).For example; IF Availability is H; Session Quality is M, Instantaneity is M andSecurity is L, then GoS is JA; When expression availability, quality of the conversation, service delay and four Attribute domain performance rates of fail safe were respectively H, M, M, L, then the integrated service grade for business of this network (Grade of Service) was JA.

Table-2

What table-2 provided is a sample in the fuzzy inference rule storehouse of specific transactions.Inference rule output is defined as:

Definition-3 this programme are estimated integrated service grade GoS and are defined as:

p _GoS＝min{p ₁，p ₂，p ₃，p ₄} (5)

Wherein, p _iRepresent that the i Attribute domain is the probable value (being fuzzy membership) of particular performance level.Like Rule-1 (i.e. table-2 in the 1st Rule):

p _JA＝min{p ₁(H)，p ₂(M)，p ₃(M)，p ₄(L)}。It should be noted that different user for the customization different business, its QoE demand property of there are differences, simultaneously, the user is also inconsistent to the QoE experience standard in different attribute territory.

With all alternative network set omega={ AN ₁, AN ₂..., AN _SFuzzy membership matrix Δ={ H ₁, H ₂..., H _SThrough indistinct logic computer, obtain the overall merit vector (P of all alternative network _TB, P _NS, P _JA, P _S, P _VS) _k, wherein, k=1,2 ..., S.

Definition-4:GoS evaluation number is:

$\mathrm{GoS}\left(k\right)=\underset{i}{\mathrm{\&Sigma;}}{\mathrm{\&alpha;}}_i\&CenterDot;p_i---\left(6\right)$

α wherein _iIt is the weight coefficient of each Attribute domain.Therefore, admit the result of decision to be expressed as:

${\mathrm{AN}}_{\mathrm{best}}=\underset{k}{\mathrm{Max}}\left\{\mathrm{GoS}\left(k\right)\right\}=\underset{k}{\mathrm{Max}}\{\underset{i}{\mathrm{\&Sigma;}}{a}_i\&CenterDot;p_i\}---\left(7\right)$

Overall merit vector based on all alternative network can obtain court verdict.

The acceptance judging criterion is following:

(1) if the combination property of selected optimal network can not satisfy the basic QoE demand for experience of user, in this programme, user's basic QoE demand is divided to estimate by, subjective MOS and is obtained.Subjective MOS method draws the MOS branch by different user groups' subjective sensation contrast, averages at last.If for selected optimum network:

${\mathrm{AN}}_{\mathrm{best}}=\underset{k}{\mathrm{Max}}\left\{\mathrm{GoS}\left(k\right)\right\}\&GreaterEqual;\mathrm{MOS}---\left(8\right)$

Then selected best access network satisfies user's basic demand, shown in figure-2, by admitting control decision module result notification relevant terminal and network, inserts preparation.

(2) otherwise, AN _BestService performance do not satisfy user's primary demand, then admit of the access request of control decision module with refusing user's.

The embodiment of foregoing invention admits the control scene in many networks of isomery hot spot coverage; The present invention has taken into full account the performance requirement and the heterogeneous network multiple domain in multimedia service multiattribute territory and has striden a layer information, on the basis that the resource granularity is decomposed, utilizes fuzzy logic system that the resource information grain is described and carries out reasoning; Realized that knowledge converges; Reached the purpose of the abstract of complex information, finally formed effective admission control strategy, the elevator system overall performance.

It below is explanation to accompanying drawing

As shown in Figure 2, be the acceptance control system structural representation of embodiment under the heterogeneous wireless scene of the present invention.Present embodiment comprises: information gathering module 1, information inference module 2, admittance control decision module 3.All three modules are included in the operation controlling entity, and this entity can be the third party's decision entity that is independent of concrete Radio Access Network, also can be by the decision entity in certain Radio Access Network.

Wherein information gathering module 1 comprises availability, quality of the conversation, service delay and four Attribute domain information gathering of fail safe submodule; Be used to collect to stride from each network resource information of layer multiple domain is collected the resource information that obtains and will be carried out the vector quantization of resource information by the another one submodule-perception information preliminary treatment submodule that is included in the information gathering module 1.The information inference module is after receiving each Attribute domain information vector; According to predefined fuzzy member function; Estimating space resources grain fuzzy membership information inference module 2 about the target resource grain in the particular community territory is used for according to the dope vector from the information gathering module; And, obtain the performance evaluation result of alternative network simultaneously at each Attribute domain through fuzzy reasoning.Admit control decision module 3, each the Attribute domain performance evaluation that obtains according to the information inference module is the result of decision as a result, the merging of making a strategic decision, and admit control operation according to consolidation strategy, perhaps carry out corresponding feedback.

As shown in Figure 3, be the system configuration sketch map of the embodiment of the invention.This system comprises:

The information gathering module is used for when the access request of receiving from user terminal, and the multiple domain information of collecting each network is obtained the target QoE vector of user terminal simultaneously; And be used for the information of said each Attribute domain of multiple domain information being carried out granularity division respectively, form the information granularity vector of each Attribute domain according to predefined evaluation index;

The information inference module is used for target QoE vector and predefined fuzzy member function according to said user terminal, sets up the fuzzy membership vector of resource grains in each Attribute domain; And be used for fuzzy membership vector and inference rule based on each Attribute domain resource grains; Set up the fuzzy membership vector of resource grains in each Attribute domain and the mapping relations between the network synthesis performance evaluation index, thereby the alternative network set that obtains that each network is formed is divided into the degree of membership vector of different clusters according to said network synthesis performance evaluation index;

Admit the control decision module, be used for choosing the highest network of network classes of service as access network according to said degree of membership vector.

Fig. 4 has illustrated to carry out the model of resource granularity division and fuzzy granularity reasoning, has forgiven the process that information decomposition, information inference, decision-making are converged.

Can find out by Fig. 5; Under many network multi-services scene that this programme sets; Select (RN-AC) and do not support the admission control algorithm (SD-AC) of granularity division to compare with random network, the fuzzy admittance controlling schemes (MD-FAC) in embodiment of the invention scheme-multiattribute territory can effectively reduce the rejection probability of user admission request.This be because support granularity division all sidedly taking into account system stride the effective information of layer multiple domain; Can discover the variation of overall performance of network sensitively; And the introducing of fuzzy reasoning; Help similitude between the evaluating network resource and target resource better and user fuzzy behaviour, thereby guarantee that the user finds " suitable network " to insert for the QoE perception.Relative, all there is certain limitation in other two kinds of comparison algorithms: stochastic selection algorithm can not the sensing network changes of properties, has certain blindness; And the SD-AC algorithm is pursued single attribute territory optimization, and is therefore poor to the tolerance of network performance variation on the whole, and therefore the QoE index of single granularity causes the rapid rising of reject rate easily for the variation and the sensitivity of network performance.

Can find out by Fig. 6; Under many network multi-services scene that this programme sets; Select (RN-AC) and do not support the admission control algorithm (SD-AC) of granularity division to compare with random network; Embodiment of the invention scheme (MD-FAC) is the utilance of elevator system better, under the prerequisite that guarantees the QoE performance, admits more user's request because the present invention utilize fuzzy logic all sidedly evaluation system stride the effective information of layer multiple domain; Thereby, make full use of utilizable resource for the user finds " suitable network ".Relative, random network selects then to exist very big assumption property, and the number of users that therefore can carry is minimum; The SD-AC algorithm is exceedingly pursued " optimal network " in the single attribute territory, causes the decline of system resource overall utilization rate on the contrary, as shown in Figure 5, is accompanied by the rapid rising of the rate of breaking off relations, and the receptive number of users of institute of system is also less relatively.

The above only is an execution mode of the present invention; Should be pointed out that for those skilled in the art, under the prerequisite that does not break away from know-why of the present invention; Can also make some improvement and modification, these improve and modification also should be regarded as protection scope of the present invention.

Claims (4)

1. the acceptance controlling method under the heterogeneous wireless network environment is characterized in that, may further comprise the steps:

S1, when the access request of receiving from user terminal, the multiple domain information of collecting each network, the targeted customer who obtains user terminal simultaneously experiences vector;

S2 divides according to the information that predefined evaluation index is carried out the multiattribute territory to said multiple domain information, forms the resource information vector of each Attribute domain;

S3 experiences vector and predefined fuzzy member function according to the targeted customer of said user terminal, sets up the fuzzy membership vector of resource grains in each Attribute domain;

S4; Fuzzy membership vector and fuzzy inference rule based on resource grains in each Attribute domain; Set up the fuzzy membership vector of resource grains in each Attribute domain and the mapping relations between the network synthesis performance evaluation index, thereby obtain the comprehensive performance evaluation of each alternative network;

S5 selects the highest network of comprehensive performance evaluation as best access network, carries out acceptance judging.

2. the acceptance controlling method under the heterogeneous wireless network environment as claimed in claim 1 is characterized in that, said targeted customer experiences the component that vector comprises availability, quality of the conversation, service delay and four aspects of fail safe.

3. the acceptance controlling method under according to claim 1 or claim 2 the heterogeneous wireless network environment; It is characterized in that; When the information of in step S2, carrying out is divided, said multiple domain information is divided into the information of availability, quality of the conversation, service delay and four Attribute domains of fail safe.

4. the acceptance control system under the heterogeneous wireless network environment is characterized in that, comprising:

The information gathering module is used for when the access request of receiving from user terminal, the multiple domain information of collecting each network, and the targeted customer who obtains user terminal simultaneously experiences vector; And be used for dividing, form the resource information vector of each Attribute domain according to the information that predefined evaluation index is carried out four Attribute domains to said multiple domain information;

The information inference module is used for experiencing vector and predefined fuzzy member function according to the targeted customer of said user terminal, sets up the fuzzy membership vector of resource grains in each Attribute domain; And based on the fuzzy membership vector and the inference rule of resource grains in each Attribute domain, set up the fuzzy membership of resource grains in each Attribute domain and the mapping relations between the network synthesis performance evaluation index, thereby obtain the comprehensive performance evaluation of each alternative network;

Admit the control decision module, select the highest network of comprehensive performance evaluation, carry out acceptance judging as best access network.

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