CN103139860B - Based on the joint handoff method of speed adaptive in a kind of isomery cognitive radio networks - Google Patents

Abstract

A kind of joint handoff method based on speed adaptive in isomery cognitive radio networks is protected in request of the present invention, relates to wireless communication field.For the switching problem moving generation due to secondary user's position, the present invention proposes the joint handoff method of frequency spectrum broker assisted Selection network and the switching of secondary user's terminal control.At network side, frequency spectrum broker obtains attribute weights based on analytic hierarchy process (AHP), carries out network selection; In end side, propose the method for handover control of speed adaptive, control from former network to the switching of objective network.And different switch decision gate method is proposed to different switching type.Method of the present invention according to the business demand of secondary user's and network condition, can select more suitably network, controls better to switch, and decreases number of times and the outage probability of secondary user's switching, improves the performance of handoffs of secondary user's.

Description

Based on the joint handoff method of speed adaptive in a kind of isomery cognitive radio networks

Technical field

The present invention relates generally to wireless communication field, especially about the frequency spectrum switching problem in isomery cognitive radio networks.

Background technology

Along with the develop rapidly of wireless communication technology and the continuous increase of people's demand, traditional single network can not adapt to requirement, and the technology of multiple heterogeneous wireless network convergence becomes study hotspot.Along with the fast development of cognitive radio networks research, it is also further obvious to the demand of heterogeneous wireless network.If secondary user's moves to another place from a place, may switch by the frequency spectrum carried out because of the change of available frequency band between heterogeneous network.

In heterogeneous wireless network, internetwork Vertical Handover judgement is key technology.Existing Vertical Handover decision method mainly contains: the first kind adopts the horizontal handoff method in similar cellular communication system, the signal strength signal intensity from heterogeneous networks access point that terminal use's measurement receives, when received signal strength is greater than certain predetermined threshold value, the network selecting signal strength signal intensity maximum is as the preferred network of access, but these class methods are owing to simply using the method for horizontal handoff, the decision criteria used is single, often can not meet the demand of user's various aspects of performance; Equations of The Second Kind adopts Dynamic Programming and artificial intelligence theory to make comparisons the judgement of accurate Vertical Handover, such as pattern recognition, neural net, fuzzy reasoning, and in conjunction with network characteristic and user's request, the complexity of this type of algorithm is high, and will consume the long period and learn in advance, be not suitable for computing capability and the limited mobile device of electricity; 3rd class, from network agent, is studied process and the property indices of Vertical Handover, and is carried out perception based on to contextual information, analyze the impact of switch decision with this; 4th class adopts cost function method, general consideration affects the combination of one of condition of vertical handoff method performance or several condition, these conditions mainly comprise the system available bandwidth, connection time delay etc. of network side, and the received signal strength of user side, user terminal electric quantity consumption, user velocity and service fee etc., by the judgement of optimization object function determination Vertical Handover and the selection of optimum network.Cost function method, owing to having considered the multiple attribute of access network and user terminal, can realize the validity of Vertical Handover better compared with other several class methods and ensure the combination property of network.

In cognitive radio networks, primary user is not any time in its legal frequency range had of use, and there will be some idle frequency spectrum situations, these idle frequency spectrums general can put together (being called spectrum pool), managed by a frequency spectrum broker entity, frequency spectrum broker entity also include spectrum allocation may algorithm and management policy (Xie Xianzhong. " cognitive radio power technology and application thereof ". Beijing: Electronic Industry Press 2008.4).

To the multiple heterogeneous wireless networks based on cognitive radio, secondary user's communicates owing to can take to opportunistic the frequency range of primary user's free time, generally often select from the spectrum pool of frequency spectrum broker entity management when selecting idle frequency range, so the optional frequency range in spectrum pool is more, the communication opportunity of secondary user's is larger.But the communication condition that single network brings secondary user's is limited, and authorize the opportunity available in frequency range less, so adopt multiple heterogeneous wireless network will bring more available frequency band for secondary user's in cognitive radio networks, and higher-quality network.On the other hand, secondary user's terminal has reconfigurability, while not revising hardware configuration, when not interrupt communication, can adjust radio parameter in real time, as frequency, symbol rate, through-put power, modulation and type of coding etc.Due to such characteristic, in heterogeneous wireless network, communicate also to secondary user's bring convenience; Secondary user's can need according to the performance and application of oneself, selects suitable network and frequency, then the various parameter of correct configuration.

In the method that network is selected, often adopt analytic hierarchy process (AHP) (AHP) to obtain the weights of attribute, then carry out the calculating of web results.At document ShengmeiLiu, SuPan. " AnImprovedTOPSISVerticalHandoffAlgorithmforHeterogeneous WirelessNetworks ", IEEEInternationalConferenceonCommunicationTechnology, in 2010:750-754, analytic hierarchy process (AHP) (AHP) is improved, switch effect and had lifting, throughput also improves a lot.But it combines the comentropy of attribute, do not consider the change of attribute objective status, its switching times is higher, court verdict inaccuracy.

At terminal switch control section, conventional decision parameter is generally the resident chronon of sluggish level Summing Factor, can be used for reducing the ping-pong of terminal, improves the performance switched.At document MinLiu, ZhongchengLi. " PerformanceAnalysisandOptimizationofHandoffAlgorithmsinH eterogeneousWirelessNetworks ", IEEETransactionsonMobileComputing, 2008, two kinds of conventional method for handover control combinations above in 7 (7): 846-857, propose a kind of method for handover control, reduce the outage probability of terminal during switching.But the coefficient in its controlled condition gets fixed value simply, does not change in conjunction with the change of actual conditions, be not inconsistent and actual network environment.

Summary of the invention

The present invention is directed to the above-mentioned defect that the vertical handoff method in prior art in cognitive radio networks between heterogeneous wireless network exists, for the characteristic of cognitive radio networks, the present invention proposes a kind of joint handoff method of frequency spectrum broker entity assisted Selection and the switching of secondary user's terminal control.At network side, frequency spectrum broker entity obtains the method for attribute weights based on improved H (AHP), carries out network selection; In end side, propose the method for handover control of speed adaptive, control from former network to the switching of objective network.

The technical scheme that the present invention solves the problems of the technologies described above is: propose a joint handoff method, when the position of secondary user's changes, just the information of secondary user's oneself and frequency spectrum handover request are sent to frequency spectrum broker entity, information comprises: as the received signal strength of each network, the type of service used, user preference and speed etc.; Frequency spectrum broker receives the received signal strength that first information number analyze each network, ignore the network that signal strength signal intensity is ineligible, for the qualified network of signal strength signal intensity, utilize the network attribute values such as the available bandwidth of network side, Channel holding time, network charges, the attribute weights of computing terminal, use network selecting method to calculate the relative proximity of eligible network, select a best switching object network, and selection result is returned to secondary user's; Secondary user's controls the switching between former network and objective network according to self translational speed and received signal strength.

In the selection course of network side, network selecting method is specially: analyze secondary user's to the selection of network in moving process, and use multiple attributive decision making method, needs first to obtain attribute weights for this reason.The present invention proposes to be combined with comentropy and attribute change trend by analytic hierarchy process (AHP) (AHP) to determine that the objective weight-values combined with attribute change trend by comentropy revises the subjective weights obtained by analytic hierarchy process (AHP) (AHP).Like this, the subjectivity both having overcome analytic hierarchy process (AHP) is random large, calculate coarse and that precision is low shortcoming, considers again the objective difference between network, makes network selection result more accurate.

In the switching controls of end side, the present invention proposes jointly controlling in conjunction with the sluggish resident chronon of level Summing Factor, and make switching controls condition with velocity variations adaptively changing, improve control switch time performance.The present invention adopts logarithm to adjust control method or index replacement control method dynamically-adjusting parameter, and rule changes according to the change of moving velocity of terminal to make parameter, and contrast properties result display outage probability obviously reduces.

Number adjusting method is adopted to the relative value of Changing Pattern adjustment α and β affecting received signal strength with velocity variations, its citation form is logarithmic function.In secondary user's moving process, the change of Negotiation speed regulates the value of α, to reach the object adjusting sluggish level method ratio, and the relative value size of the controlled condition of resident timing method and received signal strength has nothing to do, and does not adjust resident timing controlled factor-beta.

Index replacement method adopts rule affect velocity ratio with velocity variations to go the relative value of adjustment α and β, and its citation form is exponential function.In secondary user's moving process, work as v<v _hOtime, the slope of exponential function is comparatively large, the value of adjustment α and β that can be obvious, thus it is best that the performance of sluggish level method and resident timing method can be made to coordinate; Work as v>v _hOtime, the slope of exponential function is less, and the value of α and β can be made more and more close, and the combination of sluggish level method and resident timing method can be made to tend to be steady.

The present invention also considers that Vertical Handover has asymmetry, according to upwards switching (switching from wlan network to UMTS network) and switching (switching to wlan network from UMTS network) downwards, adopt dissimilar switch decision thresholding, when for switching downwards, handoff procedure is easy, for selection type switches, now wlan network is optional network specific digit, and secondary user's is not to switch, and its target improves QoS, now increase decision threshold, switch again when performance reaches requirement.When for upwards switching, handoff procedure is complicated, and secondary user's is about to leave wlan network and covers, can data loss be produced, can have a great impact performance loss, for pressure type switches, now reduce decision threshold, make it switch in time more fast, to reduce Transmission.

Technical scheme of the present invention is, based on the joint handoff method of speed adaptive in a kind of isomery cognitive radio networks, at network side, frequency spectrum broker entity according to the cost type attribute of network and profit evaluation model property calculation network attribute weights, carries out network selection according to network attribute weights based on analytic hierarchy process (AHP); In end side, switch to objective network from former network according to velocity variations self adaptation.Frequency spectrum broker entity computing network attribute weights specifically comprise: according to the accessible collection of network of isomery cognitive radio networks, and each network attribute set, set up multiattribute matrix, standardization is carried out to multiattribute matrix, obtains the information entropy e of a network jth attribute according to standardized nature matrix _j, call formula according to information entropy: obtain the entropy weight of network attribute j, according to the subjective weight of the normalization of a network jth attribute be ε j (j=1,2 ..., n) and call formula:

${\mathrm{\&omega;}}_{\mathrm{ij}}=\frac{{\mathrm{\&epsiv;}}_j\&CenterDot;{\mathrm{\&eta;}}_j\&CenterDot;e^{b_{\mathrm{ij}}-b_{\mathrm{ij}}^n}}{\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{\mathrm{\&epsiv;}}_k\&CenterDot;{\mathrm{\&eta;}}_k\&CenterDot;e^{b_{\mathrm{ik}}-b_{\mathrm{ik}}^n}},(i=\mathrm{1,2},\&CenterDot;,m)(j=\mathrm{1,2},\&CenterDot;,n)$ Obtain the actual weights of network i network attribute j, wherein, for the b of a front n attribute _ijmean value, according to formula: μ _ij=ω _ijb _ijto the standardized value b of attribute _ijbe weighted to obtain and add attributes, according to the distance of each network of weighting property calculation and ideal network and the poorest network, calculate the relative proximity of each network and ideal network, choose the maximum network of relative proximity value and switch object network for best.In end side, terminal adopts the joint handoff based on the resident chronon of sluggish level Summing Factor to control, and determines to switch, when meeting formula according to resident chronon and the sluggish level factor: $\mathrm{\&alpha;}\frac{D_{\mathrm{\&Phi;}(N-1)}\left(N\right)}{h_y}+\mathrm{\&beta;}\frac{T_{\mathrm{\&Phi;}(N-1)}\left(N\right)}{t_{\mathrm{dw}}}<-\mathrm{\&delta;},$ Terminal sends switching controls, wherein, and T _{Φ (N-1)}(N) time of staying of secondary user's in network Ф (N-1) is represented, D _{Ф (N1)}(N) signal strength signal intensity of network Ф (N-1) and the difference of handoff threshold is represented, t _dwrepresent resident chronon, h _yrepresent the sluggish level factor, α represents sluggish level method controlling elements, and β represents resident timing method controlling elements, and δ is decision threshold.

Handover scheme of the present invention is according to the business demand of secondary user's and network condition, select best object network, control better to switch, decrease number of times and the outage probability of secondary user's switching, improve the performance of handoffs of secondary user's, to the multiple heterogeneous wireless network convergence based on cognitive radio, there is important value.

Accompanying drawing explanation

The handoff process figure of Fig. 1 heterogeneous network;

The access model figure of Fig. 2 heterogeneous network;

The analysis of shift figure of Fig. 3 heterogeneous wireless network;

The average cumulative switching times comparison diagram of Fig. 4 secondary user's;

The outage probability comparison diagram of the secondary user's of the different method for handover control of Fig. 5;

The average transmission data volume variation diagram of Fig. 6 secondary user's.

Embodiment

Below in conjunction with accompanying drawing and instantiation, enforcement of the present invention is described specifically.

The handoff process figure of Fig. 1 heterogeneous network.The present invention is directed to the characteristic of cognitive radio networks, propose the joint handoff method of frequency spectrum broker assisted Selection and the switching of secondary user's terminal control.At network side, frequency spectrum broker, based on analytic hierarchy process AHP, according to available bandwidth, Channel holding time, user preference, network charges computing network attribute weights, carries out network selection according to attribute weights; In end side, implement switching controls from former network to objective network according to velocity variations self adaptation, carry out switching controls from former network to objective network.

The model of heterogeneous network of the present invention as shown in Figure 2, covers the wide area network UMTS of low bandwidth and the WLAN of low covering high bandwidth by the height with typical representative and forms heterogeneous wireless network.Specific embodiment of the invention scheme is as follows.

When the position of secondary user's changes, frequency spectrum handover request is sent to frequency spectrum broker entity by secondary user's, and request comprises the information as the received signal strength of each network, the type of service used, user preference and speed etc.

Frequency spectrum broker entity, according to the secondary user's frequency spectrum handover request received, is analyzed the received signal strength of each network, is ignored the network that signal strength signal intensity is ineligible, the qualified network of primary election signal strength signal intensity.

The attribute weights of network side computing terminal

For the qualified network of signal strength signal intensity, the network attribute value of network side computing terminal and corresponding attribute weights.The present embodiment selects available bandwidth, Channel holding time, and user preference and network charges 4 network attributes are that example further illustrates:

Be provided with m qualified heterogeneous wireless network: X={x ₁, x ₂, x ₃, x _m: m accessible collection of network }, as UMTS network, wlan network etc.If each network adopts n judgement attribute: S={s ₁, s ₂, s ₃, s _n: n network attribute set }, as network network expense, user preference, available bandwidth, Channel holding time etc.Use a _ijrepresent network i(i=1,2, jth m) (j=1,2, n) individual property value, can obtain multiattribute matrix A:

$A={\left(a_{\mathrm{ij}}\right)}_{m\&times;n}=\left[\begin{array}{cccc}{a}_{11}& a_{12}& \&CenterDot;& a_{1n}\\ a_{21}& a_{22}& \&CenterDot;& a_{2n}\\ \&CenterDot;& \&CenterDot;& & \&CenterDot;\\ a_{m1}& a_{m2}& \&CenterDot;& a_{\mathrm{mn}}\end{array}\right]---\left(1\right)$

Network attribute is divided into cost type attribute and profit evaluation model attribute by character, network charges, user preference etc. is classified as cost type attribute, available bandwidth, Channel holding time etc. are profit evaluation model attribute.

Character according to network attribute carries out standardization to multiattribute matrix A.If network attribute is the cost such as network charges, user preference type attribute, standardization adopts the smaller the better type, according to formula:

$b_{\mathrm{ij}}=\frac{\min \left\{a_{\mathrm{ij}}\right|1\&le;i\&le;m\}}{a_{\mathrm{ij}}},(i=\mathrm{1,2},\&CenterDot;,m)$ Standardization is carried out to matrix property value.

Be the profit evaluation model such as available bandwidth, Channel holding time attribute for network attribute, standardization adopts the type that is the bigger the better, according to formula:

$b_{\mathrm{ij}}=\frac{a_{\mathrm{ij}}}{\max \left\{a_{\mathrm{ij}}\right|1\&le;i\&le;m\}},(i=\mathrm{1,2},\&CenterDot;,m)$ Standardization is carried out to matrix property value.

After above-mentioned process, obtain standardized nature matrix B:

$B={\left(b_{\mathrm{ij}}\right)}_{m\&times;n}=\left[\begin{array}{cccc}{b}_{11}& b_{12}& \&CenterDot;& b_{1n}\\ b_{21}& b_{22}& \&CenterDot;& b_{2n}\\ \&CenterDot;& \&CenterDot;& & \&CenterDot;\\ b_{m1}& b_{m2}& \&CenterDot;& b_{\mathrm{mn}}\end{array}\right]---\left(2\right)$

Call formula:

$e_j=-\frac{\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}\left(\frac{b_{\mathrm{ij}}}{\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{b}_{\mathrm{ij}}}\right)\&CenterDot;\mathrm{In}\left(\frac{b_{\mathrm{ij}}}{\underset{i=1}{\overset{m}{\mathrm{\&Sigma;}}}{b}_{\mathrm{ij}}}\right)}{\mathrm{Inm}},(j=\mathrm{1,2},\&CenterDot;,n)---\left(3\right)$ The information entropy e of a computing network jth attribute _j.In formula (3), then make xInx=0 as x=0.Obtain the entropy weight of a jth attribute thus:

${\mathrm{\&eta;}}_j=\frac{1-e_j}{\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}(1-e_k)},(j=1,2,\&CenterDot;,n)---\left(4\right)$

In addition, if the subjective weight of the normalization of each network jth attribute is ε _j(j=1,2 ..., n), can require and operator strategy setting according to service quality (QoS), it reflects the relative importance of this attribute.

The present invention is according to the dynamic change situation of each network attribute.When certain network attribute value increases, just increase the weights that this attribute is corresponding, increase the impact of this attribute; Otherwise, when certain property value reduces, just reduce the weights that this attribute is corresponding, reduce the impact of this attribute.Therefore, convolution (3) and formula (4), according to formula:

${\mathrm{\&omega;}}_{\mathrm{ij}}=\frac{{\mathrm{\&epsiv;}}_j\&CenterDot;{\mathrm{\&eta;}}_j\&CenterDot;e^{b_{\mathrm{ij}}-b_{\mathrm{ij}}^n}}{\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{\mathrm{\&epsiv;}}_k\&CenterDot;{\mathrm{\&eta;}}_k\&CenterDot;e^{b_{\mathrm{ik}}-b_{\mathrm{ik}}^n}},(i=\mathrm{1,2},\&CenterDot;,m)(j=\mathrm{1,2},\&CenterDot;,n)---\left(5\right)$

Obtain the actual weights of network i attribute j.Wherein, for the b of a front n attribute _ijmean value.

Network side determines best switching object network

After obtaining network attribute weights, ordinal number preference method (TOPSIS) is used to determine best switching object network according to the actual weights of network and attribute.The principle of ordinal number preference method be the gap between selected network and ideal solution minimum and with the disparity of the poorest solution.The Perfected process determined is made up of all possible optimum attributes value, and the poorest solution party's rule is made up of the poorest all possible property value.

First, weights ω is used _ijaccording to formula: μ _ij=ω _ijb _ijto standardized attribute b _ijbe weighted to obtain add attributes.Ideal network A is determined respectively according to following formula according to weighted results ⁺the poorest network A ^-:

A ⁺={(maxμ _ij|j∈J),(minμ _ij|j∈K)}(i=1,2,·,m)（6）

A ^-={(minμ _ij|j∈J),(maxμ _ij|j∈K)}(i＝1,2,·,m)（7）

Wherein, J is the set of profit evaluation model attribute, and K is the set of cost type attribute.

Attributesly the distance that formula (8) and (9) calculate each network and ideal network and the poorest network is called according to adding:

$s_i^{+}=\sqrt{\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{({\mathrm{\&mu;}}_{\mathrm{ij}}-{\mathrm{\&mu;}}_j^{+})}^2}---\left(8\right)$

$s_i^{-}=\sqrt{\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{({\mathrm{\&mu;}}_{\mathrm{ij}}-{\mathrm{\&mu;}}_j^{-})}^2}---\left(9\right)$

In formula, represent the set of ideal network attribute, represent the set of the poorest network attribute.

According to formula: calculate the relative proximity of each network and ideal network.Choose relative proximity being worth maximum network is best switching object network.Namely select the network that maximum is corresponding:

$A_{\mathrm{TOP}}^{*}=\arg \max c_i^{*},(i=\mathrm{1,2},\&CenterDot;,m)---\left(10\right)$

The adaptive switching controls of terminal velocity

After obtain best object network from network side, secondary user's is considered to switch under what conditions with regard to needs.Because the general overlay area of UMTS is wide, WLAN often with isolated island formal distribution in UMTS overlay area, therefore, what need emphasis to solve is the switching of secondary user's discrepancy WLAN both sides.

As shown in Figure 3, end side secondary user's is according to network received signal intensity determination handoff threshold, and when the AP distance of secondary user's distance wlan network i is di, the received signal strength of wlan network is:

RSS _i=RSS(d _i)=K ₁-K ₂lg(d _i)+Ω(d _i)（11）

In formula, K ₁represent transmission and receiving antenna gain, K ₂represent environment multiplicative characteristic, Ω (d) represents zero mean Gaussian white noise.

If RSS ₀=K ₁-K ₂lg (r)+Ω (r) is handoff threshold value, and r is handoff threshold distance.Definition D _i=RSS _i-RSS ₀, as d=r, D=0 _i.Make Ф (N) be N number of sampled point (moment) network select, then

So, as not X and Y in the same time, if Ф (X) ≠ Ф (Y) (X<Y), mean and select Ф (X) and Y moment network to select Ф (Y) difference at X moment network, illustrate at least to there occurs and once switch.Distinguishingly, Ф (X) Ф (Y) >0 represents and there occurs horizontal handoff; Ф (X) Ф (Y) <0 represents and there occurs Vertical Handover.

Distinguishingly, when secondary user's enters wlan network from UMTS network, as long as the received signal strength that there is wlan network i meets RSS _i(N) >RSS ₀+ h _y, be just switched to wlan network from UMTS network, when secondary user's is left from wlan network i, need RSS _i(N) <RSS ₀-h _yjust can switch.Parameter h _yrepresent the sluggish level factor.

Terminal switch can adopt the joint handoff based on the resident chronon of sluggish level Summing Factor to control.

If T _i(N) represent the time of staying of secondary user's in wlan network i, work as T _i(N), during >0, RSS is represented _i>RSS ₀duration; Work as T _i(N), during <0, RSS is represented _i<RSS ₀duration.

Joint handoff control program then based on the resident chronon of sluggish level Summing Factor is:

As Ф (N-1) ≠ Ф (N), according to resident chronon and the sluggish level factor, switch when meeting formula (13) terminal.

$\mathrm{\&alpha;}\frac{D_{\mathrm{\&Phi;}(N-1)}\left(N\right)}{h_y}+\mathrm{\&beta;}\frac{T_{\mathrm{\&Phi;}(N-1)}\left(N\right)}{t_{\mathrm{dw}}}<-\mathrm{\&delta;}---\left(13\right)$

In formula, D _{Ф (N1)}(N) be the signal strength signal intensity of N number of sampled point (moment) network Ф (N-1) and the difference of handoff threshold value, T _{Φ (N-1)}(N) be time of staying of N number of sampled point (moment) network Ф (N-1), parametric t _dwrepresent resident chronon, parameter alpha represents sluggish level method controlling elements, and parameter beta represents resident timing method controlling elements, and δ is dynamic decision thresholding.

Be illustrated in figure 3 heterogeneous wireless network analysis of shift figure.Normal conditions, get α=β=1, below we provide the parameter alpha of speed adaptive, the dynamic defining method of β, δ.Can adopt number adjusting method or index replacement method determination parameter alpha, β.To number adjusting method determination parameter alpha, β:

Work as d=d ⁺(d ⁺<r), time, can obtain:

RSS(d ⁺)-RSS ₀＝K ₂lg(r)-K ₂lg(d ⁺)＝h _y（14）

Represent secondary user's speed with v, make d=r-vt _dw, desirable

$\mathrm{\&alpha;}=\frac{1g\left(d^{+}\right)}{1g|r-v\&CenterDot;t_{\mathrm{dw}}|},\mathrm{\&beta;}=1---\left(15\right)$

The method of index replacement method determination parameter alpha, β:

Work as d=d ^-(d ^->r), time, can obtain:

RSS ₀-RSS(d ^-)=K ₂log(d ^-)-K ₂log(r)=h _y（18）

If represent the performance separation speed of sluggish level method and resident timing method, adopt v/v _hOratio adjusts the ratio of two kinds of methods.Due at v<v _hOtime, sluggish level method is than the poor performance of resident timing method, and need to push the speed the adjustment changed sluggish level method and resident timing method ratio; And at v>v _hOtime, substantially based on the performance of sluggish level method.

In order to make the adjustment of velocity variations to sluggish level method and resident timing method become steady, to sum up analyze, desirable

$\mathrm{\&alpha;}=1+e^{-\frac{2v\&CenterDot;t_{\mathrm{dw}}}{d^{-}-d^{+}}},$ $\mathrm{\&beta;}=1-e^{-\frac{2v\&CenterDot;t_{\mathrm{dw}}}{d^{-}-d^{+}}}---\left(19\right)$

Finally, the present invention adopts dynamic decision thresholding δ to adjust controlled condition:

$\mathrm{\&delta;}=\left\{\begin{array}{cc}1+\mathrm{\&theta;}& \mathrm{UMTS}\&RightArrow;\mathrm{WLAN}\\ 1-\mathrm{\&theta;}& \mathrm{WLAN}\&RightArrow;\mathrm{UMTS}\\ 1& \mathrm{ELSE}\end{array}\right.---\left(20\right)$

According to quality of service requirement, in the present invention, consider the requirement of transmitted data amount and outage probability, generally get 0< θ <0.5.

The present invention uses MATLAB software to carry out emulation experiment.UMTS network and wlan network arrange respectively according to 3GPP and IEEE802.11 standard, and other simulation parameter is as follows: R=150m, d ⁺=120m, d ^-=140m, r=129.6m, sample frequency interval T=0.05s, resident chronon t _dw=5s, the initial velocity v=30m/s of perception user.The total bandwidth of setting UMTS network is 2Mbps, and the total bandwidth of wlan network is 11Mbps.Simulation result is as accompanying drawing Fig. 4, Fig. 5 and Fig. 6, wherein: AHP+TOPSIS is algorithm in document [3], SAE+TOPSIS is algorithm in document [2], MODM be document (Shi Wenxiao etc. the heterogeneous wireless network access selection algorithm based on multiobjective decision-making) in algorithm, and the inventive method is improved one's methods with AHP+TOPSIS and is represented.Fig. 4, Fig. 5 and Fig. 6 show switching times and the outage probability that the present invention reduces secondary user's effectively, improve transmitted data amount.

Claims (7)

1. in an isomery cognitive radio networks based on the joint handoff method of speed adaptive, it is characterized in that, at network side, frequency spectrum broker entity according to the cost type attribute of network and profit evaluation model property calculation network attribute weights, carries out network selection according to network attribute weights based on analytic hierarchy process (AHP); In end side, determine to switch according to resident chronon and the sluggish level factor based on terminal velocity change, complete and switch to objective network from former network, wherein, at network side, frequency spectrum broker entity is according to the accessible collection of network of isomery cognitive radio networks, and each network attribute set, set up multiattribute matrix, standardization is carried out to multiattribute matrix, obtain the information entropy e of network attribute according to standardized nature matrix ^j, call formula according to information entropy: j=1,2 ..., n obtains the entropy weight of a jth network attribute; Be ε according to the normalized weight of network _j, j=1,2 ..., n, calls formula:

i=1,2 ..., m, j=1,2 ..., n obtains the actual weights of a network i jth attribute; According to formula: μ _ij=ω _ijb _ijto the standardized value b of attribute _ijbe weighted to obtain add attributes, according to the distance of each network of weighting property calculation and ideal network and the poorest network, calculate the relative proximity of each network and ideal network, choose the maximum network of relative proximity value and switch object network for best, wherein for a front n b _ijmean value, m is network number, n be each network adopt attribute number; Wherein, in end side, terminal adopts the joint handoff based on the resident chronon of sluggish level Summing Factor to control, and determines to switch, when meeting formula according to resident chronon and the sluggish level factor:

terminal sends switching controls, completes and switches to objective network from former network, wherein, and D _{Φ (N-1)}(N) be N number of signal strength signal intensity of moment network i and the difference of handoff threshold, T _{Φ (N-1)}(N) the N number of time of staying of moment secondary user's in network i is represented, t _dwrepresent resident chronon, h _yrepresent the sluggish level factor, α represents sluggish Automatic level control scale factor, and β represents resident timing controlled scale factor, and δ is decision threshold.

2. joint handoff method according to claim 1, is characterized in that, described ideal network and the poorest network are specially: call formula:

A ⁺＝{(maxμ _ij|j∈J),(minμ _ij|j∈K)}，i＝1,2,…,m

A ^-＝{(minμ _ij|j∈J),(maxμ _ij|j∈K)}，i＝1,2,…,m

Determine ideal network A respectively ⁺the poorest network A ^-, wherein, J is the set of profit evaluation model attribute, and K is the set of cost type attribute.

3. joint handoff method according to claim 1, is characterized in that, call formula:

$s_i^{+}=\sqrt{\underset{j=1}{\overset{n}{\&Sigma;}}{({\mathrm{\&mu;}}_{ij}-{\mathrm{\&mu;}}_j^{+})}^2},s_i^{-}=\sqrt{\underset{j=1}{\overset{n}{\&Sigma;}}{({\mathrm{\&mu;}}_{ij}-{\mathrm{\&mu;}}_j^{-})}^2}$ The distance of computing network i and ideal network and the poorest network with in formula, represent the set of ideal network attribute, represent the set of the poorest network attribute, according to formula: the relative proximity of computing network and ideal network.

4. joint handoff method according to claim 1, is characterized in that, described standardization is specially: when network attribute is cost type attribute, according to formula:

i=1,2 ..., m is to element a in multiattribute matrix _ijcarry out standardization; Be profit evaluation model attribute for network attribute, according to formula:

i=1,2 ..., m is to element a in multiattribute matrix _ijcarry out standardization, obtain standardized nature matrix.

5. joint handoff method according to claim 1, is characterized in that, to adopt number adjusting method according to formula: sluggish Automatic level control scale factor and resident timing controlled scale factor are determined in β=1, and wherein, v represents secondary user's translational speed, and r represents secondary user's handoff threshold distance, d ⁺represent the distance being greater than secondary user's handoff threshold distance.

6. joint handoff method according to claim 1, is characterized in that, adopts index replacement method according to formula: determine sluggish Automatic level control scale factor and resident timing controlled scale factor, wherein, v represents secondary user's translational speed, and r represents secondary user's handoff threshold distance, d ⁺represent the distance being greater than secondary user's handoff threshold distance, d ^-represent the distance being less than secondary user's handoff threshold distance.

7. joint handoff method according to claim 1, is characterized in that, call formula according to service quality: $\mathrm{\&delta;}=\left\{\begin{array}{cc}1+\mathrm{\&theta;}& UMTS\&RightArrow;WLAN\\ 1-\mathrm{\&theta;}& WLAN\&RightArrow;UMTS\\ 1& ELSE\end{array}\right.$ Determine the handoff threshold δ between heterogeneous networks, wherein, 0 < θ < 0.5.