CN101656989B - Method and device for switching heterogeneous networks - Google Patents

Abstract

The invention discloses a method and a device for switching heterogeneous networks. The method comprises the following steps: determining first weights of parameters in a QoS parameter set, wherein the first weights are subjective weights required by a user; determining second weights of the parameters in the QoS parameter set according to the current QoS parameter value of networks to be evaluated; carrying out fusion of coincidence degree on the first weights and the second weights, and determining third weights of the parameters in the QoS parameter set; and determining a target network according to the third weights so as to switch the networks. According to the embodiment of the invention, when the heterogeneous networks are switched, the method and the device increase the possibility for finding the target network and improve the success ratio of switching so as to enable the terminal to enjoy better service quality of other networks and further improve the satisfaction of the user.

Description

Heterogeneous network switching method and device

Technical Field

The present invention relates to the field of wireless mobile communications technologies, and in particular, to a method and an apparatus for heterogeneous network handover.

Background

At present, different types of radio access technologies are rapidly evolving, due to their respective characteristics and suitable applications. Therefore, networks composed of different access technologies are referred to as heterogeneous networks. There are differences between heterogeneous networks in terms of bandwidth, mobility support, effective coverage, QoS (Quality of service), charging rate, security, etc.

The heterogeneous network switching means that a terminal crosses the existing network boundary to switch a service from one network to another network, and after the network switching is completed, the switched network is used for managing the current service. In order to better utilize network technology and improve QoS of users, handover between heterogeneous networks is a key technology for future mobile communication development, and is mainly divided into three parts: switching triggering, switching judgment and switching execution. The switching trigger is the terminal triggering to select the network, the switching judgment is the selection of the network to be evaluated so as to determine the target network, and the switching execution is the process of executing the switching.

In the prior art, when performing heterogeneous network handover, an AHP (analytic hierarchy Process) based method needs to be adopted to evaluate QoS parameters of a current service, so as to obtain QoS parameter weights of the current service, that is, relative importance degrees between the QoS parameters, where the weights only represent a subjective requirement of a user for each QoS parameter, and then a handover decision is performed according to the QoS parameter weights representing the subjective requirement of the user, and the handover is performed after a target network is determined.

However, the QoS parameter weight of the current service determined by the heterogeneous network switching method only reflects a subjective requirement of the user on each QoS parameter, and it is likely that the current condition of each network to be evaluated cannot meet the subjective requirement of the terminal, and finally the result of the switching decision is that no switching is performed, so that the probability of switching failure is increased, and the terminal still operates the service in the original network and cannot enjoy better service quality of other networks.

Disclosure of Invention

The embodiment of the invention provides a method and a device for switching a heterogeneous network, which are used for improving the success rate of switching the heterogeneous network.

The embodiment of the invention discloses a method for switching heterogeneous networks, which comprises the following steps: determining a first weight of a parameter in a QoS parameter set, wherein the first weight is a subjective weight required by a user, and determining a second weight of the parameter in the QoS parameter set according to a current QoS parameter value of a network to be evaluated; performing coincidence degree fusion on the first weight and the second weight, and determining a third weight of the parameters in the QoS parameter set; and determining a target network according to the third weight, and performing network switching.

The embodiment of the invention also discloses a device for switching the heterogeneous network, which comprises the following steps: a first weight determining unit, configured to determine a first weight of a parameter in a QoS parameter set, where the first weight is a subjective weight required by a user; the second weight determining unit is used for determining the second weight of the parameters in the QoS parameter set according to the current QoS parameter value of the network to be evaluated; a third weight determining unit, configured to perform overlap-ratio fusion on the first weight and the second weight, and determine a third weight of a parameter in a QoS parameter set; a target network determining unit, configured to determine a target network according to the third weight; and the switching execution unit is used for switching the network.

It can be seen from the foregoing embodiments of the present invention that, in determining the QoS parameter weight of the current service, in addition to considering a subjective requirement of the terminal for each QoS parameter, obtaining the first weight of the QoS parameter according to the subjective requirement of the terminal, the current status of each network to be evaluated is also considered, that is, obtaining the second weight of the QoS parameter according to the current QoS parameter value state of the network. After the first weight and the second weight are comprehensively considered, the final fusion weight, namely the third weight is determined, and the third weight is used for carrying out switching judgment, so that the possibility of finding a target network is increased, the switching success rate is improved, the terminal can enjoy better service quality of other networks, and the satisfaction degree of a user is further improved.

Drawings

Fig. 1 is a flowchart illustrating a method for heterogeneous network handover according to a first embodiment of the present invention;

FIG. 2 is a flowchart illustrating a method for heterogeneous network handover according to a second embodiment of the present invention;

FIG. 3 is a diagram illustrating a heterogeneous network scenario;

FIG. 4 is a flow chart of an AHP process of the present invention;

FIG. 5 is a flow chart of the GRA method of the present invention;

FIG. 6 is a flow diagram of a UMADM method of the present invention;

fig. 7 is a flowchart illustrating a method for heterogeneous network handover according to a third embodiment of the present invention;

fig. 8 is a block diagram of a device for heterogeneous network handover according to a first embodiment of the present invention.

Detailed Description

Embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

Please refer to fig. 1, which is a flowchart illustrating a method for heterogeneous network handover according to a first embodiment of the present invention, including the following steps:

step 101: determining a first weight of a parameter in a QoS parameter set, wherein the first weight is a subjective weight required by a user, and determining a second weight of the parameter in the QoS parameter set according to a current QoS parameter value of a network to be evaluated;

step 102: performing coincidence degree fusion on the first weight and the second weight, and determining a third weight of the parameters in the QoS parameter set;

step 103: and determining a target network according to the third weight, and performing network switching.

It can be seen from the above embodiments of the present invention that, when determining the QoS parameter weight of the current service, in addition to considering a subjective requirement of the terminal on each QoS parameter, obtaining the first weight of the QoS parameter according to a subjective judgment of the terminal, and also considering the current status of each network to be evaluated, obtaining the second weight of the QoS parameter according to the current state of the QoS parameter of the network, after comprehensively considering the first weight and the second weight, determining the final fusion weight, i.e., the third weight, and performing a handover decision by using the third weight, thereby increasing the probability of finding a target network, and improving the success rate of handover, so that the terminal enjoys better service quality of other networks, and further improving the satisfaction degree of users.

Please refer to fig. 2, which is a flowchart illustrating a method for handover between heterogeneous networks according to a second embodiment of the present invention. In this embodiment, it is assumed that there are two networks capable of supporting a certain type of service in a network coverage area, for example, a UMTS (Universal Mobile telecommunications System) and a Wimax (Worldwide Interoperability for Microwave Access) System, and when a terminal runs a session type service at Wimax and periodically detects a service QoS, it finds that the QoS of a current network is not satisfied, and then triggers a network handover, where the handover process includes the following steps:

step 201: the terminal sends a switching request to an NM (Network Manager) of an original Network;

the UMTS and Wimax are connected to an IP backbone network, and the IP backbone network has at least one HMS (Handover Management Service) for performing inter-network Handover decision and Handover decision. The HMS is connected to a RADA (Radio access Database) for recording the current QoS information of UMTS and Wimax.

Both UMTS and Wimax have a NM for collecting current QoS information of the network to update RADA and manage handover events of the network. Operations performed by the NM may be performed by an RNC (Radio Network Controller) in a UMTS Network, or by a BS (Base Station) in a WiMax Network, and a scenario diagram thereof is shown in fig. 3.

In this embodiment, the original network is Wimax, and thus, the terminal transmits a handover request to the BS.

Step 202: NM of original network sends service quality report to HMS;

the QoS parameter set of the session service currently running by the terminal is carried in the QoS report.

Step 203: HMS utilizes AHP method to confirm the first weight of each parameter in QoS parameter set of the conversational service;

the AHP method is an evaluation method widely applied in the field of comprehensive evaluation, and a method combining qualitative analysis and quantitative calculation is used to analyze, compare and calculate a plurality of elements in an evaluation target one by one, so as to finally obtain a comprehensive weight value of each element in the evaluation target, and a specific implementation manner of the AHP method is shown in fig. 4, and includes the following steps:

step 401: establishing a system hierarchical structure;

through the deep knowledge of research objects, an evaluation index system is provided, and the index system is layered to form a hierarchical structure. The system has three hierarchical structures: a target layer, a criteria layer, and a scheme layer. The target network is set as a target layer, and in this embodiment, the target network is an optimal QoS network that conforms to the conversational services. The QoS parameter set of the original network is set as a criterion layer, and in this embodiment, the QoS parameter set of the original network is the QoS parameter set of the Wimax session class.

Step 402: constructing a judgment matrix B;

wherein each parameter is scaled by a "scale 1-9" method, the scale method of "scale 1-9" is listed in table 1. According to the scaling method in table 1, the degree of importance between any two parameters is scaled, and these scale values representing the degree of importance are used as elements to establish the judgment matrix B. For example, element B in decision matrix B_ijIndicating the degree of importance of parameter i to parameter j. As shown in table 2, which is the value of each element of a decision matrix.

TABLE 1 method for scaling parameters

Scale	Means of
		1	Indicates that the two factors have the same importance
3	Indicating that the former is slightly more important than the latter
		5	Indicating that the former is significantly more important than the latter in comparison with two factors
7	Indicating that the former is more important than the latter
		9	Indicating that the former is extremely important compared to the latter
2，4，6，8	Intermediate value representing the above-mentioned adjacent judgment
		Reciprocal of the	If the ratio of the importance of element I to element j is aijThe ratio of the importance of element j to element I is then aji＝1/aij

TABLE 2 example decision matrix

	Bandwidth of	Time delay	Dithering	Security	Cost of
						Bandwidth of	1	4	0.5	1	2
Time delay	0.25	1	0.125	0.25	0.5
						Dithering	2	8	1	2	4
Security	1	4	0.5	1	2
						Cost of	0.5	2	0.25	0.5	1

Step 403: checking and judging the consistency of the matrix B;

the consistency check process for the judgment matrix B in the step comprises the following steps:

(1) calculating a consistency index CI of the judgment matrix B;

wherein, <math> <mrow> <mi>CI</mi> <mo>=</mo> <mfrac> <mrow> <msub> <mi>&lambda;</mi> <mi>max</mi> </msub> <mo>-</mo> <mi>n</mi> </mrow> <mrow> <mi>n</mi> <mo>-</mo> <mn>1</mn> </mrow> </mfrac> <mo>.</mo> </mrow> </math> here, λ_maxTo determine the maximum eigenvalue of the matrix B, n is the order of the determination matrix B.

(2) Obtaining an average random consistency index RI of the judgment matrix B;

as shown in table 3, the decision matrix with n equal to 1, …, and 9 is the corresponding relationship between the decision matrix order n and RI. According to the correspondence described in table 3, the average random consistency index RI of the interpretation matrix B can be obtained.

TABLE 3 determination of the correspondence between matrix order n and average random consistency index RI

n	1 2 3 4 5 6 7 8 9
		RI	0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45

(3) Calculating a consistency ratio CR;

$\mathrm{CR}=\frac{\mathrm{CI}}{\mathrm{RI}}$

(4) according to the consistency ratio CR, carrying out consistency check;

and when CR is less than 0.10, the judgment matrix B is considered to have consistency, otherwise, the judgment matrix B is considered not to have consistency, the step 402 is returned, and the judgment matrix is reconstructed.

Step 404: obtaining a first weight vector W of the QoS parameter set according to the judgment matrix with consistency₁；

After the consistency check is passed, calculating the eigenvalue of the judgment matrix, obtaining the eigenvector corresponding to the maximum eigenvalue according to the maximum eigenvalue, and normalizing the eigenvector to obtain a first weight vector W of the QoS parameter₁First weight vector W₁The element in (1) is the first weight of each parameter in the QoS parameter set of the session-like service.

After determining the first weight of the corresponding parameter in the QoS parameter set of the session class, the process returns to the heterogeneous network handover process, and step 204 is executed.

Step 204: the HMS sends a QoS query request of a network to be evaluated to the RADA, and requests to acquire a QoS parameter value of the network to be evaluated;

the network to be evaluated comprises an original network and all candidate networks. In this embodiment, the network to be evaluated is Wimax and UMTS.

The HMS is connected with RADA, which is used for recording the current QoS information of UMTS and Wimax.

In step 204, when RADA does not exist in the network, the HMS may directly obtain QoS parameter values of session classes of UMTS and Wimax from the NM.

Step 205: RADA returns a network QoS query response to be evaluated to HMS;

the QoS query response of the network to be evaluated carries QoS parameter values of the network to be evaluated.

Step 206: according to the QoS parameter value of the network to be evaluated, a second weight vector W of the QoS parameter set is obtained₂；

Wherein the second weight vector W is obtained by using the coefficient of variation method₂The method comprises the following steps:

the first step is as follows: and constructing an original data matrix X according to the QoS parameter value of the network to be evaluated.

$X=\left[\begin{array}{cccc}{x}_{11}& x_{12}& ...& x_{1m}\\ x_{n1}& {\mathrm{<figure-callout\; id="2"\; label="x\; n"\; filenames="H2008102101336E00031.png"\; state="\{\{state\}\}">x</figure-callout>}}_n& ...& x_{\mathrm{nm}}\end{array}\right]$

Wherein m represents the number of parameters in the QoS parameter set, n represents the number of networks to be evaluated, x_nmRepresenting the value of the mth parameter of the nth network. In this embodiment, the network to be evaluated includes all candidate networks and the original network, so n is 2.

The second step is that: calculating the standard deviation S of each QoS parameter_j；

Wherein, the standard deviation of the QoS parameter reflects the absolute variation degree of each QoS parameter, and the calculation formula is as follows:

<math> <mrow> <msub> <mi>S</mi> <mi>j</mi> </msub> <mo>=</mo> <msqrt> <mfrac> <mrow> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>ij</mi> </msub> <mo>-</mo> <mover> <msub> <mi>x</mi> <mi>j</mi> </msub> <mo>&OverBar;</mo> </mover> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> <mi>n</mi> </mfrac> </msqrt> </mrow> </math>

<math> <mrow> <mover> <msub> <mi>x</mi> <mi>j</mi> </msub> <mo>&OverBar;</mo> </mover> <mo>=</mo> <mfrac> <mrow> <msub> <mi>x</mi> <mrow> <mn>1</mn> <mi>j</mi> </mrow> </msub> <mo>+</mo> <msub> <mi>x</mi> <mrow> <mn>2</mn> <mi>j</mi> </mrow> </msub> <mo>+</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>+</mo> <msub> <mi>x</mi> <mi>nj</mi> </msub> </mrow> <mi>n</mi> </mfrac> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mi>m</mi> </mrow> </math>

in the formula, S_jIndicating the standard deviation of the jth QoS parameter.

The third step: calculating the variation coefficient of each QoS parameter;

the variation coefficient of the QoS parameter reflects the relative variation degree of each QoS parameter, and the calculation formula is as follows:

<math> <mrow> <msub> <mi>v</mi> <mi>j</mi> </msub> <mo>=</mo> <mfrac> <msub> <mi>S</mi> <mi>j</mi> </msub> <mover> <msub> <mi>x</mi> <mi>j</mi> </msub> <mo>&OverBar;</mo> </mover> </mfrac> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mi>m</mi> </mrow> </math>

the fourth step: normalizing the variation coefficient of each QoS parameter to obtain a second weight vector W of the QoS parameter set₂。

Wherein the second weight vector W₂The element in (1) is the second weight of each parameter in the QoS parameter set.

After determining the second weight of the corresponding parameter in the QoS parameter set, the process returns to the heterogeneous network handover process, and step 207 is executed.

Step 207: according to a first weight vector W₁And a second weight vector W₂Obtaining a third weight vector W₃；

Wherein, first, a first weight vector W is calculated according to the contact ratio function₁And a second weight vector W₂Degree of correlation between α and β, and then a first weight vector W is obtained using the degree of correlation α and β₁And a second weight vector W₂The fused weight vector of (2), i.e. the third weight vector W₃。

According to the definition of the coincidence function, m parameters exist in the QoS parameter set of the conversational class, and the first weight vector W of the QoS parameter set₁Is (x)₁，x₂，...x_m) A second weight vector W₂Is (y)₁，y₂，...y_m). Wherein x is₁+x₂+...+x_m＝1，y₁+y₂+...+y _m1. Will vector W₁And W₂Maps to two points X, Y in 4-dimensional space, and characterizes the vector W by the Euclidean distance between the two points₁And W₂The degree of correlation of (c).

The Euclidean distance between two points is:

$d=\sqrt{{(y_1-x_1)}^2+{(y_2-x_2)}^2+...+{(y_m-x_m)}^2}$

<math> <mrow> <mi>&alpha;</mi> <mo>=</mo> <mfrac> <mi>d</mi> <msub> <mi>d</mi> <mi>max</mi> </msub> </mfrac> <mo>,</mo> </mrow> </math> $d_{\max }=\sqrt{2}$

β＝1-α

W₃＝αW₁+βW₂

step 208: third weight vector W of HMS according to QoS parameter set₃Network selection is carried out, and a target network is determined;

according to the third weight vector of the QoS parameter set, a GRA (gray scale association analysis) method may be used to determine the network selection condition, or a UMADM (Uncertain Multiple Attribute Decision) method may be used to determine the network selection condition, and the final target network is determined according to the network selection condition.

When the network selection condition is determined by adopting the GRA method, the association degree between the QoS performance indexes of the session classes of UMTS and Wimax and the ideal session class QoS performance index can be obtained respectively, the association degree is used as the condition of network selection, and the network with the large association degree with the ideal session class QoS performance index is determined as the final target network.

Before switching heterogeneous network, presetting ideal QoS parameter value, forming reference sequence Y and storing in HMS, and comparing sequence X formed by QoS parameter value of session class of UMTS and Wimax_n' (n-1, 2) is stored in HMS. Referring to fig. 5, the method for GRA to determine the handover cost function includes the following steps:

step 501: comparing the sequences X_n' normalization to obtain the sequence X_n；

Step 502: calculating the sequence X_nAnd the correlation coefficient of the reference sequence Y;

the correlation coefficient calculation formula is as follows: <math> <mrow> <msub> <mi>&Gamma;</mi> <mrow> <mn>0</mn> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>&Delta;</mi> <mi>min</mi> </msub> <mo>+</mo> <msub> <mi>&Delta;</mi> <mi>max</mi> </msub> </mrow> <mrow> <msubsup> <mi>&Delta;</mi> <mi>i</mi> <mo>&prime;</mo> </msubsup> <mo>+</mo> <msub> <mi>&Delta;</mi> <mi>max</mi> </msub> </mrow> </mfrac> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> </mrow> </math>

wherein, <math> <mrow> <msubsup> <mi>&Delta;</mi> <mi>n</mi> <mo>&prime;</mo> </msubsup> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>w</mi> <mi>j</mi> </msub> <mo>|</mo> <mi>y</mi> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>x</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>,</mo> <mi>n</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> </mrow> </math> w_jis a third weight vector W₃The elements of (a) and (b),

<math> <mrow> <msub> <mi>&Delta;</mi> <mi>min</mi> </msub> <mo>=</mo> <munder> <mi>min</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>,</mo> <mi>j</mi> <mo>)</mo> </mrow> </munder> <mrow> <mo>(</mo> <mo>|</mo> <mi>y</mi> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>x</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </math> <math> <mrow> <msub> <mi>&Delta;</mi> <mi>max</mi> </msub> <mo>=</mo> <munder> <mi>max</mi> <mrow> <mo>(</mo> <mi>n</mi> <mo>,</mo> <mi>j</mi> <mo>)</mo> </mrow> </munder> <mrow> <mo>(</mo> <mo>|</mo> <mi>y</mi> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>x</mi> <mi>n</mi> </msub> <mrow> <mo>(</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>|</mo> <mo>)</mo> </mrow> <mo>,</mo> <mi>n</mi> <mo>=</mo> <mn>1,2</mn> <mo>.</mo> </mrow> </math>

the L-shaped section_0，1Representing the correlation coefficient, Γ, between the Session-class QoS Performance indicator of UMTS and the Ideal Session-class QoS Performance indicator_0，2And the correlation coefficient between the QoS performance index of the session class representing Wimax and the ideal session class QoS performance index is obtained, and the network with the large correlation coefficient is determined as the final target network.

When the UMADM method is adopted to determine the network selection condition, the closeness degree between the QoS performance indexes of the session classes of UMTS and Wimax and the ideal session class QoS performance index respectively can be obtained, the closeness degree is used as the network selection condition, and the network with the large closeness degree with the ideal session class QoS performance index is determined as the final target network.

Referring to fig. 6, a method for determining a handover cost function by a umam includes the following steps:

step 601: comparing the reference sequence Y with the comparison sequence X_nCombining to obtain a combined matrix Q;

wherein, <math> <mrow> <msub> <mi>q</mi> <mi>ij</mi> </msub> <mo>=</mo> <mrow> <mo>(</mo> <mfrac> <mi>Y</mi> <msubsup> <mi>X</mi> <mi>n</mi> <mo>&prime;</mo> </msubsup> </mfrac> <mo>)</mo> </mrow> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2.3</mn> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mi>m</mi> </mrow> </math>

m represents the number of parameters in the QoS parameter set.

Step 602: carrying out non-dimensionalization processing on the matrix Q to obtain a non-dimensionalized matrix R;

the non-dimensionalized formulas are shown below, the upper set of formulas being suitable for benefit type parameters and the lower set of formulas being suitable for cost type parameters. The benefit type parameter is a parameter that is larger and better, such as bandwidth; cost-type parameters are parameters that are as small as possible, such as delay, jitter, etc.

<math> <mrow> <msup> <msub> <mi>r</mi> <mi>ij</mi> </msub> <mi>L</mi> </msup> <mo>=</mo> <msubsup> <mi>q</mi> <mi>ij</mi> <mi>L</mi> </msubsup> <mo>/</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mn>3</mn> </munderover> <msubsup> <mi>q</mi> <mi>ij</mi> <mi>U</mi> </msubsup> <mo>,</mo> </mrow> </math> <math> <mrow> <msup> <msub> <mi>r</mi> <mi>ij</mi> </msub> <mi>U</mi> </msup> <mo>=</mo> <msubsup> <mi>q</mi> <mi>ij</mi> <mi>U</mi> </msubsup> <mo>/</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mn>3</mn> </munderover> <msubsup> <mi>q</mi> <mi>ij</mi> <mi>L</mi> </msubsup> </mrow> </math>

<math> <mrow> <msup> <msub> <mi>r</mi> <mi>ij</mi> </msub> <mi>L</mi> </msup> <mo>=</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msubsup> <mi>q</mi> <mi>ij</mi> <mi>U</mi> </msubsup> <mo>)</mo> </mrow> <mo>/</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mn>3</mn> </munderover> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msubsup> <mi>q</mi> <mi>ij</mi> <mi>L</mi> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> </mrow> </math> <math> <mrow> <msup> <msub> <mi>r</mi> <mi>ij</mi> </msub> <mi>U</mi> </msup> <mo>=</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msubsup> <mi>q</mi> <mi>ij</mi> <mi>L</mi> </msubsup> <mo>)</mo> </mrow> <mo>/</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mn>3</mn> </munderover> <mrow> <mo>(</mo> <mn>1</mn> <mo>/</mo> <msubsup> <mi>q</mi> <mi>ij</mi> <mi>U</mi> </msubsup> <mo>)</mo> </mrow> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mi>m</mi> </mrow> </math>

Step 603: calculating to obtain a comprehensive value

Wherein, <math> <mrow> <msub> <mover> <mi>z</mi> <mo>~</mo> </mover> <mi>i</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>w</mi> <mi>j</mi> </msub> <msub> <mover> <mi>r</mi> <mo>~</mo> </mover> <mi>ij</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2,3</mn> <mo>,</mo> </mrow> </math> W_jis a third weight vectorW₃Of (2) element(s)

Step 604: calculating to obtain a comprehensive value

A likelihood matrix P;

wherein, <math> <mrow> <msub> <mi>p</mi> <mi>ij</mi> </msub> <mo>=</mo> <mi>p</mi> <mrow> <mo>(</mo> <msub> <mover> <mi>z</mi> <mo>~</mo> </mover> <mi>i</mi> </msub> <mo>&GreaterEqual;</mo> <msub> <mover> <mi>z</mi> <mo>~</mo> </mover> <mi>j</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mi>min</mi> <mo>{</mo> <msub> <mi>l</mi> <msub> <mover> <mi>z</mi> <mo>~</mo> </mover> <mi>i</mi> </msub> </msub> <mo>+</mo> <msub> <mi>l</mi> <msub> <mover> <mi>z</mi> <mo>~</mo> </mover> <mi>j</mi> </msub> </msub> <mo>,</mo> <mi>max</mi> <mrow> <mo>(</mo> <msubsup> <mi>z</mi> <mi>i</mi> <mi>U</mi> </msubsup> <mo>-</mo> <msubsup> <mi>z</mi> <mi>j</mi> <mi>L</mi> </msubsup> <mo>,</mo> <mn>0</mn> <mo>)</mo> </mrow> <mo>}</mo> </mrow> <mrow> <msub> <mi>l</mi> <msub> <mover> <mi>z</mi> <mo>~</mo> </mover> <mi>i</mi> </msub> </msub> <mo>+</mo> <msub> <mi>l</mi> <msub> <mover> <mi>z</mi> <mo>~</mo> </mover> <mi>j</mi> </msub> </msub> </mrow> </mfrac> <mo>,</mo> </mrow> </math> $l_{\widetilde{z_i}}=z_i^U-z_i^L,$ $l_{\widetilde{z_j}}=z_j^U-z_j^L$

step 605: summing the likelihood matrix P according to rows to obtain a sequencing vector V;

wherein, <math> <mrow> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>p</mi> <mi>ij</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2,3</mn> </mrow> </math>

v₁indicates the ideal QoS performance index, v₂Representing QoS Performance index, v, of UMTS₃Represents the QoS performance index of Wimax. And v₁The closest network will be determined to be the final target network.

In the process of returning to the heterogeneous network handover after the target network is determined, step 209 is executed.

Step 209: HMS sends switching request message to NM of target network to request network switching;

step 210: NM of the target network sends a switching request response to HMS, and HMS is allowed to execute network switching;

step 211: the HMS sends a switching indication message to the terminal to indicate the terminal to be switched to a target network;

step 212: the terminal establishes a wireless link with a target network according to the switching indication message;

step 213: after the wireless link between the terminal and the target network is established, the NM of the target network sends a switching completion message to the HMS;

step 214: HMS sends wireless link release request to NM of original network to request to release wireless link between terminal and original network;

step 215: NM of original network sends response of releasing wireless link to HMS, and releases wireless link between terminal and original network.

It can be seen from the foregoing embodiments that, when determining the QoS parameter weight of the current service, in addition to considering a subjective requirement of the terminal on each QoS parameter, obtaining a first weight of the QoS parameter according to subjective judgment of the terminal, and also considering the current status of each network to be evaluated, obtaining a second weight of the QoS parameter according to the current QoS parameter value state of the network, after comprehensively considering the first weight and the second weight, determining a final fusion weight, that is, a third weight, and when the second weight determined by the current status of the network to be evaluated has a certain degree of association with the first weight determined by the subjective intention of the user, fine-tuning the first weight by the second weight can better embody an advantage of increasing the possibility of finding a target network. Therefore, the third weight is used for carrying out switching judgment, the possibility of finding a target network is increased, and the switching success rate is improved, so that the terminal can enjoy better service quality of other networks, and the satisfaction degree of a user is further improved.

Please refer to fig. 7, which is a flowchart illustrating a method for handover between heterogeneous networks according to a third embodiment of the present invention. This embodiment differs from the previous embodiment in that it is based on a third weight vector W₃And after obtaining the QoS performance index of the network to be evaluated by the UMADM, determining the target network by integrating the QoS performance index and the load parameter of the network to be evaluated to finally execute switching without directly determining the target network but considering the load parameter of the network to be evaluated.

In this embodiment, it is assumed that there are two networks capable of supporting a certain type of service in the network coverage area, for example, UMTS and Wimax, and when the terminal runs a session-type service at Wimax and periodically detects the QoS of the service, it finds that the QoS of the current network is not satisfied, and then triggers network handover, where the handover process includes the following steps:

step 701: the terminal sends a switching request to NM of the original network;

step 702: NM of original network sends service quality report to HMS;

step 703: HMS utilizes AHP (Analytic Hierarchy Process) method to determine the first weight of each parameter in QoS parameter set of session service;

step 704: the HMS sends a QoS query request of a network to be evaluated to the RADA, and requests to acquire a QoS parameter value of the network to be evaluated;

step 705: RADA returns a network QoS query response to be evaluated to HMS;

step 706: according to the QoS parameter value of the network to be evaluated, a second weight vector W of the QoS parameter set is obtained₂；

Step 707: according to a first weight vector W₁And a second weight vector W₂Obtaining a third weight vector W₃；

Step 708: third weight vector W of HMS according to QoS parameter set₃And UMADM method, obtainingObtaining the QoS performance index of the network to be evaluated;

since the umam method has been described in detail previously, it will not be described in detail here. Wherein, when a UMADM method is adopted to determine a switching cost function, a sequencing vector V is finally obtained, wherein <math> <mrow> <msub> <mi>v</mi> <mi>i</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>p</mi> <mi>ij</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2,3</mn> <mo>,</mo> </mrow> </math> v₁Indicates the ideal QoS performance index, v₂Representing QoS Performance index, v, of UMTS₃Represents the QoS performance index of Wimax. v. of₂And v₃That is, the QoS performance index of the network to be evaluated.

Step 709: the HMS sends a network load query request to the RADA to request to acquire network load parameters of the network to be evaluated;

step 710: the RADA sends a network load query response to the HMS;

the network load query response carries a network load parameter value.

Step 711: calculating a driving force value F of the network to be evaluated according to the QoS performance index and the network load parameter of the network to be evaluated;

wherein, $\left\{\begin{array}{c}{F}_{\mathrm{WiMax}}={\mathrm{av}}_3-{\mathrm{bL}}_{\mathrm{WiMax}}\\ F_{\mathrm{UMTS}}={\mathrm{av}}_2-{\mathrm{bL}}_{\mathrm{UMTS}}\end{array}\right.$

a and b are the weights of v and F values, respectively, and a + b is 1, a > 0, b > 0. F_WiMaxDriving force value of Wimax, F_UMTSIs the drive power value of UMTS.

Step 712: selecting a network according to the driving force value F of the network to be evaluated, and determining a target network;

wherein, when F_WiMax＞F_UMTSAnd if so, selecting WiMax as a target network, otherwise, selecting UMTS as the target network.

Step 713: HMS sends switching request message to NM of target network to request network switching;

step 714: NM of the target network sends a switching request response to HMS, and HMS is allowed to execute network switching;

step 715: the HMS sends a switching indication message to the terminal to indicate the terminal to be switched to a target network;

step 716: the terminal establishes a wireless link with a target network according to the switching indication message;

step 717: after the wireless link between the terminal and the target network is established, the NM of the target network sends a switching completion message to the HMS;

step 718: HMS sends wireless link release request to NM of original network to request to release wireless link between terminal and original network;

step 719: NM of original network sends response of releasing wireless link to HMS, and releases wireless link between terminal and original network.

It can be seen from the foregoing embodiments that, in the present embodiment, the third weight is used for performing handover decision, which increases the possibility of finding a target network and improves the success rate of handover, and also the load parameter of the network to be evaluated is considered, thereby preventing the problem of handover failure due to a large current load of the target network, and improving the success rate of handover at the target network side, so that the terminal enjoys better service quality of other networks, and further improving the satisfaction of the user.

In the above embodiment, the current network is a Wimax network, the candidate network is a UMTS network, and the method for selecting a network is described in the present invention by taking the session service as an example, but the present invention is not limited to these two networks and the session service, for example, when the current network is a UMTS network and the candidate networks are multiple, the service type is a streaming service or other types of services, and the method for switching networks is similar to the above embodiment, and will not be described again here.

Please refer to fig. 8, which is a diagram illustrating a heterogeneous network handover apparatus according to a first embodiment of the present invention

The apparatus includes a first weight determination unit 801, a second weight determination unit 802, a third weight determination unit 803, a target network determination unit 804, and a handover execution unit 805. The internal structure and connection relationship of the device will be further described below in conjunction with the working principle of the device.

A first weight determining unit 801, configured to determine a first weight of a parameter in a QoS parameter set, where the first weight is a subjective weight required by a user;

a second weight determining unit 802, configured to determine a second weight of a corresponding parameter in the QoS parameter set according to a current QoS parameter value of a network to be evaluated;

a third weight determining unit 803, configured to perform overlap fusion on the first weight determined by the first weight determining unit 801 and the second weight determined by the second weight determining unit 802, and determine a third weight of the parameter in the QoS parameter set;

a target network determining unit 804 configured to determine a target network according to the third weight determined by the third weight determining unit 803;

a handover performing unit 805 configured to perform network handover.

Wherein, the second weight determining unit 802 includes: parameter value acquisition unit 806, standard deviation determination unit 807, coefficient of variation determination unit 808, and normalization unit 809.

A parameter value obtaining unit 806, configured to obtain a current QoS parameter value of a network to be evaluated;

a standard deviation determining unit 807 for determining the current network to be evaluated acquired by the parameter value acquiring unit 806

QoS parameter value according to formula <math> <mrow> <msub> <mi>S</mi> <mi>j</mi> </msub> <mo>=</mo> <msqrt> <mfrac> <mrow> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mi>ij</mi> </msub> <mo>-</mo> <mover> <msub> <mi>x</mi> <mi>j</mi> </msub> <mo>&OverBar;</mo> </mover> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> <mi>n</mi> </mfrac> </msqrt> </mrow> </math> And <math> <mrow> <mover> <msub> <mi>x</mi> <mi>j</mi> </msub> <mo>&OverBar;</mo> </mover> <mo>=</mo> <mfrac> <mrow> <msub> <mi>x</mi> <mrow> <mn>1</mn> <mi>j</mi> </mrow> </msub> <mo>+</mo> <msub> <mi>x</mi> <mrow> <mn>2</mn> <mi>j</mi> </mrow> </msub> <mo>+</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <msub> <mi>x</mi> <mi>nj</mi> </msub> </mrow> <mi>n</mi> </mfrac> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mi>m</mi> </mrow> </math> calculating to obtain standard deviation of parameters in QoS parameter set, wherein m in the formula represents the number of parameters in QoS parameter set, n represents the number of networks to be evaluated, x represents_ijJ parameter, S, representing the ith network to be evaluated_jRepresenting oS the standard deviation of the jth parameter in the parameter set;

a variation coefficient determining unit 807 for determining the standard deviation of the parameters in the QoS parameter set determined by the standard deviation determining unit 806 according to the formula <math> <mrow> <msub> <mi>v</mi> <mi>j</mi> </msub> <mo>=</mo> <mfrac> <msub> <mi>S</mi> <mi>j</mi> </msub> <mover> <msub> <mi>x</mi> <mi>j</mi> </msub> <mo>&OverBar;</mo> </mover> </mfrac> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mi>m</mi> </mrow> </math> Calculating to obtain the variation coefficient of the parameters in the QoS parameter set, wherein v in the formula_jRepresenting the variation coefficient of the jth parameter in the QoS parameter set;

a normalizing unit 808, configured to perform normalization on the variation coefficient of the parameter in the QoS parameter set determined by the variation coefficient determining unit 807 to obtain a second weight of the parameter in the QoS parameter set.

The third weight determination unit 803 includes a correlation degree determination unit 809 and a fusion unit 810.

A correlation degree determining unit 809 for determining the first weight and the second weight according to the formula <math> <mrow> <mi>&alpha;</mi> <mo>=</mo> <mfrac> <mi>d</mi> <msub> <mi>d</mi> <mi>max</mi> </msub> </mfrac> <mo>,</mo> </mrow> </math> $d_{\max }=\sqrt{2},$ β ═ 1- α and $d=\sqrt{{(y_1-x_1)}^2+{(y_2-x_2)}^2+...+{(y_j-x_j)}^2},j=\mathrm{1,2},...m$ calculating to obtain the degree of correlation between the first weight and the second weight, wherein m in the formula represents the number of the first weight and the second weight, and x_jRepresenting said first weight, y_jRepresents the aboveA second weight, α and β representing a degree of correlation between the first weight and the second weight;

a fusion unit 810 for making the first weight and the second weight according to the formula w according to the correlation degree determined by the correlation degree determination unit 809_j＝αx_j+βy_jPerforming coincidence degree fusion to obtain a third weight of the parameters in the QoS parameter set, wherein w in the formula_jA third weight representing a jth parameter in the set of QoS parameters.

It can be seen from the foregoing embodiments that, when determining the QoS parameter weight of the current service, in addition to considering a subjective requirement of the terminal on each QoS parameter, the first weight determining unit 801 determines the first weight of the QoS parameter according to a subjective judgment of the terminal, and also considering the current status of each network to be evaluated, the second weight determining unit 802 determines the second weight of the QoS parameter according to the current QoS parameter value state of the network, and after comprehensively considering the first weight and the second weight, the third weight determining unit 803 determines the final fusion weight, that is, the third weight, and performs a handover decision by using the third weight, thereby increasing the possibility of finding a target network, and improving the success rate of handover, so that the terminal enjoys better service quality of other networks, and further improving the satisfaction degree of users.

Those skilled in the art will appreciate that all or part of the steps in the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, where the program may be stored in a computer readable storage medium, and the program includes the following steps: determining a first weight of a parameter in a QoS parameter set, wherein the first weight is a subjective weight required by a user, and determining a second weight of the parameter in the QoS parameter set according to a current QoS parameter value of a network to be evaluated; fusing the first weight and the second weight to determine a third weight of the parameters in the QoS parameter set; and selecting the network according to the third weight, determining a target network, and switching the network. The storage medium, such as: ROM/RAM, magnetic disk, optical disk, etc.

The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (6)

1. A method for heterogeneous network handover, comprising:

determining a first weight of a parameter in a quality of service (QoS) parameter set, wherein the first weight is a subjective weight required by a user, and determining a second weight of the parameter in the QoS parameter set according to a current QoS parameter value of a network to be evaluated, wherein the first weight comprises the following steps: obtaining the current QoS parameter value of the network to be evaluated, and carrying out formula treatment on the current QoS parameter value of the network to be evaluated

And

j is 1, 2, the standard deviation of the parameters in the QoS parameter set is obtained by calculating, m in the formula represents the number of the parameters in the QoS parameter set, n represents the number of the networks to be evaluated, and x represents the number of the networks to be evaluated_ijJ parameter, S, representing the ith network to be evaluated_jExpressing the standard deviation of the jth parameter in the QoS parameter set according to a formula

j is 1, 2,. m is calculated to obtain the variation coefficient of the parameters in the QoS parameter set, and v in the formula_jRepresenting the variation coefficient of the jth parameter in the QoS parameter set, and carrying out normalization processing on the variation coefficient of the parameters in the QoS parameter set to obtain a second weight of the parameters in the QoS parameter set;

and performing overlap ratio fusion on the first weight and the second weight, and determining a third weight of the parameters in the QoS parameter set, wherein the third weight comprises: the first weight and the second weight are expressed according to a formula

β ═ 1- α and

m, wherein m in the formula represents the number of the first weight and the second weight, and x represents the number of the first weight and the second weight_jRepresenting said first weight, y_jRepresenting the second weight, a and β representing a degree of correlation between the first weight and the second weight, the first weight and the second weight being expressed according to a formula w_j＝αx_j+βy_jPerforming coincidence degree fusion to obtain a third weight of the parameters in the QoS parameter set, wherein w in the formula_jA third weight representing a jth parameter in the set of QoS parameters;

and determining a target network according to the third weight, and performing network switching.

2. The method of claim 1, wherein the obtaining the current QoS parameter value of the network to be evaluated comprises:

acquiring a current QoS parameter value of a network to be evaluated from a network manager NM of the network to be evaluated;

or,

and acquiring the current QoS parameter value of the network to be evaluated from a radio access database RADA.

3. The method of claim 1, wherein determining the target network according to the third weight comprises:

and determining the degree of association between the QoS performance indexes of the network to be evaluated and preset ideal QoS performance indexes respectively by a gray level association analysis (GRA) method according to the third weight, and selecting the network to be evaluated with the maximum degree of association with the preset ideal QoS performance indexes as a target network.

4. The method of claim 1, wherein determining the target network according to the third weight comprises:

and determining the QoS performance index of the network to be evaluated according to the third weight by the uncertain multi-attribute decision UMADM method, and selecting the network to be evaluated with the maximum degree of closeness between the QoS performance index of the network to be evaluated and a preset ideal QoS performance index as a target network.

5. The method of claim 1, wherein determining the target network according to the third weight comprises:

determining the QoS performance index of the network to be evaluated according to the third weight by the uncertain multi-attribute decision UMADM method, and acquiring the network load parameter of the network to be evaluated;

obtaining a driving force value F of the network to be evaluated according to the QoS performance index of the network to be evaluated and the network load parameter of the network to be evaluated;

and selecting the network to be evaluated with the maximum driving force value F of the network to be evaluated as a target network.

6. An apparatus for heterogeneous network handover, comprising:

a first weight determining unit, configured to determine a first weight of a parameter in a QoS parameter set, where the first weight is a subjective weight required by a user;

a second weight determining unit, configured to determine a second weight of a parameter in the QoS parameter set according to a current QoS parameter value of a network to be evaluated, where the second weight determining unit includes: a parameter value obtaining unit for obtaining the current QoS parameter value of the network to be evaluated, a standard deviation determining unit for determining the current QoS parameter value of the network to be evaluated obtained by the parameter value obtaining unit according to a formula

And

j is 1, 2, the standard deviation of the parameters in the QoS parameter set is obtained by calculating, m in the formula represents the number of the parameters in the QoS parameter set, n represents the number of the networks to be evaluated, and x represents the number of the networks to be evaluated_ijJ parameter, S, representing the ith network to be evaluated_jA standard deviation representing the jth parameter in the QoS parameter set, a variation coefficient determining unit for determining the standard deviation of the parameters in the QoS parameter set determined by the standard deviation determining unit according to a formulaj is 1, 2,. m is calculated to obtain the variation coefficient of the parameters in the QoS parameter set, and v in the formula_jThe normalization unit is used for carrying out normalization processing on the variation coefficient v of the parameters in the QoS parameter set determined by the variation coefficient determination unit to obtain a second weight of the parameters in the QoS parameter set;

a third weight determining unit, configured to perform overlap-ratio fusion on the first weight and the second weight, and determine a third weight of the parameter in the QoS parameter set, where the third weight determining unit includes: a correlation degree determining unit for formulating the first weight and the second weight

β ═ 1- α and

m, wherein m in the formula represents the number of the first weight and the second weight, and x represents the number of the first weight and the second weight_jRepresenting said first weight, y_jA second weight representing the second weight, alpha and beta representing the degree of correlation between the first weight and the second weight, a fusion unit for determining the degree of correlation based on the first weight and the second weight, and a formula w_j＝αx_j+βy_jFusing to obtain a third weight of the parameter in the QoS parameter set, w in the formula_jA third weight representing a jth parameter in the set of QoS parameters;

a target network determining unit, configured to determine a target network according to the third weight;

and the switching execution unit is used for switching the network.

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