CN114698012B - Network vertical switching method of multimode intelligent terminal - Google Patents

Network vertical switching method of multimode intelligent terminal Download PDF

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CN114698012B
CN114698012B CN202210063451.4A CN202210063451A CN114698012B CN 114698012 B CN114698012 B CN 114698012B CN 202210063451 A CN202210063451 A CN 202210063451A CN 114698012 B CN114698012 B CN 114698012B
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attributes
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attribute
sample
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CN114698012A (en
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王雪
苏荣昕
钱志鸿
肖�琳
高鑫
韩英斌
史昊天
周跃飞
焦钰辉
许天宇
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Jilin University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/14—Reselecting a network or an air interface
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/08—Testing, supervising or monitoring using real traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0055—Transmission or use of information for re-establishing the radio link
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0083—Determination of parameters used for hand-off, e.g. generation or modification of neighbour cell lists
    • H04W36/0085—Hand-off measurements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/16—Performing reselection for specific purposes
    • H04W36/165—Performing reselection for specific purposes for reducing network power consumption
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality

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  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Quality & Reliability (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention relates to a network vertical switching method of a multimode intelligent terminal, and belongs to the technical field of communication. The method comprises the following steps: calculating the mean value, variance and correlation coefficient matrix of QoS sample attributes of the wireless network; calculating the mahalanobis distance of the candidate network to be accessed and the importance degree of the QoS attribute set; establishing a utility evaluation model; and determining the optimal candidate network according to the switching strategy, and executing vertical switching. According to the method and the device for performing the vertical switching of the terminal, the sample data are processed, the related parameters are calculated, the utility evaluation model is constructed, the calculated utility value and the switching strategy are further constructed, the terminal can be switched to the optimal heterogeneous wireless network, error switching and invalid switching are reduced, and user experience and the service efficiency of the heterogeneous wireless network are improved.

Description

Network vertical switching method of multimode intelligent terminal
Technical Field
The invention belongs to the technical field of communication, and particularly relates to a network vertical switching method of a multimode intelligent terminal.
Background
In order to meet the increasing network demands of end users, technologies such as wireless broadband access and wireless cellular access are evolving continuously, and wireless networks are not replaced and there is no wireless network integrating various advantages. Thus, the next generation wireless network will be a heterogeneous wireless network system in which a plurality of wireless networks coexist, and the new generation wireless network will be a converged network.
The existing multimode terminal equipment is provided with various wireless network interfaces, so that the multimode terminal provides natural conditions for vertical switching of wireless networks, and the multimode terminal with an intelligent switching algorithm can automatically execute switching among heterogeneous networks under the condition that the terminal keeps optimal network connection. Currently, there are many algorithms to solve the problem of wireless network handover, and there are mainly the following types of algorithms: 1) received signal strength and refinement algorithm based switching algorithm 2) neural network based switching algorithm 3) deep reinforcement learning based switching algorithm 4) fuzzy logic based switching algorithm. However, the above-mentioned switching algorithm is mainly based on linear utility theory, and the switching decision algorithm is based on the utility values which are constructed on the premise of independent properties such as AHP and entropy.
Therefore, considering the network evaluation method of the non-independent and nonlinear additive of the actual QoS, the completion of the efficient and accurate vertical handover of the heterogeneous wireless network is an urgent problem to be solved.
Disclosure of Invention
The invention aims to overcome the defects and shortcomings of the prior art, and provides a network vertical switching method of a multimode intelligent terminal.
According to one aspect of the present invention, there is provided a network vertical handover method of a multimode intelligent terminal, the method comprising the steps of:
S1: acquiring quality of service (QoS) sample attributes of a wireless network, wherein the attributes comprise bandwidth, time delay, jitter, bit error rate and signal to noise ratio;
S2: calculating to obtain a correlation coefficient matrix of the QoS sample attribute according to the mean value and the variance of the QoS sample attribute;
S3: calculating the mahalanobis distance of the QoS attribute of the candidate network to be accessed according to the correlation coefficient matrix, and calculating the importance degree of the QoS attribute set of the candidate network to be accessed according to the mahalanobis distance;
S4: according to the importance coefficient and interaction degree between every two attributes, calculating interaction indexes between every two attributes;
s5: constructing a nonlinear network utility evaluation model according to the importance degree of the QoS attribute set and the interaction index between every two attributes;
S6: and calculating the utility value of the candidate network to be accessed according to the utility evaluation model, taking the candidate network to be accessed with the maximum utility value as the optimal network, and executing vertical switching.
Preferably, the acquiring quality of service QoS sample attributes of the wireless network includes:
The multimode terminal monitors the QoS attribute value of the wireless network in real time, processes the QoS attribute value to obtain a sample set X= { X i |i=1, 2, …, m } and an attribute set G= { y j |j=1, 2, …, n }, and constructs a standard sample matrix A= [ a ij]m×n; where x i is the ith sample, y j is the jth attribute, and a ij represents the value of the jth attribute y j of the ith sample x i.
Preferably, the average value of the QoS sample attributes is:
the variance of the QoS sample attributes is:
Preferably, the calculating the correlation coefficient matrix of the QoS sample attribute includes:
Normalizing a= [ a ij]m×n, obtaining normalized QoS sample attribute index matrix b= [ B ij]m×n:
calculating a correlation coefficient matrix:
Namely:
Where |g| is the number of attributes of the wireless network in the attribute set G, B ij is the QoS sample attribute index, and B G (k) is the kth sample.
Preferably, the calculating the mahalanobis distance of the QoS attribute of the candidate network to be accessed according to the correlation coefficient matrix includes:
Assuming that p candidate networks to be accessed are provided, qoS attribute indexes of the candidate networks to be accessed collected by the multimode terminal are formed Pair/>, using the mean and variance of standard sample a= [ a ij]m×n ] as a referenceNormalization was performed and denoted as [ z ij]p×n:
calculating the mahalanobis distance of the QoS attribute of the candidate network set to be accessed:
Where r ij represents the value of the j-th attribute y j of the i-th candidate network to be accessed, and z ij represents the value of the j-th attribute index of the i-th candidate network to be accessed after standard sample measurement.
Preferably, the calculating the importance degree of the candidate network QoS attribute set to be accessed according to the mahalanobis distance includes:
The importance degree of the QoS attribute set of the candidate network to be accessed is calculated, specifically:
Where G is a subset of the network attribute set G and Q is the number of elements in G.
Preferably, the calculating the interaction index between the two attributes according to the importance coefficient and the interaction degree between the two attributes includes:
the n QoS attributes in G are compared in pairs to obtain an importance coefficient matrix H and an interaction matrix V between every two attributes:
H＝[hij]n×n,0≤hij≤1,hij＝1-hji
V＝[vij]n×n,-1≤vij≤1,vij＝vji
Wherein h ij represents the importance degree of y j to y i, and v ij represents the interaction degree between every two attributes;
obtaining a relative importance matrix C from the importance coefficient matrix H:
C＝[cij]＝[hik/hjk]n×n
The maximum eigenvector of the relative importance matrix C is obtained (lambda 1,λ2,…λn)T, according to eigenvalue vector, V is updated, and interaction indexes between every two attributes are obtained:
where sgn () is a sign function.
Preferably, the constructing a nonlinear network utility evaluation model according to the importance degree of the QoS attribute set and the interaction index between the two attributes includes:
Constructing a nonlinear network utility evaluation model:
wherein w i represents the importance of the QoS attribute set, and w ij is an interaction index between every two attributes; when y i is a benefit type QoS, When y i is a cost QoS,/>
Preferably, the importance degree w i of the QoS attribute set satisfies the following objective function:
The limiting conditions are as follows:
wherein, the global importance of w g set denoted by alpha is lower bound to the difference value of the attribute indexes in the set to act independently.
Preferably, the performing vertical handover with the candidate network to be accessed with the largest utility value as the optimal network includes:
calculating utility values of p candidate networks to be accessed, and finishing vertical switching according to a switching strategy pi:
π＝max Un(G)，n＝1，2…p
where pi represents the candidate network to which the maximum utility function corresponds.
The beneficial effects are that: the invention abandons the excessively ideal assumption of independent QoS and linearly additive in the prior method, and provides the multi-mode intelligent terminal heterogeneous wireless network vertical switching method based on the QoS correlation and heterogeneous wireless network performance evaluation of the multi-attribute nonlinear set in the actual wireless network, which can enable the terminal to be switched to the optimal heterogeneous wireless network, reduce error switching and invalid switching, maintain always the optimal link principle and improve the user experience QoE and the service efficiency of the heterogeneous wireless network.
Features and advantages of the present invention will become apparent by reference to the following drawings and detailed description of embodiments of the invention.
Drawings
FIG. 1 is a flow chart of a network vertical handover method of a multimode intelligent terminal;
fig. 2 is a schematic diagram of a network vertical handover scenario of a multimode intelligent terminal.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1 and 2, in an embodiment of the present invention, a network vertical handover method for a multimode intelligent terminal is provided, where the method includes the following steps:
S1: quality of service, qoS, sample attributes of a wireless network are obtained, including bandwidth, latency, jitter, bit error rate, and signal-to-noise ratio.
S2: calculating to obtain a correlation coefficient matrix of the QoS sample attribute according to the mean value and the variance of the QoS sample attribute;
S3: calculating the mahalanobis distance of the QoS attribute of the candidate network to be accessed according to the correlation coefficient matrix, and calculating the importance degree of the QoS attribute set of the candidate network to be accessed according to the mahalanobis distance;
S4: according to the importance coefficient and interaction degree between every two attributes, calculating interaction indexes between every two attributes;
s5: constructing a nonlinear network utility evaluation model according to the importance degree of the QoS attribute set and the interaction index between every two attributes;
S6: and calculating the utility value of the candidate network to be accessed according to the utility evaluation model, taking the candidate network to be accessed with the maximum utility value as the optimal network, and executing vertical switching.
According to the embodiment, the sample data are processed, the related parameters are calculated, the utility evaluation model is constructed, the calculated utility value and the switching strategy are further constructed to execute the vertical switching of the terminal, the terminal can be switched to the optimal heterogeneous wireless network, error switching and invalid switching are reduced, and user experience and the service efficiency of the heterogeneous wireless network are improved.
Preferably, the acquiring quality of service QoS sample attributes of the wireless network includes:
The multimode terminal monitors the QoS attribute value of the wireless network in real time, processes the QoS attribute value to obtain a sample set X= { X i |i=1, 2, …, m } and an attribute set G= { y j |j=1, 2, …, n }, and constructs a standard sample matrix A= [ a ij]m×n; where x i is the ith sample, y j is the jth attribute, and a ij represents the value of the jth attribute y j of the ith sample x i.
Specifically, the multimode terminal inputs experimental sample data; the method for obtaining the sample data comprises the following steps: the method comprises the steps that mode terminals are randomly distributed in an heterogeneous wireless network area, multimode terminals are to be accessed into a wireless network, the attribute value of the wireless QoS network is monitored in real time, and data collected by the multimode terminals are cleaned, namely: and removing the invalid network attribute combination and the error format data, and screening according to QoE user experience quality to obtain a relatively better network. Obtaining m wireless network QoS attribute index sets, and selecting n important wireless network QoS indexes as performance evaluation combinations of the wireless network, wherein x= { X i |i=1, 2, …, m }, X represents a sample set, an ith sample is denoted as X i, a jth attribute is denoted as y j, the set of attributes is G, g= { y j |j=1, 2, …, n }, thereby forming an a= [ a ij]m×n standard sample matrix, and a ij represents a value of a jth attribute y j of an ith sample X i.
Preferably, the average value of the QoS sample attributes is:
the variance of the QoS sample attributes is:
In this step, the mean and variance of the sample matrix a are calculated column by column.
Preferably, the calculating the correlation coefficient matrix of the QoS sample attribute includes:
Normalizing a= [ a ij]m×n, obtaining normalized QoS sample attribute index matrix b= [ B ij]m×n:
calculating a correlation coefficient matrix:
Namely:
Where |g| is the number of attributes of the wireless network in the attribute set G, B ij is the QoS sample attribute index, and B G (k) is the kth sample.
In this step, normalize a= [ a ij]m×n ] and normalize y j by column, and then obtain normalized QoS sample attribute index b ij, |g|×|g| representing the size of the matrix.
Preferably, the calculating the mahalanobis distance of the QoS attribute of the candidate network to be accessed according to the correlation coefficient matrix includes:
Assuming that p candidate networks to be accessed are provided, qoS attribute indexes of the candidate networks to be accessed collected by the multimode terminal are formed Pair/>, using the mean and variance of standard sample a= [ a ij]m×n ] as a referenceNormalization was performed and denoted as [ z ij]p×n:
calculating the mahalanobis distance of the QoS attribute of the candidate network set to be accessed:
Where r ij represents the value of the j-th attribute y j of the i-th candidate network to be accessed, and z ij represents the value of the j-th attribute index of the i-th candidate network to be accessed after standard sample measurement.
Preferably, the calculating the importance degree of the candidate network QoS attribute set to be accessed according to the mahalanobis distance includes:
The importance degree of the QoS attribute set of the candidate network to be accessed is calculated, specifically:
Where G is a subset of the network attribute set G and Q is the number of elements in G.
In this step, the method of Ma Shitian ports is used to calculate the importance of the network attribute set to be accessed.
Preferably, the calculating the interaction index between the two attributes according to the importance coefficient and the interaction degree between the two attributes includes:
the n QoS attributes in G are compared in pairs to obtain an importance coefficient matrix H and an interaction matrix V between every two attributes:
H＝[hij]n×n,0≤hij≤1,hij＝1-hji
V＝[vij]n×n,-1≤vij≤1,vij＝vji
Wherein h ij represents the importance degree of y j to y i, and v ij represents the interaction degree between every two attributes;
obtaining a relative importance matrix C from the importance coefficient matrix H:
C＝[cij]＝[hik/hjk]n×n
The maximum eigenvector of the relative importance matrix C is obtained (lambda 1,λ2,…λn)T, according to eigenvalue vector, V is updated, and interaction indexes between every two attributes are obtained:
where sgn () is a sign function.
In this step, the n QoS attributes in G are compared in pairs by using a diamond pair comparison method (diamond pairwise comprations), which is an algorithm proposed by japanese scientist Takahagi in 2008, and is applied in other fields.
Preferably, the constructing a nonlinear network utility evaluation model according to the importance degree of the QoS attribute set and the interaction index between the two attributes includes:
Constructing a nonlinear network utility evaluation model:
wherein w i represents the importance of the QoS attribute set, and w ij is an interaction index between every two attributes; when y i is a benefit type QoS, When yi is a cost QoS,/>
In the step, an evaluation model is built based on choquet nonlinear integration operators, and choquet nonlinear integration operators are fuzzy integration and are applied to other fields. The embodiment introduces the integration operator into the technical field of network vertical switching to indicate the nonlinear relationship among attributes.
Preferably, the importance degree w i of the QoS attribute set satisfies the following objective function:
The limiting conditions are as follows:
wherein, the global importance of w g set denoted by alpha is lower bound to the difference value of the attribute indexes in the set to act independently.
In this step, the network attribute value is subjected to homodromous processing, namely: when y i is a benefit type QoS,When y i is a cost QoS,/>All the attributes in the attribute index set become positive cooperative relations after the same orientation, only the interactive relations between every two decision attributes are considered, and more than three interactive relations are zero. By solving wi, let/>The largest, representing the role of the network attribute set in the decision process, plays the largest role.
Preferably, the performing vertical handover with the candidate network to be accessed with the largest utility value as the optimal network includes:
calculating utility values of p candidate networks to be accessed, and finishing vertical switching according to a switching strategy pi:
π＝max Un(G)，n＝1，2…p
where pi represents the candidate network to which the maximum utility function corresponds.
The invention abandons the over ideal assumption of independent QoS and linear addable in the prior method, and provides the multi-mode intelligent terminal heterogeneous wireless network vertical switching method based on the QoS correlation and heterogeneous wireless network performance evaluation of the multi-attribute nonlinear set in the actual wireless network, which can enable the terminal to be switched to the optimal heterogeneous wireless network, reduce error switching and invalid switching, maintain the always optimal link principle and improve the user experience QoE and the service efficiency of the heterogeneous wireless network.
The foregoing description is only of the preferred embodiments of the present invention and is not intended to limit the scope of the invention, and all equivalent structural changes made by the specification and drawings of the present invention or direct/indirect application in other related technical fields are included in the scope of the present invention.

Claims (8)

1. The network vertical switching method of the multimode intelligent terminal is characterized by comprising the following steps of:
s1: acquiring quality of service (QoS) sample attributes of a wireless network, wherein the attributes comprise bandwidth, time delay, jitter, bit error rate and signal to noise ratio;
s2: calculating to obtain a correlation coefficient matrix of the QoS sample attribute according to the mean value and the variance of the QoS sample attribute;
s3: calculating the mahalanobis distance of the QoS attribute of the candidate network to be accessed according to the correlation coefficient matrix, and calculating the importance degree of the QoS attribute set of the candidate network to be accessed according to the mahalanobis distance;
s4: according to the importance coefficient and interaction degree between every two attributes, calculating interaction indexes between every two attributes;
s5: constructing a nonlinear network utility evaluation model according to the importance degree of the QoS attribute set and the interaction index between every two attributes;
S6: according to the utility evaluation model, calculating utility values of candidate networks to be accessed, taking the candidate network to be accessed with the maximum utility value as an optimal network, and executing vertical switching;
The obtaining quality of service QoS sample attributes of the wireless network includes:
The multimode terminal monitors the QoS attribute value of the wireless network in real time, processes the QoS attribute value to obtain a sample set X= { X i |i=1, 2, …, m } and an attribute set G= { y j |j=1, 2, …, n }, and constructs a standard sample matrix A= [ a ij]m×n; where x i is the ith sample, y j is the jth attribute, and a ij represents the value of the jth attribute y j of the ith sample x i;
the average value of the QoS sample attributes is:
the variance of the QoS sample attributes is:
2. The method of claim 1 wherein said calculating a correlation coefficient matrix for said QoS sample attributes comprises:
Normalizing a= [ a ij]m×n, obtaining normalized QoS sample attribute index matrix b= [ B ij]m×n:
calculating a correlation coefficient matrix:
Namely:
Where |g| is the number of attributes of the wireless network in the attribute set G, B ij is the QoS sample attribute index, and B G (k) is the kth sample.
3. The method of claim 2, wherein said calculating a mahalanobis distance of QoS attributes of the candidate network to be accessed based on the correlation coefficient matrix comprises:
assuming that p candidate networks to be accessed are provided, qoS attribute indexes of the candidate networks to be accessed collected by the multimode terminal are formed Pair/>, using the mean and variance of standard sample a= [ a ij]m×n ] as a referenceNormalization was performed and denoted as [ z ij]p×n:
calculating the mahalanobis distance of the QoS attribute of the candidate network set to be accessed:
where r ij represents the value of the j-th attribute y j of the i-th candidate network to be accessed, and z ij represents the value of the j-th attribute index of the i-th candidate network to be accessed after standard sample measurement.
4. The method of claim 3, wherein the calculating the importance of the set of QoS attributes of the candidate network to be accessed according to the mahalanobis distance comprises:
The importance degree of the QoS attribute set of the candidate network to be accessed is calculated, specifically:
Where G is a subset of the network attribute set G and Q is the number of elements in G.
5. The method of claim 4, wherein calculating the interaction index between the two attributes based on the importance coefficient and the interaction degree between the two attributes comprises:
The n QoS attributes in G are compared in pairs to obtain an importance coefficient matrix H and an interaction matrix V between every two attributes:
H＝[hij]n×n,0≤hij≤1,hij＝1-hji
V＝[vij]n×n,-1≤vij≤1,vij＝vji
Wherein h ij represents the importance of y j to y i, and v ij represents the interaction degree between every two attributes;
obtaining a relative importance matrix C from the importance coefficient matrix H:
C＝[cij]＝[hik/hjk]n×n
The maximum eigenvector of the relative importance matrix C is obtained (lambda 1,2,…λn)T, according to eigenvalue vector, V is updated, and interaction indexes between every two attributes are obtained:
where sgn () is a sign function.
6. The method of claim 5, wherein constructing a nonlinear network utility evaluation model based on the importance of the QoS attribute set and the interaction index between the two attributes comprises:
Constructing a nonlinear network utility evaluation model:
Wherein w i represents the importance of the QoS attribute set, and w ij is an interaction index between every two attributes; when y i is a benefit type QoS, When y i is a cost QoS,/>
7. The method of claim 6 wherein the importance level w i of the QoS attribute set satisfies the following objective function:
The limiting conditions are as follows:
Wherein, the global importance of w g set denoted by alpha is lower bound to the difference value of the attribute indexes in the set to act independently.
8. The method of claim 7, wherein the performing the vertical handover with the candidate network to be accessed with the largest utility value as the optimal network comprises:
calculating utility values of p candidate networks to be accessed, and finishing vertical switching according to a switching strategy pi:
π＝max Un(G),n＝1,2…p
where pi represents the candidate network to which the maximum utility function corresponds.
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CN105704741A (en) * 2014-12-12 2016-06-22 华北电力大学 Heterogeneous network access selection policy
CN107889195A (en) * 2017-11-16 2018-04-06 电子科技大学 A kind of self study heterogeneous wireless network access selection method of differentiated service
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