CN107659977A - Indoor heterogeneous network access selection method based on VLC - Google Patents

Indoor heterogeneous network access selection method based on VLC Download PDF

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CN107659977A
CN107659977A CN201711022173.3A CN201711022173A CN107659977A CN 107659977 A CN107659977 A CN 107659977A CN 201711022173 A CN201711022173 A CN 201711022173A CN 107659977 A CN107659977 A CN 107659977A
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mtd
msub
network
parameter
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CN107659977B (en
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孙志鹏
尚韬
董赞扬
李骞
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Xidian University
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Xidian University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/02—Access restriction performed under specific conditions
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
    • H04B10/11—Arrangements specific to free-space transmission, i.e. transmission through air or vacuum
    • H04B10/114—Indoor or close-range type systems
    • H04B10/116—Visible light communication
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/02—Access restriction performed under specific conditions
    • H04W48/04—Access restriction performed under specific conditions based on user or terminal location or mobility data, e.g. moving direction, speed
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/02—Access restriction performed under specific conditions
    • H04W48/06—Access restriction performed under specific conditions based on traffic conditions
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/08—Access restriction or access information delivery, e.g. discovery data delivery
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/16—Discovering, processing access restriction or access information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W48/00—Access restriction; Network selection; Access point selection
    • H04W48/18—Selecting a network or a communication service

Abstract

The invention discloses a kind of indoor heterogeneous network access selection method based on VLC, mainly solve the problems, such as that prior art can not carry out network preferentially in real time.Its scheme is：1. increasing the fields such as bandwidth, average delay, handling capacity, average transmission rate, the bit error rate in original beacon frame, the status information of network is indicated in real time by these fields；2. receiving the beacon frame that each network is sent, according to the heterogeneous network information detected, with reference to customer service demand and the parameter value of reception, master, the objective weight of each parameter are obtained；3. considering the uniformity of main, objective scheme and the optimality of overall plan, mathematical model of optimization is established, the main, distribution coefficient of objective weight is calculated, and then calculates the fractional value of each network, selects fractional value highest network as optimal network.The present invention can go out optimal network by real-time selection in heterogeneous network, lift the service quality of user, available for the optimal network selection under indoor visible light communication VLC heterogeneous networks.

Description

Indoor heterogeneous network access selection method based on VLC
Technical field
The invention belongs to communication technical field, further relates to a kind of access selection method of heterogeneous network, can be used for Optimal network selection under indoor visible light communication VLC heterogeneous networks.
Background technology
Indoor visible light communication VLC is a kind of novel radio optical communication mode developed rapidly based on white light LEDs, and it is utilized The light of visible light wave range is as information carrier, by the high-frequency fast blink of white light LEDs come transmission information.Compared to traditional Radio-Frequency Wireless Communication, VLC have green, electromagnetic-radiation-free, strong security, without spectrum authorization, available bandwidth is big, communication Many advantages, such as speed is high, the concern and research of increasing researcher and enterprise are obtained.
Due to white light LEDs have low energy consumption, sustainable use time length, stable performance, size it is small, it is green, illumination Work well, many advantages, such as response sensitivity is high, and the just natural light that white light LEDs are sent, to human eye fanout free region, make it As following very competitive lighting system.
Therefore, the VLC technologies based on White-light LED illumination light source are applied to have feasibility base in next generation wireless communication Plinth, widely available with LED illumination, VLC will be indoor indispensable communication mode, before having very big engineer applied Scape.
Indoors under environment, VLC access points can also carry out the data transfer of high-speed while illumination is provided the user. But if VLC is as a kind of single communication, there is also LED modulation bandwidths are limited, communication chain Louis is blocked, Multipath effect is obvious, and up-link realizes many defects such as difficulty.Therefore, increasing researcher wirelessly connects according to various The characteristics of entering technology attempts to combine VLC progress isomery fusions, sets up indoor VLC heterogeneous networks.By setting up indoor VLC isomeries It network, can be complementary to one another various wireless access technologys, provide the user a high bandwidth, wide covering, support data, language The high performance network of the multiple business such as sound, multimedia；Various wireless access technologys can also be made to form an entirety, preferably carried The power system capacity of network is risen, network resource utilization is improved, is preferably seamlessly connected etc..It is but different in an indoor VLC In network forming network, how business demand according to user and objective network performance, on the premise of user QoS is met, in real time It is a major issue firstly the need of solution that optimal network is selected from multiple candidate networks.
In the last few years, the access selection algorithm under heterogeneous network was paid close attention to and studied by many researchers.Traditional base In single factor test, such as received signal strength RSS, Signal to Interference plus Noise Ratio SNR selection algorithms, it is impossible to networks with different systems in heterogeneous network Performance reasonably judged, can not solve under heterogeneous network environment to the preferentially problem of network.At present, research is compared Extensive heterogeneous network access selection algorithm can be divided into 3 classes：1) selection algorithm based on fuzzy logic or neutral net；2) it is based on The selection algorithm of game theory；3) the multifactor selection algorithm based on multiple attribute decision making (MADM) MADM.Wherein, the multifactor choosing based on MADM Select algorithm and typically consider multiple decision factors, multiple multiple attributive decision making methods are combined, used from the point of view of user preference The subjective business demand at family, but the objective performance of the business demand of user and network is not effectively combined and carries out net Network preferentially, and it is most of do not account for the problems such as how dynamically obtaining network parameter according to the time-varying characteristics of network, such as： A.Sgora, D.D.Vergados and P.Chatzimisios et al. exist " An access network selection A kind of analytic hierarchy process AHP and partially is proposed in algorithm for heterogeneous wireless environments " The heterogeneous network selection algorithm that good ordinal number method TOPSIS is combined, the algorithm consider handling capacity, time delay, delay variation, price Etc. parameter, go to determine the weight of each attribute using AHP, go to obtain final access network ranking, this side using TOPSIS methods Method has no mention of how to obtain various network parameters although it is contemplated that the subjective demand of multiple network parameter and user, and Scheme is excessively subjective, does not account for objective network performance, it is impossible to which the performance of networks with different systems in heterogeneous network is closed The judge of reason, can not preferably solve under heterogeneous network environment to the preferentially problem of network.
Therefore indoors in heterogeneous network, the real-time acquisition problem of multiple network parameter how is considered, and it is how effective The business demand by user combine the access selection carried out in heterogeneous network with the objective performance of network, will be indoor different The major issue solved is needed in network forming network.
The content of the invention
It is an object of the invention to for above-mentioned the deficiencies in the prior art, there is provided a kind of indoor heterogeneous network based on VLC Access selection method, the business demand of user is combined with objective network performance, it is right under heterogeneous network environment to realize The real-time access selection of network.
The present invention technical thought be：Indoors under VLC heterogeneous networks, beacon frame is improved first, in original letter Marking increases the fields such as bandwidth, average delay, handling capacity, average transmission rate, the bit error rate in frame, indicated in real time by these fields The status information of network；Each network is according to the respective improved beacon frame of the broadcast of beacon interval period；User receives each net After the beacon frame that network is sent, the network information of oneself present position is detected；Inputted with reference to own service demand to each ginseng Several preference values, while user utilizes the parameter value in each networked beacons frame and the signal power value detected；Layer is respectively adopted Fractional analysis and dispersion method, obtain the subjective weight and objective weight of each parameter；According to the uniformity of subjective and objective scheme with And the optimality of overall plan, establish mathematical model of optimization and solve, led, the distribution coefficient of objective weight；Using point Distribution coefficient weights to the master of each parameter, objective weight, so as to acquire the final weight of parameters, further according to simple weighted Method, the fractional value of each network is obtained, using fractional value highest network as the optimal network in heterogeneous network.
According to above-mentioned technical thought, it is as follows to realize that technical scheme that the object of the invention is taken includes：
(1) each existing beacon frame structure of network in indoor heterogeneous network is improved：I.e. in the existing frame of each network Increase in body 4bytes bandwidth, 4bytes average delay, 4bytes handling capacity, 4bytes average transmission rate, 4bytes bit error rate field, to indicate the status information of each network in real time；
(2) indoors under heterogeneous network environment, the broadcast of beacon interval period of each network in beacon frame is each Beacon frame after improvement；
(3) user receives the beacon frame that each network is sent, and detects the heterogeneous network information for present position of controlling oneself；
(4) user is according to the heterogeneous network information detected, with reference to own service demand, input to bandwidth, average delay, Handling capacity, average transmission rate, the bit error rate, received signal strength, the setting value of price these parameters, structure comparator matrix A；
(5) user utilizes the parameter value in each networked beacons frame received, structure according to the heterogeneous network information detected Build parameter matrix S；
(6) user obtains bandwidth, average delay, handling capacity, average transmission speed according to comparator matrix A and parameter matrix S Rate, the bit error rate, received signal strength, the final weight w of price these parametersj, j=1,2...7, w1, w2…w7On corresponding to respectively State the final weight of each parameter：
(6a), using analytic hierarchy process (AHP), obtains the subjective weight w of each parameter according to comparator matrix Aj′；
(6b), using dispersion method, obtains the objective weight w of each parameter according to parameter matrix Sj″；
(6c) is according to the subjective weight w of each parameterj' and objective weight wj" establish mathematical model of optimization：
S.t. alpha+beta=1,0≤α≤1,0≤β≤1
Wherein, m is the network number in VLC heterogeneous networks, and n is the number of parameters that considers when network selects, sijFor user The normalized value of j-th of parameter of i-th of network of detection, α are the distribution coefficient of subjective weight, and β is the distribution of objective weight Coefficient；
(6d) solves to above-mentioned mathematical model of optimization, obtains the distribution coefficient α and objective weight of subjective weight Distribution coefficient β, and the two distribution coefficients α and β is utilized, to the subjective weight w of each parameterj' and objective weight wj" it is weighted, Obtain the final weight w of each parameterj；
(7) user is according to the final weight w of each parameterjAnd parameter matrix S, using simple additive weight, obtain each network Fractional value Gi；
(8) fractional value highest network is selected from the fractional value of each network, the network is indoor VLC heterogeneous networks In optimal network.
The present invention has advantages below compared with prior art：
1. the present invention is due to have selected many kinds of parameters as decision factor, and the real-time acquisition for considering network parameter is asked Topic, in selection course is accessed, both subjective demands of user from the point of view of customer service demand, and from network performance Angle considers objective parameter value difference, and considers the uniformity of subjective and objective scheme and the optimality of overall plan, builds Mathematical model of optimization has been found, has obtained the distribution coefficient of subjective demand and objective network performance, has effectively needed the business of user Ask and combine with the objective performance of network, can preferably solve user under VLC heterogeneous network environments indoors and network is selected Excellent problem, realize under heterogeneous network environment indoors, both considered customer service demand and network performance, and can is completed to net in real time The access selection of network, improve the QoS of user.
2. the present invention due on the basis of original beacon frame, added in frame bandwidth, average delay, handling capacity, These network information fields of average transmission rate, the bit error rate, the statistics and renewal that these fields can be by network cycle, use To indicate the status information of network in real time, by the design of this frame structure, beacon of the user according to periodic broadcast can be made Frame, various network parameters are obtained dynamically and in real time, and then user is obtained optimal net in real time according to current network conditions Network, and this frame does not influence the normal work of original frame, has compatibility.
Brief description of the drawings：
Fig. 1 be the present invention realize general flow chart；
Fig. 2 is improved beacon frame structure general structure schematic diagram in the present invention；
Fig. 3 is the sub-process figure for indoor heterogeneous network access selection in the present invention
Fig. 4 is according to the improved WiFi of IEEE 802.11b standards beacon frame frame structure schematic diagram in the present invention；
Fig. 5 is according to the improved VLC of IEEE 802.15.7 standards beacon frame frame structure schematic diagram in the present invention；
Fig. 6 is according to IrDA in the present invention:1.0 standards of Advanced Infrared (AIr)-Version are improved red Outer beacon frame frame structure schematic diagram；
Fig. 7 is the access comparative selection figure for using distinct methods in the present invention for same business demand；
Fig. 8 is the access comparative selection figure for using the inventive method in the present invention for different business demand；
Embodiment
The present invention is described in detail below in conjunction with the accompanying drawings：
Reference picture 1, step of realizing of the invention are：
Step 1, each existing beacon frame structure of network in indoor heterogeneous network is improved.
Each existing beacon frame structure of network includes three parts, frame head, frame and Frame Check Sequence, wherein：
Frame head, it is used to refer to the information such as protocol version, frame type, frame whereabouts and channel busy；
Frame, the information such as synchronizing information, frame transmission interval, network name are used to refer to, and the length of frame is variable；
Frame Check Sequence, for checking the integrality of the beacon frame received.
Although existing beacon frame can indicate the essential information of current network, can not reflect and work as by periodically broadcasting The actual performance of preceding network, and the real time status information of current network can not be indicated, such as bandwidth, time delay, handling capacity, therefore need Beacon frame is improved.
In order to not influence the normal work of original frame, ensure the compatibility of frame structure, the improved beacon frame structure of the present invention Realized on the basis of existing beacon frame.
Reference picture 2, the improved beacon frame structure of the present invention are bandwidth, the 4bytes for increasing 4bytes in existing frame Average delay, 4bytes handling capacity, 4bytes average transmission rate and 4bytes bit error rate field, these fields can lead to Beacon frame periodically renewal and broadcast is crossed, to indicate the status information of each network in real time；User is by receiving periodic broadcast Beacon frame, dynamic and various network parameters can be obtained in real time, and then optimal network be obtained according to network parameter in real time.Example Such as：
Improvement to WiFi IEEE 802.11b beacon frame be on the premise of frame head and Frame Check Sequence is not changed, Only bandwidth, the bit error rate, handling capacity, mean time are added in frame extends to average transmission rate field, as shown in figure 4,
Improvement to VLC IEEE 802.15.7 beacon frame, exactly adds band in the frame in super-frame beacon period Width, the bit error rate, handling capacity, mean time extend to average transmission rate field, as shown in Figure 5；
To infrared IrDA:The improvement of Advanced Infrared (AIr)-Version 1.0 beacon frame, is in frame In add bandwidth, the bit error rate, handling capacity, mean time and extend to average transmission rate field, as shown in Figure 6；
In the field that beacon frame frame after improvement newly adds, the definition of bandwidth, message transmission rate, the bit error rate refers to Existing definition and formula, here is omitted, and the calculation formula difference of handling capacity and average delay is as follows：
The calculation formula of handling capacity：
Wherein, header is mac frame frame head length, and Payload is the data packet length sent；Ptr、Ps、PN、PcRespectively Touched when user transmits the idle probability of the probability of packet, the probability of packet Successful transmissions, incoming end, user sends packet The probability hit, its calculation formula difference are as follows：
Ptr=1- (1- τ)n
PN=1-Ptr=(1- τ)n
Pc=Ptr(1-Ps)
N is user's number of current network connection in formula, and τ is the sending probability of each user data package；
The calculation formula of average delay：
In formula, K is the maximum times that user carries out data re-transmission, and p is the collision probability of user, and RTS is what user sent Request access frame frame length, Rate is uplink transmission rate, RateVLCFor descending VLC transmission rate, DIFS is between data frame Time interval, SIFS is most short interFrameGap, and ACK is respond request frame frame length, and header is mac frame frame head length, Payload is data packet length, E [U(j)] it is that user carries out the average backoff value that jth time is kept out of the way.
Step 2, user receives the beacon frame that each network is sent, and the heterogeneous network information of position is detected, according to user Demand and the parameter value received, it is strong to ask for bandwidth, average delay, handling capacity, average transmission rate, the bit error rate, reception signal Degree, the master of price these parameters, objective weight.
Multiple decision factors are typically considered in the existing heterogeneous network access selection method based on Multifactor Decision Making, are led to Multiple decision-making techniques are crossed to be ranked up multigroup scheme and preferentially, but do not account for the objective differences of each network parameter values with And the problems such as obtaining network parameter in real time, therefore need to be improved existing heterogeneous network access selection method.
Reference picture 3, the specific implementation step of this step are as follows：
(2a) user, with reference to own service demand, is inputted to bandwidth, mean time according to the heterogeneous network information detected Prolong, the setting value of handling capacity, average transmission rate, the bit error rate, received signal strength, price these parameters, build comparator matrix A：
Wherein, the number of parameters considered when n selects for network, xjiIt is important journey of j-th of parameter with respect to i-th of parameter Degree, xijFor the significance level of relative j-th of the parameter of i-th of parameter, its value determines according to Satty 1-9 numeric scales method, the party Method is that the relative importance of things is carried out into digital quantization scale, and its quantitative calibration value can refer to table 1,
Table 1Satty 1-9 significance level quantitative calibrations
Significance level scale value The significance level being compared to each other
1 Both no less importants
3 Compared with another element, the element is slightly important
5 Compared with another element, the element is substantially important
7 Compared with another element, the element is strongly important
9 Compared with another element, the element is extremely important
2,4,6,8 Represent the median of adjacent judgement
(2b), using analytic hierarchy process (AHP), obtains the subjective weight w of each parameter according to the comparator matrix A of structurej′：
(2b1) calculates eigenvalue of maximum λ in comparator matrix A by following formulamaxCorresponding characteristic vector w0：
Aw0=λmaxw0；
(2b2) is according to characteristic vector w0The subjective weight w of calculating parameterj′：
Wherein, the number of parameters considered when n selects for network, wj 0It is characterized vectorial w0The weight of middle j-th of parameter of correspondence Value；
(2c) user is according to the heterogeneous network information detected, using the parameter value in each networked beacons frame received, Build parameter matrix S；
Wherein, m is the network number in heterogeneous network, and n is the number of parameters that considers when network selects, skiFor heterogeneous network In k-th of network value of i-th of parameter after normalization, the benefit shape parameter being the bigger the better for value, it normalizes public Formula is：
For being worth the smaller the better cost shape parameter, its normalization formula is：
Wherein, bkiThe value of i-th of parameter of k-th of the network detected for user；
(2d), using dispersion method, obtains the objective weight w of each parameter according to parameter matrix Sj", calculation formula is：
Wherein, n is the number of parameters that considers when network selects, and m is the network number in heterogeneous network, sijFor heterogeneous network In i-th of network value of j-th of parameter after normalization.
Step 3：Mathematical model of optimization is established, is led, the distribution coefficient of objective weight, obtains final weight wj。
(3a) mathematical model of optimization：
The weighted results for considering to finally give both need the business demand for meeting user, need to meet objective internetworking again Can, i.e., final result should keep the uniformity of main, objective scheme, and the result of all schemes is the bigger the better, and establish following optimal Change mathematical modeling：
S.t. alpha+beta=1,0≤α≤1,0≤β≤1
Wherein, m is the network number in heterogeneous network, and n is the number of parameters that considers when network selects, sijDetected for user I-th of network j-th of parameter normalized value, α be subjective weight distribution coefficient, β be objective weight distribution coefficient；
(3b) solve to above-mentioned mathematical model of optimization 8, obtains the distribution coefficient α and objective weight of subjective weight Distribution coefficient β, and the two distribution coefficients α and β is utilized, to the subjective weight w of each parameterj' and objective weight wj" it is weighted, Obtain the final weight w of each parameterj, calculation formula is as follows：
wj=α wj′+βwj″。
Step 4：According to the final weight w of each parameterjAnd parameter matrix S, obtain the fractional value G of each networki。
Using simple additive weight, the fractional value G of each network is calculatedi：
Wherein, the number of parameters considered when n selects for network, wjFor the final weight of j-th of parameter, sijRepresent i-th Value of j-th of parameter after normalization in network.
Step 5：Fractional value highest network is selected in each network fractional value calculated from step 4, the network is room Optimal network in interior VLC heterogeneous networks.
The technique effect of the present invention can combine following emulation experiment, further illustrate：
1. simulated conditions：
Indoors under VLC heterogeneous network environments, the isomery of VLC, WiFi and infrared three kinds of networks is considered, it is determined that access selection When the parameter that considers have average transmission rate, bandwidth, average delay, handling capacity, the bit error rate, received signal strength, price, according to Existing WiFi parameters, operator's investigation result and VLC, infrared development trend, every ginseng of a certain moment heterogeneous network is set Number, as shown in table 1：
The parameters of a certain moment heterogeneous network of table 1
For session service, user both sides need to be linked up, and propagation delay time is excessive or received signal strength is too low all The service experience of user is influenced whether, therefore user is more strict to propagation delay time and signal strength requirement, and to data rate It is required that it is relatively low, and allow relatively low error code.
According to the demand of session service, the relative importance value of each parameter is set, as shown in table 2：
The relative importance of each parameter of the session service of table 2
For real-time audio/video stream class business, if the excessive or distortion that is delayed can seriously have a strong impact on the body of user Test, now user is higher to time delay (allowing short time time delay), bandwidth, the bit error rate, rate requirement, and price and system are handled up Amount requires relatively low.
According to the demand of stream class service, the relative importance value of each parameter is set, as shown in table 3：
The relative importance of each parameter of the stream class service of table 3
For background class traffic, it is desirable to the integrality of packet, and tend to the relatively low network of rate, it is to time delay, band Width, rate requirement are relatively low, higher to price and bit error rate requirement.
According to the demand of background class traffic, the relative importance value of each parameter is set, as shown in table 4：
The relative importance of each parameter of the background class traffic of table 4
2. emulation content and result：
Emulation 1, under identical session service demand, using of the invention and existing analytic hierarchy process (AHP) and average variance method Access selection is carried out to heterogeneous network, as a result such as Fig. 7.
As seen from Figure 7, indoors under VLC heterogeneous networks, for identical session service demand, using different networks Selection method carries out access selection, and at a time, the subjective weight of each parameter is constant, now according to the present invention, level Analytic approach and average variance method carry out access selection to network, and the fractional value of each network has larger difference, illustrates each network performance With otherness, when user by received beacon frame to update the real-time parameter value of network when, you can embody the present invention and enter in real time Row network of network preferentially the characteristics of；For session service, user both sides need to carry out real-time communication, and propagation delay time is excessive or connects The too low service experience that can all have influence on user of signal intensity is received, therefore user is more tight to propagation delay time and signal strength requirement Lattice, and it is relatively low to data rate requirement, and allow relatively low error code, and according to the parameter list of setting, WiFi in current heterogeneous network Signal preferably but time delay it is also larger, IR signal is worst but time delay is smaller, and VLC time delays are relatively low and signal is stronger, and other ginsengs Number otherness is larger, and with the inventive method, the optimal network that user finally selects is VLC, illustrates that the present invention both considers use The business demand at family, it is also considered that objective network performance, meet expected effect.
As can be seen from Figure 7, analytic hierarchy process (AHP) is always located in using the fractional value of the present invention and (meets customer service demand Subjective preferences) between average variance method (considering objective network performance), the result for illustrating the present invention is in comprehensive subjective use Family preference and objective network performance and draw, and tried one's best according to Optimized model and reduce otherness that is main, seeing scheme.
Emulation 2, under different conversation class, stream class and background class traffic demand, heterogeneous network is carried out using the present invention Access selection, the result for accessing selection are as shown in Figure 8.
From figure 8, it is seen that indoors under VLC heterogeneous networks, for different business demands, user is to parameters Preference value is different, i.e., the subjective weight of parameter is different under different business, and for same network, the visitor of network It is at a time constant to see performance, i.e. the objective weight of parameter is identical, using the present invention in same isomerous environment When being selected for different type of service progress networks down, result is different, it was demonstrated that the business of user needs in the present invention Ask and embodied.
To sum up, a kind of indoor heterogeneous network access selection method based on VLC proposed by the present invention, is based on existing MADM multifactor selection algorithm is compared, and have selected many kinds of parameters as decision factor, and is considered by the improvement of beacon frame The real-time of parameter obtains problem, this method both subjective demand of user from the point of view of customer service demand, and from net Objective parameter value difference from the point of view of network performance, and consider subjective and objective scheme uniformity and overall plan most Dominance, mathematical model of optimization is established, the business demand of user is effectively combined into progress with the objective performance of network Network is preferentially.

Claims (7)

  1. A kind of 1. indoor heterogeneous network access selection method based on VLC, it is characterised in that including：
    (1) each existing beacon frame structure of network in indoor heterogeneous network is improved：I.e. in the existing frame of each network Increase 4bytes bandwidth, 4bytes average delay, 4bytes handling capacity, 4bytes average transmission rate, 4bytes bit error rate field, to indicate the status information of each network in real time；
    (2) indoors under heterogeneous network environment, the broadcast of beacon interval period of each network in beacon frame each improves Beacon frame afterwards；
    (3) user receives the beacon frame that each network is sent, and detects the heterogeneous network information for present position of controlling oneself；
    (4) user, with reference to own service demand, inputs to bandwidth, average delay, handled up according to the heterogeneous network information detected Amount, average transmission rate, the bit error rate, received signal strength, the setting value of price these parameters, structure comparator matrix A；
    (5) user utilizes the parameter value in each networked beacons frame received, structure ginseng according to the heterogeneous network information detected Matrix number S；
    (6) user obtains bandwidth, average delay, handling capacity, average transmission rate, mistake according to comparator matrix A and parameter matrix S Code check, received signal strength, the final weight w of price these parametersj, j=1,2...7, w1, w2…w7Correspond to respectively above-mentioned each The final weight of parameter：
    (6a), using analytic hierarchy process (AHP), obtains the subjective weight w of each parameter according to comparator matrix Aj′；
    (6b), using dispersion method, obtains the objective weight w of each parameter according to parameter matrix Sj″；
    (6c) is according to the subjective weight w of each parameterj' and objective weight wj" establish mathematical model of optimization：
    <mrow> <mi>min</mi> <mi> </mi> <mi>F</mi> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <mo>{</mo> <msup> <mrow> <mo>(</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>&amp;alpha;s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <msup> <msub> <mi>w</mi> <mi>j</mi> </msub> <mo>&amp;prime;</mo> </msup> <mo>-</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>&amp;beta;s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <msup> <msub> <mi>w</mi> <mi>j</mi> </msub> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msup> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>}</mo> <mo>-</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mrow> <mo>(</mo> <msup> <msub> <mi>&amp;alpha;w</mi> <mi>j</mi> </msub> <mo>&amp;prime;</mo> </msup> <mo>+</mo> <msup> <msub> <mi>&amp;beta;w</mi> <mi>j</mi> </msub> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msup> <mo>)</mo> </mrow> </mrow>
    S.t. alpha+beta=1,0≤α≤1,0≤β≤1
    Wherein, m is the network number in VLC heterogeneous networks, and n is the number of parameters that considers when network selects, sijDetected for user I-th of network j-th of parameter normalized value, α be subjective weight distribution coefficient, β be objective weight distribution coefficient；
    (6d) solves to above-mentioned mathematical model of optimization, obtains distribution coefficient α and the distribution of objective weight of subjective weight Factor beta, and the two distribution coefficients α and β is utilized, to the subjective weight w of each parameterj' and objective weight wj" it is weighted, obtains The final weight w of each parameterj；
    (7) user is according to the final weight w of each parameterjAnd parameter matrix S, using simple additive weight, obtain the fractional value of each network Gi；
    (8) fractional value highest network is selected from the fractional value of each network, the network is in indoor VLC heterogeneous networks Optimal network.
  2. 2. according to the method for claim 1, it is characterised in that：The comparator matrix A of structure in step (4), is represented as follows：
    <mfenced open = "" close = ""> <mtable> <mtr> <mtd> <mrow> <mi>A</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>x</mi> <mn>11</mn> </msub> </mtd> <mtd> <msub> <mi>x</mi> <mn>12</mn> </msub> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>x</mi> <mrow> <mn>1</mn> <mi>n</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>x</mi> <mn>21</mn> </msub> </mtd> <mtd> <msub> <mi>x</mi> <mn>22</mn> </msub> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>x</mi> <mrow> <mn>2</mn> <mi>n</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>x</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> </mtd> <mtd> <mn>...</mn> </mtd> </mtr> <mtr> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>x</mi> <mrow> <mi>j</mi> <mi>i</mi> </mrow> </msub> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> </mtr> <mtr> <mtd> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mn>1</mn> </mrow> </msub> </mtd> <mtd> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mn>2</mn> </mrow> </msub> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>x</mi> <mrow> <mi>n</mi> <mi>n</mi> </mrow> </msub> </mtd> </mtr> </mtable> </mfenced> </mrow> </mtd> <mtd> <mrow> <msub> <mi>x</mi> <mrow> <mi>j</mi> <mi>i</mi> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mo>/</mo> <msub> <mi>x</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>,</mo> <msub> <mi>x</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>&amp;NotEqual;</mo> <mn>0</mn> </mrow> </mtd> </mtr> </mtable> </mfenced>
    Wherein, the number of parameters considered when n selects for network, xjiIt is significance level of j-th of parameter with respect to i-th of parameter, xij For the significance level of relative j-th of the parameter of i-th of parameter, its value determines according to Satty 1-9 numeric scales method.
  3. 3. according to the method for claim 1, it is characterised in that：The parameter matrix S of structure in step (5), is represented as follows：
    <mrow> <mi>S</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>s</mi> <mn>11</mn> </msub> </mtd> <mtd> <msub> <mi>s</mi> <mn>11</mn> </msub> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>s</mi> <mn>11</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>s</mi> <mn>21</mn> </msub> </mtd> <mtd> <msub> <mi>s</mi> <mn>22</mn> </msub> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>s</mi> <mrow> <mn>2</mn> <mi>n</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>s</mi> <mrow> <mi>k</mi> <mi>i</mi> </mrow> </msub> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> </mtr> <mtr> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> </mtr> <mtr> <mtd> <msub> <mi>s</mi> <mrow> <mi>m</mi> <mn>1</mn> </mrow> </msub> </mtd> <mtd> <msub> <mi>s</mi> <mrow> <mi>m</mi> <mn>2</mn> </mrow> </msub> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <mn>...</mn> </mtd> <mtd> <msub> <mi>s</mi> <mrow> <mi>m</mi> <mi>n</mi> </mrow> </msub> </mtd> </mtr> </mtable> </mfenced> </mrow>
    Wherein, m is the network number in heterogeneous network, and n is the number of parameters that considers when network selects, skiFor in heterogeneous network Value of i-th of the parameter of k network after normalization.
  4. 4. according to the method for claim 1, it is characterised in that：According to comparator matrix A in step (6a), using step analysis Method, obtain the subjective weight w of each parameterj', carry out as follows：
    (6a1) calculates eigenvalue of maximum λ in comparator matrix A by following formulamaxCorresponding characteristic vector w0：
    Aw0=λmaxw0；
    (6a2) is according to characteristic vector w0The subjective weight w of calculating parameterj′：
    <mrow> <msup> <msub> <mi>w</mi> <mi>j</mi> </msub> <mo>&amp;prime;</mo> </msup> <mo>=</mo> <mfrac> <mrow> <msup> <msub> <mi>w</mi> <mi>j</mi> </msub> <mn>0</mn> </msup> </mrow> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msup> <msub> <mi>w</mi> <mi>j</mi> </msub> <mn>0</mn> </msup> </mrow> </mfrac> </mrow>
    Wherein, the number of parameters considered when n selects for network, wj 0It is characterized vectorial w0The weighted value of middle j-th of parameter of correspondence.
  5. 5. according to the method for claim 1, it is characterised in that：According to parameter matrix S in step (6b), using standard deviation Method, obtain the objective weight w of each parameterj", calculated by equation below：
    <mfenced open = "" close = ""> <mtable> <mtr> <mtd> <mrow> <msup> <msub> <mi>w</mi> <mi>j</mi> </msub> <mrow> <mo>&amp;prime;</mo> <mo>&amp;prime;</mo> </mrow> </msup> <mo>=</mo> <mfrac> <msqrt> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>-</mo> <mfrac> <mn>1</mn> <mi>m</mi> </mfrac> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msqrt> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>-</mo> <mfrac> <mn>1</mn> <mi>m</mi> </mfrac> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> </mrow> </mfrac> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2...</mn> <mi>m</mi> <mo>,</mo> </mrow> </mtd> <mtd> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2...</mn> <mi>n</mi> </mrow> </mtd> </mtr> </mtable> </mfenced>
    Wherein, n is the number of parameters that considers when network selects, and m is the network number in heterogeneous network, sijFor in heterogeneous network Value of j-th of the parameter of i network after normalization.
  6. 6. according to the method for claim 1, it is characterised in that：In step (6d) using and to each parameter with add Power, obtains the final weight w of each parameterj, calculated by equation below：
    wj=α wj′+βwj″,
    α is subjective weight distribution coefficient, β objective weight distribution coefficients, wj" it is objective weight, wj' it is subjective weight.
  7. 7. according to the method for claim 1, it is characterised in that：The fractional value G of each network is obtained in step (7)i, by such as Lower formula calculates：
    <mrow> <msub> <mi>G</mi> <mi>i</mi> </msub> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>w</mi> <mi>j</mi> </msub> <msub> <mi>s</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> </mrow>
    Wherein, the number of parameters considered when n selects for network, wjFor the final weight of j-th of parameter, sijRepresent i-th of network In value of j-th of parameter after normalization.
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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109150756A (en) * 2018-10-25 2019-01-04 重庆邮电大学 A kind of queue scheduling weight quantization method based on SDN power telecom network
CN109474338A (en) * 2019-01-22 2019-03-15 重庆邮电大学 A kind of interior VLC-WiFi hybrid communication system access selection method
CN109684689A (en) * 2018-12-12 2019-04-26 云南电网有限责任公司电力科学研究院 A kind of insulating gas comprehensive performance evaluation method of multi-parameter fusion
CN110493837A (en) * 2019-07-04 2019-11-22 西安理工大学 The method efficiently switched is realized in a kind of VLC/RF heterogeneous network
CN111510926A (en) * 2020-04-08 2020-08-07 中国农业大学 Visible light communication and WiFi heterogeneous convergence network and resource scheduling method
CN113099406A (en) * 2021-04-09 2021-07-09 重庆邮电大学 Cross-layer resource allocation mechanism for service quality perception of indoor VLC-WiFi heterogeneous network
CN113328802A (en) * 2021-05-27 2021-08-31 北方工业大学 OCC-VLC heterogeneous networking system and operation method thereof
CN114630450A (en) * 2022-03-29 2022-06-14 江苏拓邮信息智能技术研究院有限公司 Industrial internet multichannel data uploading system

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080101318A1 (en) * 2006-10-31 2008-05-01 Pouya Taaghol Vertical handover composite quality measures
CN101951663A (en) * 2010-08-26 2011-01-19 湘潭大学 User-based multi-access network selection method being used under wireless heterogeneous network environment
CN102638870A (en) * 2012-03-27 2012-08-15 迈普通信技术股份有限公司 Method for selecting wireless heterogeneous network access
CN102781072A (en) * 2012-07-27 2012-11-14 南京邮电大学 Network selecting method based on multi-attribute decision-making and group decision-making
CN102791010A (en) * 2012-07-16 2012-11-21 北京邮电大学 Heterogeneous system vertical switching method based on dual channel
CN103874132A (en) * 2014-03-25 2014-06-18 北京工业大学 Heterogeneous wireless network access selection method based on users
CN104185248A (en) * 2014-02-19 2014-12-03 上海物联网有限公司 Hierarchy-based heterogeneous network joint access control method
CN105208624A (en) * 2015-08-27 2015-12-30 重庆邮电大学 Service-based multi-access network selection system and method in heterogeneous wireless network
CN105704741A (en) * 2014-12-12 2016-06-22 华北电力大学 Heterogeneous network access selection policy
CN107071841A (en) * 2017-03-02 2017-08-18 重庆邮电大学 The vertical handoff method optimized in heterogeneous network based on changeable weight

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20080101318A1 (en) * 2006-10-31 2008-05-01 Pouya Taaghol Vertical handover composite quality measures
CN101951663A (en) * 2010-08-26 2011-01-19 湘潭大学 User-based multi-access network selection method being used under wireless heterogeneous network environment
CN102638870A (en) * 2012-03-27 2012-08-15 迈普通信技术股份有限公司 Method for selecting wireless heterogeneous network access
CN102791010A (en) * 2012-07-16 2012-11-21 北京邮电大学 Heterogeneous system vertical switching method based on dual channel
CN102781072A (en) * 2012-07-27 2012-11-14 南京邮电大学 Network selecting method based on multi-attribute decision-making and group decision-making
CN104185248A (en) * 2014-02-19 2014-12-03 上海物联网有限公司 Hierarchy-based heterogeneous network joint access control method
CN103874132A (en) * 2014-03-25 2014-06-18 北京工业大学 Heterogeneous wireless network access selection method based on users
CN105704741A (en) * 2014-12-12 2016-06-22 华北电力大学 Heterogeneous network access selection policy
CN105208624A (en) * 2015-08-27 2015-12-30 重庆邮电大学 Service-based multi-access network selection system and method in heterogeneous wireless network
CN107071841A (en) * 2017-03-02 2017-08-18 重庆邮电大学 The vertical handoff method optimized in heterogeneous network based on changeable weight

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
徐龙: "基于多属性决策的异构无线网络选择算法研究", 《中国优秀硕士学位论文全文数据库》 *
麻少娟: "基于层次分析法和熵理论的网络选择算法", 《陕西科技大学学报》 *

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109150756A (en) * 2018-10-25 2019-01-04 重庆邮电大学 A kind of queue scheduling weight quantization method based on SDN power telecom network
CN109684689A (en) * 2018-12-12 2019-04-26 云南电网有限责任公司电力科学研究院 A kind of insulating gas comprehensive performance evaluation method of multi-parameter fusion
CN109474338A (en) * 2019-01-22 2019-03-15 重庆邮电大学 A kind of interior VLC-WiFi hybrid communication system access selection method
CN109474338B (en) * 2019-01-22 2021-05-28 重庆邮电大学 Access selection method for indoor VLC-WiFi hybrid communication system
CN110493837A (en) * 2019-07-04 2019-11-22 西安理工大学 The method efficiently switched is realized in a kind of VLC/RF heterogeneous network
CN110493837B (en) * 2019-07-04 2021-08-06 西安理工大学 Method for realizing efficient switching in VLC/RF heterogeneous network
CN111510926A (en) * 2020-04-08 2020-08-07 中国农业大学 Visible light communication and WiFi heterogeneous convergence network and resource scheduling method
CN113099406A (en) * 2021-04-09 2021-07-09 重庆邮电大学 Cross-layer resource allocation mechanism for service quality perception of indoor VLC-WiFi heterogeneous network
CN113099406B (en) * 2021-04-09 2022-04-19 重庆邮电大学 Cross-layer resource allocation method for indoor VLC-WiFi heterogeneous network service quality perception
CN113328802A (en) * 2021-05-27 2021-08-31 北方工业大学 OCC-VLC heterogeneous networking system and operation method thereof
CN113328802B (en) * 2021-05-27 2022-04-22 北方工业大学 OCC-VLC heterogeneous networking system
CN114630450A (en) * 2022-03-29 2022-06-14 江苏拓邮信息智能技术研究院有限公司 Industrial internet multichannel data uploading system

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