CN110191472A - A kind of destination channel access method based on improvement multi-Objective Chaotic PSO optimization - Google Patents

A kind of destination channel access method based on improvement multi-Objective Chaotic PSO optimization Download PDF

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CN110191472A
CN110191472A CN201910439379.9A CN201910439379A CN110191472A CN 110191472 A CN110191472 A CN 110191472A CN 201910439379 A CN201910439379 A CN 201910439379A CN 110191472 A CN110191472 A CN 110191472A
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CN110191472B (en
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朱家晟
赵知劲
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Hangzhou Dianzi University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/14—Spectrum sharing arrangements between different networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
    • H04W16/22—Traffic simulation tools or models
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0453—Resources in frequency domain, e.g. a carrier in FDMA
    • 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
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention discloses a kind of based on the destination channel access method for improving multi-Objective Chaotic PSO optimization.It first has to channel access sequential conversions be particle position, carries out correcting encoder after channel designator is encoded into discrete binary [0,1] sequence.Then it introduces " S " type function improvement inertia weight and successively decreases update mode to improve particle rapidity update method, it introduces " V " type function and updates particle position, time delay and channel capacity will be accumulated as objective function to determine non-domination solution according to the definition that Pareto is dominated and be added to external concentration.Selection globally optimal solution is concentrated from outside using adaptive mesh and it is carried out based on the chaos optimization for improving Tent mapping.When reaching maximum number of iterations, the solution in external collection is exported, each solution corresponds to a kind of destination channel access order, these solutions are all Pareto optimal solutions.Complexity of the present invention is lower, helps algorithmic statement, effectively jumps out locally optimal solution.

Description

A kind of destination channel access method based on improvement multi-Objective Chaotic PSO optimization
Technical field
It is the invention belongs to cognition wireless electrical domain in wirelessly communicating, in particular to a kind of using in conjunction with the more of chaotic motion Destination channel access method in the accumulation time delay of target PSO optimization and the destination channel access of channel capacity combined optimization.
Background technique
The high speed development of wireless communication technique and traditional static spectral method of salary distribution, the caused availability of frequency spectrum are low Problem, frequency spectrum resource are more nervous.Univ California-Berkeley finds that local 3GHz or less is frequently by spectrum measurement Section occupancy is 70%, and 3~4GHz frequency range utilization rate is 0.5%, and 4~5GHz frequency range is only 0.3%.
Cognitive radio (Cognitive Radio, CR), i.e. dynamic spectrum access (Dynamic Spectrum Access, DSA), Secondary Users (Secondary User, SU) perceived spectral in continually changing spectrum environment can be made Cavity simultaneously utilizes, and is a kind of autonomous, efficient, dynamic frequency spectrum use method, greatly improves the availability of frequency spectrum.The present invention For being wherein frequency spectrum handoff technique, i.e., when Secondary Users (Secondary User, SU) are occupying a certain channel, Present channel is forced off because channel performance is bad or primary user (Primary User, PU) arrives and perceived spectral is empty, connects Enter new channel to guarantee the process of Secondary Users' continuity.
The target that destination channel switches as user, performance will greatly influence systematic entirety energy.Currently, selection The foundation of destination channel sequence has following several: remaining free time longest, idle maximum probability, handover delay be most short, system Handling capacity is maximum, switching times are minimum, reduces energy consumption etc..
However existing method is mostly the angle Selection destination channel from single target, this is unilateral, incomplete , while there is the channel of longer free time and biggish channel capacity undoubtedly can preferably guarantee to communicate, rather than it is single The channel that performance is prominent, other performances are bad.On the other hand, spectrum space is continually changing, and early some studies pointed out that channel skies It is also possible to obeying other different distributions between idle, current most methods are all built upon hypothesis idle time of channel On the basis of obeying exponential distribution, this is also the insufficient of consideration.
Summary of the invention
The present invention is directed to the limitation of existing destination channel sequence design methodology, comprehensively considers based on idle time of channel Switching accumulation time delay and channel capacity in the hypothesis of Rayleigh distributed, this is a multi-objective problem, therefore proposes one kind Based on the destination channel access method for improving multi-Objective Chaotic PSO optimization, the accumulation time delay optimized using multi-Objective Chaotic PSO With the destination channel access method of channel capacity combined optimization, to take into account networked-induced delay and high-throughput demand.
The technical solution adopted by the present invention to solve the technical problems includes the following steps:
Step 1 establishes frequency spectrum handover optimization model；
Step 2 establishes destination channel access mechanism in frequency spectrum switching, obtains this kind of mechanism lower channel free time obedience When rayleigh distributed, handover delay and channel capacity function formula, and design object function；
Step 3, coding and initialization access time ordered pair particle position x using destination channel and encode, and initialize various Parameter calculates the target function value E [D] and-E of each particle using particle current location as the individual optimal solution p of particle [C] determines that non-domination solution is added in external collection Archive, selects the smallest particle of density as complete using adaptive mesh Office optimal solution g；
Step 4 updates individual speed v and position x with improved speed and location update formula, calculates each particle Target function value, i.e. handover delay and channel capacity；
Step 5, more new individual optimal value p determine non-domination solution, update external collection Archive and globally optimal solution g.
Globally optimal solution g is mapped to chaotic space from former solution space and is carried out by improved Tent mapping by step 6 Chaos iteration, then former solution space is returned into solution inverse mapping, dominance relation is judged with former globally optimal solution g and updates globally optimal solution g；
Step 7 repeats step 4- step 6, when reaching maximum number of iterations, exports non-dominant in external collection Archive Disaggregation (forward position PF) collects as a result.
The beneficial effects of the present invention are:
1, set forth herein one kind assuming that idle time of channel Rayleigh distributed on the basis of comprehensively consider accumulation switching The destination channel access method of time delay and efficient channel capacity two objects.This method can take into account networked-induced delay and height gulps down Rate is spat, there is validity and practicability.
2, it proposes improved multi-objective particle, reduces time complexity, ensure that the requirement of real-time.
3, coding, decoding process are redesigned, this method being capable of the selection as limited as possible while correcting repeated encoding Performance more preferably channel.
4, inertia weight more new formula is redesigned, the global search of the formula energy active balance algorithm and part are explored Ability avoids precocity.
5, location update formula is redesigned, which can update position in a manner of more reasonable, enhance algorithm optimizing Ability.
6, it proposes based on the chaos optimization for improving Tent mapping, helps algorithm more rapid convergence, and can effectively jump out office Portion's optimal solution.
Detailed description of the invention
Fig. 1 is frequency spectrum switching signal.
Specific embodiment
Implementation steps of the invention that the present invention is described in further detail below in conjunction with the accompanying drawings.
As shown in Figure 1, it is a kind of based on improve multi-Objective Chaotic PSO optimization destination channel access method, specifically include as Lower step:
Step 1 establishes frequency spectrum handover optimization model, specific as follows:
During cognitive user perceived spectral cavity, communicating pair is by shared frequency spectrum cavity-pocket information, to find common Frequency spectrum cavity-pocket, these frequency spectrum cavity-pockets are target idle channel, are denoted as ci, i ∈ { 1,2,3 ... M }, total M item.This M target letter Road progress will constitute M！Kind feasible solution.
User both sides shake hands channel is accessed after determining destination channel access sequence, adjusting parameter, required time For Tc；If because primary user arrive or other rise emergency case cause this shake hands unsuccessfully (do not consider channel status change twice or The multiple situation of person) it then attempts to access remaining destination channel with cycle T until success.When user both sides shake hands into certain channel Then this frequency spectrum switches successfully function；Conversely, still failed when having accessed all destination channels, then this frequency spectrum switching is lost It loses.
Step 2 establishes destination channel access mechanism in frequency spectrum switching, obtains this kind of mechanism lower channel free time obedience When rayleigh distributed, handover delay and channel capacity function formula, and design object function, it is specific as follows:
2-1. assumes idle time of channel Rayleigh distributed, idle time of channel probability density function are as follows:
T in formulaciIndicate channel ci, the mean down time of i ∈ { 1,2,3 ... M }.If user is in channel ciIt shakes hands Period has primary user's arrival or emergency case to will lead to failure, we are by user in channel ciOn the shake hands probability of failure be Pi, i ∈ { 1,2,3 ... M }, then PiIt is as follows:
Then user is in channel ciOn shake hands successful probability P 'iIt is as follows:
The then probability P of this frequency spectrum handover failure of userfIt is as follows:
Channel c is then successfully accessed after i times is shaken handsiProbability Ps{ r=i } is as follows:
2-2. handoff delay shake hands when mainly having handover success generation time delay and handover failure when be wasted in periodical visit The time delay for asking channel is collectively referred to as accumulative handover delay, therefore handover delay E [D] is as follows:
2-3. assumes that total bandwidth in a network is B, gives N number of channel, then the M target in frequency spectrum handoff procedure The band frame of channel is all B/N, channel ciSignal-to-noise ratio be SNRci.According to shannon formula, efficient channel capacity E [C] is as follows:
2-4. establishes following objective function:
Wherein c*=[c1,c2,…,cM] ∈ Ω expression optimum target channel access sequence.
Step 3, coding and initialization access time ordered pair particle position x using destination channel and encode, and initialize various Parameter, individual optimal solution p, globally optimal solution g and external collection Archive, specific as follows:
3-1., which is set, M channel in destination channel access sequence, then the collection of channel number is combined into Θ=[0,1,2 ..., M- 1]；Each channel number L=ceil (log2M) bit indicates, ceil expression rounds up, then each particle coding Dimension is d=LM.Since Initial Channel Assignment sequence is random in algorithm, it is thus possible to the channel duplicated, so needing Correcting encoder, the specific steps are as follows:
3-1-1. decoding: by i-th of particle position xi=(xi1,xi2,…,xid) with the progress decimal system decoding of every L bit Postorder is classified as zi=(zi1,zi2,…,ziM).Wherein zijBy xiIn (xi,(j-1)L+1,…,xi,jL) decode and acquire；
3-1-2. is by ziCompare with Θ=[0,1,2 ..., M-1], different elements are placed in set P
3-1-3.ziWhen 2 identical elements of middle appearance, the best element λ of selection performance from set PiTo substitute；
3-1-4. updates P=[P λi], and 3-1-3 and 3-1-4 is repeated until set P is empty set.
3-2. initializes particle rapidity v, obeys and is uniformly distributed on [Varmin, Varmax], usually enables Varmax=- Varmin=4.The initial position for defaulting particle is individual optimal value p, outside collection Archive=[], setting greatest iteration time Number I, enables t=1.
3-3. initial globally optimal solution g and individual optimal solution p, using the particle position of initialization and target function value as Individual optimal solution p judges the dominance relation between individual optimal solution, and non-domination solution is added in external collection Archive, is utilized Adaptive mesh selects the smallest particle of density as globally optimal solution g, and concrete mode is as follows:
3-3-1. is decoded according to the position of each particle and is obtained destination channel sequence access order, utilizes 2-2 and 2-3 points The target function value E [D] and-E [C] for not calculating each particle determine that non-domination solution is added in external collection Archive, non-branch It is defined as follows with solution:
Pareto dominates (Pareto Dominance): a channel disaggregation c=[c1,c2,…,cM] < c'=[c'1, c'2,…,c'M] (< indicate dominate) and if only if minE [D]≤minE'[D] ∧-E [C]≤- E'[C], otherwise, claim two solutions It does not dominate mutually.
3-3-2. calculates the boundary [min (E of grid in the t times iterationt(D)),max(Et(D))]、 [min(-Et(C)), max(-Et(C)) it], is divided into M × M small grid, each small grid is long and width is respectivelyWithThen i-th Grid where particle, which is numbered, isWhereinExpression takes upwards It is whole,.Then the population in each grid is counted, selects the smallest particle of density as g.
Step 4 updates individual speed v and position x with improved speed and location update formula, calculates each particle Target function value, i.e. handover delay and channel capacity, specific as follows:
4-1. updates individual speed v according to formula (9):
WhereinIndicate the value of the particle i speed that jth is tieed up in the t times iteration,Indicate particle i in the t times iteration The value of the position of middle jth dimension,Indicate the value of the position of the jth dimension of individual optimum point in the t times iteration particle i,Table Show the value of the position of the jth dimension of particle i globe optimum in the t times iteration, r1And r2Uniformly divide to be obeyed on [0,1] The stochastic variable of cloth is known as Studying factors, and w is inertia weight, will be improved to carry out update of successively decreasing according to formula (10).
4-2. is according to formula (11) and formula (12) more new individual position x:
After 4-3. more new individual position x, according to 3-1 correcting encoder, then decoding obtains destination channel access order, Finally calculate the handover delay E [D] and channel capacity-E [C] under this kind of sequence.
Step 5, more new individual optimal value p determine non-domination solution, update external collection Archive and globally optimal solution g, tool Body is as follows:
Two target function values for calculating particle, particle is currently solved and the p of last time compares, if current solution dominates p, is enabled Current solution is p, and otherwise p is remained unchanged.If the two does not dominate mutually, p is used as from random selection one between the two.Referring to 3- 3, update external collection Archive and globally optimal solution g.
Decoded globally optimal solution g is decoded and is passed through formula (13) and maps to chaotic space simultaneously from former solution space by step 6 Chaos iteration is carried out by improved Tent mapping formula (15) (16), then solution is returned into former solution space by formula (14) inverse mapping, with Former globally optimal solution g judges dominance relation and updates globally optimal solution g；
WhereinFor the chaos sequence variable of the t times iteration, t is chaos iteration number, K For maximum chaos iteration number,For globally optimal solution g after the iteration of the t times particle swarm algorithmtIt is obtained after binary decoding Destination channel sequence in m-th of channel number, αmAnd βmThe respectively variable desirable maximum value and minimum value,For Globally optimal solution after by k chaos iteration and completing inverse mappingThe corresponding reality of m-th of channel in destination channel sequence Value number, M are destination channel number.
Step 7 repeats step 4- step 6, when reaching maximum number of iterations, exports the non-dominant disaggregation that Archive is concentrated Collect as a result, specific as follows:
Judge whether t≤I is true, executes step 4- step 7 if setting up, utilize handover delay E [D] and channel capacity-E [C] is used as fitness function, instructs particle flight, finds optimal destination channel access order and is put into external collection Archive In, when reaching maximum number of iterations, output Archive concentrates non-domination solution.

Claims (8)

1. it is a kind of based on improve multi-Objective Chaotic PSO optimization destination channel access method, it is characterised in that this method include with Lower step:
Step 1 establishes frequency spectrum handover optimization model；
Step 2 establishes destination channel access mechanism in frequency spectrum switching, obtains this kind of mechanism lower channel free time obedience Rayleigh point When cloth, handover delay and channel capacity function formula, and design object function；
Step 3, coding and initialization access time ordered pair particle position x using destination channel and encode, and initialize various parameters, Using particle current location as the individual optimal solution p of particle, the target function value E [D] and-E [C] of each particle are calculated, is determined Non-domination solution is added in external collection Archive, selects the smallest particle of density as globally optimal solution using adaptive mesh g；
Step 4 updates individual speed v and position x with improved speed and location update formula, calculates the target letter of each particle Numerical value, i.e. handover delay and channel capacity；
Step 5, more new individual optimal value p determine non-domination solution, update external collection Archive and globally optimal solution g；
Globally optimal solution g is mapped to chaotic space from former solution space and is changed by improved Tent mapping progress chaos by step 6 Generation, then former solution space is returned into solution inverse mapping, dominance relation is judged with former globally optimal solution g and updates globally optimal solution g；
Step 7 repeats step 4- step 6, when reaching maximum number of iterations, exports the non-dominant disaggregation in external collection Archive (forward position PF) collects as a result.
2. it is according to claim 1 a kind of based on the destination channel access method for improving multi-Objective Chaotic PSO optimization, it is special Sign is to establish frequency spectrum handover optimization model described in step 1, specific as follows:
During cognitive user perceived spectral cavity, communicating pair is by shared frequency spectrum cavity-pocket information, to find common frequency spectrum Cavity, these frequency spectrum cavity-pockets are target idle channel, are denoted as ci, i ∈ { 1,2,3 ... M }, total M item；This M destination channel into It is about to that M can be constituted！Kind feasible solution；
User both sides shake hands channel is accessed after determining destination channel access sequence, adjusting parameter, required time Tc； If because primary user arrive or other rise emergency case cause this shake hands unsuccessfully, with cycle T attempt access remaining destination channel Until success；When user both sides certain channel shake hands successfully then this frequency spectrum handover success；Conversely, when having accessed all target letters Road is still failed, then this frequency spectrum handover failure.
3. it is according to claim 2 a kind of based on the destination channel access method for improving multi-Objective Chaotic PSO optimization, it is special It levies and is to establish destination channel access mechanism in frequency spectrum switching described in step 2, obtain this kind of mechanism lower channel free time clothes When from rayleigh distributed, handover delay and channel capacity function formula, and design object function, it is specific as follows:
2-1. assumes idle time of channel Rayleigh distributed, idle time of channel probability density function are as follows:
T in formulaciIndicate channel ci, the mean down time of i ∈ { 1,2,3 ... M }；If user is in channel ciHave during being shaken hands Primary user arrives or emergency case will lead to failure, we are by user in channel ciOn the shake hands probability of failure be Pi,i∈{1, 2,3 ... M }, then PiIt is as follows:
Then user is in channel ciOn shake hands successful probability Pi' it is as follows:
The then probability P of this frequency spectrum handover failure of userfIt is as follows:
Channel c is then successfully accessed after i times is shaken handsiProbability Ps{ r=i } is as follows:
2-2. handoff delay shake hands when mainly having handover success generation time delay and handover failure when be wasted in periodic access letter The time delay in road is collectively referred to as accumulative handover delay, therefore handover delay E [D] is as follows:
2-3. assumes that total bandwidth in a network is B, gives N number of channel, then M destination channel in frequency spectrum handoff procedure Band frame is all B/N, channel ciSignal-to-noise ratio beAccording to shannon formula, efficient channel capacity E [C] is as follows:
2-4. establishes following objective function:
Wherein c*=[c1, c2..., cM] ∈ Ω expression optimum target channel access sequence.
4. it is according to claim 3 a kind of based on the destination channel access method for improving multi-Objective Chaotic PSO optimization, it is special Sign is coding described in step 3 and initialization, accesses time ordered pair particle position x using destination channel and encodes, and initializes each Kind parameter, individual optimal solution p, globally optimal solution g and external collection Archive, specific as follows:
3-1., which is set, M channel in destination channel access sequence, then the collection of channel number is combined into Θ=[0,1,2 ..., M-1]；Often A channel number L=ceil (log2M) bit indicates, ceil expression rounds up, then the dimension of each particle coding is d =LM；Since Initial Channel Assignment sequence is random in algorithm, it is thus possible to which the channel duplicated is compiled so needing to correct Code, the specific steps are as follows:
3-1-1. decoding: by i-th of particle position xi=(xi1,xi2,…,xid) with sequence after the progress decimal system decoding of every L bit For zi=(zi1,zi2,…,ziM)；Wherein zijBy xiIn (xi,(j-1)L+1,…,xi,jL) decode and acquire；
3-1-2. is by ziCompare with Θ=[0,1,2 ..., M-1], different elements are placed in set P
3-1-3.ziWhen 2 identical elements of middle appearance, the best element λ of selection performance from set PiTo substitute；
3-1-4. updates P=[P λi], and 3-1-3 and 3-1-4 is repeated until set P is empty set；
3-2. initializes particle rapidity v, obeys and is uniformly distributed on [Varmin, Varmax], usually enables Varmax=-Varmin= 4；The initial position for defaulting particle is individual optimal value p, and outside collection Archive=[] is arranged maximum number of iterations I, enables t= 1；
3-3. initial globally optimal solution g and individual optimal solution p, most using the particle position of initialization and target function value as individual Excellent solution p, judges the dominance relation between individual optimal solution, and non-domination solution is added in external collection Archive, adaptive net is utilized Lattice select the smallest particle of density as globally optimal solution g, and concrete mode is as follows:
3-3-1. is decoded according to the position of each particle and is obtained destination channel sequence access order, counted respectively using 2-2 and 2-3 The target function value E [D] and-E [C] for calculating each particle determine that non-domination solution is added in external collection Archive, non-domination solution It is defined as follows:
Pareto is dominated: a channel disaggregation c=[c1,c2,…,cM] < c'=[c '1,c′2,…,c′M], < indicates to dominate；When And if only if minE [D]≤minE'[D] ∧-E [C]≤- E'[C], otherwise, two solutions is claimed not dominate mutually；
3-3-2. calculates the boundary [min (E of grid in the t times iterationt(D)),max(Et(D))]、[min(-Et(C)),max(-Et (C)) it], is divided into M × M small grid, each small grid is long and width is respectivelyWithThen i-th Grid where sub, which is numbered, isWhereinExpression rounds up,；So The population in each grid is counted afterwards, selects the smallest particle of density as g.
5. it is according to claim 4 a kind of based on the destination channel access method for improving multi-Objective Chaotic PSO optimization, it is special Sign is to calculate each particle described in step 4 with improved speed and location update formula update individual speed v and position x Target function value, i.e. handover delay and channel capacity, specific as follows:
4-1. decodes according to the position of each particle and obtains destination channel sequence access order, utilize step 2-2 and step 2-3 The target function value E [D] and-E [C] for calculating separately each particle, determine that non-domination solution is added in NP, the definition of non-domination solution It is as follows:
4-1. updates individual speed v according to formula (9):
WhereinIndicate the value of the particle i speed that jth is tieed up in the t times iteration,Indicate particle i jth in the t times iteration The value of the position of dimension,Indicate the value of the position of the jth dimension of individual optimum point in the t times iteration particle i,Indicate particle The value of the position of the jth dimension of i globe optimum in the t times iteration, r1And r2It is equally distributed random to be obeyed on [0,1] Variable is known as Studying factors, and w is inertia weight, will be improved to carry out update of successively decreasing according to formula (10)；
4-2. is according to formula (11) and formula (12) more new individual position x:
After 4-3. more new individual position x, according to 3-1 correcting encoder, then decoding obtains destination channel access order, finally counts Calculate the handover delay E [D] and channel capacity-E [C] under this kind of sequence.
6. according to claim 5 a kind of based on the destination channel access method for improving multiple target PSO optimization, feature exists More new individual optimal value p described in step 5 determines non-domination solution, updates external collection Archive and globally optimal solution g, specifically It is as follows:
Two target function values for calculating particle, particle is currently solved and the p of last time compares, if current solution dominates p, enables current solution For p, otherwise p is remained unchanged；If the two does not dominate mutually, p is used as from random selection one between the two；Referring to 3-3, update outer Portion collects Archive and globally optimal solution g.
7. according to claim 6 a kind of based on the destination channel access method for improving multiple target PSO optimization, feature exists Globally optimal solution g is subjected to chaos optimization by improved Tent mapping described in step 6, specific as follows:
Decoded globally optimal solution g is decoded and passes through formula (13) and maps to chaotic space from former solution space and passes through improved Tent maps formula (15) (16) and carries out chaos iteration, then solution is returned former solution space by formula (14) inverse mapping, with former global optimum Solution g judges dominance relation and updates globally optimal solution g；
WhereinFor the chaos sequence variable of the t times iteration, t is chaos iteration number, and K is most Big chaos iteration number,For globally optimal solution g after the iteration of the t times particle swarm algorithmtThe mesh obtained after binary decoding Mark the number of m-th of channel in channel sequence, αmAnd βmThe respectively variable desirable maximum value and minimum value,For by k Secondary chaos iteration simultaneously completes the globally optimal solution after inverse mappingThe corresponding real number value of m-th of channel is compiled in destination channel sequence Number, M is destination channel number.
8. according to claim 7 a kind of based on the destination channel access method for improving multiple target PSO optimization, feature exists The non-dominant disaggregation that output Archive described in step 7 is concentrated collects as a result, specific as follows:
Judge whether t≤I is true, executes step 4- step 7 if setting up, made using handover delay E [D] and channel capacity-E [C] For fitness function, particle flight is instructed, optimal destination channel access order is found and is put into external collection Archive, when reaching To maximum number of iterations, exports Archive and concentrate non-domination solution.
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