CN103561457B - A kind of multi-target networks power distribution method in heterogeneous wireless network collaboration communication - Google Patents
A kind of multi-target networks power distribution method in heterogeneous wireless network collaboration communication Download PDFInfo
- Publication number
- CN103561457B CN103561457B CN201310513423.9A CN201310513423A CN103561457B CN 103561457 B CN103561457 B CN 103561457B CN 201310513423 A CN201310513423 A CN 201310513423A CN 103561457 B CN103561457 B CN 103561457B
- Authority
- CN
- China
- Prior art keywords
- power
- gene
- population
- value
- fitness
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Abstract
The invention discloses the multi-target networks power distribution method in a kind of heterogeneous wireless network collaboration communication, comprises the following steps：Step 1, mobile intelligent terminal detect the accessible wireless network of available free Traffic Channel, and from accessible network, select the preferable wireless network of N number of channel condition to access；Step 2, the heredity expression for defining a kind of power allocation scheme；Step 3, the fitness function for defining power allocation scheme；Step 4, M array of generation；Step 5, according to the preferential method of high fitness value, randomly chooses m from population1Bar gene carries out genetic recombination；Probability random selection m is pressed in step 6, the population from after genetic recombination in the relatively low gene of fitness2Bar gene is mutated；Step 7, selection produce population of new generation；Step 8, repeat step 5～7, when the increasing continuous l time for highest fitness value of population gene is less than given threshold value as optimal power allocation scheme.Have the advantages that algorithm is flexible.
Description
Technical field
The present invention relates to a kind of wireless communication technology, the multiple target in more particularly to a kind of heterogeneous wireless network collaboration communication
Network power distribution method.
Background technology
Various heterogeneous wireless communication networks extensively coexist at present, the heterogeneous wireless network input business no less than 25 kinds
With, but each network work independently, it is internetwork it is seamless interconnection and making full use of for Internet resources become significant problem.As solution
The scheme of the problem, heterogeneous wireless network cooperative communication technology have obtained domestic and international great attention.Heterogeneous wireless network cooperation is logical
Letter technology can realize fusion access, collaborative work and internetwork seamless interconnection between heterogeneous network so that terminal can be with
Carried out data transmission using multiple different type networks simultaneously, so as to significantly improve network resource utilization and system communication energy
Power.
In heterogeneous wireless network cooperation communication system, intelligent mobile terminal is carried out using multiple different type networks simultaneously
Data transfer, also significantly increases the requirement to power consumption while higher transmission rates are obtained, and terminal is being obtained to the greatest extent
May high transfer rate while to consume alap power be a key issue, need to exist the power of terminal for this
Effectively and rationally distributed to reach on each transmission network while optimizing performance of both the transfer rate and power consumption of terminal
Purpose.
In wireless communications, had at present it is substantial amounts of researched and proposed the various methods with regard to power distribution, it is but existing
Power distribution method mainly for single standard network, single type business, with single performance indications as optimization aim, and
Calculate complicated, less efficient.Such as classical water flood is with maximum channel capacity as optimization aim, but calculates complicated, and
Power consumption this index can not be optimized.Publication No. CN102752840A, publication date are the patent of invention " on October 24th, 2012
Plant broadcast channel power distribution method ", there is provided a kind of gain signal to noise ratio according to each channel and each receiving terminal
Weights are the method that each receiving terminal distributes transmission power, although because need not solve water injection power level and iterative process
Algorithm complex, but the invention are reduced for the homogeneous network of single standard, and only with maximum system throughput is
Optimization aim, does not account for the optimization to power consumption performance.Publication No. CN101364823A, publication date are on 2 11st, 2009
Patent of invention " power distribution method in collaboration communication based on MCPA thresholdings ", employ a kind of average channel with source node
Power attenuation（MCPA）Come selecting collaboration node the scheme to the cooperative node mean allocation power chosen as threshold value, but
Homogeneous network of the invention for single standard, only with system break probability performance as optimization aim, and power is in selection
The optimization that the method for mean allocation causes that the utilization rate of power is not high, do not account for power consumption performance on cooperative node.Publication number
For CN101588627A, publication date is the patent of invention " power of source and via node in collaboration communication on November 25th, 2009
Thought of the optimal joint distribution method " based on water-filling algorithm, the invention equally only with maximum channel capacity as optimization aim, do not have
There is the optimization considered to power consumption performance.
Network, polytype business and multiple service quality due to being related to multiple types（quality of
service,QoS）Require, the power allocation requirement of heterogeneous wireless network cooperation communication system is with multiple performance indications to optimize mesh
Mark（And these optimization aims are often collided with each other）, it is existing mainly for single standard network, single type business, with list
Individual performance indications are no longer suitable for for the power distribution method of optimization aim.
The content of the invention
It is an object of the invention to overcome the shortcoming and deficiency of prior art, there is provided a kind of heterogeneous wireless network collaboration communication
In multi-target networks power distribution method, the method propose purpose be to cooperate with work in heterogeneous wireless network collaboration communication
The network of work provides simple, efficient multiple target power allocation scheme, with maximize intelligent mobile terminal channel capacity and
The optimization aim of the power as power allocation scheme of consumption needed for which is minimized, while the transmission speed of Intelligent Optimal mobile terminal
Performance of both rate and power consumption.
The purpose of the present invention is achieved through the following technical solutions：Multi-target networks work(in heterogeneous wireless network collaboration communication
Rate distribution method, comprises the following steps：
Step 1, mobile intelligent terminal detect the accessible wireless network of available free Traffic Channel in communication, and according to
Channel condition information selects the preferable wireless network of N number of channel condition to access from accessible network.
Step 2, the heredity expression for defining a kind of power allocation scheme.Containing the one-dimensional of N+1 element defined in the present invention
Real number array power is used as the heredity expression of power allocation scheme, and wherein N is the selected network of step 1（Channel）Quantity,
In power, value power [n] (n=1,2 ..., N) of nth elements represents that the program distributes to n-th network（Channel）Power
Value, value power [N+1] of last element is for depositing the fitness value of allocative decision.Thus, an array is just represented
A kind of power allocation scheme, and contain the fitness of the power allocation scheme.
Step 3, defines the fitness function of power allocation scheme.Consider the channel capacity summation of mobile intelligent terminal
CtotalAnd total power consumption P, using power consumption as punishment, construction shape is such asFitness function be used for count
Calculate the fitness value of each power allocation scheme.In fitness function, wnIt is the channel width of network n, PmaxIt is intelligent mobile terminal
Rated power, α>0,β>The concrete value of 0, α, β can according to intelligent mobile terminal in concrete scene to channel capacity with
And the specific requirement of power consumption is being adjusted.
Step 4, produce M step 2 described in array, each array represent respectively a kind of different power allocation scheme and
Its fitness value；This M array constitutes the first generation population of power allocation scheme together, and wherein M is referred to as the scale of population, population
In an array be referred to as a gene.
Step 5, according to the preferential method of high fitness value, randomly chooses m according to probability from population described in step 41(m1
For even number, 2≤m1≤ M) bar gene carries out genetic recombination.During genetic recombination, the gene of participation genetic recombination is selected not
Make any change and be retained in population；The legal gene that restructuring is generated adds population as new gene, and it is illegal that restructuring is generated
Gene is directly abandoned.
Step 6, the method according to most preferably keeping low fitness value preferential, in the population from after genetic recombination described in step 5
Probability random selection m is pressed in the relatively low gene of fitness2（1≤m2≤M2）Bar gene is mutated, and mutation method is：For choosing
In gene power to be mutatedk, certain several element is randomly choosed in its top n element its value is increased with adaptive probability
Add deduct step-length P of little fixationΔ, and recalculate powerkFitness value be filled into its last bit element；Judge mutation
Power afterwardskWhether legal, if legal, population retains the power after mutationk, otherwise reject.
Step 7, chooses and produces population of new generation, the method for defining a kind of optimum selection for keeping population of new generation here,
The gene families for keeping new in scale are consistent with original gene families（Gene scale remains M）, choosing construction novel species
By before fitness value highest in the population after gene mutation described in step 6 during the gene of groupIndividual gene is directly chosen new
Population in, chosen with roulette method in remaining geneIndividual gene is in new population.
Step 8, repeat step 5～7.When the growth of the highest fitness value of population gene is less than the threshold for giving for continuous l time
Value then thinks that optimal power allocation scheme occurs, chooses fitness highest gene as power distribution from the population for obtaining
Scheme, power distribution algorithm terminate.
In step 1, the present invention considers that N number of network that intelligent mobile terminal is accessed provides only a pair of Traffic Channels（Before
To Traffic Channel and reverse traffic channel）Also represent for intelligent mobile terminal transmission data, therefore heretofore described channel n
Network n.
In step 1, the noise statisticses of described channel condition information channel are represented, intelligent mobile terminal is selectedN number of channel as channel to be used, set up with map network by these channels and be connected, whereinIt is network
The noise variance of the Traffic Channel provided by n,It is the interchannel noise threshold value required by network n proper communications.
In step 2, described fitness value is the value of the F in step 3, and it is the power allocation scheme defined in invention
The score of performances evaluation standard, certain concrete power allocation scheme, the higher scheme of score are more excellent.
In step 3, CtotalRefer to that intelligent mobile terminal can be obtained channel capacity summation, by
It is determined that.P refers to the total power consumption of intelligent mobile terminal, byIt is determined that.
In step 3, described α, the selection of β value directly influence the result of final power allocation scheme.Using the party
When method carries out power distribution, can by specific situation of the intelligent mobile terminal user according to residing for oneself, to message transmission rate with
And the specific requirement of power consumption, setting α, the occurrence of β is such as more partial to fast transfer rate when energy is sufficient, can be increased
The ratio of α and β；The ratio of α and β can be reduced when business is relatively low to data transmission rates demands.
In step 4, the generation of described array mainly has following steps：
Step 4.1, the top n element of array is with 0～PmaxIn the range of random number filling；Once the top n unit of array
Element meetsOrThen cast out the array, regenerate new array.
Step 4.2, last element of the N+1 element of array, i.e. array is with representated by array top n element
The fitness value filling of power allocation scheme；Fitness value is calculated using the fitness function defined in step 3；
In step 4, described population scale size, the i.e. value of M are weighed with performance synthesis by the complexity of algorithm and are determined, M
Bigger, the precision of algorithm is higher, but complexity is also higher；M is less, and the precision of algorithm is lower, but complexity is also lower.
In step 5, described high fitness value preferentially refers to that fitness is higher, and gene is chosen to participate in the probability of restructuring and gets over
Greatly, fitness value for the probability that the gene of F is chosen to participate in restructuring isWherein FmaxFor all genes in population
The maximum of fitness value；Participate in the gene dosage m of restructuring1For random number, depending on probability f1。
In step 5, described genetic recombination mainly has the following steps：
Step 5.1, participates in the gene power of restructuring for twoi、powerj(1≤i, j≤M), defines step 2 institute
The new array stated, is denoted as powerij；
Step 5.2, from poweri、powerjOne gene of middle random selection, and it is random from the top n element of the gene
Selected part element, its value is filled to powerijThe element of middle correspondence position, powerijIn in addition to the N+1 element remaining
Unfilled element is by poweri、powerjIn the unit of another gene correspondence position usually fill；
Step 5.3, calculates powerijThe fitness of the power allocation scheme representated by top n element, and by fitness value
Fill to powerijThe N+1 element；
Step 5.4, judges powerijIt is whether legal, the power if legalijPopulation is added as new gene；If not
Method, then directly abandon；
In step 5, described illegal gene refers to the gene with following any feature：（1）, to n-th network point
The power power [n] for matching somebody with somebody causes the value of signal to noise ratio to be less than the threshold value of signal to noise ratio required during such network proper communication,
（2）、Or
In step 6, the low adaptive value mode of priority of described most preferably holding, specially for fitness value highest in population
BeforeIndividual gene keeps constant, for remaining gene is with probability f2Participate in gene mutation, f2It is defined asWherein
FminFor the minimum of a value of the fitness value of all genes in population.
In step 6, the method that element value is increasedd or decreased with adaptive probability in the gene is specifically, treat for choosing
The element value of mutation is according to probability f3Increase PΔ, with probability 1-f3Reduce PΔ.Wherein, for selected mutation element power [n],
Define whichPΔValue weighed by complexity and the performance synthesis of algorithm and determine, PΔLess algorithm
Precision is higher, but convergence of algorithm speed is also slower；PΔBigger arithmetic accuracy is lower, but convergence rate is faster.
In step 8, by default, threshold value is less, l values are bigger, the essence of power distribution algorithm for the value of described threshold value and l
Degree performance is better, but the complexity of algorithm is also higher.
The present invention is had the following advantages relative to prior art and effect：
1st, the present invention passes through different type net simultaneously for intelligent mobile terminal in heterogeneous wireless network cooperation communication system
The scene of network transceiving data, using the power distribution method based on genetic algorithm to different access networks distribution power, can make
Intelligent mobile terminal consumes relatively low power while higher transmission rates are obtained, and imitates so as to effectively improve utilizing for power
Rate；
2nd, method proposed by the present invention is based on genetic algorithm, and process is simple, does not have the mathematical analysis process of complexity, it is easy to real
Border operates and can be while two important indicator of channel capacity and power consumption of Intelligent Optimal mobile terminal.
3rd, in the present invention, the fitness function form that constructs is simple, and partial parameters can by user according in different scenes not
It is adjusted with demand, improves the flexibility of algorithm；
4th, the power distribution heredity for constructing in the present invention represents the part that fitness value is represented as heredity, is conducive to
Improvement is made in behavior of the adaptability of convenient reference gene to each step in each step of genetic algorithm；
5th, the present invention is adopted during genetic recombination the high-adaptability mode of priority, adopt during gene mutation
It is optimum to keep low adaptive value preferential and prominent nyctitropic method is determined and in population of new generation is chosen with adaptive probability
Using the optimum method for keeping, take the ergodic of genetic algorithm into account while improve the convergence rate of genetic algorithm.
Description of the drawings
Fig. 1 multi-target networks power distribution method flow charts.
Fig. 2 heterogeneous wireless networks cooperative communication network selects to access schematic diagram.
Fig. 3 heterogeneous wireless network collaboration communication power distributions and operation principle schematic diagram.
Specific embodiment
With reference to embodiment and accompanying drawing, the present invention is described in further detail, but embodiments of the present invention are not limited
In this.
Embodiment
The implementation process of the present invention mainly includes two big parts, selects network to be accessed（That is Network access control）
Power distribution is carried out with to these networks.The core process of whole power allocation procedure is as shown in Figure 1.
In this embodiment, we define the Network access control side of heterogeneous wireless network collaboration communication as shown in Figure 2
Formula, and power distribution as shown in Figure 3 and data mode.
In the present embodiment, Access Control realizes that step is as follows：
Step 1, heterogeneous wireless network as shown in Figure 2, intelligent radio access point（AP）It is special to the channel statistical of each network
Property carries out real-time monitoring.
Step 2, transmitting terminal shown in Fig. 2（Intelligent mobile terminal）When needing to send information by network, first to intelligence
The statistical property of each network channel is passed by the statistical property of each network channel of energy AP acquisition requests, intelligent AP by Zigbee protocol
Give intelligent mobile terminal.
Step 3, after transmitting terminal receives the channel statistical information of each network that intelligent AP sends, determines which network chosen
Carry out data transmission.Assume in this embodiment by the information that intelligence AP sends, transmitting terminal has learnt that K network is free idle channel,
Its noise variance is respectivelyNoise gate required by each network proper communication is respectively
And assume wherein to meetNetwork have 4, transmitting terminal selects this 4 network insertions, sets up 4 channels of connection
Noise variance is respectively
The process that power distribution is carried out to 4 networks selected is as follows：
Step 1, defines one-dimensional real number array power containing 5 elements and is used as to each network（Channel）Carry out power
The heredity expression of distribution, (n=1,2,3, distribute to net in 4) representing the program to value power [n] of the nth elements in power
Network（Channel）The performance number of n, value power [5] of last element is for depositing the fitness value of the power allocation scheme.
Step 2, defines the fitness function of power allocation schemeWherein, wnIt is network n
Channel width, PmaxIt is the rated power of intelligent mobile terminal,It is intelligent mobile end
End can be obtained channel capacity summation,It is the total power consumption of intelligent mobile terminal.In this embodiment, for
Total channel capacity gives equal attention with power consumption, therefore the value of α, β is equal, makes α=1, β=1.
Step 3, produces the array of the expression power allocation scheme described in step 1, is broadly divided into following steps：
Step 3.1, in this embodiment, usesFirst four of array described in the random number filling step 1 of scope
Element power [1], power [2], power [3], power [4], checkWhether P is less thanmaxIf being unsatisfactory for this
Condition then abandons the array, and fills front four elements in array with random number again, until meeting
Step 3.2, calculates fitness value with the fitness function described in step 2 and is inserted the 5th element of array
power[5]。
Array power produced by step 3 is a kind of heredity expression of power allocation scheme, and the array is referred to as gene,
Wherein power [1], power [2], power [3], power [4] correspond respectively to the power for four access network distribution,
Power [5] is the fitness value of the gene.
Step 4, produces the population of power allocation scheme.Using the method described in step 3, produce M and represent power distribution
The gene power of scheme and its fitness value1,power2,...,powerM, these genes constitute together and represent power distribution side
The population of case, in population, number M of gene is referred to as population scale, sets population scale as M=100 in the present embodiment.
Step 5, to population described in step 4, according to the preferential method of high fitness, therefrom randomly chooses gene by probability and enters
Row restructuring；In regrouping process, the gene for participating in restructuring keeps constant and is retained in population；It is new legal that restructuring is generated
Gene adds population, illegal gene to abandon.The concrete grammar of genetic recombination is broadly divided into following steps：
Step 5.1, to population described in step 4 in i-th gene poweri, withProbability by poweriChoosing
For recombination to be participated in, wherein Fmax=max(power1[5],power2[5],...,power100[5])；
Step 5.2, for two genes poweri, power being chosen as participating in recombinatingj(1≤i, j≤100), define one
New array described in individual step 1, is denoted as powerij；
Step 5.3, from poweri、powerjOne gene of middle random selection, and it is random from front 4 elements of the gene
Choose L element（The element of half, i.e. L=2 are chosen in the present embodiment）, its value is filled to powerijThe unit of middle correspondence position
Element, powerijIn remaining unfilled element in addition to the 5th element by poweri、powerjIn another gene pairs should
The unit of position usually fills；
Step 5.4, calculates powerijThe fitness of the power allocation scheme representated by front 4 elements, and by fitness value
Fill to powerijThe 5th element；
Step 5.5, judges powerijIt is whether legal, the power if legalijPopulation is added as new gene；If not
Method, then directly abandon；
In step 5, described illegal gene refers to the gene with following any feature：（1）To n-th network allocation
Power power [n] required signal to noise ratios when causing the value of signal to noise ratio to be less than network n proper communications threshold value,
Step 6, to the population after genetic recombination described in step 5, according to the low fitness value mode of priority is most preferably kept, by general
Rate therefrom randomly chooses gene and is mutated, if the illegal gene described in the gene step 5 after mutation, then abandon.Gene is dashed forward
The concrete grammar of change mainly has following steps：
Step 6.1, to population in all genes sorted by fitness value from high to low, keep front 50 genes constant；
For remaining gene, gene power thereiniWithProbability elect as and treat mutator, wherein Fmin=min
(power1[5],power2[5],......,powerM1[5]), M1 is the scale of the population after genetic recombination described in step 5.
Step 6.2, it is selected in step 6.1 to treat mutator poweriN-th（1≤n≤4）Individual element, with
ProbabilityBy poweri[n] is updated toWith probabilityWill
poweri[n] is updated to
Step 7, chooses in the population from after gene mutation described in step 6 and produces population of new generation, mainly have following steps：
Step 7.1, to the population after gene mutation described in step 6, gene is sorted from high to low by fitness value, that is, is pressed
poweri[5]（1≤i≤M1）Value sort from high to low；
Step 7.2, to sorting described in step 7.1 after gene families, choose front 50 genes as a new generation population
Half gene, and with the system of selection of roulette choose from remaining M1-50 gene 50 genes as a new generation kind
Second half gene of group, abandons remaining gene for not being selected into population of new generation.So the scale of a new generation population is still 100,
In population of new generation, the maximum of the fitness value of all genes is designated as
In step 7.2, the system of selection of roulette is specially：For remaining M1-50 gene, wherein gene powerj
The selected probability as population gene of new generation isWherein powertotal_rest[5] it is this M1-50 base
The fitness value summation of cause.
Step 8, repeat step 5,6,7, when continuous ten generations populationGrowth when being less than 5%, power point
Terminate with algorithm.NowThe gene at place（It is labeled as power*）Final power allocation scheme is represented, is docked
Four networks chosen in entering control process（Channel）The power of distribution is respectively power*[1],power*[2],power*[3],
power*[4]。
Above-described embodiment is the present invention preferably embodiment, but embodiments of the present invention not by above-described embodiment
Limit, other any Spirit Essences without departing from the present invention and the change, modification, replacement made under principle, combine, simplification,
Equivalent substitute mode is should be, is included within protection scope of the present invention.
Claims (10)
1. the multi-target networks power distribution method in a kind of heterogeneous wireless network collaboration communication, it is characterised in that including following
Step：
Step 1, mobile intelligent terminal detect the accessible wireless network of available free Traffic Channel in communication, and according to channel
Status information selects N number of wireless network to access from accessible network；
Step 2, the heredity expression for defining a kind of power allocation scheme；Define one-dimensional real number array power containing N+1 element
It is used as the heredity expression of power allocation scheme, wherein N is the selected network of step 1 i.e. channel quantity, n-th in power
Value power [n] of element represents that the program distributes to the n-th network i.e. performance number of channel, n=1,2 ..., N, last
Value power [N+1] of element is for depositing the fitness value of allocative decision；
Step 3, the fitness function for defining power allocation scheme；Consider channel capacity summation C of mobile intelligent terminaltotal
And total power consumption P, using power consumption as punishment, construction shape is such asFitness function be used for calculating each
The fitness value of power allocation scheme；In fitness function, wnIt is the channel width of network n, PmaxIt is the volume of intelligent mobile terminal
Determine power, α>0,β>The concrete value of 0, α, β can according to intelligent mobile terminal in concrete scene to channel capacity and work(
The specific requirement of consumption is being adjusted；
Array described in step 4, M step 2 of generation, each array represent a kind of different power allocation scheme respectively and its fit
Answer angle value；M array constitutes the first generation population of power allocation scheme together, and wherein M is referred to as the scale of population, in population
Individual array is referred to as a gene；
Step 5, according to the preferential method of high fitness value, m is randomly choosed from population described in step 4 according to probability1Bar gene enters
Row genetic recombination；During genetic recombination, the gene for being selected participation genetic recombination is not made any change and is retained in population；
The legal gene that restructuring is generated adds population as new gene, and the illegal gene for generating of recombinating directly is abandoned；The m1For even number,
The m1Span be 2≤m1≤M；
Step 6, the method according to most preferably keeping low fitness value preferential, adapt in the population from after genetic recombination described in step 5
Probability random selection m is pressed in the relatively low gene of degree2Bar gene is mutated；
Step 7, selection produce population of new generation, define a kind of optimum method for choosing population of new generation for keeping here, on rule
The gene families for keeping new on mould are consistent with original gene families, and gene scale remains M, choosing construction new population
By before fitness value highest in the population after gene mutation described in step 6 during geneIndividual gene directly chooses new kind
In group, chosen with roulette method in remaining geneIndividual gene is in new population；
Step 8, repeat step 5～7, make when the growth of the highest fitness value of population gene is less than given threshold value continuous l time
For optimal power allocation scheme, fitness highest gene is chosen from the population for obtaining as power allocation scheme, power point
Terminate with algorithm.
2. the multi-target networks power distribution method in heterogeneous wireless network collaboration communication according to claim 1, which is special
Levy and be, in the step 1, N number of network that the intelligent mobile terminal is accessed provides only a pair of Traffic Channels for intelligence
Mobile terminal transmission data, described channel n also represent network n, the pair of Traffic Channel include forward traffic channel with
Reverse traffic channel；
The noise statisticses of described channel condition information channel represent that intelligent mobile terminal is selectedIt is N number of
Channel is set up with map network by these channels and is connected as channel to be used, wherein,It is industry that network n is provided
The noise variance of business channel,It is the interchannel noise threshold value required by network n proper communications.
3. the multi-target networks power distribution method in heterogeneous wireless network collaboration communication according to claim 1, which is special
Levy and be, in the step 2, described fitness value is the performances evaluation standard of power allocation scheme, i.e.,：Power allocation scheme
Score.
4. the multi-target networks power distribution method in heterogeneous wireless network collaboration communication according to claim 1, it is characterised in that
In the step 3, CtotalRefer to that intelligent mobile terminal can be obtained channel capacity summation, byReally
Fixed, P refers to the total power consumption of intelligent mobile terminal, byIt is determined that；
The α, the selection of β value directly influence the result of final power allocation scheme, are carrying out power distribution using the method
When, the specific situation by intelligent mobile terminal user according to residing for oneself, the specific requirement to message transmission rate and power consumption
To set α, the occurrence of β when the fast transfer rate of the sufficient deflection of energy, then increases the ratio of α and β；When business is to data
When transmission rate request is low, then reduce the ratio of α and β.
5. the multi-target networks power distribution method in heterogeneous wireless network collaboration communication according to claim 1, which is special
Levy and be, in the step 4, the generation of described array is comprised the following steps：
Step 4.1, the top n element of array are with 0～PmaxIn the range of random number filling；Once the top n element of array is full
FootOrThen cast out the array, regenerate new array；
Power of last element of the N+1 element of step 4.2, array, i.e. array representated by array top n element
The fitness value filling of allocative decision, fitness value are calculated using the fitness function defined in step 3.
6. the multi-target networks power distribution method in heterogeneous wireless network collaboration communication according to claim 1, which is special
Levy and be, in the step 4, described population scale size, the i.e. value of M weigh true with performance synthesis by the complexity of algorithm
Fixed, M is bigger, represents that the precision and complexity of algorithm is higher；M is less, represents that the precision and complexity of algorithm is lower.
7. the multi-target networks power distribution method in heterogeneous wireless network collaboration communication according to claim 1, which is special
Levy and be, in the step 5, described high fitness value preferentially refers to that fitness is higher, gene is chosen to participate in the general of restructuring
Rate is bigger, and fitness value for the probability that the gene of F is chosen to participate in restructuring isWherein, FmaxFor all bases in population
The maximum of the fitness value of cause；Participate in the gene dosage m of restructuring1For random number, depending on probability f1；
Described genetic recombination comprises the steps：
Step 5.1, the gene power for two being participated in restructuringi、powerj, wherein, the span of i is：1≤i≤M, j
Span be：1≤j≤M, defines the new array described in a step 2, is denoted as powerij；
Step 5.2, from poweri、powerjOne gene of middle random selection, and randomly select from the top n element of the gene
Partial Elements, its value is filled to powerijThe element of middle correspondence position, powerijIn in addition to the N+1 element, remaining is not filled out
The element for filling is by poweri、powerjIn the unit of another gene correspondence position usually fill；
Step 5.3, calculating powerijThe fitness of the power allocation scheme representated by top n element, and fitness value is filled
To powerijThe N+1 element；
Step 5.4, judge powerijIt is whether legal, if legal, powerijPopulation is added as new gene；Otherwise directly lose
Abandon.
8. the multi-target networks power distribution method in heterogeneous wireless network collaboration communication according to claim 1, which is special
Levy and be, in the step 5, described illegal gene refers to the gene with the feature in following (1) or in (2)：(1) it is right
The power power [n] of n-th network allocation causes the value of signal to noise ratio to be less than signal to noise ratio required during such network proper communication
Threshold value, (2)Or
9. the multi-target networks power distribution method in heterogeneous wireless network collaboration communication according to claim 1, which is special
Levy and be, in the step 6, the low adaptive value mode of priority of described most preferably holding, specially in population fitness value is most
Before highIndividual gene keeps constant, for remaining gene is with probability f2Participate in gene mutation, f2It is defined asIts
In, FminFor the minimum of a value of the fitness value of all genes in population；
Element value is increasedd or decreased with adaptive probability in the gene method is specifically, for choosing element to be mutated
Value is according to probability f3Increase PΔ, with probability 1-f3Reduce PΔ；Wherein, for selected mutation element power [n], define whichPΔValue weighed by complexity and the performance synthesis of algorithm and determine, PΔThe precision of less algorithm is more
Height, but convergence of algorithm speed is also slower；PΔBigger arithmetic accuracy is lower, but convergence rate is faster；
The mutation method is：For the gene power to be mutated for choosingk, it is several certain to be randomly choosed in its top n element
Its value is increasedd or decreased fixed step-length P with adaptive probability by elementΔ, and recalculate powerkFitness value be filled into
Its last bit element；Judge the power after mutationkWhether legal, if legal, population retains the power after mutationk, it is no
Then reject；The m2Span be 1≤m2≤M/2。
10. the multi-target networks power distribution method in heterogeneous wireless network collaboration communication according to claim 1, which is special
Levy and be, in the step 8, by default, threshold value is less, and l values are bigger for the value of described threshold value and l, represents power distribution
The precision property of algorithm is better, algorithm complexity is higher.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310513423.9A CN103561457B (en) | 2013-10-25 | 2013-10-25 | A kind of multi-target networks power distribution method in heterogeneous wireless network collaboration communication |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310513423.9A CN103561457B (en) | 2013-10-25 | 2013-10-25 | A kind of multi-target networks power distribution method in heterogeneous wireless network collaboration communication |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103561457A CN103561457A (en) | 2014-02-05 |
| CN103561457B true CN103561457B (en) | 2017-04-05 |
Family
ID=50015563
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310513423.9A Expired - Fee Related CN103561457B (en) | 2013-10-25 | 2013-10-25 | A kind of multi-target networks power distribution method in heterogeneous wireless network collaboration communication |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103561457B (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105611635B (en) * | 2015-12-18 | 2019-01-18 | 华南理工大学 | A kind of multi-target networks power distribution method in heterogeneous wireless network collaboration communication |
| CN105848293B (en) * | 2016-03-17 | 2019-05-21 | 南京邮电大学 | Collaboration power optimum allocation method in heterogeneous wireless network |
| CN105792378B (en) * | 2016-04-19 | 2019-02-19 | 重庆电子工程职业学院 | Virtual resource multiple target mapping method based on Wireless Heterogeneous Networks |
| CN108521666B (en) * | 2018-03-14 | 2020-06-19 | 华南理工大学 | Multi-relay system dynamic power distribution method based on nonlinear energy acquisition model |
| CN113098642B (en) * | 2021-04-22 | 2023-05-09 | 浙江万里学院 | Logistics management method based on Beidou satellite positioning technology |
| CN114363996B (en) * | 2022-01-19 | 2022-08-26 | 东北电力大学 | Heterogeneous wireless network service access control method and device based on multiple targets |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102892188A (en) * | 2012-10-09 | 2013-01-23 | 中兴通讯股份有限公司 | Uplink power control method and device based on genetic algorithm in communication network |
| CN103347299A (en) * | 2013-06-07 | 2013-10-09 | 北京邮电大学 | Centralized resource management method based on genetic algorithm |
-
2013
- 2013-10-25 CN CN201310513423.9A patent/CN103561457B/en not_active Expired - Fee Related
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102892188A (en) * | 2012-10-09 | 2013-01-23 | 中兴通讯股份有限公司 | Uplink power control method and device based on genetic algorithm in communication network |
| CN103347299A (en) * | 2013-06-07 | 2013-10-09 | 北京邮电大学 | Centralized resource management method based on genetic algorithm |
Non-Patent Citations (2)
| Title |
|---|
| A novel low-complexity transmission power adaptation in MS-CDMA systems with a-MRC receiver over Nakagami-m fading channels;Yizhi feng, et al;《INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS》;20091015;全文 * |
| Joint sbcarrier power allocation and equal BER power control for uplink MC-CDMA systems;Yizhi feng, et al;《Procedings of ICCTA2009》;20091231;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103561457A (en) | 2014-02-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103561457B (en) | A kind of multi-target networks power distribution method in heterogeneous wireless network collaboration communication | |
| CN102892188B (en) | Based on the ascending power control method of genetic algorithm and device in communication network | |
| CN112469100B (en) | Hierarchical routing algorithm based on rechargeable multi-base-station wireless heterogeneous sensor network | |
| CN108834080B (en) | Distributed cache and user association method based on multicast technology in heterogeneous network | |
| CN111182511B (en) | AGA-based NOMA resource allocation method in mMTC scene | |
| CN111246416B (en) | Underwater wireless sensor network topology control method based on genetic algorithm | |
| CN104853399B (en) | Cooperating relay system of selection based on improved Genetic Particle Swarm hybrid algorithm | |
| CN107396448A (en) | A kind of resource allocation methods in heterogeneous network | |
| CN105873214B (en) | A kind of resource allocation methods of the D2D communication system based on genetic algorithm | |
| CN105792218B (en) | The optimization method of cognitive radio networks with RF energy capacity gauge | |
| CN109905864A (en) | A kind of cross-layer Resource Allocation Formula towards electric power Internet of Things | |
| CN106411469A (en) | Multicast resource allocation and transmission method based on scalable video in multi-base station heterogeneous network | |
| CN103781166B (en) | Mobile terminal power distribution method in heterogeneous wireless network cooperative communication system | |
| CN104796991B (en) | The resource allocation methods of OFDMA system based on gesture game | |
| CN104284433A (en) | Heterogeneous network per-bit energy minimization resource distribution method based on rate limitation | |
| CN103347299B (en) | A kind of centralized resource management method based on genetic algorithm | |
| CN107969007B (en) | Data fusion collection method based on unequal clustering sensor network | |
| CN101711033A (en) | Dynamic channel allocating method applicable for perceiving radio network and system thereof | |
| Khalid et al. | RTOP: Optimal user grouping and SFN clustering for multiple eMBMS video sessions | |
| CN101489298A (en) | Discrete speed cross-layer power distribution method based on mobile multicast system | |
| CN102355699B (en) | Adaptive resource allocation method for multicast/broadcast single frequency network (MBSFN) | |
| CN102148664B (en) | Inter-multicast network coding control method applied to multi-source multi-destination network | |
| CN117336818A (en) | WSN clustering routing algorithm based on locust optimization FCM | |
| CN105611635B (en) | A kind of multi-target networks power distribution method in heterogeneous wireless network collaboration communication | |
| CN110753365B (en) | Heterogeneous cellular network interference coordination method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20170405 Termination date: 20211025 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |