CN106131853B - Radio Spectrum Resource planing method based on conflict resolution iteration optimization algorithms - Google Patents
Radio Spectrum Resource planing method based on conflict resolution iteration optimization algorithms Download PDFInfo
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- CN106131853B CN106131853B CN201610435137.9A CN201610435137A CN106131853B CN 106131853 B CN106131853 B CN 106131853B CN 201610435137 A CN201610435137 A CN 201610435137A CN 106131853 B CN106131853 B CN 106131853B
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- 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
- H04W16/02—Resource partitioning among network components, e.g. reuse partitioning
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
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Abstract
The invention discloses a kind of Radio Spectrum Resource planing methods based on conflict resolution iteration optimization algorithms, this method comprises: planning contradiction according to frequency spectrum, Radio Spectrum Resource plan model is constructed using the iteration optimization algorithms of frequency spectrum conflict resolution, realizes the planning to the Radio Spectrum Resource of different business.Then Model for Comprehensive is constructed using grey entropy fuzzy evaluation algorithm, quantitative evaluation is carried out to the planning, obtains optimal programme.The method of the present invention comprehensively considers the factor of various aspects, frequency spectrum resource is planned and is combined closely with business demand, the collision problem in Radio Spectrum Resource planning can effectively be cleared up, and quantitative evaluation is carried out to programme, by constantly adjusting and optimizing, the Radio Spectrum Resource programme of strong operability is ultimately formed.
Description
Technical field
The present invention relates to Radio Spectrum Resource planning, in particular to a kind of nothing based on conflict resolution iteration optimization algorithms
Line electricity frequency spectrum resource planing method, belongs to radio control field.
Background technique
Currently, being difficult to coordinate and programme hardly possible there are Radio Spectrum Resource planning conflict in radio control field
To verify its rational problem.In existing radio frequency spectrum planning technology, the utilization of frequency resource common optimization is generallyd use
Combine the schemes such as planning with frequency resource, wherein in frequency resource common optimization Utilization plan, mainly have in mind and follow with for the moment
Between, the principle that the frequency in the same place of covering does not collide formulate, in conjunction with different communication conditional systems efficiency, interfere with each other, real
The comprehensive simulating of existing complexity etc. problem and assessment, make every effort to while improving frequency resource utilization efficiency, realize many
Channeling, deficiency existing for the program show as effectively realizing that the frequency based on multiple-object information is time-multiplexed, and
Frequency resource is combined in programme, based on frequency resource common technology, the analysis of combining wireless electricity frequency spectrum resource demand,
Plan model is established, and by carrying out comprehensive descision and aid decision to spatial frequency resource information, to improve planning rationally
Property while, clear one section of period space from now on is planned with frequency, and deficiency existing for the program shows as the plan model established and lead to
Not strong with property, the conclusion of comprehensive assessment also lacks certain specific aim and operability.
Summary of the invention
Present invention aims to overcome that above-mentioned the deficiencies in the prior art and provide and a kind of calculated based on conflict resolution iteration optimization
The Radio Spectrum Resource planing method of method, this method combine closely frequency spectrum resource planning with business demand, formation operation
Strong Radio Spectrum Resource programme.
Realize the object of the invention the technical solution adopted is that a kind of radio frequency line based on conflict resolution iteration optimization algorithms
Spectrum resource planing method utilizes the iteration optimization algorithms of frequency spectrum conflict resolution this method comprises: planning contradiction according to frequency spectrum
Radio Spectrum Resource plan model is constructed, realizes the planning to the Radio Spectrum Resource of different business.
Further, Model for Comprehensive is constructed using grey entropy fuzzy evaluation algorithm, to the planning amount of progress
Change assessment, obtains optimal programme.
The method of the present invention comprehensively considers the factor of various aspects, and frequency spectrum resource is planned and is combined closely with business demand, can be had
Collision problem in effect resolution Radio Spectrum Resource planning, and quantitative evaluation is carried out to programme, by constantly adjusting
With optimization, the Radio Spectrum Resource programme of strong operability is ultimately formed.
Detailed description of the invention
Fig. 1 is for embodiment based on conflict resolution iteration optimization algorithms to the flow chart of TD-LTE frequency spectrum resource planing method.
Fig. 2 is the process flow diagram that frequency spectrum plans that section clashes.
Specific embodiment
The following further describes the present invention in detail with reference to the accompanying drawings and specific embodiments.
The planning of TD-LTE frequency spectrum resource not only be unable to do without the demand analysis demonstration of TD-LTE frequency spectrum resource, it is also desirable to country,
The local related support for dividing regulation and programme.In terms of demand analysis demonstration, mainly development of new techniques is grasped in tracking
The TD-LTE frequency spectrum resource changes in demand and application mode caused with factors such as technical system updates is changed, comprehensive analysis
Domestic and international TD-LTE frequency spectrum resource demand developments and with other possible mutual shadows of communication technology system frequency spectrum resource demand
Ring, according to TD-LTE frequency spectrum resource Demand Forecast Model calculate estimate TD-LTE frequency spectrum resource demand and can support, with
It forms the demand analysis of TD-LTE frequency spectrum resource and proves conclusion；In terms of correlation divides regulation and programme, state should be strictly observed
Series of rules, standard, suggestion and the radio-frequency spectrum that border Electricity Federation, country and place are put into effect divide regulation, and implement mobile logical
Communication service development programme.The factor analysis of the present embodiment in summary two aspects, using the method for the present invention, in conjunction with
Utilization in relation to distribution model is reached the predistribution of TD-LTE frequency spectrum resource, then by constantly adjustment and amendment, is ultimately formed
TD-LTE frequency spectrum resource programme, as shown in Figure 2, the specific steps are as follows:
S100, programme is generated
Frequency spectrum planning contradiction analysis rule is established, the iteration optimization algorithms of frequency spectrum conflict resolution are designed, building is wireless
Electric frequency spectrum resource plan model, may achieve the pre-planning of the Radio Spectrum Resource based on different business.
S101, planning and designing
The design of S1011, conflict resolution iteration optimization algorithms
(1) determination in initial spectrum planning section
Initial spectrum plans that the determination in section is completed on the basis of spectrum requirement.
(a) model hypothesis
Assuming that frequency spectrum planning reference interval is [a1,b1],[a2,b2],…,[an,bn], it is now desired to obtain one with it is above-mentioned
Section is planned as final frequency spectrum in the highest section of the reference interval goodness of fit.
Since the data source of above-mentioned reference interval is different, therefore its property of can refer to is different.According to different reference intervals can
Referential assigns each reference interval one weight αi(i=1,2 ..., n), αiDescribe reference interval [ai,bi] property of can refer to
Size.
Wherein
(b) foundation of model
It takesThen reference interval
The length in section is longer, and validity is stronger, and accuracy is poorer；Siding-to-siding block length is shorter, and validity is poorer, accurately
Property is stronger.
The validity and accuracy for comprehensively considering frequency spectrum planning section take the length in planning section for the half of [a, b], if
Distributing section is [x, y], then
Define frequency spectrum planning section [x, y] and reference interval [ai,bi] (i=1,2 ..., n) the goodness of fit it is as follows:
Wherein, | | | | indicate the length in section.
(c) model solution
A) initial value x is enabled0=a,It calculates frequency spectrum and plans section [x0,y0] with the goodness of fit of reference interval；
B) step-length ε=0.1 (or 0.01, can voluntarily determine as needed) is taken, [x is successively calculatedi+1,yi+1] and reference interval
The goodness of fit；
Wherein xi+1=xi+ ε, yi+1=yi+ ε (i=1,2 ...)
If c) yi+1≤ b then constantly repeats step b), if yi+1> b then stops recycling.
It enablesThen η*Corresponding frequency spectrum plans section [x*,y*] it is required.
The processing that S1012, frequency spectrum planning section clash
Various conflicts will necessarily occur for initial spectrum planning section, carry out justice in proportion again according to importance
Planning.
(a) planing method again for the frequency range that conflicts
Assuming that the separate service x of certain operation system1…xnFrequency spectrum planning section be respectively [a1,b1],[a2,b2],…,[an,
bn], without loss of generality, it might as well assume a1≤a2≤…≤an。
If separate service x1…xnIt interferes with each other, then its frequency spectrum planning section cannot clash, i.e., to arbitraryMeet
If(might as well assume i < j), so thatThen illustrate separate service xiAnd xj
Frequency spectrum planning section conflicted, need that fair planning principles is planned again in proportion to the frequency range of conflict.
Due to ai≤aj, thenWherein c=aj, d=min { bi,bj}。
By separate service xiAnd xjThe significance level weight beta to play a role in the operation systemiAnd βjDescription, then will punching
Prominent frequency range [c, d] is planned in following ratio, i.e., willIt plans to xi,It plans to xj。
At this point, separate service xiFrequency spectrum planning section by assignment again are as follows:
Separate service xjFrequency spectrum planning section by assignment again are as follows:
(b) implementation steps, algorithm flow are as shown in Figure 2, comprising:
If separate service x1…xnInitial spectrum planning sequence of intervals be [a1,b1],[a2,b2],…,[an,bn], and a1≤
a2≤…≤an。
A) i=1, j=i+1 are enabled；
B) judged, if [ai,bi]∩[aj,bj] ≠ φ then plans conflict frequency range again, and by frequency spectrum planning region
Between sequence assignment, i.e. [a againi,bi]=[ai′,bi'], [aj,bj]=[aj′,bj′].Step 2 is executed again；IfIt then executes c)；
C) j=j+1 is enabled, is executed b)；It until j=n, terminates, executes d)；
D) i=i+1 is enabled, is executed a)；Until i=n is terminated.
S200, assessment programme
Since the evaluation index of programme not only has ambiguity, but also there are grey majorized model, this method designs grey entropy mould
Paste assessment algorithm carries out comprehensive assessment to it, the specific steps are as follows:
S201, analyzing influence Factor system
Classify to each factor for influencing programme superiority and inferiority by attribute, establishes the Recurison order hierarchy relationship of influence factor.
If set of factors is U, { U1,U2,…UnThe 1st layer of programme assessment factor is constituted, { U11,U12,U13,U21,…,Unm-1,Unm}
Constitute the 2nd layer of programme assessment factor layer, i.e., sub- factor layer.Consider the operability and accuracy of assessment, selected 5 grades are commented
Language collection, assessment result is divided into: outstanding (V1), good (V2), medium (V3), qualification (V4), unqualified (V5) 5 grades, it is alternative
Collection (or Comment gathers) may be expressed as: V={ V1,V2,…,V5}。
S202, simple element evaluation
(a) single factor judgment matrix is established
Single factor judgment matrix can be considered sub- set of factors { UijAnd alternative collection between Theory of Grey Fuzzy Relation.According to UijIt gives
Object is judged out to the degree of membership of each element in Comment gathers, and corresponding gray scale is provided according to the abundant degree of information, can be used
Expert judging method determines.
Since information content is difficult to be measured with numerical value, so this project is certain to correspond to using some descriptive language
The abundant degree of information is such as divided into following a few classes by tonal range: and it is very sufficiently, relatively sufficiently, generally, poorer, it is very poor
It is weary }, respectively correspond gray value [0,0.2), [and 0.2,0.4), [0.4,0.6), [0.6,0.8), [0.8,1.0].
(b) sub- set of factors { U is determinedijWeight
In view of every evaluation index in the otherness for measuring programme superiority and inferiority degree, reasonably commented to be more acurrate
Estimate, science is needed to determine the weight of indexs at different levels.There are many method for determining evaluation index weight, and this system is mainly using based on letter
The index weights of breath entropy theory determine method.
If iotave evaluation data matrix X=(xij)n×m, wherein xij>=0 (i=1,2 ..., n；J=1,2 ..., m).Believing
The variable-value range in entropy is ceased between 0~1, it is therefore desirable to be pre-processed to iotave evaluation data matrix X, this project is adopted
It is handled with normalized method, the matrix E=[e after obtaining normalizedij], wherein
For some index i in planning appraisal, comentropy are as follows:
The entropy weight of i-th of index are as follows:
In formula: 0≤wi≤ 1, and
Weight sets can be considered the Theory of Grey Fuzzy Relation judged between object and set of factors.It is closed according to influence factor Recurison order hierarchy
System, provides each sub- factor { U in same level with information entropy theoryijAbout upper one layer of criterion UiWeight and corresponding point ash
Degree constitutes weight sets.
Each weighted value requires normalization in formula, i.e.,
(c) simple element evaluation vector is found out
To retain judge information as much as possible, using M (,+) operator in the operation of mould portion, and used in the operation of ash portion
M (⊙ ,+) operator, therefore, single factor test U out according to the following formulaiJudge vector:
S203, Comprehensive Evaluation
By sub- set of factors UiAs the element of the first level factor collection U thereon, the simple element evaluation vector found out by front can structure
At comprehensive evaluation matrix:
Equally factor U is provided with information entropy theoryiAbout destination layer weight and accordingly put gray scale, constitute weight
Collection.
Wherein, each weighted value requires normalization, i.e.,
Find out the Comprehensive Evaluation vector of planning concept:
The processing of S204, evaluation result
In Grey Fuzzy Comprehensive Evaluation, gray scale is also to be understood as the description of the insufficient degree of information to information
Insincere degree, corresponding whiteness are the confidence level of information.Therefore, above-mentioned evaluation result can be handled as follows:
If bi≥bj, then bi≥bjConfidence level are as follows: pij=P (bi≥bj)=(1-vi)(1-vj) (i, j=1,2,3,4,5
And i ≠ j)；
Conversely, bi≥bjCan not reliability, i.e. bj> biConfidence level are as follows: pji=1-pij=1- (1-vi)(1-vj)(i,j
=1,2,3,4,5 and i ≠ j)；
In above-mentioned evaluation result, degree of membership biFor maximum confidence level are as follows:
According to maximum membership grade principle, the maximum p of confidence value is choseniCorresponding comment ViFor the most final review of programme
Sentence as a result, the superiority and inferiority of programme has thus been determined.
Claims (3)
1. a kind of Radio Spectrum Resource planing method based on conflict resolution iteration optimization algorithms, it is characterised in that: according to frequency
Spectrum planning contradiction constructs Radio Spectrum Resource plan model using the iteration optimization algorithms of frequency spectrum conflict resolution, realizes
Planning to the Radio Spectrum Resource of different business；
It is described to include: with the iteration optimization algorithms building Radio Spectrum Resource plan model of frequency spectrum conflict resolution
Determine that frequency spectrum plans section；
Justice in proportion is carried out according to importance to the frequency range clashed in frequency spectrum planning section to plan again；
Wherein, the determining frequency spectrum planning section includes:
Taking frequency spectrum planning reference interval is [ai, bi], assign each reference interval one weight αi(i=1,2 ..., n), αiFor ginseng
[a between examination districti,bi] property of can refer to size,
It takesThen reference intervalFrequency spectrum planning region
Between be [xi,yi], [xi,yi] length be [ai,bi] half, then
According toIt calculates frequency spectrum and plans section [xi,yi] and reference interval [ai,bi] kiss
It is right, wherein | | | | indicate the length in section；Calculating the gained goodness of fit highest frequency spectrum planning section is final reference
Section；
The frequency range of described pair of conflict in proportion plan again and include: by fair planning principles
Due to ai≤aj, then [ai,bi]∩[aj,bj]=[c, d], wherein c=aj, d=min { bi,bj}；
By separate service xiAnd xjThe significance level weight beta to play a role in operation systemiAnd βjDescription, then will conflict frequency range
[c, d] is planned in following ratio, i.e., willIt plans to xi,Rule
Give xj；
At this point, separate service xiFrequency spectrum planning section by assignment again are as follows:
Separate service xjFrequency spectrum planning section by assignment again are as follows:
2. special according to claim 1 based on the Radio Spectrum Resource planing method of conflict resolution iteration optimization algorithms
Sign is: constructing Model for Comprehensive using grey entropy fuzzy evaluation algorithm, carries out quantitative evaluation to the planning, obtain most
Excellent programme.
3. special according to claim 1 based on the Radio Spectrum Resource planing method of conflict resolution iteration optimization algorithms
Sign is to clash in frequency spectrum planning section to be judged according to following manner:
The separate service x of operation system1…xnFrequency spectrum planning section be respectively [a1,b1],[a2,b2],…,[an,bn]；
If separate service x1…xnIt interferes with each other, then its frequency spectrum planning section cannot clash, i.e., to arbitraryMeet [ai,bi]∩[aj,bj]=φ；
IfSo thatThen separate service xiAnd xjFrequency spectrum planning section hair
Conflict is given birth to.
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