CN107277816A - A kind of High Altitude Platform networking frequency spectrum distributing method - Google Patents
A kind of High Altitude Platform networking frequency spectrum distributing method Download PDFInfo
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- CN107277816A CN107277816A CN201710296629.9A CN201710296629A CN107277816A CN 107277816 A CN107277816 A CN 107277816A CN 201710296629 A CN201710296629 A CN 201710296629A CN 107277816 A CN107277816 A CN 107277816A
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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
- H04W16/06—Hybrid resource partitioning, e.g. channel borrowing
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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
- H04W16/10—Dynamic resource partitioning
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Abstract
This application discloses a kind of High Altitude Platform networking frequency spectrum distributing method, comprise the following steps：The frequency spectrum income of each High Altitude Platform is calculated, the influence factor of the frequency spectrum income includes own spectrum resource resources profit, borrowing frequency spectrum resource income, borrowing frequency spectrum resource expense, taxi frequency spectrum resource income；Change the frequency spectrum resource borrow amount between High Altitude Platform, frequency spectrum resource or each High Altitude Platform are borrowed at least one other High Altitude Platform comprising each High Altitude Platform and lend frequency spectrum resource at least one other High Altitude Platform, change the frequency spectrum income of each High Altitude Platform；Calculating network income, is the summation of the frequency spectrum income of the multiple High Altitude Platform；Repeat the above steps, draw the frequency spectrum resource borrow amount between High Altitude Platform when network profit is maximum.Most preferred embodiment changes the frequency spectrum resource borrow amount between High Altitude Platform with Elman neural networks.The present processes improve the spectrum utilization efficiency of High Altitude Platform networking, overall efficiency and improved.
Description
Technical field
The application is related to the communications field, more particularly to a kind of frequency spectrum distributing method of High Altitude Platform networking.
Background technology
In the networking plan of Incorporate, High Altitude Platform (NSP, Near Space Platform) with its capacity compared with
Greatly, the features such as flexibility is relatively strong, coverage is wider, by the extensive concern of industry, is increasingly becoming in Incorporate network
Indispensable communication node.Open in view of High Altitude Platform communication scenes, signal transmission attenuation decay is smaller, therefore using frequency
The resource splitting scheme of rate multiplexing, to avoid minizone from interfering.But with continuing to develop for existing communication technology, multimedia
Gradually increase etc. broadband services proportion, while the position of hot spot region and number of users are continually changing, it is solid according to tradition
Determine the demand that spectrum allocation schemes are difficult to meet wideband communications service.
The content of the invention
In view of this, the present invention proposes a kind of frequency spectrum distributing method of High Altitude Platform networking, solves frequency spectrum distribution benefit low
The problem of.
Embodiments of the invention propose a kind of High Altitude Platform networking frequency spectrum distributing method, comprise the following steps：
The frequency spectrum income of each High Altitude Platform is calculated, the influence factor of the frequency spectrum income is received comprising own spectrum resource
Benefit, borrowing frequency spectrum resource income, borrowing frequency spectrum resource expense, taxi frequency spectrum resource income；
Change the frequency spectrum resource borrow amount between High Altitude Platform, comprising each High Altitude Platform at least one other high
Hollow panel borrows frequency spectrum resource or each High Altitude Platform lends frequency spectrum resource at least one other High Altitude Platform, changes
The frequency spectrum income of each High Altitude Platform；
Calculating network income, is the summation of the frequency spectrum income of the multiple High Altitude Platform；
Repeat the above steps, draw the frequency spectrum resource borrow amount between High Altitude Platform when network profit is maximum.
In one embodiment of the present of invention, the frequency spectrum income of k-th of High Altitude Platform is calculated with the following methods, is
Wherein,
Represent the own spectrum resource resources profit of k-th of High Altitude Platform；
Represent k-th of High Altitude Platform borrowing frequency spectrum resource income；
Represent k-th of High Altitude Platform borrowing frequency spectrum resource expense；
Represent that k-th of High Altitude Platform hires out frequency spectrum resource income；
Wherein, Qk(i) represent that k-th of High Altitude Platform provides the profit margin of i classes service, Pk(i) k-th of High Altitude Platform is represented
The price of i classes service is provided,Represent that i classes service the transmission rate on k High Altitude Platform；
Borrowing price is represented,Represent lending price, bkAnd b (j)j(k) k-th of High Altitude Platform is represented respectively
The frequency spectrum of j-th of High Altitude Platform is leased to from frequency spectrum, k-th of the High Altitude Platform of j-th of High Altitude Platform borrowing.
In the embodiment that High Altitude Platform networking frequency spectrum distributing method of the present invention further optimizes, each High Altitude Platform
Own spectrum resource priority meet own spectrum demand, then：When the own spectrum resource has residue, the borrowing frequency spectrum
Resource resources profit, borrowing frequency spectrum resource expense value are 0；When the own spectrum inadequate resource, the taxi frequency spectrum resource is received
Beneficial value is 0.
In the embodiment that High Altitude Platform networking frequency spectrum distributing method of the present invention further optimizes, with Elman nerves
Network technique changes the frequency spectrum resource borrow amount between High Altitude Platform.
Specifically, the embodiment that High Altitude Platform networking resources distribution method of the present invention further optimizes includes following step
Suddenly：
In k-th of High Altitude Platform of t prediction, each speed serviced is
The usable spectrum and borrowing frequency spectrum designation of t are BkAnd ζk,t, BkInitial value be B, ζk,tInitial value be 0；
High Altitude Platform k idle frequency spectrum resource is
ηk(j) utilization rates of the platform k using platform j frequency spectrum is represented, that is to say, that the speed/availability of frequency spectrum=required
Frequency spectrum；
Judge whether
If it is not, then takingMake
Therefore have
DefinitionIf σk,t＞ 0, then take
ρk,t=max (σk,t,0)；
When changing the frequency spectrum resource borrow amount between High Altitude Platform, the priority that k platforms borrow frequency spectrum to j platforms is calculated
And priority is ranked up,Represent the frequency spectrum that High Altitude Platform k exceeds；
IfThen take
IfThen take
Priority is recalculated according to the value after renewal, until all frequency spectrums are assigned, finally according to High Altitude Platform
Between frequency spectrum resource borrow amount update Bk；
Leasing frequency spectrum isBorrowing frequency spectrum is
At least one above-mentioned technical scheme that the embodiment of the present application is used can reach following beneficial effect：The side of the application
Method improves the spectrum utilization efficiency of High Altitude Platform networking, overall efficiency and improved；By neatly controlling each high-altitude node to borrow
Bandwidth and lending bandwidth, can adapt dynamically to the broadband services proportion such as multimedia and gradually increase, while hot spot region
The situation that position and number of users are continually changing.
Brief description of the drawings
Accompanying drawing described herein is used for providing further understanding of the present application, constitutes the part of the application, this Shen
Schematic description and description please is used to explain the application, does not constitute the improper restriction to the application.In the accompanying drawings：
Fig. 1 is High Altitude Platform group-net communication schematic diagram of a scenario；
Fig. 2 is the application frequency spectrum distributing method embodiment flow chart；
Fig. 3 is Elman schematic network structures；
Fig. 4 is the embodiment schematic diagram distributed using Elman neural networks frequency spectrum.
Embodiment
To make the purpose, technical scheme and advantage of the application clearer, below in conjunction with the application specific embodiment and
Technical scheme is clearly and completely described corresponding accompanying drawing.Obviously, described embodiment is only the application one
Section Example, rather than whole embodiments.Based on the embodiment in the application, those of ordinary skill in the art are not doing
Go out the every other embodiment obtained under the premise of creative work, belong to the scope of the application protection.
This patent proposes one kind under High Altitude Platform networking scene, the frequency spectrum based on Elman neural network prediction models
Distribution method.Frequency spectrum situation of Profit in cell is divided into 4 classes by this method first --- " own spectrum resource resources profit, lease frequency
Spectrum resource income, lease frequency spectrum resource expense, hire out frequency spectrum resource income ", then by increase a centralized control unit (CCU,
Center Control Unit), all frequency bands are placed in frequency band pond and are allocated, using the gradient descent algorithm of optimization,
The training speed of network can be improved, can effectively suppress network again is absorbed in local minimum point.The purpose of this algorithm self study is to use
The predicted velocity (real output value) of every kind of business and the difference of the actual speed rate (output sample value) of every kind of business are come in network
Change weights and threshold value so that the error sum of squares of network output layer is minimum, reaches network integral benefit supreme good.
Below in conjunction with accompanying drawing, the technical scheme that each embodiment of the application is provided is described in detail.
Fig. 1 is High Altitude Platform group-net communication schematic diagram of a scenario.Assuming that thering are 7 High Altitude Platforms (NSP) to collectively form one to be
System, the height of each High Altitude Platform is 30km, and covering radius is 175km, and the frequency band that each High Altitude Platform is used is different.And
By increasing a centralized control unit (CCU) in this scheme, all frequency bands are placed in frequency band pond and are allocated, often
Individual High Altitude Platform is 7B can initially be assigned to B bandwidth, frequency band pond overall width.
The frequency spectrum income of High Altitude Platform is that own spectrum resource resources profit+borrowing frequency spectrum resource income-borrowing frequency spectrum resource is opened
Pin+taxi frequency spectrum resource income.
In the embodiment of High Altitude Platform networking frequency spectrum distributing method of the present invention, the own spectrum of each High Altitude Platform
Resource priority meets own spectrum demand, then：When the own spectrum resource has residue, the borrowing frequency spectrum resource income,
It is 0 to borrow frequency spectrum resource expense value；When the own spectrum inadequate resource, the taxi frequency spectrum resource income value is 0.
Fig. 2 is the application frequency spectrum distributing method embodiment flow chart.
Step 1, the frequency spectrum income for calculating each High Altitude Platform, the influence factor of the frequency spectrum income include own spectrum
Resource resources profit, borrowing frequency spectrum resource income, borrowing frequency spectrum resource expense, taxi frequency spectrum resource income；
Step 2, change High Altitude Platform between frequency spectrum resource borrow amount, comprising each High Altitude Platform at least one
Other High Altitude Platforms borrow frequency spectrum resource or each High Altitude Platform at least one other High Altitude Platform lending frequency spectrum money
Source, changes the frequency spectrum income of each High Altitude Platform；
Step 3, calculating network income, are the summation of the frequency spectrum income of the multiple High Altitude Platform；
Step 4, repeat the above steps, draw the frequency spectrum resource borrow amount between High Altitude Platform when network profit is maximum.
In one embodiment of the present of invention, the frequency spectrum income of k-th of High Altitude Platform is calculated with the following methods, is
Wherein,
Represent the own spectrum resource resources profit of k-th of High Altitude Platform；
Represent k-th of High Altitude Platform borrowing frequency spectrum resource income；
Represent k-th of High Altitude Platform borrowing frequency spectrum resource expense；
Represent that k-th of High Altitude Platform hires out frequency spectrum resource income；
Wherein, Qk(i) represent that k-th of High Altitude Platform provides the profit margin of i classes service, Pk(i) k-th of High Altitude Platform is represented
The price of i classes service is provided,Represent that i classes service the transmission rate on k High Altitude Platform；
Borrowing price is represented,Represent lending price, bkAnd b (j)j(k) k-th of High Altitude Platform is represented respectively
The frequency spectrum of j-th of High Altitude Platform is leased to from frequency spectrum, k-th of the High Altitude Platform of j-th of High Altitude Platform borrowing.
Each platform using meet own spectrum demand as first it is important on the premise of, it is impossible to while lease and borrow frequency
Spectrum, so the frequency spectrum income in (1) formula can be divided into two kinds of situations
Own spectrum has residue, can lease
Own spectrum is without residue, it is necessary to borrow
Assuming that B is the frequency spectrum that each High Altitude Platform is averagely assigned at the beginning, BkAfter to be that k platforms are actual borrow and lease can
With frequency spectrum, then be also classified into following two situations：
Own spectrum has residue, when leasing frequency spectrum, and usable spectrum is：
Own spectrum is without residue, and during borrowing frequency spectrum, usable spectrum is：
With ηk(j) utilization rates of the platform k using platform j frequency spectrum is represented, for example, is expressed as：
Wherein γk(j) matching received signal to noise ratio is represented,Represent the target bit of k platforms.
In order that network profit highest, optimizing purpose is
It needs to be determined that each platform is borrowing frequency spectrum or leases frequency spectrum, so as to be calculated with corresponding formula.
It should be noted that because the final purpose of each High Altitude Platform is to meet the biography of user in platform coverage
Defeated rate requirement, therefore the spectrum requirement situation of each High Altitude Platform can be equivalent to the transmission rate need of user in platform covering
Ask.
Fig. 3 is Elman schematic network structures.It is set forth below a kind of using Elman neutral nets, it is pre- by historical information
The method for surveying the transmission rate requirements of user in each High Altitude Platform coverage of t, so as to obtain each High Altitude Platform of t
Spectrum requirement situation.
Firstly the need of being transmitted rate prediction.M is provided in k-th of High Altitude PlatformkThe service of type, it is assumed that in t-1
The transmission rate of moment each type isIf united always since initial time
Count the t-1 moment, the matrix of speed is
The transmission rate of t is predicted in this programme with Elman neutral nets, Elman recurrent nerve metanetworks are general
It is divided into four layers：Input layer, intermediate layer (hidden layer), accepts layer and output layer.The connection class of its input layer, hidden layer and output layer
Feedforward network is similar to, the unit of input layer only plays signal transmitting effect, the linear weighting effect of output layer unit.Implicit layer unit
Transmission function can accept layer using linearly or nonlinearly function and be also known as context level or state layer, it is used for remembering implicit
The output valve of layer unit previous moment, it is believed that be a step delay operator.
The characteristics of Elman recurrent nerve metanetworks be the output of hidden layer by accepting the delay and storage of layer, be linked to certainly
The input of hidden layer, this its data to historic state is had sensitiveness from connection mode, the addition of internal feedback network increases
The ability for having added network basis to be in reason multidate information, so as to reach the purpose of dynamic modeling.In addition, Elman recurrent nerve nets
Network can approach arbitrary nonlinear mapping with arbitrary accuracy, can not consider concrete form of the external noise to systematic influence, such as
Fruit provides the inputoutput data pair of system, it is possible to which system is modeled.
As shown in figure 3, the non-linear state space expression of Elman neutral nets is：
Y (k)=g (w3x(k)+b2) (9)
X (k)=f (w1xc(k)+w2(u(k-1))+b1) (10)
xc(k)=x (k-1) (11)
Wherein, k represents moment, y, x, u, xcRepresent that 1 ties up output node vector respectively, m ties up hidden layer node unit vector,
N dimensional input vectors and m dimension feedback state vectors.w3,w2,w1Respectively represent hidden layer to input layer, input layer to hidden layer, hold
Layer is connect to the connection weight matrix of hidden layer.F () is the transmission function of hidden layer neuron, and g () is output layer transmission function.
b1,b2The respectively threshold value of input layer and hidden layer.The gradient that Elman Learning Algorithms use optimization declines calculation
Method, i.e. adjusting learning rate momentum gradient decline back-propagation algorithm, and it can improve the training speed of network, again can be effective
Suppress network and be absorbed in local minimum point.The destination of study is to be changed with the real output value of network with exporting the difference of sample value
Weights and threshold value so that the error sum of squares of network output layer is minimum.If the reality output vector of kth step system is yd(k), exist
In period (0, T), defining error function is：
With w3,w2Exemplified by, by E to w3,w2Local derviation is sought respectively, and can obtain modified weight formula is：
Wherein, φ is learning rate, and mc is factor of momentum, and default value is 0.9.So not only allowed for when being updated
Current gradient direction, it is also contemplated that the gradient direction of previous moment, reduces sensitiveness of the network performance to parameter adjustment.Effectively suppression
Local minimum is made.
The pre- flow gauge of transmission rate is
Step A, training network, it is assumed that the length of training sequence is α, this length represents to be entered with how much rows in (8)
Row training, α length will determine the frequency of training and training precision of network, also determine will be carried out with how many historical information it is pre-
Survey.If such as α be 3, t be 10, then will be with { 1,2,3 }, { 2,3,4 }, { 3,4,5 } ..., { 6,7,8 } train 6 times, then with
{ 7,8,9 } come estimate 10 speed.
Step B, input vector will be 3 × MkDimension, then the number of implicit layer unit is rule of thumb set to 2Mk- 1, meeting
Acquisition is better to predict the outcome, while output vector will be 1 × MkDimension.
Step C, it is predicted
By above method, the speed for predicting each service of High Altitude Platform k in t is
Thus the user in each High Altitude Platform coverage is can obtain in the prediction transmission rate of t, the speed
It is used to calculate spectrum requirement situation of each High Altitude Platform in t so that frequency spectrum is hired out or borrowed between platform and is possibly realized,
Maximization network income.Illustrate the method according to transmission rate allocation frequency spectrum below.
Fig. 4 is the embodiment schematic diagram distributed using Elman neural networks frequency spectrum.
It is B by the usable spectrum of t and borrowing frequency spectrum designation for High Altitude Platform kkAnd ζk,t, BkInitial value be
B, ζk,tInitial value be 0.High Altitude Platform k idle frequency spectrum resource is defined as ρk,t, then it can be defined as
Step 10, forecast period, the speed of each service is calculated according to usable spectrum；
If meeting following formula, then the High Altitude Platform k frequency spectrums of itself meet demand, and may have frequency spectrum sale
If can not meet, then set satisfiable speed asThen
The part so exceeded is defined as
Step 20, renewal and removing stage, calculate the borrowing frequency spectrum and idle frequency spectrum resource of each High Altitude Platform；
σ is defined for High Altitude Platform kk,t
If σk,t＞ 0, then illustrate that frequency spectrum resource is sufficient, such as following formula updates ζk,t
ρk,t=max (σk,t,0) (21)
Step 30, scheduling phase, calculate the borrowing frequency spectrum of High Altitude Platform, hire out frequency spectrum, update available frequency spectrum.
Step 301, when scheduler receives the borrowing frequency spectrum request of High Altitude Platform, he will see that other platforms are
It is no to have usable spectrum, and calculate priority
(income that borrowing is produced subtracts rent)
Step 302, priority is ranked up,Represent the frequency spectrum that High Altitude Platform k exceeds, λk(i, j) represents k and put down
Platform borrows the priority of frequency spectrum to j platforms
There are two kinds of situations：
(1) demand for being more than k platforms by means of frequency spectrum resource of j platforms, that is to say, thatSo k
Platform would not be borrowed from other platform, then update as follows
(2)Compare ρj,tGreatly (the borrowing the demand that frequency spectrum resource is less than k platforms of j platforms), that is to say, thatThen update as follows,
Step 303, priority recalculated according to the value after renewal, finished until all frequency spectrums are allocated
Borrowing situation of leasing finally according to High Altitude Platform updates B with following formulak
Lease frequency spectrum：
Borrow frequency spectrum：
Step 304, execution batch operation.
It should also be noted that, term " comprising ", "comprising" or its any other variant are intended to nonexcludability
Comprising so that process, method, commodity or equipment including a series of key elements are not only including those key elements, but also wrap
Include other key elements being not expressly set out, or also include for this process, method, commodity or equipment intrinsic want
Element.In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that wanted including described
Also there is other identical element in process, method, commodity or the equipment of element.
Embodiments herein is the foregoing is only, the application is not limited to.For those skilled in the art
For, the application can have various modifications and variations.It is all any modifications made within spirit herein and principle, equivalent
Replace, improve etc., it should be included within the scope of claims hereof.
Claims (5)
1. a kind of High Altitude Platform networking frequency spectrum distributing method, it is characterised in that comprise the following steps：
Calculate the frequency spectrum income of each High Altitude Platform, the influence factor of the frequency spectrum income comprising own spectrum resource resources profit,
Borrow frequency spectrum resource income, borrowing frequency spectrum resource expense, hire out frequency spectrum resource income；
Change the frequency spectrum resource borrow amount between High Altitude Platform, it is flat at least one other high-altitude comprising each High Altitude Platform
Platform borrows frequency spectrum resource or each High Altitude Platform lends frequency spectrum resource at least one other High Altitude Platform, changes each
The frequency spectrum income of individual High Altitude Platform；
Calculating network income, is the summation of the frequency spectrum income of the multiple High Altitude Platform；
Repeat the above steps, draw the frequency spectrum resource borrow amount between High Altitude Platform when network profit is maximum.
2. High Altitude Platform networking frequency spectrum distributing method as claimed in claim 1, it is characterised in that
The frequency spectrum income of k-th of High Altitude Platform is
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Wherein,
Represent the own spectrum resource resources profit of k-th of High Altitude Platform；
Represent k-th of High Altitude Platform borrowing frequency spectrum resource income；
Represent k-th of High Altitude Platform borrowing frequency spectrum resource expense；
Represent that k-th of High Altitude Platform hires out frequency spectrum resource income；
Wherein, Qk(i) represent that k-th of High Altitude Platform provides the profit margin of i classes service, Pk(i) represent that k-th of High Altitude Platform provides i
The price of class service,Represent that i classes service the transmission rate on k High Altitude Platform；
Borrowing price is represented,Represent lending price, bkAnd b (j)j(k) represent k-th of High Altitude Platform from jth respectively
Frequency spectrum, k-th of the High Altitude Platform of individual High Altitude Platform borrowing are leased to the frequency spectrum of j-th of High Altitude Platform.
3. High Altitude Platform networking frequency spectrum distributing method as claimed in claim 2, it is characterised in that
The own spectrum resource priority of each High Altitude Platform meets own spectrum demand；
When the own spectrum resource has residue, the borrowing frequency spectrum resource income, borrowing frequency spectrum resource expense value are 0；
When the own spectrum inadequate resource, the taxi frequency spectrum resource income value is 0.
4. the High Altitude Platform networking resources distribution method as described in claims 1 to 3, it is characterised in that
Change the frequency spectrum resource borrow amount between High Altitude Platform with Elman neural networks.
5. High Altitude Platform networking resources distribution method as claimed in claim 4, it is characterised in that comprise the steps of
In k-th of High Altitude Platform of t prediction, each speed serviced is
The usable spectrum and borrowing frequency spectrum designation of t are BkAnd ζk,t, BkInitial value be B, ζk,tInitial value be 0；
High Altitude Platform k idle frequency spectrum resource is
Judge whether
If it is not, then takingMake
Therefore have
DefinitionIf σk,t＞ 0, then take
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</mrow>
</msub>
</mrow>
</mtd>
</mtr>
<mtr>
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</mrow>
</mtd>
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</mtable>
</mfenced>
<mo>,</mo>
</mrow>
ρk,t=max (σk,t,0)；
When changing the frequency spectrum resource borrow amount between High Altitude Platform, the priority that k platforms borrow frequency spectrum to j platforms is calculated
<mrow>
<msub>
<mi>&lambda;</mi>
<mi>k</mi>
</msub>
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</msub>
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</mrow>
<msubsup>
<mi>R</mi>
<mrow>
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<mi>t</mi>
</mrow>
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</msubsup>
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<mi>i</mi>
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</msubsup>
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And priority is ranked up,Represent the frequency spectrum that High Altitude Platform k exceeds；
IfThen take
IfThen take
Priority is recalculated according to the value after renewal, until all frequency spectrums are assigned, finally according between High Altitude Platform
Frequency spectrum resource borrow amount update Bk
Leasing frequency spectrum is
Borrowing frequency spectrum is
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| CN102316465A (en) * | 2011-09-23 | 2012-01-11 | 北京邮电大学 | Frequency spectrum gaming distribution method in cognitive wireless network |
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| EP2836926A1 (en) * | 2012-04-11 | 2015-02-18 | Intel Corporation | Implementing a dynamic cloud spectrum database as a mechanism for cataloging and controlling spectrum availability |
| CN103533551A (en) * | 2013-10-25 | 2014-01-22 | 上海交通大学 | Method for distributing spectrum resource in cognitive radio network |
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