CN103200670B - The cognitive radio primary user localization method of convex set projection is checked based on backtracking - Google Patents

The cognitive radio primary user localization method of convex set projection is checked based on backtracking Download PDF

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CN103200670B
CN103200670B CN201310057842.6A CN201310057842A CN103200670B CN 103200670 B CN103200670 B CN 103200670B CN 201310057842 A CN201310057842 A CN 201310057842A CN 103200670 B CN103200670 B CN 103200670B
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iteration
primary user
backtracking
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user
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CN103200670A (en
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杜利平
雷雨
康璐璐
姜少坤
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University of Science and Technology Beijing USTB
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Abstract

The present invention proposes a kind of cognitive radio primary user localization method checking convex set projection based on backtracking, with the coordinate of L perception user for the center of circle, utilizes convex set projection algorithm to carry out Mc to primary user and walks rectangular projection iteration; Carry out mc step backtracking audit by comparison, calculate the distance between adjacent iteration point, and compare with threshold value λ; If the distance existence part between adjacent iteration point is zero or is greater than the situation of λ, then carry out Mb on convex set circle border, territory and walk Projection Iteration, with mb step backtracking audit by comparison, calculate the distance value between adjacent two iteration points, again compare with threshold value λ, if be all less than λ, then by the iteration result b of Mb step mbbe defined as the positioning result of primary user's positional information.Backtracking in the present invention checks that convex set projection location algorithm compensate for the deficiency of existing convex set projection location algorithm, location algorithm is good, and less by the impact of range error, adapt to for perception user in cognitive radio networks the acquisition link of primary user's positional information.

Description

The cognitive radio primary user localization method of convex set projection is checked based on backtracking
Technical field
The present invention relates to a kind of method to primary user location in cognitive radio networks, particularly a kind of convex set projection localization method checked based on backtracking.
Background technology
Along with the connected applications of wireless mobile communications and computer network develops more and more ripe, mobile Internet has been called that the world today is with the fastest developing speed, market potential is maximum, one of development service that commercial value is the highest.Abundant application mainly relies on the information bearing modes such as word, image, video, and along with people are to the continuous pursuit of application quality, requires that the transmission of information is more and more efficient, convenient.The innovating and developing of these application needs broad spectrum and higher download speed.The concept of cognitive radio has catered to the needs of frequency spectrum recycling, can, by the perception realization of wireless environment and the conflict avoidance of primary user, utilize optimized decision-making effectively dynamically to utilize frequency spectrum cavity-pocket.If the positional information of primary user can be obtained, so will be greatly improved to the performance of frequency spectrum perception, and also will play very large help in the management and distribution of follow-up frequency spectrum resource.
Position primary user in cognition network, the Main Function obtaining the positional information of primary user has the following aspects:
1. for dynamic spectrum resource management provides support.When primary user's positional information is known, the availability of frequency spectrum can be improved better according to its positional information, instruct better perception user not interfere with primary users frequency spectrum use.
2. reduce the power consumption of user in cognition network.When primary user's positional information is known, the perception user in cognition network can determine the direction of frequency spectrum perception according to the positional information of primary user, under the running status of minimum power, just accurately can judge the frequency spectrum service condition of primary user.
3. avoid the interference to primary user.When primary user's positional information is known, can in conjunction with multi-antenna technology, frequency spectrum perception is carried out in the position, direction for primary user, avoids the possibility of interference mutually between frequency spectrum.
4. be conducive to the position optimization of perception user.When primary user's positional information is known, according to the positional information of primary user, can the position of rational distributed awareness user, improve the utilance in frequency spectrum and space, avoid better disturbing primary user.
Convex set projection method conventional at present comprises Circular POCS, Hyperbolic POCS, BoundaryPOCS and Hybrid POCS etc., wherein Hybrid POCS is the merging of first two POCS method, show according to result of study, the positioning precision of Hybrid POCS method is better than front several method, but, when primary user is away from perception user, due to hyperbolic projections location in Hybrid POCS algorithm for primary user outside perception user polygon convergence point comparatively large by noise fluctuations, therefore error increases along with range finding and increases.
Summary of the invention
The present invention is intended to solve above-mentioned technological deficiency, proposes a kind of being applied in cognition network the backtracking convex set projection algorithm (BackCheck POCS) that primary user positions.
The method comprises the following steps:
Step one, with the coordinate of L perception user for the center of circle, utilize convex set projection algorithm to carry out Mc to primary user and walk rectangular projection iteration, obtain Mc iteration point x k, wherein k=1,2,3 ..., Mc;
Step 2., to Mc the iteration point obtained in step one, carry out mc step backtracking audit by comparison, calculate the distance between adjacent iteration point || x m+1-x m||, wherein, m=Mc-1 ..., Mc-mc
Step 3. if in the backtracking audit by comparison in step 2, the distance between adjacent iteration point is all less than λ and non-vanishing, then using the positioning result of L iteration average last in step one as primary user's positional information; If in the backtracking audit by comparison in step 2, the distance existence part between adjacent iteration point is zero or is greater than the situation of λ, continues to perform step 4;
Step 4. walk iteration result x with Mc mcfor initial point b 0, carry out rectangular projection iteration on convex set circle border, territory, iteration checks that step number is Mb, obtains Mb iteration point b h, wherein h=1,2,3 ... Mb;
Step 5., to Mb the iteration point obtained in step 4, carry out mb step backtracking audit by comparison, calculate the distance value between adjacent two iteration points || b n+1-b n||, wherein, n=Mb-1 ..., Mb-mb, and compare with threshold value λ;
Step 6. if in the backtracking audit by comparison in step 5, the distance value between adjacent iteration point is all less than λ, then using the positioning result of L iteration average last in step 4 as primary user's positional information; If in the backtracking audit by comparison in step 5, there is the situation being greater than λ in the distance value between adjacent iteration point, jumps to step 4 and walk iteration result b with Mb mbfor initial point b 0, and convert Projection Iteration order, until the distance value between adjacent iteration point is all less than λ.
Preferably, described step one comprises:
1.1) initialization step: initial point x is set 0, wherein x 0for a bit on optional position;
1.2) following formula is utilized to carry out Projection Iteration:
Wherein, represent orthogonal convex set projection point, represent P ito P i+1vector; P ibe the position coordinates of i-th perception user, i ∈ [1, L].D ifor with i-th perception user for the center of circle, convex set that record with i-th perception user and between primary user distance measure is radius circle territory.
Preferably, the value size of λ depends on the mean value of perception user to primary user's range measurement, and λ is a small value relative to this average distance.
Preferably, mb and mc value is identical, is the integral multiple of L.
Preferably, described step 4 comprises:
4.1) initialization step: 1) initial point b is set 0, b 0=x mc
4.2) following formula is utilized to carry out Projection Iteration:
b h+1=P hmodL(b h),h=0,1,2,3…Mb-1
Wherein, P i ( y ) = arg min x ∈ C i | | y - x | | = P i + d i * y - P i | | y - P i | |
Wherein, P ibe the position coordinates of i-th perception user, i ∈ [1, L].D iit is that i-th perception user records and between primary user distance measure; C i={ y ∈ R 2: || y-P i||=d ibe i-th determined radius of perception user be d iround edge circle.
This algorithm is based on the improvement of convex set projection location algorithm, compensate for the deficiency of existing convex set projection location algorithm, impact by range error is relatively little, be applicable to being applied to perception user in cognitive radio networks and, to the acquisition link of primary user's positional information, the location to primary user can be realized more accurately.
Accompanying drawing explanation
Fig. 1 is the flow chart based on BackCheck POCS localization method in the present invention.
Fig. 2 is the iteration schematic diagram that the present invention is based on BackCheck POCS localization method.
Fig. 3 is the position error contrast schematic diagram of BackCheck POCS and Hybrid POCS.
Fig. 4 is the contrast schematic diagram that different range error affects BackCheck POCS and Hybrid POCS position error.
Being exemplary below by the embodiment be described with reference to the drawings, only for explaining the present invention, and can not limitation of the present invention being interpreted as.
Suppose there be L the location of perception user participation to primary user, the position coordinates of L perception user is known, is expressed as:
{ P i = ( X i Y i ) ∈ R 2 } i = 1 L
That L perception user records and between primary user distance measure is expressed as:
{ d i > 0 } i = 1 L
With each perception user for the center of circle, with distance measure d ifor the convex set circle domain representation of radius is:
{ D i ⋐ R 2 } i = 1 L
I-th determined radius of perception user is d iround edge circle be expressed as follows:
C i={y∈R 2:||y-P i||=d i}
Localization method of the present invention POCS algorithm used can be Circular POCS, Hyperbolic POCS and Boundary POCS.Now for Circular POCS algorithm, provide the concrete steps based on BackCheck POCS algorithm:
Step one. with the coordinate of L perception user for the center of circle, utilize Circular POCS to carry out Mc to primary user and walk rectangular projection iteration, obtain Mc iteration point x 1, x 2... x mc-1, x mc.
Check that step number is Mc in the iteration of this setting Circular POCS, because the convergence rate of Circular POCS is very fast, the value of Mc suitably can get a smaller value.
According to the Projection Iteration rule of Circular POCS, the step of primary user being carried out to Mc step rectangular projection iteration is:
1) initialization: initial point x is set 0, wherein x 0for any point in plane, as shown in square in Fig. 2;
2) the rectangular projection iteration of the circular POCS simplified is carried out:
Wherein represent orthogonal convex set projection point, represent P ito P i+1vector, the order of iteration can be indicated by i, this order be determine according to the order of perception user; When successive iterations enters endless loop or do not restrain, the order of iteration can be changed, continue iteration.
Step 2. to Mc the iteration point obtained in step one, carry out the backtracking of mc step and check.Calculate the distance between adjacent iteration point || x m+1-x m||, wherein, m=Mc-1 ..., Mc-mc, and compare with threshold value λ.Wherein, the value size of λ depends on the mean value of perception user to primary user's range measurement, and λ is a small value relative to this average distance, such as: the ratio of λ and this average distance is less than or equal to 0.02, consider the computational complexity of algorithm, this ratio can be limited in 0.005 ~ 0.02 further.
Backtracking checks step number to be the value of mc, this mc is the integral multiple of the number L of the perception user participating in location.
If step 3. in the backtracking audit by comparison in step 2, distance between adjacent iteration point is all less than λ and non-vanishing, then can judge that primary user is positioned within the polygon that perception user formed, by L iteration average last in step one, i.e. the average of the last iteration of each convex set belonging to perception user as the positioning result of the positional information of primary user; If in the backtracking audit by comparison in step 2, the distance existence part between adjacent iteration point is zero or is greater than the situation of λ, continues to perform step 4.
Step 4. walk iteration result x with Mc mcfor initial point b 0, carry out rectangular projection iteration on convex set circle border, territory, iteration checks that step number is Mb, obtains Mb iteration point.
The inspection step number of setting border rectangular projection iteration is Mb, owing to eliminating the judgement being iterated a position, the convergence rate of border rectangular projection iteration is uncertain, may very near rapid convergence to primary user, also slow circulation may be absorbed in, therefore Mb gets higher value, makes border rectangular projection iteration abundant.
Wherein, according to the rule of border rectangular projection iteration, iterative step primary user being carried out to Mb step is:
1) initial point b is set 0, b 0=x mc
2)b h+1=P hmodL(b h),h=0,1,2,3...Mb-1
Wherein, P i ( y ) = arg min x ∈ C i | | y - x | | = P i + d i * y - P i | | y - P i | |
Step 5. to Mb the iteration point obtained in step 4, carry out backtracking mb and walk inspection.Calculate the distance value between adjacent two iteration points, and compare with threshold value λ.
Backtracking checks that step number is mb, and this mb value is identical with mc, is the integral multiple of L.
Step 6. if in the backtracking audit by comparison in step 5, the distance value between adjacent iteration point is all less than λ, then by L iteration average last in step 4, i.e. the average of the last iteration of each convex set belonging to perception user as the positioning result of the positional information of primary user; If in the backtracking audit by comparison in step 5, there is the situation being greater than λ in the distance value between adjacent iteration point, illustrate that border rectangular projection is after have passed through Mb and walking abundant iteration, does not still converge near primary user position, but be absorbed in slow loop iteration.Now, jump procedure four continues to perform the borderline rectangular projection iteration in convex set circle territory, wherein, walks Mb in rectangular projection iteration walk iteration result b with previous Mb mbfor initial point b 0, convert original Projection Iteration order, until the distance value between adjacent iteration point is all less than λ.
Below in conjunction with accompanying drawing and concrete example, the present invention is described in further detail.
Step one. with the coordinate of L perception user for the center of circle, utilize Circular POCS to carry out Mc to primary user and walk rectangular projection iteration, obtain Mc iteration point x k.
Setting perception number of users is L=3, and the position coordinates of perception user is [(700m1500m), (500m1000m), (1000m, 1000m)].Wherein, input white noise perceptually user obtain with the measured value d of the spacing of primary user i, variance is 8m.Setting boss collection Projection Iteration step number is reached the standard grade Mc=10, with coordinate position x 0=(1600m, 2100m) carries out Projection Iteration for original position (as shown in Fig. 2 square), obtains 10 iteration point x k, k=1,2,3 ... 10.
Step 2. to 10 iteration points obtained in step one, carry out the backtracking of mc step and check, backtracking checks that step number is mc=2L=6.Calculate the distance between adjacent iteration point, and compare with threshold value λ.Suppose all participate in location perception user obtains is R with the mean value of the measured value of the spacing of primary user, then inspection door limit value λ is set as one of relative R comparatively in a small amount, and the ratio setting λ and distance average is here λ/R=0.01.
|| x m+1-x m||≤λ, wherein, m=Mc-1 ..., Mc-mc
Step 3. due in the backtracking audit by comparison in step 2, the distance existence part between adjacent iteration point is zero or is greater than the situation of λ, continues to perform step 4.
As can be seen from Figure 2, from initial point x 0start the iteration through two step Circular POCS, iteration point is just stagnated in the intersection area in three convex set circle territories, now according to the result that backtracking inspection judges, there is the situation that a part is zero in the change difference of iteration point, thus continue to perform step 4, carry out to the borderline rectangular projection iteration in convex set circle territory.
Step 4. walk iteration result x with Mc mcfor initial point, carry out the borderline rectangular projection iteration in convex set circle territory and Mb step rectangular projection iteration is carried out to primary user, obtain Mb iteration point b h, h=1,2,3 ... Mb.
First, setting border rectangular projection iterative steps upper limit Mb=30, owing to eliminating the judgement being iterated a position, the convergence rate of border rectangular projection iteration is uncertain, may very near rapid convergence to primary user, also may be absorbed in slow circulation, therefore Mb gets higher value, makes border rectangular projection iteration abundant; Afterwards, according to the rule of border rectangular projection iteration, Mb is carried out to primary user and walks positioning projection, obtain 10 iteration point b h, h=1,2,3 ... 30.
Step 5. to Mb the iteration point obtained in step 4, carry out backtracking mb and walk inspection.The step number mb=2L=6 that backtracking checks.Calculate the distance value between adjacent two iteration points, and compare with threshold value λ.
Step 6. in iteration after Mb step, backtracking checks the iteration point changing value of mb=6 step, find that the distance value between adjacent iteration point exists the situation being greater than λ, Projection Iteration has been absorbed in slow circulation Projection Iteration, therefore, need to jump to step 4, and walk the iteration result of Mb step in rectangular projection iteration for initial point b with Mb first 0again perform the convex set circle borderline Mb in territory and walk rectangular projection iteration, now convert Projection Iteration order first, the order of former Projection Iteration is changed into P2-P3-P1 by P1-P2-P3, when again walking iteration through Mb, backtracking checks mb=6 step, finds that the changing value of iteration point is less than thresholding λ, illustrate near iteration convergence primary user position, therefore second time Mb is walked last L iteration average (as shown in Fig. 2 asterisk) in rectangular projection iteration and determine primary user position.
Fig. 3 is the location simulation results contrast figure of Hybrid POCS location algorithm and BackCheck POCS location algorithm.In figure, abscissa is emulation number of repetition, and ordinate is difference between estimated position and target actual position and the ratio of actual distance mean value between perception user to primary user.As can be seen from Figure 3, generally the positioning precision of two kinds of algorithms relatively, but in some cases, the positioning precision of BackCheckPOCS location algorithm compares and has superiority.This is because, when primary user is away from perception user, it is obvious that hyp asymptote character easily causes hyp intersection point to be subject to the influence of fluctuations of distance measuring noises, therefore in this case, can find out that the locating effect of BackCheck POCS algorithm is more superior than HybridPOCS algorithm.
Fig. 4 describes Hybrid POCS location algorithm from BackCheck POCS location algorithm under different range error affects, the comparison of positioning precision.As can be seen from Figure 4, BackCheck POCS location algorithm has certain advantage than Hybrid POCS location algorithm, this mainly due to hyperbolic projections location in Hybrid POCS algorithm for primary user outside perception user polygon convergence point comparatively large by noise fluctuations, therefore along with the increase of range error.
Although illustrate and describe embodiments of the invention, for the ordinary skill in the art, be appreciated that and can carry out multiple change, amendment, replacement and modification to these embodiments without departing from the principles and spirit of the present invention, scope of the present invention is by claims and equivalency thereof.

Claims (4)

1. in cognitive radio networks to primary user location a method, it is characterized in that, the method comprises the following steps:
Step one, with the coordinate of L perception user for the center of circle, utilize convex set projection algorithm to carry out Mc to primary user and walk rectangular projection iteration, obtain Mc iteration point x k,wherein k=1,2,3 ..., Mc;
Step 2., to Mc the iteration point obtained in step one, carry out mc step backtracking audit by comparison, calculate the distance between adjacent iteration point || x m+1-x m||, wherein, m=Mc-1 ..., Mc-mc, and compare with threshold value λ;
Step 3. if in the backtracking audit by comparison in step 2, the distance between adjacent iteration point is all less than λ and non-vanishing, then using the positioning result of L iteration average last in step one as primary user's positional information; If in the backtracking audit by comparison in step 2, the distance existence part between adjacent iteration point is zero or is greater than the situation of λ, continues to perform step 4;
Step 4. walk iteration result x with Mc mcfor initial point b 0, carry out rectangular projection iteration on convex set circle border, territory, iteration checks that step number is Mb, obtains Mb iteration point b h, wherein h=1,2,3 ..., Mb;
Step 5., to Mb the iteration point obtained in step 4, carry out mb step backtracking audit by comparison, calculate the distance value between adjacent two iteration points || b n+1-b n||, wherein, n=Mb-1 ..., Mb-mb, and compare with threshold value λ;
Step 6. if in the backtracking audit by comparison in step 5, the distance value between adjacent iteration point is all less than λ, then using the positioning result of L iteration average last in step 4 as primary user's positional information; If in the backtracking audit by comparison in step 5, there is the situation being greater than λ in the distance value between adjacent iteration point, jumps to step 4 and walk iteration result b with Mb mbfor initial point b 0, and convert Projection Iteration order, until the distance value between adjacent iteration point is all less than λ;
Described step one comprises:
1.1) initialization step: initial point x is set 0, wherein x 0for a bit on optional position;
1.2) following formula is utilized to carry out Projection Iteration:
,k=0,1,2...Mc-1
Wherein, represent orthogonal convex set projection point, represent P ito P i+1vector; P ibe the position coordinates of i-th perception user, i ∈ [1, L]; D ifor with i-th perception user for the center of circle, convex set that record with i-th perception user and between primary user distance measure is radius circle territory.
2. the method to primary user location in cognitive radio networks as claimed in claim 1, it is characterized in that, the value size of λ depends on the mean value of perception user to primary user's range measurement, and λ is a small value relative to this average distance.
3. the method to primary user location in cognitive radio networks as claimed in claim 1, it is characterized in that, mb and mc value is identical, is the integral multiple of L.
4. the method to primary user location in cognitive radio networks as claimed in claim 1, it is characterized in that, described step 4 comprises:
4.1) initialization step: 1) initial point b is set 0, b 0=x mc
4.2) following formula is utilized to carry out Projection Iteration:
b h+1=P h mod L(b h),h=0,1,2,3...Mb-1
Wherein, if h mod L is i, b hfor y, then P i ( y ) = arg min x ∈ C 1 | | y - x | | = P i + d i * y - P i | | y - P i | |
Wherein, P ibe the position coordinates of i-th perception user, i ∈ [1, L]; d iit is that i-th perception user records and between primary user distance measure; C i={ y ∈ R 2: || y-P i||=d ibe i-th determined radius of perception user be d iround edge circle.
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