CN101944961A - Double threshold cooperative sensing method in cognitive wireless network - Google Patents

Abstract

The invention discloses a double threshold cooperative sensing method in a cognitive wireless network, comprising the following steps: 1. recovering a signal through local compressed sensing, and recovering the whole broadband frequency spectrum in the invention through the compressed sensing, thus a low-speed A/D commutator can be used, so as to lower the hardware requirement; 2. determining a sub frequency band, being capable of obtaining a frequency spectrum edge point of the recovered broadband frequency spectrum signal through the compressed sensing through a wavelet edge detection, and forming a plurality of sub frequency bands by segmenting the frequency spectrum; and 3. cooperative sensing: carrying out double threshold energy detection on all sub frequency bands by each cognitive user, transmitting the detection result to a fusion center for judgment to obtain the existing condition of the main user of the whole frequency spectrum, and self-adaptively determining the position of the spectrum hole in the frequency band. Through the steps, the cognitive network can carry out sampling sensing on the main user signals under the condition of low nyquist frequency, and can self-adaptively determine the position of the spectrum hole in the frequency band.

Description

Double threshold cooperative sensing method in a kind of cognition wireless network

Technical field

The invention belongs to the cognitive radio technology field, more specifically say, relate to the double threshold cooperative sensing method in a kind of cognition wireless network.

Background technology

Along with the development of dynamic frequency spectrum deployment (Dynamic Spectrum Access) in recent years, cognitive radio is devoted to solve the frequency spectrum resource problem of shortage from the angle of spectrum allocation may.Cognitive radio should be able to exist or potential frequency spectrum hole in the adaptive identification surrounding environment, and main users is not being caused under the situation of interference, known frequency spectrum hole is used, and cognitive radio is considered to satisfy the technology of people to the broader frequency spectrum demand.

In theory, cognitive radio can conscious perception surrounding environment, and utilizes the frequency spectrum resource that is in idle state to communicate.Therefore, cognitive radio has very high demand to the frequency spectrum perception ability.But the frequency spectrum perception technology based on Shannon's theorems can not satisfy demands of applications in the environment of broader frequency spectrum at present: on the one hand, sample rate keeps or surpasses the nyquist sampling rate becoming more and more difficult; On the other hand, only be to have reduced signal based on the sampling of Shannon's theorems, and the relevant information of frequency spectrum hole information does not obtain handling.

Summary of the invention

The object of the invention is to overcome the deficiency of existing cognitive radio technology, double threshold cooperative sensing method in a kind of cognition wireless network is proposed, can be lower than nyquist frequency, and can determine the position of frequency spectrum hole in frequency band adaptively the perception of sampling of main subscriber signal.

For achieving the above object, the double threshold cooperative sensing method in the cognition wireless network of the present invention is characterized in that, may further comprise the steps:

(1), the local compressed sensing and the recovery of main signal

In the broadband cognitive network, have 1,2 ..., I main user and 1,2 ..., J cognitive user, cognitive user j, j=1,2 ..., J adopts the main subscriber signal r of low rate A/D converter to receiving _j(t) carry out compression sampling, its sample frequency is lower than nyquist frequency, obtains compression sampling signal x _j(t);

According to compression sampling x _j(t) recover, signal is restored

(2), Wavelet Edge Detection

A1, all cognitive user j incite somebody to action restoring signal separately

Send to fusion center, at first J restoring signal asked on average at fusion center, so that rim detection is more accurate;

$X=\frac{1}{J}\underset{j=1}{\overset{J}{\mathrm{\Σ}}}{\hat{r}}_j\left(t\right)$

X represents restoring signal

Average;

Then, ask the power density of restoring signal average X:

$S_X\left(f\right)={\&Integral;}_{-\&infin;}^{+\&infin;}{R}_X\left(\mathrm{\&tau;}\right)\&CenterDot;e^{-\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HSA00000256642300012.png"\; state="\{\{state\}\}">j</figure-callout>}2\mathrm{\&pi;f\&tau;}}\mathrm{d\&tau;}$

Wherein, S _X(f) represent the power spectral density of restoring signal average X, R _X(τ) represent the auto-correlation function of restoring signal average X;

A2, to power spectral density S _X(f) carry out multi-scale wavelet transformation:

$W_s{S}_X\left(f\right)=\underset{s=1}{\overset{S}{\mathrm{\&Pi;}}}{W}_{2^s}{S}_X\left(f\right)$

$=\underset{s=1}{\overset{S}{\mathrm{\&Pi;}}}{\mathrm{\&phi;}}_{2^s}\left(f\right)*S_X\left(f\right)$

W _sS _X(f) represent multi-scale wavelet transformation result, 2 ^sBe scale factor, * represents convolution algorithm, and the span of S is an integer;

Then, to wavelet transformation W as a result _sS _X(f) ask the single order inverse:

W _s' S _X(f) be W _sS _X(f) ask the result of first derivative.

Be

Yardstick single order derived function.

W as a result to first derivative _s' S _X(f) ask extreme value to transport, obtain some extreme points

Be the estimated value of frequency spectrum marginal point:

It is the number of frequency spectrum marginal point that extreme value computing, n are asked in expression;

(3), double threshold energy cooperative detection

B1, cognitive user j, j=1,2 ..., the estimated value of the frequency spectrum marginal point that J obtains according to fusion center

Broader frequency spectrum is divided into the experimental process frequency range, to each frequency sub-band k, k=1,2 ..., n carries out double threshold cooperation energy measuring:

Cognitive user j is at first according to restoring signal Calculating is in each frequency sub-band In the received signal energy:

$E_{k,j}={\&Integral;}_{{\hat{f}}_{k-1}}^{{\hat{f}}_k}{\left|{\hat{r}}_f^{\left(j\right)}\right|}^2\mathrm{df}$

Wherein, E _{K, j}J is at frequency sub-band for the expression cognitive user

The received signal energy,

Represent the restoring signal of this cognitive user j through compressed sensing

Frequency-domain expression;

B2, cognitive user j are to each frequency sub-band In the received signal ENERGY E _{K, j}Judge, and send judged result to fusion center:

If received signal ENERGY E _{K, j}Be between two thresholdings, send E so _{K, j}Energy value; If be lower than low threshold, determine that then main users does not exist in the k frequency sub-band, sends 0; If be higher than high threshold, then determine to have main users in the k frequency sub-band, send 1, that is:

$L_{k,j}=\left\{\begin{array}{c}\mathrm{0,0}<E_{k,j}<{\mathrm{\&eta;}}_0\\ 1,E_{k,j}>{\mathrm{\&eta;}}_1\end{array}\right.$

R _{K, j}Represent k the frequency sub-band received signal energy judged result that j cognitive user sends, η ₀Represent low threshold, η ₁Represent high threshold;

All cognitive user j with it to each frequency sub-band

Received signal energy judged result R _k, j, k=1,2 ..., n sends to fusion center;

The energy signal E of fusion center to receiving _{K, j}Carry out the second time and judge, at fusion center, in J cognitive user, have P to send the result of determination of determining, so always total J-P cognitive user sent energy value, and fusion center is with the signal energy E that receives _{K, j}Carry out determination processing:

$D_k=\left\{\begin{array}{c}\mathrm{0,0}\&le;\underset{j=1}{\overset{J-K}{\mathrm{\&Sigma;}}}{E}_{k,j}\&le;\mathrm{\&lambda;}\\ 1,\underset{j=1}{\overset{J-K}{\mathrm{\&Sigma;}}}{E}_{k,j}\&GreaterEqual;\mathrm{\&lambda;}\end{array}\right.$

D _kExpression is to the result of determination of k frequency sub-band energy information, and λ represents to judge for the second time the thresholding that uses;

Fusion center to the end product that this frequency sub-band k judges is:

D[k] represent the result of determination of fusion center, d[k]=0 represent the k frequency sub-band not have main subscriber signal, d[k]=1 represent the k frequency sub-band to have main subscriber signal;

Other frequency sub-band are carried out identical energy measuring and judgement, know the situation that exists of the interior whole main subscriber signals of whole broader frequency spectrum, determine the position of frequency spectrum hole in frequency band adaptively.

In the present invention, pass through following steps:

1, local compressed sensing restoring signal

Because the poor efficiency of broader frequency spectrum, the main users signal will inevitably show as sparse signal at frequency domain, and it is zero that a large amount of position energy is promptly arranged on whole broadband, and this point meets the application scenarios of compressed sensing.In the present invention, whole broader frequency spectrum is recovered out, reduced requirement like this, can use the low rate A/D converter, thereby reduce hardware requirement for the sampling A/D converter by compressed sensing.

2, determine sub-band

The broader frequency spectrum signal that compressed sensing is recovered out can access the frequency spectrum marginal point of this signal by Wavelet Edge Detection, can be segmented into plurality of sub-bands afterwards on frequency spectrum.

3, cooperative sensing

Each cognitive user is all carried out the double threshold energy measuring to all sub-bands, and testing result is sent to fusion center judges, obtains entire spectrum master user's the situation that exists, and determines the position of frequency spectrum hole in frequency band adaptively.

By above step, cognition network can be lower than nyquist frequency to the perception of sampling of main subscriber signal, and can determine the position of frequency spectrum hole in frequency band adaptively.

Description of drawings

Fig. 1 is a kind of embodiment theory diagram of the double threshold cooperative sensing method in the cognition wireless network of the present invention;

Fig. 2 is under the different compression samplings ratios, the fusion center restoring signal

The spectrogram of average;

Fig. 3 is that different compression samplings compares down the frequency spectrum edge point position figure that the fusion center Wavelet Edge Detection goes out;

Fig. 4 is different compression samplings than under, the different cognitive users quantity, and cognition network is to the cooperate figure as a result of double threshold energy perception of the main signal of the frequency sub-band that using.

Embodiment

Below in conjunction with accompanying drawing the specific embodiment of the present invention is described, so that those skilled in the art understands the present invention better.What need point out especially is that in the following description, when perhaps the detailed description of known function and design can desalinate main contents of the present invention, these were described in here and will be left in the basket.

Fig. 1 is a kind of embodiment theory diagram of the double threshold cooperative sensing method in the cognition wireless network of the present invention.

In the broadband cognitive network, have 1,2 ..., I main user and 1,2 ..., J cognitive user.

In this enforcement, as shown in Figure 1, a main user baseband signal bandwidth B=20MHz through ovennodulation, moves carrier frequency f _cOn=the 2GHz, send by channel then.In Fig. 1, the process of transmitting of the main subscriber signal that only drawn, other main user's process of transmitting is identical, so do not draw.

Equally, in Fig. 1, a cognitive user receives the main subscriber signal r that each main user sends _j(t), sample with the low rate A/D converter then, obtain compression sampling signal x _j(t), according to compression sampling x _j(t) recover, signal is restored

Carry out the frequency spectrum segmentation with Wavelet Edge Detection then, obtain some extreme points

Be the estimated value of frequency spectrum marginal point, broader frequency spectrum is divided into n frequency sub-band.At last,, the signal in each frequency sub-band is carried out integration, obtains its energy, judge according to energy whether this frequency sub-band exists the judgement d[n of main signal according to obtaining n frequency sub-band], from determining the position of frequency spectrum hole frequency band adaptively.

In cognition network, the signal that each cognitive user j receives is:

$r_j\left(t\right)=\underset{i=1}{\overset{I}{\mathrm{\&Sigma;}}}{h}_{\mathrm{ij}}\left(t\right)*s_i\left(t\right)+w_j\left(t\right)$

Wherein, s _i(t) expression comes from the signal of i main users.r _j(t) j signal that cognitive user receives of expression.h _Ij(t) frequency response of expression channel.w _j(t) be illustrated in white Gaussian noise signal on this channel, average is zero.* represent convolution algorithm.

Following formula is carried out in the M point discrete Fourier can obtaining behind the leaf transformation:

$r_f^{\left(j\right)}=\underset{i=1}{\overset{I}{\mathrm{\&Sigma;}}}{h}_f^{\left(\mathrm{ij}\right)}\&CenterDot;s_f^{\left(i\right)}+w^{\left(j\right)}$

Wherein, M is greater than the channel memory span.

And w (j) is respectively h _Ij(t), s _i(t) and w _j(t) frequency-domain expression.

Because the signal that cognitive user j receives

Being sparse signal, according to the compressed sensing theory, is K for degree of rarefication _bReceived signal r _j(t), as long as satisfy 1≤K _b＜＜M needs K measurement number just can recover fully, and restoring signal is

Wherein, K=CK _bLogM, C are the over-sampling coefficient.

Fig. 2 be different compression samplings than under the K/M, the fusion center restoring signal

The spectrogram of average, wherein, (a) is main subscriber signal r among the figure _j(t) spectrogram, all the other (b)～(e) are respectively different compression samplings than K/M=8%, 10%, 14%, 20% time, fusion center restoring signal

The spectrogram of average.In the present embodiment, carry out emulation in spectral range 0Hz～9GHz.Degree of rarefication K _b=50, the frequency domain M=2000 that counts, sampling number K=800.As can be seen from Figure 2, as long as satisfy K=CK _bLogM＜＜M all can recover main subscriber signal r well _j(t).

Fig. 3 be different compression sampling than under the K/M, the frequency spectrum edge point position figure that the fusion center Wavelet Edge Detection goes out.As shown in Figure 3, in the present embodiment, detected frequency spectrum marginal point has four, is respectively

It is right to have only

Carry out integral operation, just obtain having certain received signal energy, have two thereby judge main signal, the center that is respectively is the signal of 0.1078G and center 3.022 in 1.023GHz, bandwidth, bandwidth is the signal of 0.108GHz, and other do not use frequency to be the frequency spectrum hole.

Fig. 4 be different compression samplings than under the K/M, under the different cognitive users quantity, cognition network is to the cooperate figure as a result of double threshold energy perception of the main signal of the frequency sub-band [0.9692GHz 1.077GHz] that using.As shown in Figure 2, cognitive user quantity J quantity is many more, and sensing results is just reliable more, and compression sampling is lower than at 0.1 o'clock than K/M, and the reliability of sensing results descends significantly, and 0.16 when above, sensing results promptly detects accuracy rate Qd and is tending towards 1 compression sampling than K/M.

Although above the illustrative embodiment of the present invention is described; so that the technical staff of present technique neck understands the present invention; but should be clear; the invention is not restricted to the scope of embodiment; to those skilled in the art; as long as various variations appended claim limit and the spirit and scope of the present invention determined in, these variations are conspicuous, all utilize innovation and creation that the present invention conceives all at the row of protection.

Claims (2)

1. the double threshold cooperative sensing method in the cognition wireless network is characterized in that, may further comprise the steps:

(1), the local compressed sensing and the recovery of main signal

In the broadband cognitive network, have 1,2 ..., I main user and 1,2 ..., J cognitive user, cognitive user j, j=1,2 ..., J adopts the main subscriber signal r of low rate A/D converter to receiving _j(t) carry out compression sampling, its sample frequency is lower than nyquist frequency, obtains compression sampling signal x _j(t); According to compression sampling x _j(t) recover, signal is restored

(2), Wavelet Edge Detection

A1, all cognitive user j incite somebody to action restoring signal separately

Send to fusion center, at first J restoring signal asked average at fusion center;

$X=\frac{1}{J}\underset{j=1}{\overset{J}{\mathrm{\&Sigma;}}}{\hat{r}}_j\left(t\right)$

X represents restoring signal

Average;

Then, ask the power density of restoring signal average X:

$S_X\left(f\right)={\&Integral;}_{-\&infin;}^{+\&infin;}{R}_X\left(\mathrm{\&tau;}\right)\&CenterDot;e^{-j2\mathrm{\&pi;f\&tau;}}\mathrm{d\&tau;}$

Wherein, S _X(f) represent the power spectral density of restoring signal average X, R _X(τ) represent the auto-correlation function of restoring signal average X;

A2, to power spectral density S _X(f) carry out multi-scale wavelet transformation:

$W_s{S}_X\left(f\right)=\underset{s=1}{\overset{S}{\mathrm{\&Pi;}}}{W}_{2^s}{S}_X\left(f\right)$

$=\underset{s=1}{\overset{S}{\mathrm{\&Pi;}}}{\mathrm{\&phi;}}_{2^s}\left(f\right)*S_X\left(f\right)$

W _sS _X(f) represent multi-scale wavelet transformation result, 2 ^sBe scale factor, * represents convolution algorithm, and the span of S is an integer;

Then, to wavelet transformation W as a result _sS _X(f) ask the single order inverse:

W _s' S _X(f) be W _sS _X(f) ask the result of first derivative, Be

Yardstick single order derived function.

W as a result to first derivative _s' S _X(f) ask extreme value to transport, obtain some extreme points

Be the estimated value of frequency spectrum marginal point:

It is the number of frequency spectrum marginal point that extreme value computing, n are asked in expression;

(3), double threshold energy cooperative detection

B1, cognitive user j, j=1,2 ..., the estimated value of the frequency spectrum marginal point that J obtains according to fusion center

Broader frequency spectrum is divided into the experimental process frequency range, to each frequency sub-band k, k=1,2 ..., n carries out double threshold cooperation energy measuring:

Cognitive user j is at first according to restoring signal Calculating is in each frequency sub-band

In the received signal energy:

$E_{k,j}={\&Integral;}_{{\hat{f}}_{k-1}}^{{\hat{f}}_k}{\left|{\hat{r}}_f^{\left(j\right)}\right|}^2\mathrm{df}$

Wherein, E _{K, j}J is at frequency sub-band for the expression cognitive user The received signal energy,

Represent the restoring signal of this cognitive user j through compressed sensing Frequency-domain expression;

B2, cognitive user j are to each frequency sub-band In the received signal ENERGY E _{K, j}Judge, and send judged result to fusion center:

If received signal ENERGY E _{K, j}Be between two thresholdings, send E so _{K, j}Energy value; If be lower than low threshold, determine that then main users does not exist in the k frequency sub-band, sends 0; If be higher than high threshold, then determine to have main users in the k frequency sub-band, send 1, that is:

$L_{k,j}=\left\{\begin{array}{c}\mathrm{0,0}<E_{k,j}<{\mathrm{\&eta;}}_0\\ 1,E_{k,j}>{\mathrm{\&eta;}}_1\end{array}\right.$

R _{K, j}Represent k the frequency sub-band received signal energy judged result that j cognitive user sends, η ₀Represent low threshold, η ₁Represent high threshold;

All cognitive user j with it to each frequency sub-band

Received signal energy judged result R _{K, j}, k=1,2 ..., n sends to fusion center;

The energy signal E of fusion center to receiving _{K, j}Carry out the second time and judge, at fusion center, in J cognitive user, have P to send the result of determination of determining, so always total J-P cognitive user sent energy value, and fusion center is with the signal energy E that receives _{K, j}Carry out determination processing:

$D_k=\left\{\begin{array}{c}\mathrm{0,0}\&le;\underset{j=1}{\overset{J-K}{\mathrm{\&Sigma;}}}{E}_{k,j}\&le;\mathrm{\&lambda;}\\ 1,\underset{j=1}{\overset{J-K}{\mathrm{\&Sigma;}}}{E}_{k,j}\&GreaterEqual;\mathrm{\&lambda;}\end{array}\right.$

D _kExpression is to the result of determination of k frequency sub-band energy information, and λ represents to judge for the second time the thresholding that uses;

Fusion center to the end product that this frequency sub-band k judges is:

D[k] represent the result of determination of fusion center, d[k]=0 represent the k frequency sub-band not have main subscriber signal, d[k]=1 represent the k frequency sub-band to have main subscriber signal;

Other frequency sub-band are carried out identical energy measuring and judgement, know the situation that exists of the interior whole main subscriber signals of whole broader frequency spectrum, determine the position of frequency spectrum hole in frequency band adaptively.

2. the double threshold cooperative sensing method in the cognition wireless network according to claim 1 is characterized in that, the compression sampling described in the step (1), its compression sampling than K/M greater than 0.16, wherein, M carries out counting of discrete Fourier transform, and K is for measuring number.

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