CN105471529A - Spectrum signal sensing method and device - Google Patents

Abstract

The invention provides a spectrum signal sensing method and device. The method comprises the following steps: determining a weighted term v(pi) corresponding to the ith element of a spectrum signal vector according to the ith element in a reconstruction spectrum signal (the formula is described in the specification) obtained by (k-1)th iteration and the minimum distance of the elements in a support set of (the formula is described in the specification); ai expresses the ith column of a known measurement matrix, rk-1 expresses a residual error, adding the imkth column of the known measurement matrix in a measurement matrix reconstruction atom set obtained in the (k-1)th iteration to form a measurement matrix reconstruction atom set updated by k th iteration; determining the reconstruction spectrum signal (the formula is described in the specification) of the k th iteration according to the minimum value of (the formula is described in the specification); and wherein, Y expresses a measured value of the spectrum signal to be reconstructed, and (the formula is described in the specification) expresses the measurement matrix reconstruction atom set updated by the k th iteration. The spectrum signal sensing method and device provided by the invention are convenient to apply and can be used for improving the signal reconstruction performance.

Description

Spectrum signal cognitive method and device

Technical field

The present invention relates to wireless communication field, particularly relate to a kind of spectrum signal cognitive method and device.

Background technology

Along with the growth of radio communication service, available frequency band day is becoming tight, and the problem of frequency spectrum resource scarcity is day by day serious.The existing frequency usage policy in countries in the world adopts license granting mechanisms mostly, and the user secured permission the not round-the-clock licensed band that takies, in some band portion times, user does not use, and separately has some just occupied once in a while.How to improve the availability of frequency spectrum, in zones of different and different time sections, effectively utilize different idle channels, become the technical problem that people pay special attention to.

Cognition wireless network is a kind of new intellectual technology for improving wireless communication spectrum utilance.The Wireless Telecom Equipment with cognitive function can environment around perception, recycling distributes to authorized user, but under a certain specific moment and environment, do not have occupied frequency band, namely dynamically " frequency spectrum cavity-pocket " is recycled, to realize no matter when and where can ensureing the high efficiency that wireless frequency spectrum utilizes.Therefore, perceived spectral environment is the primary task of cognitive radio, and it embodies the most significant feature of cognitive radio: can perception analyze the frequency range of specific region, finds out the spectrum interposition being applicable to communication.

At present, the spectrum signal cognitive method of compressed sensing technology is adopted to obtain more concern.Compressive sensing theory is pointed out: if signal is sparse (or compressible), so just can to sample to signal far below the sample rate of Nyquist (Nyquist) speed, and with high probability Accurate Reconstruction original signal.In compressive sensing theory, can carry out under low sampling rate the sampling of signal, therefore the requirement of sample devices be reduced greatly.

Distributed compression perception utilizes correlation and cross correlation in signal to carry out combined reconstruction to multiple signal, takes full advantage of the temporal correlation of distributed sensor data, decreases transmitted data amount, further reduce communication overhead.Joint sparse model (jointsparsemodel, JSM) is the basis that distributed compression perception theory is set up, and whether contain common sparse part according in all signals, JSM can be divided into three kinds of models, JSM-1, JSM-2, JSM-3.

In JSM-1 model, related sparse spectrum signal is added by common ground and unique portion and forms, namely

s _j＝z _c+z _j,j∈{1,2,…,J}

Signal z _crepresent all s _jcommon ground, signal z _jrepresent each s _junique portion, and two parts are all sparse.JSM-1 model is highly suitable for the modeling to frequency spectrum.Common ground corresponds to all sensing nodes frequency spectrum that can receive, unique portion corresponding to the frequency spectrum only having certain sensing node to receive, the frequency spectrum namely only used near this sensing node.

The combined signal reconfiguration scheme overwhelming majority under existing JSM-1 model adopts l ₁norm algorithm realization, this algorithm quality reconstruction is better, but its speed is slow, is difficult to practical application for solution large scale problem; Under JSM-1 model based on l ₀the restructing algorithm speed of norm, but this kind of algorithm needs the prior informations such as known degree of rarefication, and these prior informations are difficult to obtain, and limit its practical application.

Summary of the invention

The embodiment of the present invention provides a kind of spectrum signal cognitive method and device, in order to solve the problem in frequency spectrum sensing method of the prior art, the requirement of signal element nonzero probability prior information being limited to its practical application.

The spectrum signal cognitive method that the embodiment of the present invention provides, comprising:

According to the reconstructed spectrum signal that kth-1 iteration obtains in i-th element and described support set in the minimum range of each element, determine the weighted term v (p that spectral signal vector i-th element is corresponding _i); The support set of reconstructed spectrum signal represents the set of nonzero element position in described reconstructed spectrum signal; I and k be more than or equal to 1 integer;

Determine to make reach the value of the i of maximum, in kth time iteration, this value is designated as i _mk; Wherein, a _irepresent the i-th row of known calculation matrix, r _k-1the residual error of the measured value of the described spectrum signal rebuild after representing the measured value of spectrum signal and kth-1 iteration;

By the i determined in described kth time iteration _mkvalue joins in the support set of the reconstructed spectrum signal that kth-1 iteration obtains, and forms the support set after upgrading in kth time iteration, and by i-th of described known calculation matrix _mkrow add the calculation matrix obtained in kth-1 iteration and rebuild in atom set, and the calculation matrix formed after kth time iteration renewal rebuilds atom set; The support set of described reconstructed spectrum signal represents the set of nonzero element position in described reconstructed spectrum signal;

According to the reconstructed spectrum signal of minimum value determination kth time iteration wherein, Y represents the measured value of spectrum signal to be reconstructed, represent that the calculation matrix after time iteration renewal of described kth rebuilds atom set, the measured value of the described spectrum signal rebuild after representing described kth time iteration.

In another embodiment, described basis the reconstructed spectrum signal of minimum value determination kth time iteration afterwards, also comprise:

According to the i that described kth time iteration obtains _mk, described in determining i-th _mksubsignal z belonging to individual element _j; Wherein z _j∈ { z _c, z ₁..., z _j, according to upgrade described subsignal z _jsub-support set wherein, n represents described subsignal z _jlength, J represents the number of described frequency spectrum subsignal to be reconstructed, J and N be more than or equal to 1 integer; z _crepresent the common ground of described J frequency spectrum subsignal to be reconstructed, z ₁..., z _jrepresent the unique portion of described J frequency spectrum subsignal to be reconstructed;

Determine described subsignal z _jsub-support set element number whether reach described signal z _jdegree of rarefication K _j∈ { K _c, K ₁..., K _j, wherein, degree of rarefication K _c, K ₁..., K _jrepresent subsignal z _c, z ₁..., z _jmiddle nonzero element number; If reached, then kth+1 iteration finds i _{m (k+1)}time do not consider subsignal z _jany element.

In another embodiment, the described i obtained according to described kth time iteration _mk, described in determining i-th _mksubsignal z belonging to individual element _jalso comprise: described in determining i-th _mkindividual element is at described subsignal z _jin position i', for finding i in kth+1 iteration _{m (k+1)}time do not consider i-th in each subsignal ' individual element.

In another embodiment, the described reconstructed spectrum signal obtained according to kth-1 iteration in i-th element and described support set in weighted term corresponding to minimum range determination spectral signal vector i-th element of each element comprise:

According to the reconstructed spectrum signal that described kth-1 iteration obtains in i-th element and the support set of reconstructed spectrum signal that obtains of described kth-1 iteration in the minimum range of each element, determine the nonzero probability of described reconstructed spectrum signal i-th element;

Weighted term v (the p of described reconstructed spectrum signal i-th element is determined according to the nonzero probability of i-th element in described reconstructed spectrum signal _i).

In another embodiment, the described reconstructed spectrum signal obtained according to described kth-1 iteration in i-th element and the support set of reconstructed spectrum signal that obtains of described kth-1 iteration in the minimum range of each element, determine the nonzero probability of described reconstructed spectrum signal i-th element, comprising:

According to

p _i＝C·exp(-n _i/α)

Determine the nonzero probability of described reconstructed spectrum signal i-th element;

Wherein, p _irepresent the nonzero probability of i-th element, C represents a constant, is positive count, n _irepresent the reconstructed spectrum signal that kth-1 iteration obtains the minimum value of the distance of each element in the support set of the reconstructed spectrum signal that i-th element and described kth-1 iteration obtain, α represents decay factor, control p _ithe speed of decay.

In another embodiment, the described nonzero probability according to i-th element in described reconstructed spectrum signal determines the weighted term of described reconstructed spectrum signal i-th element, comprising:

According to

$v\left(p_i\right)=\frac{g}{2}\left(2\right(K+1-k)-1+2{\left(\frac{\mathrm{\σ}}{g}\right)}^2)log\frac{p_i}{1-p_i}$

Determine the weighted term of described reconstructed spectrum signal i-th element;

Wherein, v (p _i) representing the weighted term of described reconstructed spectrum signal i-th element, g is the average of nonzero element in the measured value of described spectrum signal, and σ is the standard deviation of noise, and k represents iterations, and K represents the joint sparse degree of spectrum signal to be reconstructed, wherein, K=K _c+ K ₁+ ... + K _j.

In another embodiment, describedly determine described subsignal z _jsub-support set element number whether reach described signal z _jdegree of rarefication K _j∈ { K _c, K ₁..., K _j, if reached, then next iteration finds i _{m (k+1)}time do not consider subsignal z _jany element after, also comprise:

The residual error of the measured value rebuild after upgrading the measured value of described spectrum signal and kth time iteration and iterations k;

Judge whether described iterations k meets k>K, if met, then stop iteration.

In another embodiment, describedly judge whether described iterations k meets k>K, if met, then, after stopping iteration, also comprise:

By described reconstructed spectrum signal matrix be split as reconstruction subsignal obtain the reconstructed results of described frequency spectrum subsignal

The embodiment of the present invention also provides a kind of spectrum signal sensing device, comprising:

Determination module, for:

According to the reconstructed spectrum signal that kth-1 iteration obtains in i-th element and described support set in the minimum range of each element, determine the weighted term that spectral signal vector i-th element is corresponding; I and k be more than or equal to 1 integer;

Determine to make or reach the value of the i of maximum, in kth time iteration, this value is designated as i _mk; Wherein, a _irepresent the i-th row of known calculation matrix, r _k-1the residual error of the measured value rebuild after representing the measured value of spectrum signal and kth-1 iteration, v (p _i) represent the weighted term that spectral signal vector i-th element is corresponding; I and k be more than or equal to 1 integer;

Update module, for: by the i determined in described kth time iteration _mkvalue joins in the support set of the reconstructed spectrum signal that kth-1 iteration obtains, form the support set after upgrading in kth time iteration, and the i-th row of calculation matrix described in described kth time iteration are added in the calculation matrix reconstruction atom set obtained in kth-1 iteration, the calculation matrix after formation kth time iteration upgrades rebuilds atom set; The support set of described reconstructed spectrum signal represents the set of nonzero element position in described reconstructed spectrum signal;

Described determination module, also for:

According to the reconstructed spectrum signal of minimum value determination kth time iteration wherein, Y represents the measured value of spectrum signal to be reconstructed, represent that the calculation matrix of kth time iteration rebuilds atom set; the measured value of the described spectrum signal rebuild after representing described kth time iteration.

The embodiment of the present invention also provides another spectrum signal sensing device, comprising: processor and memory, and the software program instructions that described processor is used for storing in execute store realizes the method described in said method embodiment.

The frequency spectrum sensing method that the embodiment of the present invention provides and device, the reconstructed spectrum signal obtained by kth-1 iteration in i-th element and described support set in the minimum range of each element, determine the position i of the nonzero element of kth time iteration intermediate frequency spectrum signal vector _mk, and by i _mkjoin in the support set of the reconstructed spectrum signal that kth-1 iteration obtains, form the support set after upgrading in kth time iteration, and the i-th row of calculation matrix described in described kth time iteration are added in the calculation matrix reconstruction atom set obtained in kth-1 iteration, the calculation matrix after formation kth time iteration upgrades rebuilds atom set; Basis again the reconstructed spectrum signal of minimum value determination kth time iteration wherein, Y represents the measured value of spectrum signal to be reconstructed, represent that the calculation matrix after time iteration renewal of described kth rebuilds atom set, the measured value of the described spectrum signal rebuild after representing described kth time iteration; The frequency spectrum sensing method that the embodiment of the present invention provides, utilizes the minimum range of spectrum signal element and support set element, determines the nonzero probability of spectrum signal element, thus obtains the position of the nonzero element in spectral signal vector, avoids based on l ₀to the requirement of signal element nonzero probability prior information in the restructing algorithm of norm, can be used widely, and the performance of signal reconstruction can be improved.

Accompanying drawing explanation

In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, introduce doing one to the accompanying drawing used required in embodiment or description of the prior art simply below, apparently, accompanying drawing in the following describes is some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.

Fig. 1 is the schematic flow sheet of embodiment of the present invention spectrum signal cognitive method;

Fig. 2 is the structural representation of embodiment of the present invention spectrum signal sensing device;

Fig. 3 is the structural representation of another embodiment of the present invention spectrum signal sensing device;

Fig. 4 is the structural representation of yet another embodiment of the invention spectrum signal sensing device.

Embodiment

For making the object of the embodiment of the present invention, technical scheme and advantage clearly, below in conjunction with the accompanying drawing in the embodiment of the present invention, technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.

The spectrum signal cognitive method that the embodiment of the present invention provides and device are for perception in cognition wireless network and analyze the frequency range of specific region, find out the spectrum interposition being applicable to communication, so that Wireless Telecom Equipment can utilize distribute to authorized user, but under a certain particular moment and environment, there is no occupied frequency band, improve the utilance of wireless frequency spectrum.

The spectrum signal cognitive method that the embodiment of the present invention provides and device are in cognition wireless network, utilize J sensing node and 1 central fusion center to carry out collaborative spectrum sensing.For jth (1≤j≤J) individual sensing node, to be the measured value of the spectrum signal of M be its length received known calculation matrix is then y _j=Φ _js _j, wherein the spectrum signal of to be length be N.According to JSM-1 model, any 1 spectrum signal all can be expressed as s _j=z _c+ z _j, use K _cand K _jrepresent z respectively _cand z _jdegree of rarefication, then joint sparse degree is K=K _c+ ∑ K _j.Because joint sparse degree K is less than the degree of rarefication sum ∑ (K of each node institute perceptual signal _c+ K _j)=NK _c+ ∑ K _j, so can obviously improve signaling protein14-3-3 performance by integrated restoration.The embodiment of the present invention accurately judges the support set of spectrum signal by frequency spectrum sensing method spectrum signal being carried out to integrated restoration, i.e. nonzero element location sets.

Particularly, the measured value that J sensing node receives by fusion center merges, and obtains and calculation matrix corresponding for J spectrum signal is merged by mode below:

Fusion center is when known Y and Φ, and the spectrum signal reconstructed is to be J spectrum signal to be reconstructed to recombinate the result obtained by common ground and unique portion described Z, meets Y=Φ Z; The support set of described spectrum signal Z by the subsignal z of Z _c, z ₁..., z _jsupport set get union and obtain.Wherein, represent described subsignal z respectively _c, z ₁..., z _jsupport set.

Fig. 1 is the schematic flow sheet of embodiment of the present invention spectrum signal cognitive method.Refer to Fig. 1, the spectrum signal cognitive method that the embodiment of the present invention provides comprises:

S101: the reconstructed spectrum signal obtained according to kth-1 iteration in i-th element and described support set in weighted term v (p corresponding to minimum range determination spectral signal vector i-th element of each element _i); The support set of reconstructed spectrum signal represents the set of nonzero element position in described reconstructed spectrum signal; I and k be more than or equal to 1 integer;

Particularly, the described reconstructed spectrum signal obtained according to kth-1 iteration in i-th element and described support set in weighted term corresponding to minimum range determination spectral signal vector i-th element of each element comprise:

According to the reconstructed spectrum signal that described kth-1 iteration obtains in i-th element and the support set of reconstructed spectrum signal that obtains of described kth-1 iteration in the minimum range of each element, determine the nonzero probability of described reconstructed spectrum signal i-th element;

Weighted term v (the p of described reconstructed spectrum signal i-th element is determined according to the nonzero probability of i-th element in described reconstructed spectrum signal _i).

The described reconstructed spectrum signal obtained according to described kth-1 iteration in i-th element and the support set of reconstructed spectrum signal that obtains of described kth-1 iteration in the minimum range of each element, determine the nonzero probability of described reconstructed spectrum signal i-th element, comprising:

According to

p _i＝C·exp(-n _i/α)

Determine the nonzero probability of described reconstructed spectrum signal i-th element;

Wherein, p _irepresent the nonzero probability of i-th element, C represents a constant, is positive count, n _irepresent the reconstructed spectrum signal that kth-1 iteration obtains the minimum value of the distance of each element in the support set of the reconstructed spectrum signal that i-th element and described kth-1 iteration obtain, α represents decay factor, control p _ithe speed of decay.

The described nonzero probability according to i-th element in described reconstructed spectrum signal determines the weighted term of described reconstructed spectrum signal i-th element, comprising:

According to

$v\left(p_i\right)=\frac{g}{2}\left(2\right(K+1-k)-1+2{\left(\frac{\mathrm{\σ}}{g}\right)}^2)log\frac{p_i}{1-p_i}$

Determine the weighted term of described reconstructed spectrum signal i-th element;

Wherein, v (p _i) representing the weighted term of described reconstructed spectrum signal i-th element, g is the average of nonzero element in the measured value of described spectrum signal, and σ is the standard deviation of noise, and k represents iterations, and K represents the joint sparse degree of spectrum signal to be reconstructed, wherein, K=K _c+ K ₁+ ... + K _j.

S102: determine to make reach the value of the i of maximum, in kth time iteration, this value is designated as i _mk; Wherein, a _irepresent the i-th row of known calculation matrix, r _k-1the residual error of the measured value of the described spectrum signal rebuild after representing the measured value of spectrum signal and kth-1 iteration;

S103: by the i determined in described kth time iteration _mkvalue joins in the support set of the reconstructed spectrum signal that kth-1 iteration obtains, and forms the support set after upgrading in kth time iteration, and by i-th of described known calculation matrix _mkrow add the calculation matrix obtained in kth-1 iteration and rebuild in atom set, and the calculation matrix formed after kth time iteration renewal rebuilds atom set; The support set of described reconstructed spectrum signal represents the set of nonzero element position in described reconstructed spectrum signal;

S104: according to the reconstructed spectrum signal of minimum value determination kth time iteration wherein, Y represents the measured value of spectrum signal to be reconstructed, represent that the calculation matrix after time iteration renewal of described kth rebuilds atom set, the measured value of the described spectrum signal rebuild after representing described kth time iteration;

Particularly, before execution step S101, the sensing node in cognition wireless network first carries out this locality to spectrum signal and detects, and obtains the measured value y of spectrum signal _j.A described J sensing node will detect the described measured value y obtained _jsend to described fusion center, the measured value y that a described J sensing node receives by described fusion center _jmerge, obtain by calculation matrix Φ corresponding for J spectrum signal _jmerge into Φ, can above-mentioned steps S101-S104 be performed.

The frequency spectrum sensing method that the embodiment of the present invention provides, the reconstructed spectrum signal obtained by kth-1 iteration in i-th element and described support set in the minimum range of each element, determine the position i of the nonzero element of kth time iteration intermediate frequency spectrum signal vector _mk, and by i _mkjoin in the support set of the reconstructed spectrum signal that kth-1 iteration obtains, form the support set after upgrading in kth time iteration, and the i-th row of calculation matrix described in described kth time iteration are added in the calculation matrix reconstruction atom set obtained in kth-1 iteration, the calculation matrix after formation kth time iteration upgrades rebuilds atom set; Basis again the reconstructed spectrum signal of minimum value determination kth time iteration wherein, Y represents the measured value of spectrum signal to be reconstructed, represent that the calculation matrix after time iteration renewal of described kth rebuilds atom set, the measured value of the described spectrum signal rebuild after representing described kth time iteration; The frequency spectrum sensing method that the embodiment of the present invention provides, utilizes the minimum range of signal element and support set element, determines the nonzero probability of spectrum signal element, thus obtains the position of the nonzero element in spectral signal vector, avoids based on l ₀to the requirement of signal element nonzero probability prior information in the restructing algorithm of norm, and the performance of signal reconstruction can be improved.

Further, in order to ensure that the number of the nonzero element in described reconstructed spectrum signal is no more than the sparse angle value of setting, described basis the reconstructed spectrum signal of minimum value determination kth time iteration afterwards, also comprise:

According to the i that described kth time iteration obtains _mk, described in determining i-th _mksubsignal z belonging to individual element _j; Wherein z _j∈ { z _c, z ₁..., z _j, according to upgrade described subsignal z _jsub-support set wherein, n represents described subsignal z _jlength, J represents the number of described frequency spectrum subsignal to be reconstructed, J and N be more than or equal to 1 integer; z _crepresent the common ground of described J frequency spectrum subsignal to be reconstructed, z ₁..., z _jrepresent the unique portion of described J frequency spectrum subsignal to be reconstructed;

Determine described frequency spectrum subsignal z _jsub-support set element number whether reach described signal z _jdegree of rarefication K _j∈ { K _c, K ₁..., K _j, wherein, degree of rarefication K _c, K ₁..., K _jrepresent subsignal z _c, z ₁..., z _jmiddle nonzero element number; If reached, then kth+1 iteration finds i _{m (k+1)}time do not consider subsignal z _jany element position.

Further, in order to improve the efficiency that described frequency spectrum sensing method is rebuild spectrum signal, the described i obtained according to described kth time iteration _mk, described in determining i-th _mksubsignal z belonging to individual element _jalso comprise: described in determining i-th _kindividual element is at described subsignal z _jin position i', for finding i in kth+1 iteration _{m (k+1)}time do not consider i-th in each subsignal ' individual element.

Further, in order to ensure to continue before described fusion center reaches stopping criterion for iteration the reconstruction that iteration realizes described spectrum signal, and stopping iteration completing after spectrum signal is rebuild, describedly determining described subsignal z _jsub-support set element number whether reach described signal z _jdegree of rarefication K _j∈ { K _c, K ₁..., K _j, if reached, then next iteration finds i _{m (k+1)}time do not consider subsignal z _jany element position after, also comprise:

The residual error of the measured value rebuild after upgrading the measured value of described spectrum signal and kth time iteration and iterations k;

Judge whether described iterations k meets k>K, if met, then stop iteration.

Further, describedly judge whether described iterations k meets k>K, if met, then, after stopping iteration, also comprise:

By described reconstructed spectrum signal matrix be split as reconstruction subsignal obtain the reconstructed results of described frequency spectrum subsignal

The embodiment of the present invention also provides a kind of spectrum signal sensing device, and Fig. 2 is the structural representation of embodiment of the present invention spectrum signal sensing device.Refer to Fig. 2, described spectrum signal sensing device at least comprises: determination module 210 and update module 220.

Described determination module 210, for:

According to the reconstructed spectrum signal that kth-1 iteration obtains in i-th element and described support set in the minimum range of each element, determine the weighted term that spectral signal vector i-th element is corresponding; I and k be more than or equal to 1 integer;

Determine to make or reach the value of the i of maximum, in kth time iteration, this value is designated as i _mk; Wherein, a _irepresent the i-th row of known calculation matrix, r _k-1the residual error of the measured value rebuild after representing the measured value of spectrum signal and kth-1 iteration, v (p _i) represent the weighted term that spectral signal vector i-th element is corresponding; I and k be more than or equal to 1 integer;

Described update module 220, for: by the i determined in described kth time iteration _mkvalue joins in the support set of the reconstructed spectrum signal that kth-1 iteration obtains, form the support set after upgrading in kth time iteration, and the i-th row of calculation matrix described in described kth time iteration are added in the calculation matrix reconstruction atom set obtained in kth-1 iteration, the calculation matrix after formation kth time iteration upgrades rebuilds atom set; The support set of described reconstructed spectrum signal represents the set of nonzero element position in described reconstructed spectrum signal;

Described determination module 210, also for:

According to the reconstructed spectrum signal of minimum value determination kth time iteration wherein, Y represents the measured value of spectrum signal to be reconstructed, represent that the calculation matrix of kth time iteration rebuilds atom set; the measured value of the described spectrum signal rebuild after representing described kth time iteration.

The frequency spectrum sensing device that the embodiment of the present invention provides, the reconstructed spectrum signal obtained according to kth-1 iteration by determination module in i-th element and described support set in the minimum range of each element, determine the position i of the nonzero element of kth time iteration intermediate frequency spectrum signal vector _mk, by described update module by i _mkjoin in the support set of the reconstructed spectrum signal that kth-1 iteration obtains, form the support set after upgrading in kth time iteration, and the i-th row of calculation matrix described in described kth time iteration are added in the calculation matrix reconstruction atom set obtained in kth-1 iteration, the calculation matrix after formation kth time iteration upgrades rebuilds atom set; Again by described determination module according to minimum value can determine the reconstructed spectrum signal of kth time iteration wherein, Y represents the measured value of spectrum signal to be reconstructed, represent that the calculation matrix after time iteration renewal of described kth rebuilds atom set, the measured value of the described spectrum signal rebuild after representing described kth time iteration; The frequency spectrum sensing device that the embodiment of the present invention provides, utilizes the minimum range of signal element and support set element, determines the nonzero probability of spectrum signal element, thus obtains the position of the nonzero element in spectral signal vector, avoids based on l ₀to the requirement of signal element nonzero probability prior information in the restructing algorithm of norm, and the performance of signal reconstruction can be improved.

Fig. 3 is the structural representation of another embodiment of the present invention spectrum signal sensing device.Refer to Fig. 3, the spectrum signal sensing device that another embodiment of the present invention provides comprises: processor 310 and memory 320, and described processor 310 realizes the method described in preceding method embodiment for the software program instructions stored in execute store 320.Its specific implementation principle and technique effect identical with embodiment of the method, do not repeat them here.

Fig. 4 is the structural representation of yet another embodiment of the invention spectrum signal sensing device.Refer to Fig. 4, the spectrum signal sensing device that yet another embodiment of the invention provides comprises: sensing node 410 and fusion center 420.

Described sensing node 410 is for the measured value of received spectrum signal

The measured value y of described fusion center 420 for sensing node is received _jmerge, obtain spectrum signal is pressed common ground and unique portion restructuring, be expressed as by calculation matrix Φ corresponding for J spectrum signal _jmerge into Φ, and according to the method in preceding method embodiment, described spectrum signal is rebuild.Its specific implementation principle and technique effect identical with embodiment of the method, do not repeat them here.

One of ordinary skill in the art will appreciate that: all or part of step realizing above-mentioned each embodiment of the method can have been come by the hardware that program command is relevant.Aforesaid program can be stored in a computer read/write memory medium.This program, when performing, performs the step comprising above-mentioned each embodiment of the method; And aforesaid storage medium comprises: ROM, RAM, magnetic disc or CD etc. various can be program code stored medium.

Last it is noted that above each embodiment is only in order to illustrate technical scheme of the present invention, be not intended to limit; Although with reference to foregoing embodiments to invention has been detailed description, those of ordinary skill in the art is to be understood that: it still can be modified to the technical scheme described in foregoing embodiments, or carries out equivalent replacement to wherein some or all of technical characteristic; And these amendments or replacement, do not make the essence of appropriate technical solution depart from the scope of various embodiments of the present invention technical scheme.

Claims (9)

1. a spectrum signal cognitive method, is characterized in that, comprising:

According to the reconstructed spectrum signal that kth-1 iteration obtains in i-th element and described support set in the minimum range of each element, determine the weighted term v (p that spectral signal vector i-th element is corresponding _i); The support set of reconstructed spectrum signal represents the set of nonzero element position in described reconstructed spectrum signal; I and k be more than or equal to 1 integer;

Determine to make reach the value of the i of maximum, in kth time iteration, this value is designated as i _mk; Wherein, a _irepresent the i-th row of known calculation matrix, r _k-1the residual error of the measured value of the described spectrum signal rebuild after representing the measured value of spectrum signal and kth-1 iteration;

By the i determined in described kth time iteration _mkvalue joins in the support set of the reconstructed spectrum signal that kth-1 iteration obtains, and forms the support set after upgrading in kth time iteration, and by i-th of described known calculation matrix _mkrow add the calculation matrix obtained in kth-1 iteration and rebuild in atom set, and the calculation matrix formed after kth time iteration renewal rebuilds atom set;

According to the reconstructed spectrum signal of minimum value determination kth time iteration wherein, Y represents the measured value of spectrum signal to be reconstructed, represent that the calculation matrix after time iteration renewal of described kth rebuilds atom set, the measured value of the described spectrum signal rebuild after representing described kth time iteration.

2. method according to claim 1, is characterized in that, described basis the reconstructed spectrum signal of minimum value determination kth time iteration afterwards, also comprise:

According to the i that described kth time iteration obtains _mk, described in determining i-th _mksubsignal z belonging to individual element _j; Wherein z _j∈ { z _c, z ₁..., z _j, according to upgrade described subsignal z _jsub-support set wherein, n represents described subsignal z _jlength, J represents the number of described frequency spectrum subsignal to be reconstructed, J and N be more than or equal to 1 integer; z _crepresent the common ground of described J frequency spectrum subsignal to be reconstructed, z ₁..., z _jrepresent the unique portion of described J frequency spectrum subsignal to be reconstructed;

Determine described frequency spectrum subsignal z _jsub-support set element number whether reach described signal z _jdegree of rarefication K _j∈ { K _c, K ₁..., K _j, wherein, degree of rarefication K _c, K ₁..., K _jrepresent subsignal z _c, z ₁..., z _jmiddle nonzero element number; If reached, then kth+1 iteration finds i _{m (k+1)}time do not consider subsignal z _jany element.

3. method according to claim 2, is characterized in that, the described i obtained according to described kth time iteration _mk, described in determining i-th _mksubsignal z belonging to individual element _jalso comprise: described in determining i-th _mkindividual element is at described subsignal z _jin position i', for finding i in kth+1 iteration _{m (k+1)}time do not consider i-th in each subsignal ' individual element.

4. according to the method in claim 2 or 3, it is characterized in that, the described reconstructed spectrum signal obtained according to kth-1 iteration in i-th element and described support set in weighted term corresponding to minimum range determination spectral signal vector i-th element of each element, comprising:

According to the reconstructed spectrum signal that described kth-1 iteration obtains in i-th element and the support set of reconstructed spectrum signal that obtains of described kth-1 iteration in the minimum range of each element, determine the nonzero probability of described reconstructed spectrum signal i-th element;

Weighted term v (the p of described reconstructed spectrum signal i-th element is determined according to the nonzero probability of i-th element in described reconstructed spectrum signal _i).

5. method according to claim 4, is characterized in that, the described reconstructed spectrum signal obtained according to described kth-1 iteration in i-th element and the support set of reconstructed spectrum signal that obtains of described kth-1 iteration in the minimum range of each element, determine the nonzero probability of described reconstructed spectrum signal i-th element, comprising:

According to

p _i＝C·exp(-n _i/α)

Determine the nonzero probability of described reconstructed spectrum signal i-th element;

Wherein, p _irepresent the nonzero probability of i-th element, C represents a constant, is positive count, n _irepresent the reconstructed spectrum signal that kth-1 iteration obtains the minimum value of the distance of each element in the support set of the reconstructed spectrum signal that i-th element and described kth-1 iteration obtain, α represents decay factor, control p _ithe speed of decay.

6. method according to claim 4, is characterized in that, the described nonzero probability according to i-th element in described reconstructed spectrum signal determines the weighted term of described reconstructed spectrum signal i-th element, comprising:

According to

$v\left(p_i\right)=\frac{g}{2}\left(2\right(K+1-k)-1+2{\left(\frac{\mathrm{\σ}}{g}\right)}^2)log\frac{p_i}{1-p_i}$

Determine the weighted term of described reconstructed spectrum signal i-th element;

Wherein, v (p _i) representing the weighted term of described reconstructed spectrum signal i-th element, g is the average of nonzero element in the measured value of described spectrum signal, and σ is the standard deviation of noise, and k represents iterations, and K represents the joint sparse degree of spectrum signal to be reconstructed, wherein, K=K _c+ K ₁+ ... + K _j.

7. method according to claim 6, is characterized in that, describedly determines described subsignal z _jsub-support set element number whether reach described signal z _jdegree of rarefication K _j∈ { K _c, K ₁..., K _j, if reached, then next iteration finds i _{m (k+1)}time do not consider subsignal z _jany element after, also comprise:

The residual error of the measured value rebuild after upgrading the measured value of described spectrum signal and kth time iteration and iterations k;

Judge whether described iterations k meets k>K, if met, then stop iteration.

8. method according to claim 7, is characterized in that, describedly judges whether described iterations k meets k>K, if met, then, after stopping iteration, also comprises:

By described reconstructed spectrum signal matrix be split as reconstruction subsignal obtain the reconstructed results of described frequency spectrum subsignal

9. a spectrum signal sensing device, is characterized in that, comprising:

Determination module, for:

According to the reconstructed spectrum signal that kth-1 iteration obtains in i-th element and described support set in the minimum range of each element, determine the weighted term that spectral signal vector i-th element is corresponding; I and k be more than or equal to 1 integer;

Determine to make or reach the value of the i of maximum, in kth time iteration, this value is designated as i _mk; Wherein, a _irepresent the i-th row of known calculation matrix, r _k-1the residual error of the measured value rebuild after representing the measured value of spectrum signal and kth-1 iteration, v (p _i) represent the weighted term that spectral signal vector i-th element is corresponding; I and k be more than or equal to 1 integer;

Update module, for: by the i determined in described kth time iteration _mkvalue joins in the support set of the reconstructed spectrum signal that kth-1 iteration obtains, form the support set after upgrading in kth time iteration, and the i-th row of calculation matrix described in described kth time iteration are added in the calculation matrix reconstruction atom set obtained in kth-1 iteration, the calculation matrix after formation kth time iteration upgrades rebuilds atom set; The support set of described reconstructed spectrum signal represents the set of nonzero element position in described reconstructed spectrum signal;

Described determination module, also for:

According to the reconstructed spectrum signal of minimum value determination kth time iteration wherein, Y represents the measured value of spectrum signal to be reconstructed, represent that the calculation matrix of kth time iteration rebuilds atom set; the measured value of the described spectrum signal rebuild after representing described kth time iteration.