CN109309538A - A kind of frequency spectrum sensing method, device, equipment, system and storage medium - Google Patents
A kind of frequency spectrum sensing method, device, equipment, system and storage medium Download PDFInfo
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Abstract
The invention discloses a kind of frequency spectrum sensing methods, comprising: obtains radio sampled signal；Noise reduction process is carried out to sampled signal, obtains de-noising signal；Splitting and reorganizing is carried out to de-noising signal according to DAR splitting and reorganizing technology, obtains two signal matrix；The difference for calculating minimax characteristic value according to the characteristic value of two signal matrix respectively, obtains two-dimensional feature vector；Tagsort division is carried out to two-dimensional feature vector, obtains the classification results of radio sampled signal.This method passes through the extraction to signal characteristic information is carried out after signal progress DAR splitting and reorganizing by DMM, the detection performance of frequency spectrum can be preferably improved in and the lower situation of signal-to-noise ratio less in cognitive user number, promote frequency spectrum detection performance, optimize frequency spectrum perception effect, realizes the precise classification to sampled signal.The invention also discloses a kind of frequency spectrum sensing device, equipment, system and a kind of readable storage medium storing program for executing, have above-mentioned beneficial effect.
Description
Technical field
The present invention relates to radio art, in particular to a kind of frequency spectrum sensing method, device, equipment, system and one kind can
Read storage medium.
Background technique
The fast development of science and technology, the information age brings, so that wireless communication system has penetrated into every field, in society
There can be increasingly important role in economic development.Total frequency spectrum resource be it is limited and valuable, at present China frequency spectrum money
By unification of the motherland authorized appropriation, authorized user and primary user can be with legal working frequencies in source.But with radio communication service demand
Rapid growth, the i.e. time user of more and more unauthorized users is also required to band operation, but frequency spectrum resource is not enough to be filled
Distribution, the rare problem of social frequency spectrum are increasingly serious.
Cognitive radio (CR) can with ambient enviroment interactive information, to perceive and using the usable spectrum in the space, and
Limitation and the generation for reducing conflict.It solves and alleviates this contradiction, become by the research hotspot of extensive concern.Frequency spectrum sense
Know be cognitive radio technology key task, mainly understanding primary user is to the occupancy situation of present channel, to find frequency
Hole is composed, the utilization rate of frequency spectrum resource is improved.
Traditional frequency spectrum perception technology includes classical energy measuring, cyclo-stationary detection, matched filtering.Wherein circulation is flat
Steady detection accuracy is high, can distinguish signal modulation mode, but primary user is required to have cyclostationary characteristic, is only applicable to specific
Occasion.Matched filtering precision is high, and the time is short, but computation complexity is high, and is only applicable to CR node and knows prior information
Occasion.Classical energy measuring does not need prior information, needs default decision threshold, the more difficult determination of thresholding；Shadow vulnerable to noise
It rings, under the uncertain environment of low signal-to-noise ratio environment and noise, is also easy to produce erroneous judgement and sharply declines so as to cause detection performance, examine
It is long to survey the time.
Therefore, frequency spectrum detection performance how is promoted, optimizes frequency spectrum perception effect, is that those skilled in the art need to solve
The technical issues of.
Summary of the invention
The object of the present invention is to provide a kind of frequency spectrum sensing method, this method can promote frequency spectrum detection performance, optimization frequency
Compose perceived effect；It is a further object of the present invention to provide a kind of frequency spectrum sensing device, equipment, system and a kind of readable storage mediums
Matter has above-mentioned beneficial effect.
The present invention provides a kind of frequency spectrum sensing method, comprising:
Obtain radio sampled signal；
Noise reduction process is carried out to the sampled signal, obtains de-noising signal；
Splitting and reorganizing is carried out to the de-noising signal according to DAR splitting and reorganizing technology, obtains two signal matrix；
The difference for calculating minimax characteristic value according to the characteristic value of described two signal matrix respectively obtains two-dimentional spy
Levy vector；
Tagsort division is carried out to the two-dimensional feature vector, obtains the classification results of the radio sampled signal.
Preferably, described to include: to de-noising signal progress splitting and reorganizing according to DAR splitting and reorganizing technology
To the de-noising signal carry out sequence splitting and reorganizing, the first signal matrix is obtained；
Interval sampling splitting and reorganizing is carried out to the de-noising signal, obtains second signal matrix.
Preferably, described to include: to sampled signal progress noise reduction process
By EMD empirical mode decomposition method to the sampled signal carry out signal decomposition, and to the signal after decomposition into
Row intrinsic mode functions signal extraction, obtains de-noising signal.
Preferably, carrying out tagsort division to the two-dimensional feature vector includes:
To several feature vector structural matrixes of acquisition, eigenmatrix is obtained；
The eigenmatrix is input to frequency spectrum disaggregated model, obtains classification results；Wherein, the frequency spectrum disaggregated model
For the FCM Clustering Model obtained according to the training of sample characteristics matrix.
Preferably, the frequency spectrum sensing method further include:
False-alarm probability and detection probability are calculated to the classification results；
Perceptual performance analysis is carried out according to the false-alarm probability and detection probability being calculated.
The present invention discloses a kind of frequency spectrum sensing device, comprising:
Sampled signal acquiring unit, for obtaining radio sampled signal；
Noise reduction processing unit obtains de-noising signal for carrying out noise reduction process to the sampled signal；
Splitting and reorganizing unit is obtained for carrying out splitting and reorganizing to the de-noising signal according to DAR splitting and reorganizing technology
Two signal matrix；
It is special to calculate minimax according to the characteristic value of described two signal matrix for respectively for feature vector computing unit
The difference of value indicative, obtains two-dimensional feature vector；
Category division unit obtains the radio and adopts for carrying out tagsort division to the two-dimensional feature vector
The classification results of sample signal.
Preferably, the splitting and reorganizing unit includes:
Sequence splits subelement, for obtaining the first signal matrix to the de-noising signal carry out sequence splitting and reorganizing；
Interval splits subelement and carries out interval sampling splitting and reorganizing to the de-noising signal, obtains second signal matrix.
The present invention discloses a kind of frequency spectrum perception equipment, comprising:
Memory, for storing computer program；
Processor, the step of frequency spectrum sensing method is realized when for executing the computer program.
The present invention discloses a kind of frequency spectrum perception system, comprising:
Radio sample devices obtains radio sampled signal for acquiring radio signal, and by the radio
Sampled signal is sent to frequency spectrum perception equipment；
The frequency spectrum perception equipment, for obtaining radio sampled signal；Noise reduction process is carried out to the sampled signal,
Obtain de-noising signal；Splitting and reorganizing is carried out to the de-noising signal according to DAR splitting and reorganizing technology, obtains two signal matrix；
The difference for calculating minimax characteristic value according to the characteristic value of described two signal matrix respectively, obtains two-dimensional feature vector；It is right
The two-dimensional feature vector carries out tagsort division, obtains the classification results of the radio sampled signal.
The present invention discloses a kind of readable storage medium storing program for executing, and program is stored on the readable storage medium storing program for executing, and described program is located
The step of reason device realizes the frequency spectrum sensing method when executing.
In order to solve the above technical problems, the present invention provides a kind of frequency spectrum sensing method, by according to DAR splitting and reorganizing skill
Art carries out splitting and reorganizing to the radio sampled signal after noise reduction process, and a de-noising signal is split as two signal matrix,
Configure according to different by different splitting and reorganizing modes, may be implemented to analyze data into signal
The foundation split as data is needed, spectrum signal is decomposed into two signal matrix and carries out signature analysis, is used increasing cognition
Accurate rate in spectrum analysis is effectively solved the problems, such as under the premise of the number at family；According to the characteristic value of two obtained signal matrix
The difference (DMM) for calculating minimax characteristic value, obtains feature vector, and the extraction of signal matrix feature is carried out by DMM, can
To realize the accurate analysis to signal amplitude span feature, the present invention is by passing through DMM after carrying out DAR splitting and reorganizing to signal
The extraction for carrying out signal characteristic information, can preferably improve under and the lower situation of signal-to-noise ratio less in cognitive user number
The detection performance of frequency spectrum promotes frequency spectrum detection performance, optimizes frequency spectrum perception effect, realizes the precise classification to sampled signal.
The invention also discloses a kind of frequency spectrum sensing device, equipment, system and a kind of readable storage medium storing program for executing, have above-mentioned
Beneficial effect, details are not described herein.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, below will to embodiment or
Attached drawing needed to be used in the description of the prior art is briefly described, it should be apparent that, the accompanying drawings in the following description is only
The embodiment of the present invention for those of ordinary skill in the art without creative efforts, can be with
Other attached drawings are obtained according to the attached drawing of offer.
Fig. 1 is the flow chart of frequency spectrum sensing method provided in an embodiment of the present invention；
Fig. 2 is tri- kinds of signal processing effect signals of EMD+DAR, IQ+DMM and DAR+DMM provided in an embodiment of the present invention
Figure；
Fig. 3 is the structural block diagram of frequency spectrum sensing device provided in an embodiment of the present invention；
Fig. 4 is the structural block diagram of frequency spectrum perception equipment provided in an embodiment of the present invention；
Fig. 5 is the structural schematic diagram of frequency spectrum perception equipment provided in an embodiment of the present invention；
Fig. 6 is the structural block diagram of frequency spectrum perception system provided in an embodiment of the present invention.
Specific embodiment
Core of the invention is to provide a kind of frequency spectrum sensing method, after this method is by carrying out DAR splitting and reorganizing to signal
The extraction of signal characteristic information is carried out by DMM, it can be more preferable in and the lower situation of signal-to-noise ratio less in cognitive user number
Ground improves the detection performance of frequency spectrum, promotes frequency spectrum detection performance, optimizes frequency spectrum perception effect, realizes to the accurate of sampled signal
Classification；Another core of the invention is to provide a kind of frequency spectrum sensing device, system and a kind of readable storage medium storing program for executing, has above-mentioned
Beneficial effect.
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
Member's every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
Referring to FIG. 1, Fig. 1 is the flow chart of frequency spectrum sensing method provided in an embodiment of the present invention；This method can wrap
It includes:
Step s110, radio sampled signal is obtained.
One cognitive radio system can have PU and M user SU of a primary user, the sampling number of each SU
For N, adjudicating primary user according to sampled data whether there is.When with H0It is expressed as primary user's signal to be not present, H1It is expressed as primary
In the presence of the signal of family, under both states, secondary user's received signal xi(n) it is represented by the model of formula (1):
Wherein, wi(n) representing mean value is 0, variance δ2White Gaussian noise, si(n) the transmitting signal of primary user is represented.
Assuming that the sampled signal vector of i-th of SU may be expressed as: xi(n)=[xi(1), xi(2) ..., xi(N)].Sampling
Signal matrix X can be expressed as M × N-dimensional matrix X shown in (formula 2):
By carrying out matrix analysis to sampled signal to know the matrix character information in sampled signal.
Step s120, noise reduction process is carried out to sampled signal, obtains de-noising signal.
It will include much noise signal in the sampled signal of acquisition, generally to avoid noise signal to frequency spectrum perception effect
Influence, carry out noise reduction process before carrying out spectrum analysis.?
Transformation, wavelet transformation etc..
The sampled signal obtained in frequency spectrum perception at present is usually non-linear, unstable signal.And in traditional Fu
Leaf transformation, the method for other signal processings such as wavelet transformation, can only generally handle linear, stable signal, it is preferable that can
To be handled using Empirical Mode Decomposition algorithm signal, usually noise is more included in high frequency band, in low-frequency band
Noise is weaker.EMD algorithm reconstructs drop of the signal realization to whole-sample signal of low-frequency band by the noise of removal high frequency band
It makes an uproar processing.
The process for then carrying out noise reduction process to sampled signal is specifically as follows: by EMD empirical mode decomposition method to adopting
Sample signal carries out signal decomposition, and carries out intrinsic mode functions signal extraction to the signal after decomposition, obtains de-noising signal.
Step s130, splitting and reorganizing is carried out to de-noising signal according to DAR splitting and reorganizing technology, obtains two signal matrix.
The number of collaboration user is less, will affect the sensing capabilities of whole system, in order to seldom can also reach in CU user
Preferable detection performance, using splitting and reorganizing (DAR) technology to de-noising signalIt is handled.By being torn open to signal matrix
Divide and recombinate again, realizes the purpose for increasing the number of partner user in logic.
Splitting and reorganizing includes a variety of fractionation modes, such as sequence splitting and reorganizing (O-DAR) and interval splitting and reorganizing (I-
DAR) etc., wherein the de-noising signal that length is N by sequence splitting and reorganizing (O-DAR)Q is split in order
The subsignal that section is k=N/q at segment length, then recombinated, new signal is obtained, data dimension can be increased, increased in logic
Partner user number.It is spaced splitting and reorganizing (I-DAR) process to split using interval sampling, i.e., is being sampled every q-1 unit
Sampled point, then recombination signal matrix are chosen in data, obtains new signal, can not only increase data dimension, but also can be with
The correlation for reducing matrix adjacent data avoids adjacent data analysis from bringing the error of accuracy.
Double resolution is selected to recombinate to obtain two signal matrix, it is without limitation to specific splitting and reorganizing mode at this, excellent
Selection of land, according to DAR splitting and reorganizing technology to de-noising signal carry out splitting and reorganizing process be specifically as follows: to de-noising signal into
Row sequence splitting and reorganizing, obtains the first signal matrix；Interval sampling splitting and reorganizing is carried out to de-noising signal, obtains second signal
Matrix.
Specifically, to the sampled signal of i-th of SUCarry out sequence splitting and reorganizing (O-
DAR), following q signal vector has been obtained:
It is spaced splitting and reorganizing (I-DAR) and chooses sampled point, then recombination signal in sampled data every q-1 unit
Matrix obtains sampled signal as follows:
After EMD algorithm noise reduction and the processing of DAR algorithm recombination, by M × N sampled signal matrix X, processing obtains as follows
Two Mq × k tie up matrix Y1And Y2:
Step s140, the difference for calculating minimax characteristic value according to the characteristic value of two signal matrix respectively, obtains two
Dimensional feature vector.
It uses signal energy as feature in the present embodiment, utilizes the maximum eigenvalue and minimal characteristic in covariance matrix
The difference (Difference between Maximum and Minimum eigenvalue, DMM) of value is used as statistic, then
It calculating corresponding threshold value and carries out decision, DMM algorithm can reduce influence of the noise to frequency spectrum sensor-based system to a certain extent,
The detection performance of frequency spectrum can preferably can be improved in the case where cognitive user number is less and the lower situation of signal-to-noise ratio.
The covariance matrix of Y1 and Y2 is respectively as follows:
To covariance matrixWithCalculate separately relevant eigenvalue λU=1,2 ..., Mq, utilize minimax feature
The difference of value constructs decision statistics:
T=λmax-λmin
According to above method, feature vector T is obtained1And T2, constitute two-dimensional feature vector T=[T1, T2]T。
Step s150, tagsort division is carried out to feature vector, obtains the classification results of radio sampled signal.
Traditional frequency spectrum perception technology often presets a decision threshold, when decision statistics are lower than threshold value, sentences
Primary user is not present, conversely, then determining that primary user exists when decision statistics are higher than threshold value.The accurate journey of decision threshold
Degree affects system senses performance, but decision threshold is difficult to accurately calculate.This embodiment introduces unsupervised clustering algorithms.
Frequency spectrum perception problem examines primary user's existence, can regard two classification problems as, carries out tagsort to feature vector
It divides, obtains the classification results of radio sampled signal.
Without limitation according to the method for feature vector progress tagsort division, it for example can be carried out by clustering algorithm
Classification, can also be using gauss hybrid models (GMM) cluster etc..Wherein, FCM algorithm can calculate each sample to all classes
Degree of membership can provide the calculation method with reference to the sample classification result reliability, if certain sample is to the degree of membership of certain class
There is absolute predominance in the degree of membership of all classes, then it is the way extremely insured that the sample, which assigns to this class, if otherwise
The sample is relatively average in the degree of membership of all classes, then we need other supplementary means to classify.Pass through FCM algorithm
It carries out clustering and improves detection performance.Preferably, it carries out tagsort division to feature vector to be specifically as follows: to acquisition
Several feature vector structural matrixes, obtain eigenmatrix；Eigenmatrix is input to frequency spectrum disaggregated model, obtains classification knot
Fruit；Wherein, frequency spectrum disaggregated model is the FCM Clustering Model obtained according to the training of sample characteristics matrix.
Herein only to be introduced for carrying out the classifying and dividing of feature to feature vector by FCM clustering method, other
Details are not described herein for classification method.
Based on the above-mentioned technical proposal, frequency spectrum sensing method provided by the present embodiment, by according to DAR splitting and reorganizing skill
Art carries out splitting and reorganizing to the radio sampled signal after noise reduction process, and a de-noising signal is split as two signal matrix,
Configure according to different by different splitting and reorganizing modes, may be implemented to analyze data into signal
The foundation split as data is needed, spectrum signal is decomposed into two signal matrix and carries out signature analysis, is used increasing cognition
Accurate rate in spectrum analysis is effectively solved the problems, such as under the premise of the number at family；According to the characteristic value of two obtained signal matrix
The difference (DMM) for calculating minimax characteristic value, obtains feature vector, and the extraction of signal matrix feature is carried out by DMM, can
To realize the accurate analysis to signal amplitude span feature, the present invention is by passing through DMM after carrying out DAR splitting and reorganizing to signal
The extraction for carrying out signal characteristic information, can preferably improve under and the lower situation of signal-to-noise ratio less in cognitive user number
The detection performance of frequency spectrum promotes frequency spectrum detection performance, optimizes frequency spectrum perception effect, realizes the precise classification to sampled signal.
In above-described embodiment without limitation to the method for sampled signal progress noise reduction process, in order to reduce noise to cognition
The influence of radio system, guarantee system can also obtain ideal perceived effect under the lower environment of signal-to-noise ratio, can pass through
EMD empirical mode decomposition method carries out signal decomposition to sampled signal, and carries out intrinsic mode functions signal to the signal after decomposition
It extracts, obtains de-noising signal.Specifically, the present embodiment is situated between to noise reduction process process to based on sight spot model decomposing method
It continues.
Empirical mode decomposition method (Empirical Mode Decomposition, EMD) is using Fourier transform as base
One important breakthrough of the linear and stable state spectrum analysis of plinth, this method be according to data itself time scale feature come into
Row signal decomposition, without presetting any basic function.This point and establish apriority harmonic wave basic function and wavelet basis letter
Fourier decomposition and wavelet-decomposing method on number have essential difference.Just because of such feature, EMD method exists
It theoretically can be applied to the decomposition of any kind of signal, thus on processing non-stationary and nonlinear data, have very
Apparent advantage is suitable for analyzing non-linear, non-stationary signal sequence.
Sophisticated signal is decomposed into limited intrinsic mode functions (IMF) from high frequency to low frequency by EMD algorithm, is decomposited
Each IMF component come contains the local feature signal of the different time scales of original signal.Sampled signal xi(n) through EMD algorithm
After processing, it is decomposed into following form,
Wherein, IMF indicates intrinsic mode functions part, and r (n) indicates residual error portion.According to continuous mean square deviation as follows
Criterion finds the critical point m of high frequency band and low-frequency band.
Sampled signal is after EMD algorithm process, signal after having obtained following noise reduction:
In addition, in order to which the sensing results to frequency spectrum carry out Adaptability Evaluation, it is intuitive to be carried out to sensing results
Solution, it is preferable that false-alarm probability and detection probability can be calculated to classification results after carrying out frequency spectrum perception；According to calculating
The false-alarm probability and detection probability arrived carries out perceptual performance analysis.
Specifically, to the false-alarm probability P of systemfWith detection probability PdIt is defined as follows:
Pf=P [H1|H0]；
Pd=P [H0|H1]。
Fig. 2 show tri- kinds of signal processing effect diagrams of EMD+DAR, IQ+DMM and DAR+DMM, from ROC curve figure
As can be seen that when false-alarm probability is 0.1, the detection probability of EMD+DAR is general compared to the detection of IQ+DMM when signal-to-noise ratio is -14
Rate improves 42.86%, and the detection probability compared to DAR+DMM improves 11.1%.As can be seen that based on the above embodiment,
DMM algorithm carries out the frequency spectrum sensing method of feature extraction, than the frequency spectrum sensing method of IQ+DMM and DAR+DMM, in low letter
It makes an uproar than in the environment of, hence it is evident that there is better detection performance.
In above-described embodiment without limitation to the process of feature vector progress cluster feature analysis, FCM can be selected to cluster
Algorithm, to deepen to carry out FCM clustering algorithm the understanding of tagsort division, false-alarm probability P of the present embodiment based on systemf
With detection probability PdIts principle and detailed process are introduced.
FCM clustering algorithm is that one training sample is assigned to certain one kind based on fuzzy membership, and principal function is error
Sum of squares function.Prepare a feature samples collection firstWherein P is of feature vector in sample
Number.It willIt is divided into training sample setAnd test sample collectionIt usesClassifier is trained, test sample collection is finally used
The perceived effect of testing classification device.
Assuming that the degree of membership that j-th of training sample belongs to c class is ujc, then principal function can indicate are as follows:
Restrictive condition can indicate are as follows:
In formula, P indicates the number of training sample, and m indicates the Smoothness Index of FCM algorithm, ΨcIt indicates class center, will train
Feature vector is divided into C class, in frequency spectrum perception system, takes C=2.
According to restrictive condition formula, degree of membership u can be derivedjcWith cluster centre ΨcIterative difference it is as follows:
Judge that primary user whether there is with following judgement formula:
In formula, ζ indicates the false-alarm probability and detection probability of system.
FCM algorithm detailed process is as follows:
Obtain enough signal characteristics, construction feature matrixGiven class number C, FCM are calculated
Method Smoothness Index m and allowable error ε initializes degree of membership ujc.Specifically, judgement assorting process is referring to following step:
Step 1: calculating class center Ψ using the iterative formula of cluster centrec。
Step 2: calculating errorIf v < ε, terminate algorithm, otherwise continue to the next step.
Step 3: calculating new degree of membership u using degree of membership formula iterationjc。
It is continued cycling through step 4: returning to the first step, the number of iterations until reaching setting.
Step 5: output degree of membership ujcWith class center Ψc, classifier training finishes, tested.
Step 6: input test sample set
Step 7: working asWhen, export H1, otherwise export H0
Based on above-mentioned introduction.Using FCM clustering algorithm directly into two classification, avoid in traditional energy detection method
Default decision threshold is difficult to determining problem, improves the accuracy of frequency spectrum detection.
Frequency spectrum sensing device provided by the invention is introduced below, referring to FIG. 3, Fig. 3 mentions for the embodiment of the present invention
The structural block diagram of the frequency spectrum sensing device of confession；The apparatus may include: sampled signal acquiring unit 310, noise reduction processing unit
320, splitting and reorganizing unit 330, feature vector computing unit 340 are with category division unit 350.
Wherein, sampled signal acquiring unit 310 is mainly used for obtaining radio sampled signal；
Noise reduction processing unit 320 is mainly used for carrying out noise reduction process to sampled signal, obtains de-noising signal；
Splitting and reorganizing unit 330 is mainly used for carrying out splitting and reorganizing to de-noising signal according to DAR splitting and reorganizing technology, obtains
To two signal matrix；
Feature vector computing unit 340 is mainly used for calculating minimax according to the characteristic value of two signal matrix respectively
The difference of characteristic value, obtains two-dimensional feature vector；
Category division unit 350 is mainly used for carrying out tagsort division to two-dimensional feature vector, obtains radio sampling
The classification results of signal.
Preferably, noise reduction processing unit is specifically as follows EMD noise reduction processing unit, for passing through EMD empirical mode decomposition
Method carries out signal decomposition to sampled signal, and carries out intrinsic mode functions signal extraction to the signal after decomposition, obtains noise reduction letter
Number.
Preferably, splitting and reorganizing unit can specifically include:
Sequence splits subelement, for obtaining the first signal matrix to de-noising signal carry out sequence splitting and reorganizing；
Interval splits subelement, for carrying out interval sampling splitting and reorganizing to de-noising signal, obtains second signal matrix.
Preferably, category division unit can specifically include:
Matrix construction subelement obtains eigenmatrix for several feature vector structural matrixes to acquisition；
FCM clustering subelement obtains classification results for eigenmatrix to be input to frequency spectrum disaggregated model；Its
In, frequency spectrum disaggregated model is the FCM Clustering Model obtained according to the training of sample characteristics matrix.
Preferably, frequency spectrum sensing device can be with further include: performance analysis unit, it is general for calculating false-alarm to classification results
Rate and detection probability；Perceptual performance analysis is carried out according to the false-alarm probability and detection probability being calculated.
It should be noted that each unit in frequency spectrum sensing device in the specific embodiment of the invention, worked
Journey please refers to the corresponding specific embodiment of frequency spectrum sensing method, and details are not described herein.
Frequency spectrum perception equipment provided by the invention is introduced below, specifically the introduction of frequency spectrum perception equipment can be joined
The step of according to above-mentioned frequency spectrum sensing method, Fig. 4 are the structural block diagram of frequency spectrum perception equipment provided in an embodiment of the present invention；This sets
It is standby to may include:
Memory 400, for storing computer program；
Processor 401, when for executing computer program the step of realization frequency spectrum sensing method.
Referring to FIG. 5, the structural schematic diagram of frequency spectrum perception equipment provided in an embodiment of the present invention, the frequency spectrum perception equipment
Bigger difference can be generated because configuration or performance are different, may include one or more processors (central
Processing units, CPU) 322 (for example, one or more processors) and memory 332, one or one with
The storage medium 330 (such as one or more mass memory units) of upper storage application program 342 or data 344.Its
In, memory 332 and storage medium 330 can be of short duration storage or persistent storage.The program for being stored in storage medium 330 can
To include one or more modules (diagram does not mark), each module may include to the system in data processing equipment
Column instruction operation.Further, central processing unit 322 can be set to communicate with storage medium 330, set in frequency spectrum perception
The series of instructions operation in storage medium 330 is executed on standby 301.
Frequency spectrum perception equipment 301 can also include one or more power supplys 326, one or more it is wired or
Radio network interface 350, one or more input/output interfaces 358, and/or, one or more operating systems
341, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM etc..
Step in frequency spectrum sensing method described in above figure 1 can be realized by the structure of frequency spectrum perception equipment.
Frequency spectrum perception system provided in an embodiment of the present invention is introduced below, frequency spectrum perception system described below
Reference can be corresponded to each other with above-described frequency spectrum perception equipment.
Fig. 6 is the structural block diagram of frequency spectrum perception system provided in an embodiment of the present invention；The system may include: radio
Sample devices 600 and frequency spectrum perception equipment 601.
Radio sample devices 600 is mainly used for acquiring radio signal, obtains radio sampled signal, and will be wireless
Electric sampled signal is sent to frequency spectrum perception equipment；
Frequency spectrum perception equipment 601 is mainly used for obtaining radio sampled signal；Noise reduction process is carried out to sampled signal, is obtained
To de-noising signal；Splitting and reorganizing is carried out to de-noising signal according to DAR splitting and reorganizing technology, obtains two signal matrix；Root respectively
The difference that minimax characteristic value is calculated according to the characteristic value of two signal matrix, obtains two-dimensional feature vector；To two dimensional character to
Amount carries out tagsort division, obtains the classification results of radio sampled signal.
Readable storage medium storing program for executing provided in an embodiment of the present invention is introduced below, readable storage medium storing program for executing described below
Reference can be corresponded to each other with above-described frequency spectrum sensing method.
A kind of readable storage medium storing program for executing disclosed by the invention, is stored thereon with program, and frequency is realized when program is executed by processor
The step of composing cognitive method.
It is apparent to those skilled in the art that for convenience and simplicity of description, the dress of foregoing description
It sets, equipment, the specific work process of storage medium and unit can refer to corresponding processes in the foregoing method embodiment, herein
It repeats no more.
In several embodiments provided by the present invention, it should be understood that disclosed device, system, storage medium and
Method may be implemented in other ways.For example, apparatus embodiments described above are merely indicative, for example,
The division of unit, only a kind of logical function partition, there may be another division manner in actual implementation, such as multiple lists
Member or component can be combined or can be integrated into another system, or some features can be ignored or not executed.Another point,
Shown or discussed mutual coupling, direct-coupling or communication connection can be through some interfaces, device or list
The indirect coupling or communication connection of member can be electrical property, mechanical or other forms.
Unit may or may not be physically separated as illustrated by the separation member, show as unit
Component may or may not be physical unit, it can it is in one place, or may be distributed over multiple nets
On network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If integrated unit is realized in the form of SFU software functional unit and when sold or used as an independent product,
It can store in a mobile terminal.Based on this understanding, technical solution of the present invention is substantially in other words to existing skill
The all or part of part or the technical solution that art contributes can be embodied in the form of software products, the production
Product are stored in a storage medium, including some instructions are used so that a mobile terminal (can be mobile phone or plate
Computer etc.) execute all or part of the steps of each embodiment method of the present invention.And storage medium above-mentioned includes: USB flash disk, moves
Dynamic hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory,
RAM), the various media that can store program code such as magnetic or disk.
Each embodiment is described in a progressive manner in specification, the highlights of each of the examples are with other
The difference of embodiment, the same or similar parts in each embodiment may refer to each other.For device disclosed in embodiment
For, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is referring to method part
Explanation.
Professional further appreciates that, list described in conjunction with the examples disclosed in the embodiments of the present disclosure
Member and algorithm steps can realize with the combination of electronic hardware, terminal or the two, in order to clearly demonstrate hardware and soft
The interchangeability of part generally describes each exemplary composition and step according to function in the above description.These function
It can be implemented in hardware or software actually, the specific application and design constraint depending on technical solution.Professional skill
Art personnel can use different methods to achieve the described function each specific application, but this realization is not answered
Think beyond the scope of this invention.
The step of method described in conjunction with the examples disclosed in this document or algorithm, can directly use hardware, processor
The combination of the software module or the two of execution is implemented.Software module can be placed in random access memory (RAM), memory, only
Read memory (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or
In any other form of storage medium well known in technical field.
Frequency spectrum sensing method provided by the present invention, device, equipment, system and readable storage medium storing program for executing are carried out above
It is discussed in detail.Used herein a specific example illustrates the principle and implementation of the invention, above embodiments
Illustrate to be merely used to help understand method and its core concept of the invention.It should be pointed out that for the common skill of the art
, without departing from the principle of the present invention, can be with several improvements and modifications are made to the present invention for art personnel, these
Improvement and modification are also fallen within the protection scope of the claims of the present invention.
Claims (10)
1. a kind of frequency spectrum sensing method characterized by comprising
Obtain radio sampled signal；
Noise reduction process is carried out to the sampled signal, obtains de-noising signal；
Splitting and reorganizing is carried out to the de-noising signal according to DAR splitting and reorganizing technology, obtains two signal matrix；
Respectively according to the characteristic value of described two signal matrix calculate minimax characteristic value difference, obtain two dimensional character to
Amount；
Tagsort division is carried out to the two-dimensional feature vector, obtains the classification results of the radio sampled signal.
2. frequency spectrum sensing method as described in claim 1, which is characterized in that it is described according to DAR splitting and reorganizing technology to described
De-noising signal carries out splitting and reorganizing
To the de-noising signal carry out sequence splitting and reorganizing, the first signal matrix is obtained；
Interval sampling splitting and reorganizing is carried out to the de-noising signal, obtains second signal matrix.
3. frequency spectrum sensing method as described in claim 1, which is characterized in that described to carry out noise reduction process to the sampled signal
Include:
Signal decomposition is carried out to the sampled signal by EMD empirical mode decomposition method, and this is carried out to the signal after decomposition
Modular function signal extraction is levied, de-noising signal is obtained.
4. frequency spectrum sensing method as described in claim 1, which is characterized in that carry out tagsort to the two-dimensional feature vector
Division includes:
To several feature vector structural matrixes of acquisition, eigenmatrix is obtained；
The eigenmatrix is input to frequency spectrum disaggregated model, obtains classification results；Wherein, according to the frequency spectrum disaggregated model
The FCM Clustering Model that the training of sample characteristics matrix obtains.
5. frequency spectrum sensing method as described in claim 1, which is characterized in that further include:
False-alarm probability and detection probability are calculated to the classification results；
Perceptual performance analysis is carried out according to the false-alarm probability and detection probability being calculated.
6. a kind of frequency spectrum sensing device characterized by comprising
Sampled signal acquiring unit, for obtaining radio sampled signal；
Noise reduction processing unit obtains de-noising signal for carrying out noise reduction process to the sampled signal；
Splitting and reorganizing unit obtains two letters for carrying out splitting and reorganizing to the de-noising signal according to DAR splitting and reorganizing technology
Number matrix；
Feature vector computing unit, for calculating minimax characteristic value according to the characteristic value of described two signal matrix respectively
Difference obtains two-dimensional feature vector；
Category division unit obtains the radio sampling letter for carrying out tagsort division to the two-dimensional feature vector
Number classification results.
7. frequency spectrum sensing device as claimed in claim 6, which is characterized in that the splitting and reorganizing unit includes:
Sequence splits subelement, for obtaining the first signal matrix to the de-noising signal carry out sequence splitting and reorganizing；
Interval splits subelement and carries out interval sampling splitting and reorganizing to the de-noising signal, obtains second signal matrix.
8. a kind of frequency spectrum perception equipment characterized by comprising
Memory, for storing computer program；
Processor, realizing the frequency spectrum sensing method as described in any one of claim 1 to 5 when for executing the computer program
Step.
9. a kind of frequency spectrum perception system characterized by comprising
Radio sample devices obtains radio sampled signal, and the radio is sampled and is believed for acquiring radio signal
Number it is sent to frequency spectrum perception equipment；
The frequency spectrum perception equipment, for obtaining radio sampled signal；Noise reduction process is carried out to the sampled signal, is dropped
Noise cancellation signal；Splitting and reorganizing is carried out to the de-noising signal according to DAR splitting and reorganizing technology, obtains two signal matrix；Root respectively
The difference that minimax characteristic value is calculated according to the characteristic value of described two signal matrix, obtains two-dimensional feature vector；To described two
Dimensional feature vector carries out tagsort division, obtains the classification results of the radio sampled signal.
10. a kind of readable storage medium storing program for executing, which is characterized in that be stored with program on the readable storage medium storing program for executing, described program is located
It manages and is realized when device executes as described in any one of claim 1 to 5 the step of frequency spectrum sensing method.
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