CN104683050B - Multi-antenna total blind spectrum sensing method capable of effectively resisting noise uncertainty - Google Patents
Multi-antenna total blind spectrum sensing method capable of effectively resisting noise uncertainty Download PDFInfo
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Abstract
The invention relates to a multi-antenna total blind spectrum sensing method capable of effectively resisting noise uncertainty. The method uses a sampling correlation coefficient between multi-antenna receiving signal components to construct a statistical decision, and comprises the following steps: firstly, calculating a sampling covariance matrix of a multi-antenna receiving signal, then calculating the sampling correlation coefficient, wherein in a formula, the element of the ith row and the jth line of the sampling covariance matrix is represented by a character in the specification, and diagonal elements on the ith row and the ith line and on the jth row and the jth line are respectively represented by characters in the specification; secondly, calculating a formula in the specification and taking the formula as the statistical decision of the detection of a spectrum hole, wherein a parameter M is the number of antennas configured on a sensing node; finally, performing sensing decision; when the sensing decision is greater than a set threshold value, then judging that the spectrum hole does not exist, and otherwise, when the sensing decision is smaller than the threshold value, then judging that the spectrum hole exists. The multi-antenna total blind spectrum sensing method capable of effectively resisting the noise uncertainty disclosed by the invention has good robust characteristic to the variation of the noise variance, and has good characteristic of effectively resisting the negative effect caused by the noise uncertainty.
Description
Technical field
The present invention relates to a kind of method for being applied to the detection of multiple antennas cognitive radio system intermediate frequency spectrum cavity, belongs to wireless
Cognitive radio technology field in communication.
Background technology
The basic problem that radio communication faces is to hold how the utilization of resources more reasonable, network coverage wider, system
Amount bigger, bandwidth utilization efficiency is higher, so as to provide the user more preferable service quality.Multiple-input and multiple-output (MIMO, Multi-
Input Multi-Output) technology appear as solve the above problems there is provided good resolving ideas, it has become at present long
One of key technology for PHY of communication standard such as phase evolution scheme (LTE, Long Term Evolution).On the other hand, it is cognitive
Radiotechnics allows secondary user's its vacant frequency spectrum of reasonable employment on the premise of primary user's normal communication service is not disturbed to provide
Source, for the contradiction between effectively alleviating growing spectrum requirement and limited frequency spectrum resource brand-new resolving ideas are provided, it
Appearance cause academia and industrial quarters is widely paid close attention to.In view of both advantages, cognitive MIMO radio (Cognitive MIMO
Radio) technology has become the study hotspot of cognition wireless electrical domain.Before frequency spectrum perception algorithm radiotechnics is achieved
Carry and crucial, therefore effectively multiple antennas frequency spectrum perception algorithm becomes the key factor for realizing cognition MIMO radiotechnics naturally.
The classical detection method based on energy has to be realized simply, is believed without using channel and primary user in detection process
The advantage of number information and become one of the most widely used detection method.However, the method have the shortcomings that two it is fatal：Its
One, when zero-mean independent Gaussian primary user's signal is detected, the detection method based on energy has optimum detection performance.But
In actual detection process, due to the impact of the factors such as wireless channel time dispersive and over-sampling cause it is unsentenced useful
Signal component often has statistical correlation feature, and existing result of study has been proven that energy detection method in such case
Under perceptual performance will be remarkably decreased.On the other hand, in detection process, energy detection method is needed using accurate noise side
Difference.And in the middle of real world applications, it is time-varying, random that the impact of incorrect noise phenomenon will result directly in noise variance
, thus accurate noise variance value can not possibly be obtained via measurement.Existing result of study shows, the inspection of energy detection method
Survey performance to be remarkably decreased with the appearance of incorrect noise problem, ultimately result in the failure of the method.
For the problems referred to above for overcoming energy detection method to exist, some scholars are proposed based on reception signal correlation properties
Multiple antennas frequency spectrum sensing method.Classical method includes：Diagonal and off diagonal element based on sampling covariance matrix
The ratio of the ratio of absolute value, the eigenvalue of maximum based on sampling covariance matrix and minimal eigenvalue, and based on reception signal energy
Three kinds of total blindness's multiple antennas frequency spectrum sensing methods such as the ratio of amount and sampling covariance matrix minimal eigenvalue.Above-mentioned three kinds of methods are common
Advantage be：The incorrect noise met with based on the method for energy measuring is solved the problems, such as, and is received in multiple antennas
Signal shows excellent detection performance when there is dependency.However, incorrect noise problem is perceived under scene in multiple antennas
Show increasingly complex, due to the incorrect noise factor such as electronic device non-linear factor and nominal error in perception component
Exist, in the noise variance in the middle of actual aware application between different antennae and differ.And above-mentioned three kinds of methods are only had in mind
In the frequency spectrum perception under conditions of noise variance is equal between different antennae on sensing node is solved the problems, such as, differ in noise variance
The application premise that these methods are relied under conditions of cause is no longer set up, and the testing result corresponding to it will become no longer reliable.
In order to overcome the insecure problem of sensing results that noise variance inconsistence problems are brought between different antennae,
The scholars such as J.K.Tugnait exist recently《IEEE Transactions on Signal Processing,vol.60,no.4,
pp.1823-1832,Apr.2012》Entitled " On multiple antenna spectrum sensing under are delivered
(noise is uncertain with multiple antennas under flat fade condition frequently for noise variance uncertainty and flat fading
Spectrum perception algorithm) " article, this article based on receive signal Gaussian distributed precondition under, by not on the same day
Unknown noise variance between line is estimated, it is proposed that the detection method based on Generalized Likelihood Ratio technology.The method is in antenna
Between noise variance it is inconsistent under conditions of show good perceptual performance, but, its shortcoming be embodied in following three aspect：
First, the method is optimal when primary user receives signal Gaussian distributed, and signal is received for non-gaussian point in primary user
Perception scene during cloth then and is unsatisfactory for optimal coupling condition；Second, the method depends on primary user's signal in perception
Statistical nature, thus not a kind of total blindness's cognitive method；Third, the method is related to take in the calculating process for perceiving judgement amount
The determinant computation of sample covariance matrix, algorithm computation complexity is high, and this shortcoming seems under conditions of number of antennas is more
It is especially prominent.The reason for three aspect of the above, limits the method and further applies and push away in actual multiple antennas perceive scene
Extensively.Under this background, design have concurrently reliable perceptual performance and low computation complexity to be effective against noise variance not true
Total blindness's multiple antennas frequency spectrum sensing method of qualitative effect seems particularly necessary.
The content of the invention
Technical problem：The present invention proposes a kind of multiple antennas total blindness's frequency spectrum perception that can be effective against incorrect noise
Method, the method receives the statistical nature of signal and noise to implement to perceive judgement without using wireless channel, primary user, effectively
Overcome the inconsistent problem of noise variance between the multiple antennas that noise indeterminacy phenomenon causes, at the same time new method possesses
The low advantage of computation complexity, can be applied to well in the middle of actual multiple antennas frequency spectrum perception scene.
Technical scheme：A kind of multiple antennas total blindness's frequency spectrum sensing method that can be effective against incorrect noise of the present invention
Receive the sampling correlation coefficient between component of signal to construct statistical decision amount using multiple antennas：Multiple antennas are calculated first receives signal
Sampling covariance matrixAnd set its i-th row jth column element asThen sampling correlation coefficient is calculated
In formulaRepresentI-th row jth column element,WithRepresent respectivelyI-th row i-th is arranged, the diagonal element that jth row jth is arranged
Element；Secondly by calculatingAnd as the statistical decision amount of frequency spectrum cavity-pocket detection, here parameter M is sensing node
The number of antennas of upper configuration；Finally implement to perceive judgement：When judgement amount is perceived more than the threshold value for setting, then judge that frequency spectrum is empty
Hole is not present, conversely, when the perception judgement amount is less than the threshold value, then judging that frequency spectrum cavity-pocket is present.
It is described to receive the sampling correlation coefficient between component of signal to construct perception judgement amount using multiple antennas, its concrete step
Suddenly it is：
1) sensing node collects the reception signal sampling value x of the moment n on M root antennasiN (), 1≤i≤M is formed and received
Data vector x (n)=[x1(n) … xM(n)]T, the transposition computing of subscript T representing matrixs here.At the same time, sensing node
N number of receiving data vector x (n), 1≤n≤N are obtained by continuous sampling；
2) the sampling covariance matrix of received signal vector is calculated：
3) sampling correlation coefficient is calculated1≤i ＜ j≤M；Wherein：ForThe i-th row jth column element；
4) calculate and perceive judgement amount：
5) calculate and perceive decision threshold：Wherein：It is M that a is degree of freedom2The 1-P of the chi square distribution of-MFADivide position
Point, PFAIt is according to actual demand target false-alarm probability set in advance；
6) implement to perceive judgement：
If perceiving judgement amount Λ is more than decision threshold γ, judge that primary user's signal is present, i.e., now frequency spectrum cavity-pocket is not
Exist；If perceiving judgement amount Λ is less than decision threshold γ, judge that primary signal is not present, i.e., now frequency spectrum cavity-pocket is present.
All of explanation of symbols
Beneficial effect：The beneficial effects are mainly as follows three below aspect：
1. based on sampling correlation coefficient multiple antennas frequency spectrum sensing method need not by wireless channel, primary user's signal and
The statistical nature of noise is adjudicated to implement to perceive, while the determination of its decision threshold is independently of signal and noise variance, can be pre-
First calculate, be a kind of new total blindness's frequency spectrum sensing method；
2. noise variance differs between the antenna that method energy effectively solving incorrect noise provided by the present invention brings
The problem of cause.At the same time new method does not rely on the statistical property that primary user receives signal in implementation process, thoroughly breaks through
It is classical under the conditions of noise variance is inconsistent that reception depended on based on the multiple antennas frequency spectrum sensing method of Generalized Likelihood Ratio technology
The limitation of signal Gaussian distributed this premise；
3., relative to classical multiple antennas frequency spectrum sensing method, method provided by the present invention is calculating perception judgement amount
During without the need for sample covariance matrix carry out Eigenvalues Decomposition or determinant technology, computation complexity is low, in antenna number
This advantage will be apparent from the case that mesh is more.At the same time, new method provided by the present invention has decision gate
The advantage that calculating process is simple and amount of calculation is little of limit.
Description of the drawings
Fig. 1 is a kind of flowchart of the multiple antennas total blindness's frequency spectrum sensing method for being effective against incorrect noise.
Specific embodiment
The present invention proposes a kind of multiple antennas total blindness based on sampling correlation coefficient for being effective against incorrect noise
Frequency spectrum sensing method.New method is calculated sampling association first with multiple antennas primary user's signal data that sensing node is received
Variance matrixThen utilizeElement calculate sampling correlation coefficient, and on this basis using these coefficients square
Judgement amount is perceived with construction；Eventually form decision rule and implement to perceive judgement, i.e., when the perception judgement amount of construction is more than setting
Threshold value when then judge that frequency spectrum cavity-pocket is not present, and when the judgement amount be less than the threshold value when then judge frequency spectrum cavity-pocket exist.
Its specific embodiment is expressed as：
1) sensing node collects the reception signal sampling value x of the moment n on M root antennasiN (), 1≤i≤M is formed and received
Data vector x (n)=[x1(n) … xM(n)]T, and N number of receiving data vector x (n), 1≤n≤N are obtained by continuous sampling；
2) the sampling covariance matrix that M × M dimensions receive signal is calculated using N number of receiving data vector obtained above：And be marked asWherein,ForThe i-th row jth column element；
3) 1≤i ＜ j≤M is calculatedIndividual sampling correlation coefficient：
4) using sampling correlation coefficientCalculate and perceive judgement amount：
5) calculate and perceive decision threshold：Wherein：It is M that a is degree of freedom2The 1-P of the chi square distribution of-MFADivide position
Point, PFAFor target false-alarm probability set in advance.
6) construction perceives decision rule and implements judgement：If perceiving judgement amount Λ is more than decision threshold γ, frequency is judged
Spectrum cavity is not present；If perceiving judgement amount Λ is less than decision threshold γ, judge that frequency spectrum cavity-pocket is present.
Foundation below from multiple antennas frequency spectrum perception model, the total blindness's multiple antennas frequency spectrum perception reality based on sampling correlation coefficient
The establishment of applying method to three aspects such as design of concrete testing process are described in detail.
(1) frequency spectrum perception model
Setting sensing node configuration M root reception antennas the, if M × 1 dimension multiple antennas that n-th sampling instant is obtained receive signal
Vector x (n) can be expressed as x (n)=s (n)+η (n).Here, η (n) and s (n) represent respectively M × 1 dimension white Gaussian noise vector
With the primary user's received signal vector after wireless channel deformation.Concrete form is defined as：
X (n)=[x1(n) … xM(n)]T (1)
S (n)=[s1(n) … sM(n)]T (2)
η (n)=[η1(n) … ηM(n)]T (3)
Here η (n) be zero-mean and count covariance matrix beWhite Gaussian noise vector, and total N (i=
1 ..., N) individual received signal vector participation judging process.The core of multiple antennas frequency spectrum perception be using multiple antennas receiving data come
Judge whether that frequency spectrum cavity-pocket can be utilized by cognitive user, it can substantially be expressed as following binary hypothesis test
Problem：
Here, H0Represent that primary user's signal is not present, that is, there is the frequency spectrum cavity-pocket that can be used by cognitive user；H1Represent
Primary user's signal is present, i.e., there is no the frequency spectrum cavity-pocket that can be used by cognitive user.
(2) implementation
When primary user's signal does not occur, only have white noise component to exist in receiving data, thus received signal vector
Statistics covariance matrix be pair of horns matrix；And when primary user's signal occurs, due to being believed by wireless channel and primary user
The impact of number factor such as statistical nature and over-sampling, the statistics covariance matrix of received signal vector often becomes no longer to be one
Individual diagonal matrix.So if design certain statistical decision amount causes statistics covariance to characterize due to the appearance of primary user's signal
This change occurred before and after matrix, then the statistical decision amount actually implies and judges that what primary user's signal whether there is has
With information, such that it is able to as judging the foundation that frequency spectrum cavity-pocket whether there is.Notice in wireless channel, primary user's signal and make an uproar
The statistics covariance matrix of definite received signal vector cannot be obtained in the case that sound statistical nature is unknown, therefore in this programme
Approximate evaluation is made to it by calculating the existing sampling covariance matrix for receiving sample of signal data in the middle of implementation process, the square
Battle array is defined as：
For the convenience implemented, it is specifically labeled as：
HereForThe i-th row jth column element.When primary user's signal does not occur,Diagonal entry value
Size actually reflects the size of noise energy in different antennae, therefore, because the day caused by incorrect noise factor
The inconsistent phenomenon of noise variance will be between lineDiagonal entry value size on embody.
May certify thatActually one is conjugated symmetrical matrix, therefore the element in its diagonal upper right corner is reflected not
With all relevant informations of sampled signal between antenna.Sampling correlation coefficient is calculated 1≤i ＜ j≤M on this basis：
A kind of multiple antennas total blindness frequency spectrum sensing method for being effective against incorrect noise involved in the present invention is utilized
Analysis result above, devises a kind of new perception judgement amount：
May certify that 2N Λ are not when primary user's signal occurs in the case that number N of data receiver vector is larger
Obedience degree of freedom is M2The chi square distribution of-M.Therefore according to target false alarm probability P set in advanceFA, can pass through very simple
It is calculated corresponding decision threshold：
Here a is that degree of freedom is M2The 1-P of the chi square distribution of-MFAQuantile.
Above analysis and design process are taken a broad view of, the construction and the meter of decision threshold of the perception judgement amount corresponding to new method
Calculation does not rely on wireless channel, primary user's signal statistics feature and noise variance situation, is a kind of total blindness's multiple antennas frequency spectrum sense
Perception method；At the same time, due to noise variance between the different antennae caused by incorrect noise factor discordance simultaneously
The calculating for perceiving judgement amount and decision threshold is not affected, thus new method can be effective against multiple antennas frequency spectrum perception applied field
The negative effect of the incorrect noise phenomenon in the presence of scape.
(3) specific implementation step
Here in conjunction with analysis process and flow process Fig. 1 above, noise is effective against not to one kind involved in the present invention
The implementation steps of deterministic multiple antennas total blindness's frequency spectrum sensing method based on sampling correlation coefficient are further described：
A () sensing node collects the reception signal sampling of M root reception antennas, form N (1≤i≤N) individual received signal vector
X (n)=[x1(n) … xM(n)]T；
B () calculates the sampling covariance matrix for receiving signal according to formula (5)
C () calculates sampling correlation coefficient according to formula (7)
D () calculates according to formula (8) and perceives judgement amount Λ；
E () calculates decision threshold γ according to formula (9)；
F () implements to perceive judgement：If Λ is ＞ γ, judge that frequency spectrum cavity-pocket is not present；Conversely, then judging that frequency spectrum cavity-pocket is deposited
.
Claims (1)
1. a kind of multiple antennas total blindness's frequency spectrum sensing method that can be effective against incorrect noise, it is characterised in that the method profit
Receive the sampling correlation coefficient between component of signal to construct perception judgement amount with multiple antennas：Multiple antennas are calculated first receives signal
Sampling covariance matrixThen sampling correlation coefficient is calculatedIn formulaRepresentI-th row jth column element,WithRepresent respectivelyI-th row i-th is arranged, the diagonal element that jth row jth is arranged；Secondly by calculatingAnd by its
Used as the perception judgement amount of frequency spectrum cavity-pocket detection, here parameter M is the number of antennas configured on sensing node；Finally implement to perceive
Judgement：When judgement amount is perceived more than the threshold value for setting, then judge that frequency spectrum cavity-pocket is not present, conversely, working as the perception judgement amount
During less than the threshold value, then judge that frequency spectrum cavity-pocket is present；
It is described to receive the sampling correlation coefficient between component of signal to construct perception judgement amount using multiple antennas, its concrete steps
For：
1) sensing node collects the reception signal sampling value x of the moment n on M root antennasi(n), 1≤i≤M, formed receiving data to
Amount x (n)=[x1(n) … xM(n)]T, at the same time sensing node N number of receiving data vector x (n) is obtained by continuous sampling,
1≤n≤N；Wherein, the transposition computing of subscript T representing matrixs；
2) the sampling covariance matrix of received signal vector is calculated：Wherein, subscript H represents conjugation
Transposition is operated；
3) sampling correlation coefficient is calculatedWherein：ForThe i-th row jth row unit
Element；
4) calculate and perceive judgement amount：
5) calculate and perceive decision threshold：Wherein：It is M that a is degree of freedom2The 1-P of the chi square distribution of-MFAQuantile, PFA
It is according to actual demand target false-alarm probability set in advance；
6) implement to perceive judgement：
If perceiving judgement amount Λ is more than decision threshold γ, judge that primary user's signal is present, i.e., now frequency spectrum cavity-pocket is not present；
If perceiving judgement amount Λ is less than decision threshold γ, judge that primary signal is not present, i.e., now frequency spectrum cavity-pocket is present.
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| CN105813089B (en) * | 2016-05-05 | 2019-01-15 | 宁波大学 | A kind of matched filtering frequency spectrum sensing method fighting incorrect noise |
| CN106713190B (en) * | 2017-01-05 | 2020-02-14 | 西安电子科技大学 | MIMO transmitting antenna number blind estimation calculation method based on random matrix theory and characteristic threshold estimation |
| CN108111213B (en) * | 2017-12-22 | 2020-09-29 | 电子科技大学 | Spectrum sensing method for multiple antennas |
| CN114205012B (en) * | 2021-12-24 | 2023-10-20 | 宁波大学 | Energy detection spectrum sensing method based on oversampling |
| CN115276857A (en) * | 2022-07-04 | 2022-11-01 | 吉首大学 | Total-blind spectrum detection method based on combination of Cholesky decomposition and convolutional neural network |
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| CN102118201B (en) * | 2010-12-31 | 2013-09-11 | 吉首大学 | Frequency spectrum blind sensing method based on covariance matrix decomposition |
| CN102497239B (en) * | 2011-12-13 | 2014-02-19 | 北京邮电大学 | Spectrum sensing method based on polarizability |
| CN103684626A (en) * | 2012-09-20 | 2014-03-26 | 中兴通讯股份有限公司 | Multi user cooperative frequency spectrum sensing data fusion method and device |
| CN102932047A (en) * | 2012-11-07 | 2013-02-13 | 北京邮电大学 | Detection method for multitape spectrum of cognitive radio (CR) suitable for multiaerial system |
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