CN108270497A - A kind of pulse generation method of impulsive noise - Google Patents
A kind of pulse generation method of impulsive noise Download PDFInfo
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- CN108270497A CN108270497A CN201810055057.XA CN201810055057A CN108270497A CN 108270497 A CN108270497 A CN 108270497A CN 201810055057 A CN201810055057 A CN 201810055057A CN 108270497 A CN108270497 A CN 108270497A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B17/00—Monitoring; Testing
- H04B17/30—Monitoring; Testing of propagation channels
- H04B17/391—Modelling the propagation channel
- H04B17/3912—Simulation models, e.g. distribution of spectral power density or received signal strength indicator [RSSI] for a given geographic region
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Abstract
The invention belongs to power line channel noise modeling fields more particularly to a kind of pulse generation method of impulsive noise, this method to include：Frequency domain extreme point Sequential Statistical Model is established using Markov Chain；According to the extreme point statistical model, construct the extreme value point sequence of frequency domain real and imaginary parts, noise real and imaginary parts frequency-domain waveform is fitted using subsection linearity inser value method to obtained extreme value point sequence, the pulse noise for having envelope trait in the time domain can be generated through IFFT variations.Technical solution of the present invention can solve the problems, such as that there are specific envelopes for its pulse width range in power line impulsive noise modeling process, the impulsive noise of generation is made to provide practical scheme and some theoretical reference foundations for low voltage power line communication channel noise modeling problem from now on closer to real noise.
Description
Technical field
The invention belongs to power line channel noise modeling technique fields, are related to a kind of pulse generation side of impulsive noise
Method.
Background technology
Power line communication (Power Line Communication, PLC), also referred to as power-line carrier communication.
The technology is coupled to the enterprising row information of power line using conventional powerline as medium, the modulated signal of carrying information and transmits, and is connecing
Receiving end from power line is separated modulated signal with coupler, completes the transmission of information.Power line communication there are user it is more,
Distribution is wide, small investment, do not need to rewiring, operating cost it is low, using advantages such as simplicity.In recent years, power line communication is quick
Development, transmission rate greatly improve, and become and solve broadband network bottleneck --- the new access technology of " last one kilometer ".
Power line communication environment is not highly desirable.Noise, attenuation, impedance be influence power line channel transmission it is main because
One of element, at any time, frequency, place variation and change, seriously affect power line communication quality and rate, be research power line
The difficult point of communication.In order to improve the communication performance of low-voltage power line, it is necessary to which power line channel noise characteristic is studied.
Noise is generally divided into ambient noise and impulsive noise, wherein impulsive noise be the most important factor of shadow communication quality it
One.Impulsive noise in power line is mainly drawn by the plug of plug in the switch on and off and socket of load appliance in circuit
It rises.In the modeling process of impulsive noise, the practical impulsive noise for measuring household electrical appliance and generating at work finds household electrical appliance
The noise of generation is more than having burst state, but also there are specific envelope forms.
In the prior art, the scale-model investigation of impulsive noise mainly considers impulse amplitude, pulse spacing and the pulse of noise
These three elements of width.Initial Bernoulli-Gaussian (BG), Middleton Class A model modeling pulses are made an uproar
Sound, it is believed that the pulse point inside impulsive noise is mutual indepedent.Follow-up work research finds that noise occurs sometimes with bursty state,
There are several impulsive noise points in each pulse length, noise is with Memorability, it is proposed that Gilbert-Elliot,
The models such as Markov Chain models and Markov-Middleton, Markov-Gaussian for developing later.Current mould
Although type can model impulsive noise very well, and there are several continuous pulses in its pulse width to make an uproar for the noise generated
Sound, but have ignored certain impulsive noises there are specific envelope forms in its pulse width range.
Invention content
In view of this, the purpose of the present invention is to provide a kind of pulse generation method of impulsive noise, pass through this method
The impulsive noise pulse of generation not only has burst state, but also there are specific envelope forms.
In order to achieve the above objectives, the present invention provides following technical solution：
A kind of pulse generation method of impulsive noise, this method comprise the following steps：
S1：Obtain extreme point sequence samples；
S2：Calculate the model parameter of extreme point；
S3：Construct frequency domain extreme value point sequence；
S4：Construct single pulse waveforms.
Further, step S1 is specially：
Multigroup pulse noise data is measured, the pulse noise for measuring acquisition is passed through into FFT transform, respectively
The extreme point of the real and imaginary parts of frequency domain is taken, forms extreme value point sequence,
Wherein, i={ 1,2 ..., I } represents i-th group of extreme value point sequence, AI、ARRepresent the amplitude of real and imaginary parts extreme point
Sequence.FR、FIRepresent the frequency sequence of real and imaginary parts extreme point.
Further, step S2 is comprised the following steps：
S21：Calculate the state space distribution of extreme point；
S22：Calculate initial state distribution matrix；
S23：Calculate state transition probability matrix.
Further, step S21 is specially：
By extreme value point sequenceAccording to amplitude and the difference of frequency boundary size, determine
The state space of frequency and amplitude,
Real part amplitude position space：X1={ AR,1,AR,2,...,AR,m}
Imaginary part amplitude position space：X2={ AI,1,AI,2,...,AI,m}
Real part frequency state space：Y1={ FR,1,FR,2,...,FR,n}
The frequency state space of imaginary part：Y2={ FR,1,FR,2,...,FR,n,
Wherein m, n represent the state space capacity of amplitude and frequency, X respectively1, X2, Y1, Y2, represented respectively according to m, n institutes
The state space taken, AR,m、AI,mRespectively m-th of amplitude position of real and imaginary parts, FR,n、FI,nRespectively real and imaginary parts
N-th of frequency state；
Each extreme point on frequency domain is uniquely determined by frequency and amplitude, is by the state-space representation of extreme point：
ZR={ [AR,i,FR,j], i=1,2 ..m, j=1,2...n }
ZI={ [AI,i,FI,j], i=1,2 ..m, j=1,2...n }
Further, initial state distribution matrix is expressed as in step S22：
QR=[p1,p2,...,pm×n]
QI=[p1,p2,...,pm×n]
Wherein, QRFor the initial state distribution matrix of real part, QIFor the initial state distribution matrix of imaginary part, original state point
Cloth probability Pi(i=1,2 ... m × n), it is expressed as the probability of initial time state i.
Further, state transition probability matrix is expressed as in step S23：
Wherein, PRFor the state-transition matrix of real part, PIFor the state-transition matrix of imaginary part, pi,j(i=1,2 ..., m ×
N, j=1,2 ..., m × n) it is expressed as probability of the state i transfers for state j.
Further, step S3 is specially；
According to the state space of extreme point, state-transition matrix and initial state distribution matrix combination Markov chain model
Frequency domain extreme value point sequence is built,
Wherein, i={ 1,2 ..., I }, AI1、AR1Represent the amplitude sequence of real and imaginary parts frequency domain extreme point.FR1、FI1Table
Show the frequency sequence of real and imaginary parts frequency domain extreme point.
Further, step S4 is specially：
It is adjacent by two using sectional curve difference approach according to the frequency domain extreme value point sequence of the real and imaginary parts of construction
Frequency domain extreme point connected with straight line, generate the frequency-domain waveform of real and imaginary parts, be by IFFT shift conversions by frequency-domain waveform
Time domain waveform.
The beneficial effects of the present invention are：The method of the present invention solves certain impulsive noises in its pulse width range not
Burst state is only showed only as, also there are specific envelope traits.It is low from now on closer to real noise to make the impulsive noise of generation
Piezoelectricity line of force interchannel noise modeling problem provides practical scheme and some theoretical reference foundations.
Description of the drawings
In order to make the purpose of the present invention, technical solution and advantageous effect clearer, the present invention provides drawings described below and carries out
Explanation：
Fig. 1 is the flow chart of the method for the present invention；
Fig. 2 is impulse noise measurement scheme；
The partial waveform that Fig. 3 is generated when being blower operation；
Fig. 4 is 483 groups of pulse frequency-domain waveforms；
Fig. 5 realizes flow chart for extreme point sequence statistic parameter；
Fig. 6 is the Markov model of extreme value point sequence；
Fig. 7 is 4 groups of extreme value point sequences of construction；
Fig. 8 is 4 groups of single pulse waveforms of construction.
Specific embodiment
Below in conjunction with attached drawing, the preferred embodiment of the present invention is described in detail.
The method of the present invention establishes frequency domain extreme point Sequential Statistical Model using Markov Chain；It is united according to the extreme point
Model is counted, constructs the extreme value point sequence of frequency domain real and imaginary parts, subsection linearity inser value method is used to obtained extreme value point sequence
Noise real and imaginary parts frequency-domain waveform is fitted, can generate the pulse for having envelope trait in the time domain through IFFT variations makes an uproar
Sound.The method of the present invention idiographic flow is as shown in Figure 1.
Fig. 2 is the measurement scheme of impulsive noise, and LISN, that is, line impedance stabilization net work in figure, is Power System Electromagnetic Compatibility
A kind of important equipment in test, is functionally similar to wave filter and voltage-stablizer.Front end power line network will be added in and be tested and set
Between standby, it can filter out to the maximum extent outside power distribution room and other instruments equipment brings the noise in power line into power distribution room
Interference, restores pure power line network as far as possible, is accessed for equipment under test.At the same time it can also stable power line as possible
The impedance of network, and certain burning voltage is provided, to play a protective role below to voltage than more sensitive instrument.And it is tested
Equipment is sealed in the power lines of LISN after processing, and the noise generated after such exemplary apparatus work is with regard in feed-in power line.
Then, these interference signals, the coupler by one with high pass filter function are coupled in PicoScope instruments.
PicoScope instruments are the key instruments of acquisition noise, to gross examination of skeletal muscle noise waveform and acquisition noise.And it collects
Noise data can be by connecting with PC ends USB, and can directly .mat files be read by locally saving as .mat file .PC ends
It takes and analyzes.This example takes household electrical appliance hair-dryer as research object, and the PicoScope digital oscilloscopes setting sampling period is
16ns, sample frequency 62.5Mkz measure 20 groups of power line communication channel noises.
Fig. 3 is a certain group of test noise partial waveform.It can be seen that bursty state is all presented per group pulse in this group of noise,
And also certain envelope trait.It is embodied in each envelope and identical damping vibration attenuation trend is presented, but whole envelope is long
Degree, envelope range value are to change at random, and local wave crest attenuation amplitude, the wave crest frequency of occurrences are also to change at random.
Fig. 4 is real and imaginary parts frequency-domain waveform of 483 groups of pulse noises in 0-100KHz frequency ranges.It is obtained according to test
483 groups of pulse time domain waveform samples,.Find that noise is concentrated mainly on 0-100KHz frequency ranges, therefore main right from frequency domain
Sampled point in the band limits is analyzed.483 groups of pulse real and imaginary parts frequency-domain waveforms are taken with the extreme point of the frequency range,
Extreme value point sequence is formed, is expressed asI=1,2 ..., and I } represent i-th group of extreme value
Sequence, AI、ARRepresent the amplitude sequence of real and imaginary parts extreme point.FR、FIRepresent the frequency sequence of real and imaginary parts extreme point.
Fig. 5 is the markovian state transfer of a n-state.MC models are the Markov Chains based on finite time
Theory, only with current related, the behavior of process is represented following state with state.One MC model is represented by=(S, P,
Q), wherein the meaning of each member is as follows：S is the state set of non-empty that all possible state of system is formed, sometimes referred to as
The state space of system；P is the state transition probability matrix of system；Q is the initial probability distribution of system.
Fig. 6 show extreme point sequence statistic parameter and realizes flow chart.The model parameter include extreme point state space, just
Beginning state is distributed and the realization of state transition probability.
Calculate extreme point state space.Frequency domain real and imaginary parts extreme value point sequencem、n
The state space capacity of frequency and amplitude is represented respectively, and according to amplitude and the difference of frequency boundary size, m, n are distinguished into value
100th, 50, determine the state space of frequency and amplitude.
Real and imaginary parts amplitude position space：
X1={ AR,1,AR,2,...,AR,m} (1)
X2={ AI,1,AI,2,...,AI,m} (2)
In formula (1) (2), AR,m、AI,mRespectively m-th of amplitude position of real and imaginary parts.
The frequency state space of real and imaginary parts is expressed as：
Y1={ FR,1,FR,2,...,FR,n} (3)
Y2={ FR,1,FR,2,...,FR,n} (4)
F in formula (3) (4)R,n、FI,nRespectively n-th of frequency state of real and imaginary parts.
Each extreme point on frequency domain is uniquely determined by frequency and amplitude, therefore extreme point state space can represent
For
ZR={ [AR,i,FR,j], i=1,2 ..m, j=1,2...n } (5)
ZI={ [AI,i,FI,j], i=1,2 ..m, j=1,2...n } (6)
Calculate state transition probability matrix.After determining extreme point state space, it is known that each extreme value point sequence on frequency domain Corresponding state.Statistic behavior transition probability turns according to state transition probability, structure state
Move matrix.Extreme point real and imaginary parts state-transition matrix is expressed as being shown below：
In formula (7) (8), pi,j(i=1,2 ..., m × n, j=1,2 ..., m × n) it is expressed as state i to shift being state j
Probability.
Calculate initial distribution probability matrix.After determining extreme point state space, it is known that each initial extreme point on frequency domainCorresponding state.Initial state probabilities are counted, build initial state distribution
Matrix.The original state matrix Q of real and imaginary partsR、QIIt is expressed as：
QR=[p1,p2,...,pm×n] (9)
QI=[p1,p2,...,pm×n] (10)
In formula (9) (10), initial state distribution probability Pi(i=1,2 ... m × n), it is expressed as initial time state i's
Probability.
Fig. 7 is 4 groups of extreme value point sequences of construction.The shape of real and imaginary parts extreme point is respectively obtained according to sample statistics calculating
State transition probability matrix PR、PI, initial distribution probability matrix QR、QIAnd state space Z1、Z2.Utilize Markov chain model
Extreme point is modeled, the extreme value point sequence of no array frequency domain real and imaginary parts can be obtained.(a) is the 4 of construction in Fig. 7
Real part extreme value point sequence is organized, (b) is the 4 groups of imaginary part extreme value point sequences constructed in Fig. 7.
Fig. 8 is 4 groups of single pulse waveforms of construction.According to the real and imaginary parts extreme value point sequence of generation, using sectional curve
Interpolation method links up the adjacent extreme point of each two with straight line, generates the frequency-domain waveform of real and imaginary parts, frequency-domain waveform warp
IFFT variations switch to time domain waveform.The time domain waveform constructed not only has good bursty state, but also shows certain
Envelope trait, identical damping vibration attenuation trend is presented in each envelope, but whole envelope length, envelope range value are to change at random,
The wave crest attenuation amplitude of part, the wave crest frequency of occurrences are also to change at random.
Finally illustrate, preferred embodiment above is only to illustrate the technical solution of invention and unrestricted, although passing through
Above preferred embodiment is described in detail the present invention, however, those skilled in the art should understand that, can be in shape
Various changes are made in formula and to it in details, without departing from claims of the present invention limited range.
Claims (8)
1. the pulse generation method of a kind of impulsive noise, which is characterized in that this method comprises the following steps：
S1：Obtain extreme point sequence samples；
S2：Calculate the model parameter of extreme point；
S3：Construct frequency domain extreme value point sequence；
S4：Construct single pulse waveforms.
2. the pulse generation method of a kind of impulsive noise according to claim 1, which is characterized in that step S1 is specific
For：Multigroup pulse noise data is measured, the pulse noise obtained will be measured by FFT transform, take frequency respectively
The extreme point of the real and imaginary parts in domain forms extreme value point sequence,
Wherein, i={ 1,2 ..., I } represents i-th group of extreme value point sequence, AI、ARRepresent the amplitude sequence of real and imaginary parts extreme point
Row.FR、FIRepresent the frequency sequence of real and imaginary parts extreme point.
3. the pulse generation method of a kind of impulsive noise according to claim 2, which is characterized in that step S2 is included such as
Lower step：
S21：Calculate the state space distribution of extreme point；
S22：Calculate initial state distribution matrix；
S23：Calculate state transition probability matrix.
4. the pulse generation method of a kind of impulsive noise according to claim 3, which is characterized in that step S21 is specific
For：
By extreme value point sequenceAccording to amplitude and the difference of frequency boundary size, frequency is determined
With the state space of amplitude,
Real part amplitude position space：X1={ AR,1,AR,2,...,AR,m}
Imaginary part amplitude position space：X2={ AI,1,AI,2,...,AI,m}
Real part frequency state space：Y1={ FR,1,FR,2,...,FR,n}
The frequency state space of imaginary part：Y2={ FR,1,FR,2,...,FR,n,
Wherein m, n represent the state space capacity of amplitude and frequency, X respectively1, X2, Y1, Y2, represented respectively according to m, the shape that n is taken
State space, AR,m、AI,mRespectively m-th of amplitude position of real and imaginary parts, FR,n、FI,nRespectively n-th of real and imaginary parts
Frequency state；
Each extreme point on frequency domain is uniquely determined by frequency and amplitude, is by the state-space representation of extreme point：
ZR={ [AR,i,FR,j], i=1,2 ..m, j=1,2...n }
ZI={ [AI,i,FI,j], i=1,2 ..m, j=1,2...n }
5. the pulse generation method of a kind of impulsive noise according to claim 4, which is characterized in that in step S22 just
Beginning state distribution matrix is expressed as：
QR=[p1,p2,...,pm×n]
QI=[p1,p2,...,pm×n]
Wherein, QRFor the initial state distribution matrix of real part, QI is the initial state distribution matrix of imaginary part, and initial state distribution is general
Rate Pi(i=1,2 ... m × n), it is expressed as the probability of initial time state i.
A kind of 6. pulse generation method of impulsive noise according to claim 5, which is characterized in that shape in step S23
State transition probability matrix is expressed as：
Wherein, PRFor the state-transition matrix of real part, PIFor the state-transition matrix of imaginary part, pi,j(i=1,2 ..., m × n, j=
1,2 ..., m × n) it is expressed as probability of the state i transfers for state j.
7. the pulse generation method of a kind of impulsive noise according to claim 6, which is characterized in that step S3 is specific
For；
According to the state space of extreme point, state-transition matrix and initial state distribution matrix combination Markov chain model structure
Frequency domain extreme value point sequence,
Wherein, i={ 1,2 ..., I }, AI1、AR1Represent the amplitude sequence of real and imaginary parts frequency domain extreme point.FR1、FI1Represent real
Portion and the frequency sequence of imaginary part frequency domain extreme point.
8. the pulse generation method of a kind of impulsive noise according to claim 7, which is characterized in that step S4 is specific
For：
According to the frequency domain extreme value point sequence of the real and imaginary parts of construction, using sectional curve difference approach, by two adjacent frequencies
Domain extreme point is connected with straight line, generates the frequency-domain waveform of real and imaginary parts, and it is time domain that frequency-domain waveform is passed through IFFT shift conversions
Waveform.
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| CN111313985A (en) * | 2020-03-05 | 2020-06-19 | 北京振中电子技术有限公司 | Broadband power line carrier communication analog noise generation method and device and electronic equipment |
| CN112104392A (en) * | 2020-10-08 | 2020-12-18 | 广东石油化工学院 | PLC channel impulse noise detection method and system using state matrix |
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| CN111313985A (en) * | 2020-03-05 | 2020-06-19 | 北京振中电子技术有限公司 | Broadband power line carrier communication analog noise generation method and device and electronic equipment |
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