CN102263716A - Modulation type identifying method and system - Google Patents

Abstract

The invention discloses a modulation type identifying method and system. The modulation type identifying method comprises the steps of: preprocessing MQAM (multilevel quadrature amplitude modulation) signals, and separating the preprocessed MQAM signals and code elements; separating reference code elements, transforming the preprocessed MQAM signals at the same interval between code elements to a phase space domain, describing the transformed MQAM signals by a phase diagram, and extracting the characteristic parameters of the transformed MQAM signals in the phase diagram; and carrying out cluster analysis to the characteristic parameters, identifying the results of the cluster analysis in a classified way, and determining the modulation type. By applying the scheme, the preprocessed MQAM signals in the same code element are transformed to the phase space domain, the transformed MQAM signals are described by adopting the phase diagram, and the characteristic parameters of the transformed MQAM signals in the phase diagram are extracted. The parameter extracting method can reduced the number of characteristic parameters, thus the identification time is shortened, and the real-time property of identification and the identification efficiency are improved.

Description

A kind of modulation type recognition methods and system

Technical field

The application relates to the signal of communication processing technology field, particularly relates to recognition methods of a kind of signal of communication modulation type and system.

Background technology

The modulation type recognition technology is a kind of MQAM (Multiple Quadrature Amplitude Modulation that is used to discern, the M-ary orthogonal amplitude modulation(PAM)) recognition technology of the modulation type of signal, be a committed step between MQAM input and the demodulation, important use all arranged in military and civilian fields such as cognitive radio, heterogeneous wireless network convergence, self-organizing network and the detectings of communicating by letter.

MQAM is a signal of communication modulation type commonly used at present.Recognition methods generally includes two parts to the MQAM signal modulation style: the preliminary treatment of MQAM signal and the selection of sorting technique.Preliminary treatment comprises down-conversion, reduces the estimation of noise, equilibrium and chip rate etc.Mainly contain two classes in sorting technique: based on the maximum likelihood ratio method of decision theory with based on the pattern-recongnition method of feature extraction.

In the statistical pattern recognition method based on feature extraction, identifying comprises: feature extraction and Classification and Identification.Feature extraction is to extract characteristic parameter from pretreated MQAM signal, and Classification and Identification then is that the characteristic parameter that will be extracted and the parameter of known modulation pattern compare and adjudicate, and finishes the identification of signal modulation style.In the existing mode identification method, mainly be based on the cluster recognition methods of planisphere.

Patent of invention 200910219448.1 has been announced a kind of " based on the MQAM signal recognition method of clustering algorithm ", this method is according to the symmetry of planisphere, the in-phase component of extraction baseband signal and quadrature component are determined modulation type as the cluster feature collection according to the cluster centre number.When cluster centre point number is 2, judge that the MQAM signal is the 4QAM signal.When cluster centre point number is 4, judge that the MQAM signal is the 16QAM signal.When cluster centre point number is 6, judge that the MQAM signal is the 32QAM signal.When cluster centre point number is 7,8 or 9, judge that the MQAM signal is the 64QAM signal.Yet above-mentioned cluster recognition methods based on planisphere is more because of characteristic parameter, has increased recognition time, has reduced identification real-time and recognition efficiency.

Summary of the invention

In view of this, the embodiment of the present application discloses a kind of modulation type recognition methods and system, reduces the characteristic parameter number of extracting, and then has reduced recognition time, has improved identification real-time and recognition efficiency.Technical scheme is as follows:

Based on the application's one side, a kind of modulation type recognition methods is disclosed, comprising:

M-ary orthogonal amplitude modulation(PAM) MQAM signal is carried out preliminary treatment, the MQAM signal after obtaining handling and the symbol interval of the MQAM signal after the described processing;

With reference to described symbol interval, to the phase space territory, adopt phasor to describe the MQAM signal transformation after the processing in the same symbol interval, the characteristic parameter of MQAM signal in phasor after the extraction conversion to the MQAM signal after this conversion;

Described characteristic parameter is carried out cluster analysis, obtain cluster analysis result;

Described cluster analysis result is carried out Classification and Identification, determine modulation type.

Preferably, describedly the MQAM signal carried out preliminary treatment comprise:

Use is carried out Filtering Processing based on the nonlinear filter of D ü ffing oscillator system to the MQAM signal, the MQAM signal after obtaining handling.

Preferably, described D ü ffing oscillator system structure is: $\stackrel{\·\·}{x}+\mathrm{\β\ω}\stackrel{\·}{x}+{\mathrm{\ω}}^2(\mathrm{kx}+\mathrm{\μ}{x}^3)=\mathrm{F\ωs}\left(t\right),$ Wherein: s (t) is the normalized form of the MQAM signal of reception; ω is the MQAM signal center angular frequency of input; X is the MQAM signal after handling;

Second dervative for the MQAM signal after handling;

First derivative for the MQAM signal after handling; F is the driving force constant of oscillator system; β is the oscillator system damping coefficient; μ, k are the non-vanishing real number of input.

Preferably, the symbol interval of the MQAM signal after obtaining handling comprises:

MQAM signal after handling is carried out continuous wavelet transform, the signal after the acquisition conversion;

The amplitude of the signal after the detection conversion is determined the sampled point number between adjacent two peak values, draws a plurality of symbol intervals;

A plurality of symbol intervals are carried out statistical average, obtain symbol interval more accurately, determine this more accurately symbol interval be the symbol interval of the MQAM signal after handling.

Preferably, in advance standard M-ary orthogonal amplitude modulation(PAM) MQAM signal is carried out the characteristic statistics, determine the cluster numbers of various criterion quadrature amplitude modulation MQAM signal correspondence;

Described described cluster analysis result is carried out Classification and Identification, determines that modulation type comprises:

Obtain the cluster numbers of the MQAM signal correspondence after the described conversion;

The cluster numbers obtained and the cluster numbers of predetermined various criterion MQAM signal correspondence are compared, determine the system number of the MQAM signal after the described processing, the identification modulation type.

Preferably, the cluster numbers of obtaining the MQAM signal correspondence after the described processing comprises:

According to the evaluation function formula $Q_k=\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\underset{X,Y\&Element;C_i}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2+\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\left(\underset{l=1,i\&NotEqual;\mathrm{<figure-callout\; id="1"\; label="l\; k"\; filenames="HDA0000078654570000032.png"\; state="\{\{state\}\}">l</figure-callout>}}{\overset{k}{\mathrm{\&Sigma;}}}\frac{1}{\left|C_i\right|\&CenterDot;\left|C_l\right|}\underset{X\&Element;C_i,Y\&Element;C_l}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2\right),$ Determine the evaluation function Q of the characteristic parameter correspondence after the cluster analysis _kValue, wherein: k is the cluster numbers of various criterion QAM signal correspondence, C _iAnd C _lThe set number of the characteristic parameter that obtains for cluster analysis, X and Y are two characteristic parameters;

Choose the evaluation function Q of different cluster numbers k correspondences _kThe evaluation function Q of numerical value minimum in the value _kValue is determined minimum evaluation function Q _kThe corresponding cluster numbers k of value is the cluster numbers of the MQAM signal correspondence after handling.

Based on the application's one side, a kind of modulation type recognition system is also disclosed, comprising:

Pretreatment module is used for the MQAM signal is carried out preliminary treatment, the MQAM signal after obtaining handling and the symbol interval of the MQAM signal after the described processing;

Characteristic extracting module is used for reference to described symbol interval, to the phase space territory, adopts phasor to describe to the MQAM signal after this conversion the MQAM signal transformation after the processing in the same symbol interval, the characteristic parameter of MQAM signal in phasor after the extraction conversion;

The cluster analysis module is used for described characteristic parameter is carried out cluster analysis, obtains cluster analysis result;

Identification module is used for described cluster analysis result is carried out Classification and Identification, determines modulation type.

Preferably, pretreatment module comprises: filter unit is used to use the nonlinear filter based on D ü ffing oscillator system the MQAM signal to be carried out Filtering Processing, the MQAM signal after obtaining handling.

Preferably, described D ü ffing oscillator system structure is: $\stackrel{\&CenterDot;\&CenterDot;}{x}+\mathrm{\&beta;\&omega;}\stackrel{\&CenterDot;}{x}+{\mathrm{\&omega;}}^2(\mathrm{kx}+\mathrm{\&mu;}{x}^3)=\mathrm{F\&omega;s}\left(t\right),$ Wherein: s (t) is the normalization MQAM signal of the MQAM signal of input, and ω is the MQAM signal center angular frequency of input, and x is the MQAM signal after handling,

Second dervative for the MQAM signal after handling;

First derivative for the MQAM signal after handling; F is the driving force constant of oscillator system, and β is the oscillator system damping coefficient; μ, k are the non-vanishing real number of input.

Preferably, pretreatment module also comprises:

Signal conversion unit is used for the MQAM signal after handling is carried out continuous wavelet transform the signal after the acquisition conversion;

The symbol interval acquiring unit is used to detect the amplitude of the signal after the conversion, determines the sampled point number between adjacent two peak values, draws a plurality of symbol intervals;

The symbol interval determining unit is used for a plurality of symbol intervals are carried out statistical average, obtains symbol interval more accurately, determine this more accurately symbol interval be the symbol interval of the MQAM signal after handling.

Preferably, in advance standard M-ary orthogonal amplitude modulation(PAM) MQAM signal is carried out the characteristic statistics, determine the cluster numbers of various criterion quadrature amplitude modulation MQAM signal correspondence;

Described identification module comprises:

The cluster numbers acquiring unit is used to obtain the cluster numbers of the MQAM signal correspondence after the described conversion;

Recognition unit is used for the cluster numbers that will obtain and the cluster numbers of predetermined various criterion MQAM signal correspondence and compares, and determines the system number of the MQAM signal after the described processing, the identification modulation type.

Preferably, described cluster numbers acquiring unit comprises:

Evaluation function Q _kThe value determining unit is used for according to the evaluation function formula $Q_k=\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\underset{X,Y\&Element;C_i}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2+\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\left(\underset{l=1,i\&NotEqual;\mathrm{<figure-callout\; id="1"\; label="l\; k"\; filenames="HDA0000078654570000032.png"\; state="\{\{state\}\}">l</figure-callout>}}{\overset{k}{\mathrm{\&Sigma;}}}\frac{1}{\left|C_i\right|\&CenterDot;\left|C_l\right|}\underset{X\&Element;C_i,Y\&Element;C_l}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2\right),$ Determine the evaluation function Q of the characteristic parameter correspondence after the cluster analysis _kValue, wherein: k is the cluster numbers of various criterion QAM signal correspondence, C _iAnd C _lThe set number of the characteristic parameter that obtains for cluster analysis, X and Y are two characteristic parameters;

The cluster numbers determining unit is used to choose the evaluation function Q of different k correspondences _kThe evaluation function Q of numerical value minimum in the value _kValue is determined minimum evaluation function Q _kThe corresponding k of value is the cluster numbers of the MQAM signal correspondence after handling.

Use technique scheme, obtain the symbol interval of the MQAM signal after the processing, MQAM signal transformation after the processing in the same code element to the phase space territory, is adopted the MQAM signal after phasor is described conversion, the characteristic parameter of MQAM signal in phasor after the extraction conversion.The mode of this extracting parameter and existing mode according to planisphere extraction characteristic parameter have reduced the characteristic parameter number, and then have reduced recognition time, have improved identification real-time and recognition efficiency.

Description of drawings

In order to be illustrated more clearly in the embodiment of the present application or technical scheme of the prior art, to do to introduce simply to the accompanying drawing of required use in embodiment or the description of the Prior Art below, apparently, the accompanying drawing that describes below only is some embodiment that put down in writing among the application, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.

Fig. 1 is the flow chart of the disclosed a kind of modulation type recognition methods of the embodiment of the present application;

Fig. 2 is the oscillogram of 16QAM signal;

Fig. 3 is the oscillogram after using nonlinear filter based on D ü ffing oscillator system to 16QAM signal filtering shown in Figure 2;

Fig. 4 is the flow chart of the symbol interval of the MQAM signal after obtaining handling;

Fig. 5 is through the amplitude figure behind the continuous wavelet transform to 16QAM signal shown in Figure 3;

Fig. 6 is the phasor of 16QAM signal shown in Figure 3;

Fig. 7 is the characteristic parameter distribution map of phasor shown in Figure 6;

Fig. 8 is the flow chart of step S104 in the modulation type recognition methods shown in Figure 1;

Fig. 9 is the structural representation of the disclosed a kind of modulation type recognition system of the embodiment of the present application;

Figure 10 is the structural representation of pretreatment module in the modulation type recognition system shown in Figure 9;

Figure 11 is the structural representation of identification module in the modulation type recognition system shown in Figure 9.

Embodiment

For above-mentioned purpose, the feature and advantage that make the application can become apparent more, the application is described in further detail below in conjunction with the drawings and specific embodiments.

The inventor is through discovering, " based on the MQAM signal recognition method of clustering algorithm " that patent of invention 200910219448.1 is announced is when extracting characteristic parameter, symmetry according to planisphere, the in-phase component of extraction baseband signal and quadrature component are as the cluster feature collection, increased the cluster density of cluster centre point, solved because modulating system complexity, real-time difference and the low problem of discrimination that the multi-cluster radius causes.But aforesaid way causes planisphere cluster feature and feature center still more, and real-time and discrimination improve limited.

In order to address the above problem, the embodiment of the present application discloses a kind of modulation type recognition methods, the characteristic parameter of MQAM signal in phase space after the extraction conversion, thus reduce the characteristic parameter number, and then reduced recognition time, improved identification real-time and recognition efficiency.

See also Fig. 1, Fig. 1 is the flow chart of the disclosed a kind of modulation type recognition methods of the embodiment of the present application, comprising:

S101: the MQAM signal is carried out preliminary treatment, the symbol interval or the chip rate of the MQAM signal after MQAM signal after obtaining handling and the processing.

Preliminary treatment to the MQAM signal comprises: the estimation of down-conversion, reduction noise, equilibrium and chip rate etc.For above-mentioned preliminary treatment, can adopt existing mode, this is no longer set forth prior art.

Certainly, can also adopt other modes, can use nonlinear filter the MQAM signal to be carried out Filtering Processing, the MQAM signal after obtaining handling based on D ü ffing oscillator system as the embodiment of the present application to the preliminary treatment of MQAM signal.

D ü ffing oscillator system structure is: $\stackrel{\&CenterDot;\&CenterDot;}{x}+\mathrm{\&beta;\&omega;}\stackrel{\&CenterDot;}{x}+{\mathrm{\&omega;}}^2(\mathrm{kx}+\mathrm{\&mu;}{x}^3)=\mathrm{F\&omega;s}\left(t\right),$ Wherein: s (t) is the normalization MQAM signal of the MQAM signal of input, and ω is the central angle frequency of input MQAM signal, and x is the MQAM signal after handling,

Be the second dervative of the MQAM signal after handling, Be the first derivative of the MQAM signal after handling, F is the driving force constant of oscillator system, and β is the oscillator system damping coefficient, and μ, k are the non-vanishing real number of input.D ü ffing oscillator system structure is not limited to adopt said structure.Adopt the D ü ffing oscillator system of said structure to carry out computing normalization MQAM signal s (t), then can draw the MQAM signal x after the processing, promptly reduce the MQAM signal behind the noise.

With centre frequency shown in Figure 2 be 200Hz, to contain additive Gaussian noise, signal to noise ratio be that the 16QAM signal of 10dB is an example as the MQAM signal of input.MQAM signal normalization to the 10dB of input is handled, and obtains normalization MQAM signal, with the above-mentioned D ü of normalization MQAM signal substitution ffing oscillator system, gets β=0.6 respectively, k=-0.5, μ=0.5, ω=2 π * 200=1256rad/s, F=0.1.Above-mentioned 16QAM signal used based on the nonlinear filter of D ü ffing oscillator system the MQAM signal is carried out oscillogram that Filtering Processing obtains as shown in Figure 3.

Above-mentioned use is carried out not needing signal is further done down-conversion and equilibrium treatment, and then having simplified pretreatment process after the Filtering Processing to the MQAM signal based on the nonlinear filter of D ü ffing oscillator system.Simultaneously, D ü ffing oscillator system has very high sensitiveness to arrowband MQAM signal, thereby given prominence to the non-correlation between communication channel noise and the MQAM signal better, increased the signal to noise ratio of the MQAM signal after handling, strengthened the accuracy that feature extraction and chip rate are estimated.

Detect and obtain the MQAM signal behind the above-mentioned reduction noise chip rate flow chart as shown in Figure 4, comprising:

S1011: the MQAM signal after handling is carried out continuous wavelet transform, the signal after the acquisition conversion.

Continuous wavelet transform is defined as:

$\mathrm{CWT}(a,\mathrm{\&tau;})=\&Integral;s\left(t\right){\mathrm{\&psi;}}_a^{*}\left(t\right)\mathrm{dt}=\frac{1}{\sqrt{a}}\&Integral;s\left(t\right){\mathrm{\&psi;}}_a^{*}\left(\frac{t-\mathrm{\&tau;}}{a}\right)\mathrm{dt}$

Wherein: a is a scale factor, and τ is a shift factor, and * refers to complex conjugate.ψ (t) is female small echo, ψ _a(t) be the sub-small echo that on the basis of female small echo ψ (t), has carried out change of scale and displacement.The effect of scale factor a is female small echo ψ (t) to be done flexible, and a is big more, and ψ (t/a) is wide more, and the duration of small echo becomes big and broadening with a; Amplitude with

Be inversely proportional to. Effect be that the wavelet energy with different a values keep to be equated, i.e. ‖ ψ _a(t) ‖ ₂=‖ ψ (t) ‖ ₂

Suppose that r (t) is the MQAM signal that receives, its expression-form is:

$r\left(t\right)=s\left(t\right)+\mathrm{\&epsiv;}\left(t\right)=\tilde{s}\left(t\right)e^{j({\mathrm{\&omega;}}_{c}t+{\mathrm{\&theta;}}_c)}+\mathrm{\&epsiv;}\left(t\right).$

Wherein: s (t) is the plural form of MQAM signal, and ε (t) is a white complex gaussian noise, and its power is:

ω _cAnd θ _cBe respectively carrier frequency and carrier phase.If baseband signal is: $\tilde{s}\left(t\right)=\underset{i}{\mathrm{\&Sigma;}}\sqrt{S_i}{e}^{j{\mathrm{\&phi;}}_i}{u}_T(t-\mathrm{iT});$ ${\mathrm{\&phi;}}_i\&Element;{\{2\mathrm{\&pi;}(m-1)/M\}}_{m=1}^M.$

Wherein: S _iBe i symbol signal power, M is the system number of the modulation type of MQAM signal employing, and T is symbol interval or element duration.

Suppose that the MQAM signal is at k=iT place phase change in the T of time (i-1) T＜k＜(i+1), the phase change amount is: α=φ _I+1-φ _iThen should can be expressed as by the MQAM signal in the time period:

$s\left(k\right)=\left\{\begin{array}{c}\sqrt{S_i}{e}^{j({\mathrm{\&omega;}}_{c}k+{\mathrm{\&theta;}}_c)}{e}^{j{\mathrm{\&phi;}}_i},(i-1)T\&le;k<\mathrm{iT}\\ \sqrt{S_{i+1}}{e}^{j({\mathrm{\&omega;}}_{c}k+{\mathrm{\&theta;}}_c)}{e}^{j({\mathrm{\&phi;}}_i+\mathrm{\&alpha;})},\mathrm{iT}\&le;k<(i+1)T\end{array}\right.$

The MQAM signal not only has the change at random of phase place, and the change at random of symbol magnitude also can be arranged.When k satisfies

The time, promptly within same element duration, this moment, the MQAM signal did not have phase hit, and the wavelet transformation of s this moment (k) is:

$\left|\stackrel{\&OverBar;}{{\mathrm{WT}}_P}(a,n)\right|=2\sqrt{\frac{S_i}{a}}\left|\frac{{\sin }^2({\mathrm{\&omega;}}_{c}a/4)}{\sin ({\mathrm{\&omega;}}_c/2)}\right|$

Find out easily, when not having phase hit,

Be definite value.

When n=iT, in the alternation moment between adjacent code element, amplitude and phase place might change, and then the wavelet transformation of s (k) is:

Work as S _i=S _I+1The time, $\left|\stackrel{\&OverBar;}{{\mathrm{WT}}_P}(a,n)\right|=2\sqrt{\frac{S_i}{a}}\left|\frac{\sin ({\mathrm{\&omega;}}_{c}a/4)\sin ({\mathrm{\&omega;}}_{c}a/4+\mathrm{\&alpha;}/2)}{\sin ({\mathrm{\&omega;}}_c/2)}\right|$

General a is less, has | sin (ω _cA/4+ α/2) | ≈ sin (a/2)＞＞sin (ω _cA/4), ω _cA＜＜π, promptly $\left|\stackrel{\&OverBar;}{{\mathrm{WT}}_P}(a,\mathrm{iT})\right|>>\left|\stackrel{\&OverBar;}{{\mathrm{WT}}_P}(a,n)\right|.$

Work as S _i≠ S _I+1The time, $\left|\stackrel{\&OverBar;}{{\mathrm{WT}}_P}(a,\mathrm{iT})\right|>>\left|\stackrel{\&OverBar;}{{\mathrm{WT}}_P}(a,n)\right|.$

By above-mentioned formula, finish wavelet transformation to the MQAM signal after handling, obtain the signal after the conversion.Why adopt continuous wavelet transform that signal is handled, be because continuous wavelet transform logarithm value jumping moment sensitivity, and in the signal of communication zero hour of a code element also be another code element ending constantly, promptly the consecutive points place of two code elements has catastrophe point.At the catastrophe point place, the signal amplitude sudden change.Therefore, adopt continuous wavelet transform, can in time detect element position and change, and then in subsequent step, can obtain chip rate exactly signal processing.

S1012: the amplitude of the signal after the detection conversion, determine the sampled point number between adjacent two peak values, draw a plurality of symbol intervals.Wherein: peak value is the maximum amplitude of signal.

Fig. 5 is through the amplitude figure behind the continuous wavelet transform to 16QAM signal shown in Figure 3.As can be seen from the figure, be code element variation place in catastrophe point, there is tangible peak value in wavelet transformation, and peak value is not both because the power S of adjacent code element is all different with phase change amount α.Peak value by signal after the setting threshold detection conversion can draw the position that code element changes, and determines the sampled point number between adjacent two peak values, and then draws symbol interval.

Need to prove: the longitudinal axis of Fig. 3 and Fig. 5 is the amplitude after the normalized, and transverse axis is a sampling number.Wherein: the sampling number of Fig. 3 is since 3000, and the sampling number of Fig. 5 is since 0.

S1013: a plurality of symbol intervals are carried out statistical average, obtain symbol interval more accurately.

The symbol interval more accurately that obtains is defined as the symbol interval of the MQAM after the above-mentioned processing, and with reference to this symbol interval the MQAM after handling is handled in subsequent step.

S102: reference symbols sn to the phase space territory, adopts phasor to describe to the MQAM signal after this conversion the MQAM signal transformation after the processing in the same symbol interval, the characteristic parameter of MQAM signal in phasor after the extraction conversion at interval.

The description form that Fig. 6 is 16QAM signal transformation shown in Figure 3 in the phase space territory, i.e. phasor.Wherein, transverse axis is described normalized MQAM signal x, and the longitudinal axis is the first derivative x ' of described signal.

Fig. 7 is the characteristic parameter distribution map that extracts on phasor shown in Figure 6, wherein when extracting characteristic parameter with x=-1, x '=0 is a central shaft.Transverse axis represents phase space thresholding (x, x ') apart from the projection of distance on transverse axis between phasor central point (1,0) among Fig. 7, represents with A1; The longitudinal axis represents phase space thresholding (x, x ') apart from the projection of distance on the longitudinal axis between phasor central point (1,0) among Fig. 7, uses A ₂Expression.

By above-mentioned Fig. 6 and Fig. 7 as can be seen, when the MQAM signal is the 16QAM signal, the cluster centre point of characteristic parameter is 3, " based on the MQAM signal recognition method of clustering algorithm " with respect to patent of invention 200910219448.1 announcements, the characteristic parameter number of extracting reduces, and then cluster centre point number reduces.Therefore, in follow-up cluster identifying, reduce recognition time, improved identification real-time and recognition efficiency.

Above-mentioned steps S101 and S102 can be implemented in and extract characteristic parameter on the phasor, and describe characteristic parameter with phasor.But during the position that changes by the setting threshold detected symbol, the code element change location that the peak value of signal is lower than setting threshold after the conversion is not detected, and causes code element to lose, and then reduces when extracting characteristic parameter and extract accuracy.Therefore, the embodiment of the present application also comprises between step 101 and step S102:

A plurality of symbol intervals are calculated, obtain described symbol interval or chip rate.According to described chip rate, interpolation processing is carried out in variation place of nd code element, do not lose to guarantee code element, further improve and extract accuracy.Symbol interval draws to be specially a plurality of symbol intervals is averaged, and on average the symbol interval after is as described actual symbol interval, and chip rate is an actual symbol inverse at interval.

S103: characteristic parameter is carried out cluster analysis, obtain cluster analysis result.Wherein: cluster analysis result is a cluster centre point number.Can adopt the clusterdata function that sample data is carried out cluster one time to the cluster analysis of characteristic parameter, also can adopt the distribution clustering method.Because distribution clustering method flexibility height is so the embodiment of the present application preferably uses the distribution clustering method to carry out feature clustering.

S104: described cluster analysis result is carried out Classification and Identification, determine modulation type.Wherein: Classification and Identification can adopt existing classification Technology of Judgment, neural net method and SVM (support vector machine, SVMs) method.

Step S104 can also adopt Classification and Identification shown in Figure 8, comprising:

S1041: the cluster numbers of obtaining the MQAM signal correspondence after the described conversion.Be specially:

According to the evaluation function formula $Q_k=\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\underset{X,Y\&Element;C_i}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2+\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\left(\underset{l=1,i\&NotEqual;\mathrm{<figure-callout\; id="1"\; label="l\; k"\; filenames="HDA0000078654570000032.png"\; state="\{\{state\}\}">l</figure-callout>}}{\overset{k}{\mathrm{\&Sigma;}}}\frac{1}{\left|C_i\right|\&CenterDot;\left|C_l\right|}\underset{X\&Element;C_i,Y\&Element;C_l}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2\right),$ Determine the evaluation function Q of the characteristic parameter correspondence after the cluster analysis _kValue, wherein: k is the cluster numbers of various criterion QAM signal correspondence, C _iAnd C _lThe set number of the characteristic parameter that obtains for cluster analysis, X and Y are two characteristic parameters.

First refers to be classified in the above-mentioned evaluation function formula bunch is the quadratic sum that there is the distance between any two characteristic parameters in the characteristic parameter in same cluster centre point place, be about to each bunch and regard big " data point " as, " distance " between big " data point " weighed by the right average distance of characteristic parameter between the difference bunch.Compactness in this is used for weighing bunch.Second refer to the right square distance of the characteristic parameter between any two bunches and, compactness between being used for weighing bunch.Can prove evaluation function Q _kIt is reasonable more to be worth more little, corresponding classification.

Choose the evaluation function Q of different cluster numbers k correspondences _kThe evaluation function Q of numerical value minimum in the value _kValue is determined minimum evaluation function Q _kThe corresponding cluster numbers k of value is the cluster numbers of the MQAM signal correspondence after handling.

S1042: the cluster numbers obtained and the cluster numbers of predetermined various criterion MQAM signal correspondence are compared, determine the system number of the MQAM signal after the described processing, the identification modulation type.

The cluster numbers of predetermined various criterion MQAM signal correspondence is in advance standard M-ary orthogonal amplitude modulation(PAM) MQAM signal to be carried out the cluster numbers that characteristic is added up determined various criterion quadrature amplitude modulation MQAM signal correspondence.The inventor is through repetition test, the cluster numbers of determining BASK (Binary Amplitude Shift Keying, binary system amplitude keying) signal, 4QAM signal, 8QAM signal, 16QAM signal, 32QAM signal, 64QAM signal correspondence is respectively 1,1,2,3,5,9.

The inventor draws when cluster numbers k=3 evaluation function Q after adopting step S103 and step S104 to handle to characteristic parameter shown in Figure 7 _kValue is minimum, therefore, and with the cluster numbers of the MQAM signal correspondence of cluster numbers k=3 after as conversion.The cluster numbers of cluster numbers k=3 and predetermined various criterion MQAM signal correspondence compares, and determine that the MQAM signal is the 16QAM signal, and then modulation type is 16QAM as can be known.The MQAM signal of determining through the disclosed modulation type recognition methods of the embodiment of the present application is identical with the signal of the actual description of Fig. 7, i.e. the recognition accuracy height of the disclosed modulation type recognition methods of the embodiment of the present application.

In order to prove the accuracy of the disclosed modulation type recognition methods of the embodiment of the present application, adopt the Simulink7.0 simulated environment that 8QAM, 16QAM, 32QAM and 64QAM signal are carried out emulation, simulation result sees Table 1, and listed data are the correct recognition rata of MQAM signal in the table.The emulation experiment condition is to be 200Hz in centre carrier frequency, and chip rate is 20 bauds, and sampling rate is to carry out under the 10ksps; Every 1sec is once statistics, the result of per 50 statistical averages.

Table 1 simulation result

?SNR(dB)	M＝8	M＝16	M＝32	M＝64
					?35	1.00	1.00	1.00	1.00
?30	1.00	1.00	1.00	0.96
					?25	1.00	1.00	1.00	1.00
?20	1.00	1.00	1.00	0.94
					?15	0.94	1.00	0.98	0.92

Use technique scheme, through the MQAM signal after obtaining handling after the preliminary treatment, obtain the symbol interval of the MQAM signal after the processing, the phase space territory is arrived in MQAM signal transformation after the processing in the same symbol interval, adopt the MQAM signal after phasor is described institute's conversion, the characteristic parameter of MQAM signal in phasor after the extraction conversion.The mode of this extracting parameter and existing mode according to planisphere extraction characteristic parameter have reduced the characteristic parameter number of extracting, and then have reduced recognition time, have improved identification real-time and recognition efficiency.

Embodiment is corresponding with said method, and the embodiment of the present application also discloses a kind of modulation type recognition system, and structural representation comprises as shown in Figure 9: pretreatment module 81, characteristic extracting module 82, cluster analysis module 83 and identification module 84.Wherein:

Pretreatment module 81 is used for the MQAM signal is carried out preliminary treatment, the MQAM signal after obtaining handling and the symbol interval of the MQAM signal after the described processing.Wherein:

Preliminary treatment to the MQAM signal comprises: the estimation of down-conversion, reduction noise, equilibrium and chip rate etc.For above-mentioned preliminary treatment, can adopt existing mode, this is no longer set forth prior art.

Above-mentioned pretreatment module 81 structural representations see also Figure 10, comprising: filter unit 811 is used to use the nonlinear filter based on D ü ffing oscillator system the MQAM signal to be carried out Filtering Processing, the MQAM signal after obtaining handling.

D ü ffing oscillator system structure is: $\stackrel{\&CenterDot;\&CenterDot;}{x}+\mathrm{\&beta;\&omega;}\stackrel{\&CenterDot;}{x}+{\mathrm{\&omega;}}^2(\mathrm{kx}+\mathrm{\&mu;}{x}^3)=\mathrm{F\&omega;s}\left(t\right),$ Wherein: the normalization MQAM signal of the MQAM signal of s (t) input, ω is the central angle frequency of input MQAM signal, x is the MQAM signal after handling,

Be the second dervative of the MQAM signal after handling,

Be the first derivative of the MQAM signal after handling, F is the driving force constant of oscillator system, and β is the oscillator system damping coefficient, and μ, k are the non-vanishing real number of input.D ü ffing oscillator system structure is not limited to adopt said structure.The MQAM signal is carried out normalized, adopt the D ü ffing oscillator system of said structure to carry out computing normalization MQAM signal, can draw the MQAM signal after the Filtering Processing.The oscillogram that the MQAM signal is carried out after the Filtering Processing sees also Fig. 3.

Above-mentioned use is carried out not needing signal is further done down-conversion and equilibrium treatment, and then having simplified pretreatment process after the Filtering Processing to the MQAM signal based on the nonlinear filter of D ü ffing oscillator system.Simultaneously, D ü ffing oscillator system has very high sensitiveness to arrowband MQAM signal, thereby given prominence to the non-correlation between communication channel noise and the MQAM signal better, increased the signal to noise ratio of the MQAM signal after handling, strengthened the accuracy that feature extraction and chip rate are estimated.

Pretreatment module 81 shown in Figure 10 also comprises: signal conversion unit 812, symbol interval acquiring unit 813 and symbol interval determining unit 814.

Signal conversion unit 812 is used for the MQAM signal after handling is carried out continuous wavelet transform the signal after the acquisition conversion.Symbol interval acquiring unit 813 is used to detect the amplitude of the signal after the conversion, determines the sampled point number between adjacent two peak values, draws a plurality of symbol intervals.

Symbol interval determining unit 814 is used for a plurality of symbol intervals are carried out statistical average, obtains symbol interval more accurately.The symbol interval more accurately that obtains is defined as the symbol interval of the MQAM after the above-mentioned processing, and with reference to this symbol interval the MQAM after handling is handled in subsequent step.

The specific implementation process of signal conversion unit 812, symbol interval acquiring unit 813 and symbol interval determining unit 814 sees also step S1011 among the method embodiment to step S1013, and this is introduced no longer in addition in detail.

Characteristic extracting module 82 is used for reference to described symbol interval, the MQAM signal transformation after the processing in the same symbol interval to the phase space territory, is adopted the MQAM signal after phasor is described conversion, the characteristic parameter of MQAM signal in phasor after the extraction conversion.Phasor and characteristic parameter distribution map see also Fig. 6 and Fig. 7, by above-mentioned Fig. 6 and Fig. 7 as can be seen, when the MQAM signal is the 16QAM signal, the cluster centre point of characteristic parameter is 3, " based on the MQAM signal recognition method of clustering algorithm " with respect to patent of invention 200910219448.1 announcements, the characteristic parameter number of extracting reduces, and then cluster centre point number reduces.Therefore, in follow-up cluster identifying, reduce recognition time, improved identification real-time and recognition efficiency.

Cluster analysis module 83 is used for described characteristic parameter is carried out cluster analysis, obtains cluster analysis result.

Identification module 84 is used for described cluster analysis result is carried out Classification and Identification, determines modulation type.The structural representation of identification module 84 sees also Figure 11, comprising: cluster numbers acquiring unit 841 and recognition unit 842.

Cluster numbers acquiring unit 841 is used to obtain the cluster numbers of the MQAM signal correspondence after the described processing.Specifically comprise: evaluation function Q _k Value determining unit 8411 and cluster numbers determining unit 8412.

Evaluation function Q _k Value determining unit 8411 is used for according to the evaluation function formula $Q_k=\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\underset{X,Y\&Element;C_i}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2+\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\left(\underset{l=1,i\&NotEqual;\mathrm{<figure-callout\; id="1"\; label="l\; k"\; filenames="HDA0000078654570000032.png"\; state="\{\{state\}\}">l</figure-callout>}}{\overset{k}{\mathrm{\&Sigma;}}}\frac{1}{\left|C_i\right|\&CenterDot;\left|C_l\right|}\underset{X\&Element;C_i,Y\&Element;C_l}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2\right),$ Determine the evaluation function Q of the characteristic parameter correspondence after the cluster analysis _kValue, wherein: k is the cluster numbers of various criterion QAM signal correspondence, C _iAnd C _lThe set number of the characteristic parameter that obtains for cluster analysis, X and Y are two characteristic parameters.

First refers to be classified in the above-mentioned evaluation function formula bunch is the quadratic sum that there is the distance between any two characteristic parameters in the characteristic parameter in same cluster centre point place, be about to each bunch and regard big " data point " as, " distance " between big " data point " weighed by the right average distance of characteristic parameter between the difference bunch.Compactness in this is used for weighing bunch.Second refer to the right square distance of the characteristic parameter between any two bunches and, compactness between being used for weighing bunch.Can prove evaluation function Q _kIt is reasonable more to be worth more little, corresponding classification.

Cluster numbers determining unit 8412 is used to choose the evaluation function Q of different k correspondences _kThe evaluation function Q of numerical value minimum in the value _kValue is determined minimum evaluation function Q _kThe corresponding k of value is the cluster numbers of the MQAM signal correspondence after handling.

Recognition unit 842 is used for the cluster numbers that will obtain and the cluster numbers of predetermined various criterion MQAM signal correspondence and compares, and determines the system number of the MQAM signal after the described processing, the identification modulation type.

The cluster numbers of predetermined various criterion MQAM signal correspondence is in advance standard M-ary orthogonal amplitude modulation(PAM) MQAM signal to be carried out the cluster numbers that cluster numbers is added up determined various criterion quadrature amplitude modulation MQAM signal correspondence.The inventor determines that through repetition test the cluster numbers of BASK signal, 4QAM signal, 8QAM signal, 16QAM signal, 32QAM signal, 64QAM signal correspondence is respectively 1,1,2,3,5,9.

The inventor draws when cluster numbers k=3 evaluation function Q after adopting cluster analysis module 83 and identification module 84 to handle to characteristic parameter shown in Figure 7 _kValue is minimum, therefore, and with the cluster numbers of cluster numbers k=3 as the MQAM signal correspondence after handling.The cluster numbers of cluster numbers k=3 and predetermined various criterion MQAM signal correspondence compares, and determine that the MQAM signal is the 16QAM signal, and then modulation type is 16QAM as can be known.The MQAM signal of determining through the disclosed modulation type recognition system of the embodiment of the present application is identical with the signal of the actual description of Fig. 7, i.e. the recognition accuracy height of the disclosed modulation type recognition system of the embodiment of the present application.

Use technique scheme, extract method of characteristic parameters according to planisphere, reduced the characteristic parameter number of extracting, and then reduced recognition time, improved identification real-time and recognition efficiency with respect to existing.

The above only is the application's a embodiment; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the application's principle; can also make some improvements and modifications, these improvements and modifications also should be considered as the application's protection range.

Claims (12)

1. a modulation type recognition methods is characterized in that, comprising:

M-ary orthogonal amplitude modulation(PAM) MQAM signal is carried out preliminary treatment, the MQAM signal after obtaining handling and the symbol interval of the MQAM signal after the described processing;

With reference to described symbol interval, to the phase space territory, adopt phasor to describe the MQAM signal transformation after the processing in the same symbol interval, the characteristic parameter of MQAM signal in phasor after the extraction conversion to the MQAM signal after this conversion;

Described characteristic parameter is carried out cluster analysis, obtain cluster analysis result;

Described cluster analysis result is carried out Classification and Identification, determine modulation type.

2. modulation type recognition methods according to claim 1 is characterized in that, describedly the MQAM signal is carried out preliminary treatment comprises:

Use is carried out Filtering Processing based on the nonlinear filter of D ü ffing oscillator system to the MQAM signal, the MQAM signal after obtaining handling.

3. modulation type recognition methods according to claim 2 is characterized in that, described D ü ffing oscillator system structure is: $\stackrel{\&CenterDot;\&CenterDot;}{x}+\mathrm{\&beta;\&omega;}\stackrel{\&CenterDot;}{x}+{\mathrm{\&omega;}}^2(\mathrm{kx}+\mathrm{\&mu;}{x}^3)=\mathrm{F\&omega;s}\left(t\right),$ Wherein: s (t) is the normalized form of the MQAM signal of reception; ω is the MQAM signal center angular frequency of input; X is the MQAM signal after handling;

Second dervative for the MQAM signal after handling;

First derivative for the MQAM signal after handling; F is the driving force constant of oscillator system; β is the oscillator system damping coefficient; μ, k are the non-vanishing real number of input.

4. modulation type recognition methods according to claim 2 is characterized in that, the symbol interval of the MQAM signal after obtaining handling comprises:

MQAM signal after handling is carried out continuous wavelet transform, the signal after the acquisition conversion;

The amplitude of the signal after the detection conversion is determined the sampled point number between adjacent two peak values, draws a plurality of symbol intervals;

A plurality of symbol intervals are carried out statistical average, obtain symbol interval more accurately, determine this more accurately symbol interval be the symbol interval of the MQAM signal after handling.

5. modulation type recognition methods according to claim 1 is characterized in that, in advance standard M-ary orthogonal amplitude modulation(PAM) MQAM signal is carried out the characteristic statistics, determines the cluster numbers of various criterion quadrature amplitude modulation MQAM signal correspondence;

Described described cluster analysis result is carried out Classification and Identification, determines that modulation type comprises:

Obtain the cluster numbers of the MQAM signal correspondence after the described conversion;

The cluster numbers obtained and the cluster numbers of predetermined various criterion MQAM signal correspondence are compared, determine the system number of the MQAM signal after the described processing, the identification modulation type.

6. modulation type recognition methods according to claim 5 is characterized in that, the cluster numbers of obtaining the MQAM signal correspondence after the described processing comprises:

According to the evaluation function formula $Q_k=\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\underset{X,Y\&Element;C_i}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2+\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\left(\underset{l=1,i\&NotEqual;l}{\overset{k}{\mathrm{\&Sigma;}}}\frac{1}{\left|C_i\right|\&CenterDot;\left|C_l\right|}\underset{X\&Element;C_i,Y\&Element;C_l}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2\right),$ Determine the evaluation function Q of the characteristic parameter correspondence after the cluster analysis _kValue, wherein: k is the cluster numbers of various criterion QAM signal correspondence, C _iAnd C _lThe set number of the characteristic parameter that obtains for cluster analysis, X and Y are two characteristic parameters;

Choose the evaluation function Q of different cluster numbers k correspondences _kThe evaluation function Q of numerical value minimum in the value _kValue is determined minimum evaluation function Q _kThe corresponding cluster numbers k of value is the cluster numbers of the MQAM signal correspondence after handling.

7. a modulation type recognition system is characterized in that, comprising:

Pretreatment module is used for the MQAM signal is carried out preliminary treatment, the MQAM signal after obtaining handling and the symbol interval of the MQAM signal after the described processing;

Characteristic extracting module is used for reference to described symbol interval, to the phase space territory, adopts phasor to describe to the MQAM signal after this conversion the MQAM signal transformation after the processing in the same symbol interval, the characteristic parameter of MQAM signal in phasor after the extraction conversion;

The cluster analysis module is used for described characteristic parameter is carried out cluster analysis, obtains cluster analysis result;

Identification module is used for described cluster analysis result is carried out Classification and Identification, determines modulation type.

8. modulation type recognition system according to claim 7, it is characterized in that, pretreatment module comprises: filter unit is used to use the nonlinear filter based on D ü ffing oscillator system the MQAM signal to be carried out Filtering Processing, the MQAM signal after obtaining handling.

9. modulation type recognition system according to claim 7 is characterized in that, described D ü ffing oscillator system structure is: $\stackrel{\&CenterDot;\&CenterDot;}{x}+\mathrm{\&beta;\&omega;}\stackrel{\&CenterDot;}{x}+{\mathrm{\&omega;}}^2(\mathrm{kx}+\mathrm{\&mu;}{x}^3)=\mathrm{F\&omega;s}\left(t\right),$ Wherein: s (t) is the normalization MQAM signal of the MQAM signal of input, and ω is the MQAM signal center angular frequency of input, and x is the MQAM signal after handling,

Second dervative for the MQAM signal after handling;

First derivative for the MQAM signal after handling; F is the driving force constant of oscillator system, and β is the oscillator system damping coefficient; μ, k are the non-vanishing real number of input.

10. modulation type recognition system according to claim 8 is characterized in that pretreatment module also comprises:

Signal conversion unit is used for the MQAM signal after handling is carried out continuous wavelet transform the signal after the acquisition conversion;

The symbol interval acquiring unit is used to detect the amplitude of the signal after the conversion, determines the sampled point number between adjacent two peak values, draws a plurality of symbol intervals;

The symbol interval determining unit is used for a plurality of symbol intervals are carried out statistical average, obtains symbol interval more accurately, determine this more accurately symbol interval be the symbol interval of the MQAM signal after handling.

11. modulation type recognition system according to claim 7 is characterized in that, in advance standard M-ary orthogonal amplitude modulation(PAM) MQAM signal is carried out the characteristic statistics, determines the cluster numbers of various criterion quadrature amplitude modulation MQAM signal correspondence;

Described identification module comprises:

The cluster numbers acquiring unit is used to obtain the cluster numbers of the MQAM signal correspondence after the described conversion;

Recognition unit is used for the cluster numbers that will obtain and the cluster numbers of predetermined various criterion MQAM signal correspondence and compares, and determines the system number of the MQAM signal after the described processing, the identification modulation type.

12. modulation type recognition system according to claim 11 is characterized in that, described cluster numbers acquiring unit comprises:

Evaluation function Q _kThe value determining unit is used for according to the evaluation function formula $Q_k=\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\underset{X,Y\&Element;C_i}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2+\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}\left(\underset{l=1,i\&NotEqual;l}{\overset{k}{\mathrm{\&Sigma;}}}\frac{1}{\left|C_i\right|\&CenterDot;\left|C_l\right|}\underset{X\&Element;C_i,Y\&Element;C_l}{\mathrm{\&Sigma;}}{\left|\right|X-Y\left|\right|}^2\right),$ Determine the evaluation function Q of the characteristic parameter correspondence after the cluster analysis _kValue, wherein: k is the cluster numbers of various criterion QAM signal correspondence, C _iAnd C _lThe set number of the characteristic parameter that obtains for cluster analysis, X and Y are two characteristic parameters;

The cluster numbers determining unit is used to choose the evaluation function Q of different k correspondences _kThe evaluation function Q of numerical value minimum in the value _kValue is determined minimum evaluation function Q _kThe corresponding k of value is the cluster numbers of the MQAM signal correspondence after handling.

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