CN105678256A - Signal processing method, signal processing device and signal processing system - Google Patents

Abstract

The invention discloses a signal processing method for signal classification, which comprises the following steps: providing a plurality of nodes and controlling the plurality of nodes to receive input signals; comparing the input signal with sample signals to calculate a similarity value of each node, calculating a global similarity value according to the similarity value of each node, and providing a plurality of sample signals to calculate a plurality of global similarity values corresponding to the sample signals one to one; and judging the sample signal which is most similar to the input signal according to the global similarity value so as to determine the type of the input signal. The signal processing method provided by the embodiment of the invention processes and judges a plurality of global nodes, and finally obtains the type of the input signal received by the global nodes. The type of the input signal is judged by adopting a multi-node cooperative processing method, so that the accuracy of signal classification is improved. The invention also discloses a signal processing device and a signal processing system.

Description

Signal processing method, signal processing apparatus and signal processing system

Technical field

The present invention relates to signal processing field, particularly to a kind of signal processing method and signal processing apparatus.

Background technology

Modulation recognition detection refers to by extracting the useful information received in signal, to reach the purpose of classification or the pattern confirming input signal. It has been directed to Modulation recognition detection in many fields such as cognitive radio, sensor network, image procossing, pattern recognition, voice signal identification, fingerprint recognition, seismic signal analysis, Radar Signal Detection and medical diagnosiss. But, when conventionally algorithm carries out Modulation recognition, have greater probability and erroneous judgement occurs.

Summary of the invention

It is contemplated that at least solve one of technical problem of existence in prior art.

Present invention is primarily targeted at a kind of signal processing method of offer, it is intended to improve the accuracy rate of Modulation recognition.

Embodiment of the present invention provides a kind of signal processing method, and described signal processing method includes:

Rate-determining steps, it is provided that multiple nodes also control the plurality of node reception input signal;

Comparison step, described input signal is compared with sample signal the similar value calculating each described node, similar value according to each described node calculates overall situation similar value, it is provided that multiple described sample signal is to calculate and described sample signal multiple described overall situation similar value one to one; And

Judge step, judge that the described sample signal most like with described input signal is to determine the type of described input signal according to described overall situation similar value.

So, judge with the type to described input signal by the process of the input signal of each node of the overall situation is obtained overall situation similar value, improve the accuracy rate of described input Modulation recognition.

Embodiment of the present invention additionally provides a kind of signal processing apparatus, and for Modulation recognition, described signal processing apparatus includes:

Receiver module, described receiver module includes multiple node;

Controlling module, described control module is used for controlling the plurality of node and receives input signal;

Generation module, described generation module is used for generating multiple sample signal;And

Processing module, described processing module includes computing module and judge module, described computing module for comparing the similar value calculating each described node by described input signal with described sample signal, and calculating overall situation similar value for the similar value according to each described node, described processing module is for calculating and described sample signal multiple described overall situation similar value one to one according to described multiple sample signal;

According to described overall situation similar value, described judge module is for judging that the described sample signal most like with described input signal is to determine the type of described input signal.

Embodiment of the present invention can adopt the described similar value that above-mentioned formula calculates described node can also be other process or calculation obtains described similar value.

In some embodiments, described computing module also provide for each described node overall weight and according to described the overall situation weight calculation described in the overall situation similar value.

In some embodiments, described computing module can be also used for adopting below equation to calculate described overall situation similar value:

$G_i=\underset{k=1}{\overset{K}{\Σ}}{\mathrm{\ω}}_{ik}{T}_i^{\left(k\right)}$

Wherein, i is positive integer and the species number less than or equal to described sample signal, and k is positive integer and number K, G less than or equal to described node_iIt is the described overall situation similar value that i-th kind of sample signal is corresponding, ω_i,kFor the described overall situation weight of node described in kth, T_i ^(k)Described similar value for node described in kth.

In some embodiments, described computing module can be also used for adopting the described similar value of the below equation each described node of calculating:

$T_i^{\left(k\right)}=\underset{n=0}{\overset{N-1}{\Σ}}{x}^{\left(k\right)}\left(n\right)s_i\left(n\right)-\frac{1}{2}\underset{n=0}{\overset{N-1}{\Σ}}|s_i\left(n\right){|}^2$

Wherein, i is positive integer and the species number less than or equal to described sample signal, and k is positive integer and the number less than or equal to described node, s_iN () is i-th kind of described sample signal, x^(k)N described input signal that () is node described in kth.

In some embodiments, described signal processing apparatus includes reminding module, and described reminding module is used for sending prompting.

In some embodiments, described judge module also provides for similar threshold value and produces cue and described control module for sending prompting according to the described cue described reminding module of control when all described overall situation similar value are less than described similar threshold value.

In some detailed description of the invention, described judge module also provides for and described overall situation similar threshold value corresponding to similar value for type as described input signal of the described phase example signal type that selects maximum described overall situation similar value corresponding in be more than or equal to the described overall situation similar value of described similar threshold value.

In some embodiments, described signal processing apparatus includes display module, and described display module is for showing the type of described input signal.

Embodiment of the present invention additionally provides a kind of signal processing system, and described signal processing system includes said signal processing device.

The additional aspect of the present invention and advantage will part provide in the following description, and part will become apparent from the description below, or is recognized by the practice of the present invention.

Accompanying drawing explanation

Above-mentioned and/or the additional aspect of the present invention and advantage are from conjunction with will be apparent from easy to understand the accompanying drawings below description to embodiment, wherein:

Fig. 1 is the flow chart of the signal processing method of one embodiment of the present invention;

Fig. 2 is the high-level schematic functional block diagram of the signal processing apparatus of one embodiment of the present invention;

Fig. 3 is the flow chart of the signal processing method of another embodiment of the present invention;

Fig. 4 is the flow chart of the signal processing method of further embodiment of the present invention;

Fig. 5 is the high-level schematic functional block diagram of the signal processing apparatus of another embodiment of the present invention;

Fig. 6 is the flow chart of the signal processing method of yet another embodiment of the present invention;

Fig. 7 is the flow chart of the signal processing method of another embodiment of the present invention;

Fig. 8 is the flow chart of the signal processing method of further embodiment of the present invention;

Fig. 9 is the high-level schematic functional block diagram of the signal processing system of yet another embodiment of the present invention;

Figure 10 is the block diagram of the signal processing system of one embodiment of the present invention; And

Figure 11 is the cartogram of the signal processing method of one embodiment of the present invention.

Detailed description of the invention

Being described below in detail embodiments of the present invention, the example of described embodiment is shown in the drawings, and wherein same or similar label represents same or similar element or has the element of same or like function from start to finish. The embodiment described below with reference to accompanying drawing is illustrative of, and is only used for explaining embodiments of the present invention, and it is not intended that restriction to embodiments of the present invention.

Embodiment of the present invention provides a kind of signal processing method, for Modulation recognition. In some embodiments, the signal processing method of embodiment of the present invention may be used for signal is classified.

Referring to Fig. 1, the signal processing method of embodiment of the present invention comprises the following steps:

S10: multiple node is provided and controls multiple node reception input signal;

S20: input signal is compared with sample signal the similar value calculating each node, calculates overall situation similar value according to the similar value of each node, it is provided that multiple sample signal is to calculate and sample signal multiple overall situation similar value one to one; And

S30: judge that the sample signal most like with input signal is to determine the type of input signal according to overall situation similar value.

Multiple nodes of the overall situation are processed and judge by the signal processing method of embodiment of the present invention, finally draw the type inputting signal that overall situation interior joint receives. Adopt the method that multi-node collaborative processes that the type of input signal is judged, so improve the accuracy rate of Modulation recognition.

Referring to Fig. 2, embodiment of the present invention additionally provides a kind of signal processing apparatus 10, and signal can be processed signal is classified by signal processing apparatus 10.

In some embodiments, signal processing apparatus 10 includes with lower module:

Receiver module 110, receiver module 110 includes multiple node;

Control module 120, control module 120 and be used for controlling multiple node reception input signal;

Generation module 130, generation module 130 is used for generating multiple sample signal; And

Processing module 140.

Step S10 can be realized by receiver module 110 and control module 120, and step S20 can by generation module and processing modules implement, and step S30 can by processing modules implement. Specifically, processing module 140 includes computing module 142 and judge module 144, computing module 142 may be used for comparing to calculate with sample signal by input signal the similar value of each node, and may be used for the similar value calculating overall situation similar value according to each node, computing module 142 may be used for calculating and sample signal multiple described overall situation similar value one to one according to multiple sample signal, it is judged that according to described overall situation similar value, module 144 is for judging that the sample signal most like with input signal is to determine the type of input signal.

In some embodiments, it is necessary to the similarity degree of sample signal and input signal is quantified, it is possible to relate to different quantization algorithms according to different demands.Such as, in the communications field, carry out quantifying can being the similar value of a node in calculus communication system, thus obtaining the similarity degree of input signal and sample signal. General, it is possible to extract the amplitude of this input signal and phase place to compare with sample signal according to the amplitude-frequency characteristic of input signal and phase-frequency characteristic, thus the similarity of the section of sentencing input signal and sample signal.

Referring to Fig. 3, the signal processing method of embodiment of the present invention can comprise the further steps of:

S22: provide the overall weight of each node and according to overall situation weight calculation overall situation similar value.

When asking for overall situation similar value, the weight of each node of receiver module 110 is different, therefore will according to the overall weight calculation overall situation similar value of each node similar value.

In some embodiments, step S22 can be realized by computing module 142, and computing module 142 is for providing the overall weight of each node and according to overall situation weight calculation overall situation similar value.

In some embodiments, it is possible to obtain each node similar value T in calculating_i ^(k)After again to the overall situation similar value be calculated.

In some embodiments, computing module 142 can adopt below equation to calculate overall situation similar value:

$G_i=\underset{k=1}{\overset{K}{\Σ}}{\mathrm{\ω}}_{i,k}{T}_i^{\left(k\right)}$

Wherein, i is positive integer and the species number less than or equal to described sample signal, and k is positive integer and number K, G less than or equal to described node_iIt is the overall similar value that i-th kind of sample signal is corresponding, ω_i,kFor the overall weight of kth node, T_i ^(k)Similar value for kth node.

In some embodiments, the overall weights omega of kth node_i,kCan be obtained by calculating. Obtain for example, it is possible to calculate by algorithm. It is, of course, also possible to the calculating instrument by other obtains.

In some embodiments, it is H at sample Modulation recognition_iTime, calculate and obtain relevant similar threshold value τ_iAnd the overall weights omega that each node is shared in systems_i,k. Can proposing optimized algorithm in some embodiments to obtain above-mentioned two parameter, wherein ω is the vector containing K element, and K is node number.

It is H when input Modulation recognition is actual_mTime, processing module 140 judges that input signal types is also as H_mProbability be:

$P_{C_m}=P\left(H_m\right|H_m)=P(G_m\≥{\mathrm{\τ}}_m|H_m)$

Probability herein is only for calculating overall situation weights omega_i,kWith similar threshold value τ_i. Obviously, it is had overall weights omega in embodiments of the present invention_i,kWith similar threshold value τ_iAfter, just can in the hope of overall situation similar value G_i。

It is H when Modulation recognition is actual_mTime, it is H that processing module 140 judges input signal types by accident_iProbability be:

$P_{M_{m,j}}=P(G_j\≥{\mathrm{\τ}}_m|H_m)$

Optimization overall situation weights omega_mWith similar threshold value τ_iMake the maximum probability that processing module 140 correctly judges, control its probability of miscarriage of justice within the specific limits simultaneously, generally choose ∈_m,j< 0.5. Wherein ∈_m,jIt is a constant value, occurs in equation below:

$\begin{array}{cccc}st.& P_{M_{m,j}}\&le;{\&Element;}_{m,j},& \&ForAll;j\&Element;\{0,1,\mathrm{...},M-1\},& j\&NotEqual;m\end{array}$

Above formula is a restrictive condition.

That is:

$\underset{({\mathrm{\&omega;}}_m,{\mathrm{\&tau;}}_m)}{max}{P}_{C_m}$

$\begin{array}{cccc}st.& P_{M_{m,j}}\&le;{\&Element;}_{m,j},& \&ForAll;j\&Element;\{0,1,\mathrm{...},M-1\},& j\&NotEqual;m\end{array}$

In some embodiments, consider channel and the white Gaussian noise impact on input signal of system, in conjunction with the probability density function characteristic of white Gaussian noise, this problem can be attributed to a non-convex problem being limited to M-1 linear equality condition and 1 secondary equality condition. Can becoming quadratic inequality condition by lax secondary equality condition, this non-convex function just can be converted into a convex problem solving. Can obtain:

$\underset{u}{\min }{g}_{mm}^T{u}_m$

$\begin{array}{cc}st.& u_m^T{\widehat{\&Sigma;}}_m{u}_m\&le;1\end{array}$

$\begin{array}{ccc}{g}_{mm}^T{u}_m\&GreaterEqual;Q^{-1}\left({\&Element;}_{m,j}\right),& \&ForAll;j\&Element;\{0,1,\mathrm{..},M-1\},& j\&NotEqual;m\end{array}$

This equation can use the modular tool cabinet of much software to solve, such as CVX. Wherein

$u_i=\frac{{\left({\mathrm{\&tau;}}_i{{\mathrm{\&omega;}}_i}^T\right)}^T}{\sqrt{\left({\mathrm{\&tau;}}_i{{\mathrm{\&omega;}}_i}^T\right){\widehat{\&Sigma;}}_i{\left({\mathrm{\&tau;}}_i{{\mathrm{\&omega;}}_i}^T\right)}^T}}$

${\widehat{\&Sigma;}}_i=\left(\begin{array}{cc}0& 0_{1\&times;(K-1)}\\ 0_{(K-1)\&times;1}& {\mathrm{\&Sigma;}}_i\end{array}\right)$

Σ_iIt it is the covariance of noise. Symbol T representing matrix transposition. Q^-1The inverse function of () function representation white Gaussian noise probability density function.

So, it is possible to solve the overall weights omega of the node of optimum_mWith similar threshold value τ_m。

${\widehat{\mathrm{\&omega;}}}_m=\frac{{\hat{u}}_m(2:M)}{\left|\right|{\hat{u}}_m(2:M)\left|\right|}$

${\mathrm{\&tau;}}_m={\hat{u}}_m---\left(1\right)$

In some embodiments, the calculation of the similar value of each node has greatly difference.Such as, in the field of communications, step S20 can adopt the processing method of cross-correlation to remove to quantify the similarity degree of two signals.

Concrete, computing module 142 may be used for calculating the similar value of each node, and the similar value of each node can adopt below equation to calculate to obtain:

$T_i^{\left(k\right)}=\underset{n=0}{\overset{N-1}{\&Sigma;}}{x}^{\left(k\right)}\left(n\right)s_i\left(n\right)-\frac{1}{2}\underset{n=0}{\overset{N-1}{\&Sigma;}}|s_i\left(n\right){|}^2$

Wherein, i is positive integer and the species number less than or equal to sample signal, and k is positive integer and number K, s less than or equal to node_iN () is i-th kind of sample signal, x^(k)N input signal that () is kth node. Additionally, n={0,1,2 ... N-1}, represent the sampled point of signal.

So, obtain the similar value of node and just the similar value of the overall situation can be calculated, and calculate to as if the similar value of multiple nodes, in order to the overall situation is processed and judges by subsequent step, improves the accuracy rate of Modulation recognition. Additionally, the method calculating the similar value of each node is not restricted to above-mentioned computing formula.

Referring to Fig. 4, in the present embodiment, signal processing method can comprise the further steps of:

S40: similar threshold value is provided and sends prompting when all overall situation similar value are less than similar threshold value.

In the signal processing method of embodiment of the present invention, may determine that in sample signal without the signal with input signal similar when all overall situation similar value are less than similar threshold value. In other words, the type of signal and the type mismatch of all sample signals are inputted. At this point it is possible to send prompting to point out user.

Referring to Fig. 5, signal processing apparatus 10 can include reminding module 160. Reminding module 160 is used for sending prompting.

In some detailed description of the invention, step S40 can be realized by judge module 144, control module 120 and reminding module. Specifically, it is judged that module 144 also provides for similar threshold value and produces cue when all overall situation similar value are less than similar threshold value and control module 120 for sending prompting according to cue control reminding module 160.

Refer to Fig. 6, in the signal processing method of embodiment of the present invention, it is judged that step S30 can comprise the further steps of:

S301: select the type that type is input signal of the sample signal corresponding with maximum overall similar value.

This step adopts the computing formula of above-mentioned embodiment:

$G_i=\underset{k=1}{\overset{K}{\&Sigma;}}{\mathrm{\&omega;}}_{i,k}{T}_i^{\left(k\right)}$

And

$T_i^{\left(k\right)}=\underset{n=0}{\overset{N-1}{\&Sigma;}}{x}^{\left(k\right)}\left(n\right)s_i\left(n\right)-\frac{1}{2}\underset{n=0}{\overset{N-1}{\&Sigma;}}|s_i\left(n\right){|}^2$

Adopt above-mentioned computing formula, overall situation similar value G_iMore big, sample signal is more big with the similarity degree of input signal, therefore, selects the type that type is input signal of the sample signal of the maximum maximum correspondence of overall similar value.

In some embodiments, step S301 can adopt judge module 144 to realize, it is judged that the module 144 type for selecting the type of the sample signal corresponding with maximum overall similar value to be input signal.

In order to judge more accurately, signal processing method also includes providing similar threshold value to compare.

Referring to Fig. 7, in some embodiments, the step of signal processing method is further comprising the steps of:

S50: the type type as described input signal of similar threshold value the described sample signal that selects in be more than or equal to the overall similar value of similar threshold value maximum overall similar value corresponding is provided.

The effect of similar threshold value is that the similarity degree between input signal and sample signal is judged, by setting rational similar threshold value, it is believed that the sample signal corresponding be more than or equal to the overall similar value of similar threshold value belongs to compares similar signal with input signal, and the sample signal corresponding less than the overall similar value of similar threshold value belongs to the signal less similar to input signal.

Refer to Fig. 8, summary embodiment, most like sample signal can be selected in more similar signal further and its signal type is regarded as the type of input signal, if and overall similar value corresponding to all sample signals is respectively less than similar threshold value, that is, all of sample signal is all less similar to input signal, can regard as None-identified, and send prompting. The benefit so arranged is, can guarantee that that selects meets certain condition of similarity with the input most like sample signal of signal, and when all sample signal similar degree all not Gao Shineng make the judgement of None-identified, thus meeting the demand of user.

In some embodiments, input signal may be subject to channel and effect of noise in the process of transmission, thus can distortion. Thus when judging input signal types every time, it is necessary to the overall similar value G weighed_iNecessarily judge. Concrete, it is possible to adopt equation below to judge:

G_i≥τ_i

Wherein, τ_iFor similar threshold value, when this judgment formula is false, it is possible to input signal serious distortion is described, now, each node is likely to need again to receive input signal.

In some embodiments, step S50 can adopt judge module 144 to realize, it is judged that module 144 is for providing the type type as input signal of similar threshold value the sample signal that selects maximum overall similar value corresponding in be more than or equal to the overall similar value of similar threshold value. Similar threshold value τ can be calculated by algorithm for design_i. In the signal processing method of embodiment of the present invention, similar threshold value τ_iWith overall situation weights omega_i,kThe same exist as important estimation parameter. Computing module 142 can be adopted to be calculated facing to two parameters, it would however also be possible to employ other computing equipment is calculated.

So, judge overall situation similar value further according to similar threshold value to improve the accuracy rate that the type to input signal judges, reduce the error rate of Modulation recognition.

Refer to Fig. 9, present invention also offers a kind of signal processing system 20. Signal processing system 20 includes signal processing apparatus 10.

The signal processing apparatus 10 of embodiment of the present invention also includes display module 160. In some embodiments, display module is displayed for final judgement classification results, namely inputs the type of signal.

Refer to H in Figure 10, Figure 10_iCan representing the signal type that all sample signals are corresponding, wherein i is positive integer and the species number M less than or equal to sample signal. Agent1, Agent2 ..., AgentK, represent the input signal of each node, T respectively_i ^(k)For the similar value of kth node, ω_i,kOverall weight for kth node. Figure 10 adopts the form of system block diagram that the signal processing method of embodiment of the present invention is illustrated, and better illustrating embodiment of the present invention is that signal is carried out treatment classification by the synergism adopting multiple nodes.

Refer to Figure 11, Figure 11 and simply illustrate the correct impact judging probability that single node carries out signal processing classification and adopts two nodes to work in coordination with to carry out signal processing classification. Concrete, the solid line in Figure 11 represents single node and carries out signal processing sorting technique, and dotted line represents that two nodes are collaborative carries out signal processing sorting technique, wherein P_CFor correctly judging the probability of Modulation recognition, P_MProbability for false judgment Modulation recognition. This figure illustrates to adopt the accuracy that two nodes work in coordination with the method carrying out signal processing classification higher more reliable.

The signal processing method of embodiment of the present invention adopts the synergism of multiple nodes that the type of input signal is judged, it is possible to effectively reduces error rate, improves realizability and the stability of system.

In the description of embodiments of the present invention, it will be appreciated that, term " " center ", " longitudinal direction ", " transverse direction ", " length ", " width ", " thickness ", " on ", D score, " front ", " afterwards ", " left side ", " right side ", " vertically ", " level ", " top ", " end ", " interior ", " outward ", " clockwise ", orientation or the position relationship of the instruction such as " counterclockwise " are based on orientation shown in the drawings or position relationship, it is for only for ease of description embodiments of the present invention and simplifies description, rather than the device of instruction or hint indication or element must have specific orientation, with specific azimuth configuration and operation, therefore it is not intended that restriction to embodiments of the present invention. additionally, term " first ", " second " are only for descriptive purposes, and it is not intended that indicate or imply relative importance or the implicit quantity indicating indicated technical characteristic. thus, define " first ", the feature of " second " can express or implicitly include one or more described features. in the description of embodiments of the present invention, " multiple " are meant that two or more, unless otherwise expressly limited specifically.

In the description of embodiments of the present invention, it is necessary to explanation, unless otherwise clearly defined and limited, term " installation ", " being connected ", " connection " should be interpreted broadly, for instance, it is possible to it is fixing connection, can also be removably connect, or connect integratedly; Can be mechanically connected, it is also possible to be electrical connection or can communication mutually; Can be joined directly together, it is also possible to be indirectly connected to by intermediary, it is possible to be connection or the interaction relationship of two elements of two element internals. For the ordinary skill in the art, it is possible to understand above-mentioned term concrete meaning in embodiments of the present invention as the case may be.

In embodiments of the present invention, unless otherwise clearly defined and limited, fisrt feature second feature it " on " or D score can include the first and second features and directly contact, it is also possible to include the first and second features and be not directly contact but by the other characterisation contact between them. And, fisrt feature second feature " on ", " top " and " above " include fisrt feature directly over second feature and oblique upper, or be merely representative of fisrt feature level height higher than second feature. Fisrt feature second feature " under ", " lower section " and " below " include fisrt feature directly over second feature and oblique upper, or be merely representative of fisrt feature level height less than second feature.

Following disclosure provides many different embodiments or example for realizing the different structure of embodiments of the present invention. In order to simplify disclosing of embodiments of the present invention, hereinafter parts and setting to specific examples are described. Certainly, they are only merely illustrative, and are not intended to the restriction present invention. Additionally, embodiments of the present invention can in different examples repeat reference numerals and/or reference letter, this repetition is for purposes of simplicity and clarity, the relation between itself not indicating discussed various embodiment and/or arranging.Additionally, the example of the various specific technique that provides of embodiments of the present invention and material, but those of ordinary skill in the art are it can be appreciated that the use of the application of other techniques and/or other materials.

In the description of this specification, specific features, structure, material or feature that the description of reference term " embodiment ", " some embodiments ", " exemplary embodiment ", " example ", " concrete example " or " some examples " etc. means in conjunction with described embodiment or example describe are contained at least one embodiment or the example of the present invention. In this manual, the schematic representation of above-mentioned term is not necessarily referring to identical embodiment or example. And, the specific features of description, structure, material or feature can combine in an appropriate manner in any one or more embodiments or example.

Describe in flow chart or in this any process described otherwise above or method and be construed as, represent and include the module of code of executable instruction of one or more step for realizing specific logical function or process, fragment or part, and the scope of the preferred embodiment of the present invention includes other realization, wherein can not press order that is shown or that discuss, including according to involved function by basic mode simultaneously or in the opposite order, performing function, this should be understood by embodiments of the invention person of ordinary skill in the field.

Represent in flow charts or in this logic described otherwise above and/or step, such as, it is considered the sequencing list of executable instruction for realizing logic function, may be embodied in any computer-readable medium, use for instruction execution system, device or equipment (such as computer based system, including the system of processing module or other can from instruction execution system, device or equipment instruction fetch the system performing instruction), or use in conjunction with these instruction execution systems, device or equipment. For the purpose of this specification, " computer-readable medium " can be any can comprise, store, communicate, propagate or transmission procedure is for instruction execution system, device or equipment or the device that uses in conjunction with these instruction execution systems, device or equipment. The example more specifically (non-exhaustive list) of computer-readable medium includes following: have the electrical connection section (electronic installation) of one or more wiring, portable computer diskette box (magnetic device), random access memory (RAM), read only memory (ROM), erasable edit read only memory (EPROM or flash memory), fiber device, and portable optic disk read only memory (CDROM). Additionally, computer-readable medium can even is that the paper that can print described program thereon or other suitable media, because can such as by paper or other media be carried out optical scanning, then carry out editing, interpreting or be processed to electronically obtain described program with other suitable methods if desired, be then stored in computer storage.

Should be appreciated that each several part of embodiments of the present invention can realize with hardware, software, firmware or their combination. In the above-described embodiment, multiple steps or method can realize with the storage software or firmware in memory and by suitable instruction execution system execution. Such as, if realized with hardware, the same in another embodiment, can realize by any one in following technology well known in the art or their combination: there is the discrete logic of logic gates for data signal realizes logic function, there is the special IC of suitable combination logic gate circuit, programmable gate array (PGA), field programmable gate array (FPGA) etc.

Those skilled in the art are appreciated that realizing all or part of step that above-described embodiment method carries can be by the hardware that program carrys out instruction relevant and complete, described program can be stored in a kind of computer-readable recording medium, this program upon execution, including the step one or a combination set of of embodiment of the method.

Additionally, each functional unit in various embodiments of the present invention can be integrated in a processing module, it is also possible to be that unit is individually physically present, it is also possible to two or more unit are integrated in a module. Above-mentioned integrated module both can adopt the form of hardware to realize, it would however also be possible to employ the form of software function module realizes. If described integrated module is using the form realization of software function module and as independent production marketing or use, it is also possible to be stored in a computer read/write memory medium.

Storage medium mentioned above can be read only memory, disk or CD etc.

Although above it has been shown and described that embodiments of the invention, it is understandable that, above-described embodiment is illustrative of, it is impossible to be interpreted as limitation of the present invention, and above-described embodiment can be changed, revises, replace and modification by those of ordinary skill in the art within the scope of the invention.

Claims (16)

1. a signal processing method, for Modulation recognition, it is characterised in that described signal processing method includes:

Rate-determining steps, it is provided that multiple nodes also control the plurality of node reception input signal;

Comparison step, described input signal is compared with sample signal the similar value calculating each described node, similar value according to each described node calculates overall situation similar value, it is provided that multiple described sample signal is to calculate and described sample signal multiple described overall situation similar value one to one; And

Judge step, judge that the described sample signal most like with described input signal is to determine the type of described input signal according to described overall situation similar value.

2. signal processing method as claimed in claim 1, it is characterised in that described comparison step includes:

Calculate sub-step, it is provided that the overall weight of each described node overall situation similar value according to described overall situation weight calculation.

3. signal processing method as claimed in claim 2, it is characterised in that described comparison step adopts below equation to calculate described overall situation similar value:

$G_i=\underset{k=1}{\overset{K}{\&Sigma;}}{\mathrm{\&omega;}}_{i,k}{T}_i^{\left(k\right)}$

Wherein, i is positive integer and the species number less than or equal to described sample signal, and k is positive integer and number K, G less than or equal to described node_iIt is the described overall situation similar value that i-th kind of sample signal is corresponding, ω_i,kFor node described in kth described the overall situation weight,Described similar value for node described in kth.

4. signal processing method as claimed in claim 3, it is characterised in that described comparison step adopts below equation to calculate the described similar value of each described node:

$T_i^{\left(k\right)}=\underset{n=0}{\overset{N-1}{\&Sigma;}}{x}^{\left(k\right)}\left(n\right)s_i\left(n\right)-\frac{1}{2}\underset{n=0}{\overset{N-1}{\&Sigma;}}|s_i\left(n\right){|}^2$

Wherein, i is positive integer and the species number less than or equal to described sample signal, and k is positive integer and the number less than or equal to described node, s_iN () is i-th kind of described sample signal, x^(k)N described input signal that () is node described in kth.

5. signal processing method as claimed in claim 3, it is characterised in that described signal processing method includes:

Prompting step, it is provided that similar threshold value also sends prompting when all described overall situation similar value are less than described similar threshold value.

6. signal processing method as claimed in claim 3, it is characterised in that described judgement step includes the type that type is described input signal selecting the described sample signal corresponding with maximum described overall situation similar value.

7. signal processing method as claimed in claim 3, it is characterized in that, described signal processing method includes providing the type type as described input signal of similar threshold value the described sample signal that selects maximum described overall situation similar value corresponding in be more than or equal to the described overall situation similar value of described similar threshold value.

8. a signal processing apparatus, for Modulation recognition, it is characterised in that described signal processing apparatus includes:

Receiver module, described receiver module includes multiple node;

Controlling module, described control module is used for controlling the plurality of node and receives input signal;

Generation module, described generation module is used for generating multiple sample signal; And

Processing module, described processing module includes computing module and judge module;

Described computing module for comparing the similar value calculating each described node by described input signal with described sample signal, and calculating overall situation similar value for the similar value according to each described node, described processing module is for calculating and described sample signal multiple described overall situation similar value one to one according to described multiple sample signal;

According to described overall situation similar value, described judge module is for judging that the described sample signal most like with described input signal is to determine the type of described input signal.

9. signal processing apparatus as claimed in claim 8, it is characterised in that described computing module also provide for each described node overall weight and according to the described overall situation weight calculation overall situation similar value.

10. signal processing apparatus as claimed in claim 9, it is characterised in that described computing module adopts below equation to calculate described overall situation similar value:

$G_i=\underset{k=1}{\overset{K}{\&Sigma;}}{\mathrm{\&omega;}}_{i,k}{T}_i^{\left(k\right)}$

Wherein, i is positive integer and the species number less than or equal to described sample signal, and k is positive integer and number K, G less than or equal to described node_iIt is the described overall situation similar value that i-th kind of sample signal is corresponding, ω_i,kFor the described overall situation weight of node described in kth, T_i ^(k)Described similar value for node described in kth.

11. signal processing apparatus as claimed in claim 10, it is characterised in that described computing module is additionally operable to the described similar value adopting below equation to calculate each described node:

$T_i^{\left(k\right)}=\underset{n=0}{\overset{N-1}{\&Sigma;}}{x}^{\left(k\right)}\left(n\right)s_i\left(n\right)-\frac{1}{2}\underset{n=0}{\overset{N-1}{\&Sigma;}}|s_i\left(n\right){|}^2$

Wherein, i is positive integer and the species number less than or equal to described sample signal, and k is positive integer and the number less than or equal to described node, s_iN () is i-th kind of described sample signal, x^(k)N described input signal that () is node described in kth.

12. signal processing apparatus as claimed in claim 10, it is characterised in that described signal processing apparatus block includes reminding module;

Described judge module also provides for similar threshold value and produces cue when all described overall situation similar value are less than described similar threshold value; And

Described control module sends prompting for controlling described reminding module according to described cue.

13. signal processing apparatus as claimed in claim 10, it is characterised in that described judge module is additionally operable to select the type that described sample signal type be described input signal corresponding with maximum described overall situation similar value.

14. signal processing apparatus as claimed in claim 10, it is characterized in that, described judge module also provides for and described overall situation similar threshold value corresponding to similar value for type as described input signal of the described phase example signal type that selects maximum described overall situation similar value corresponding in be more than or equal to the described overall situation similar value of described similar threshold value.

15. signal processing apparatus as claimed in claim 8, it is characterised in that described signal processing apparatus includes display module, described display module is for showing the type of described input signal.

16. a signal processing system, for Modulation recognition, it is characterised in that described signal processing system includes the signal processing apparatus as described in claim 8-15 any one.