CN106209222A - A kind of method and device of optical signal-to-noise ratio monitoring - Google Patents

Abstract

The present invention provides the method and device of a kind of optical signal-to-noise ratio monitoring, and the method comprises determining that parameter X1 relevant to OSNR under multiple different condition；Determine parameter X2 relevant to system transfers cost under multiple different condition；With described parameter X1 and X2 as independent variable, OSNR measured value is dependent variable, utilizes multiple regression technical limit spacing OSNR formula；Data extracting parameter X1 (i) after recovering input signal and X2 (i), utilize the OSNR of described OSNR formula monitoring measured signal.The present invention makes full use of the Digital Signal Processing of coherent system, it is achieved take into account hardware cost and OSNR monitoring accuracy.Using the method for the invention and device, compared with prior art, it is achieved that the electrical domain monitoring of coherent system OSNR, save monitoring cost, OSNR monitoring accuracy is higher, improves the reliability of optical communication system.

Description

A kind of method and device of optical signal-to-noise ratio monitoring

Technical field

The present invention relates to the performance monitoring of optical communication field, particularly relate to the monitoring method of a kind of OSNR And device.

Background technology

The OSNR (Optical Signal to Noise Ratio is called for short OSNR) of wavelength-division multiplex system It is the key parameter weighing wavelength-division system transmission performance, is defined as channel signal power divided by signal wave strong point Noise power in 0.1nm, is typically translated into dB for convenience of use and represents.Along with wavelength-division multiplex system unicast Speed is to 40Gb/s and above development, and the difficulty of OSNR monitoring is increasing.

The monitoring of OSNR area of light mainly includes that out-of-band supervision is surveyed and (in-band) monitoring in band, and out-of-band supervision is surveyed i.e. Noise power between Measurement channel, then use interpolation to draw the noise power of signal wave strong point, thus count Calculation draws OSNR, and the defect that out-of-band supervision is surveyed is not to be suitable for wide range signal and system filter signal, typically For 10Gb/s wavelength-division multiplex system.In band, monitoring can be based on polarization state method, and spectrum relative method.Partially The light extinction method that shakes searches for the signal power maximum under various polarization states and minima, but it is multiple not to be suitable for polarization Use system；Utilize degree of polarization measuring principle to realize the measurement of OSNR, be not also suitable for palarization multiplexing system System.Spectrum relative method, based on light detection module, detects noise and signal simultaneously, and accuracy of detection is the most not Ideal, and system realize relatively costly.

The monitoring of OSNR electrical domain is study hotspot in recent years, such as, utilize Digital Signal Processing, adopt Analyze OSNR with histogram technology, but monitoring accuracy is poor under big noise when systematic cost.Relevant System is the mainstream technology of current 100Gb/s distant wavelength-division system optic communication, utilizes advanced digital signal The various transmission impairment of compensating technique, compensates including chromatic dispersion, polarization demultiplexing, frequency compensation, phase place Recover, the technology such as forward direction error code correction.

Summary of the invention

The technical problem to be solved in the present invention is to provide the method and device of a kind of optical signal-to-noise ratio monitoring, in order to The OSNR monitoring of coherent system is realized with Digital Signal Processing.

In order to solve above-mentioned technical problem, a kind of method that the invention provides optical signal-to-noise ratio monitoring, including:

Determine parameter X1 relevant to OSNR under multiple different condition；

Determine parameter X2 relevant to system transfers cost under multiple different condition；

With described parameter X1 and X2 as independent variable, OSNR measured value is dependent variable, utilizes polynary time Return technical limit spacing OSNR formula；

Data extracting parameter X1 (i) after recovering input signal and X2 (i), utilize described OSNR public The OSNR of formula monitoring measured signal.

Further, said method also has a following feature: described determine believe with light under multiple different condition Make an uproar and be achieved in the following ways than relevant parameter X1:

The OSNR obtained is calculated as parameter X1 by Error Vector Magnitude.

Further, said method also has a following feature: described determine believe with light under multiple different condition Make an uproar and be achieved in the following ways than relevant parameter X1:

Formula is utilized to obtain carrier-to-noise ratio after calculating second moment and Fourth-order moment numerical value；

Described carrier-to-noise ratio is converted into corresponding OSNR, using this OSNR as parameter X1.

Further, said method also has a following feature: described determine believe with light under multiple different condition Make an uproar and be achieved in the following ways than relevant parameter X1:

Utilize amplitude and phase information to calculate electricity signal to noise ratio, be OSNR by described electricity signal to noise ratio conversion, Using this OSNR as parameter X1.

Further, said method also has a following feature: described determine under multiple different condition with system Parameter X2 that transmission cost is relevant is achieved in the following ways:

To describe the Gauss exponent number of signal level probability distribution as parameter X2.

Further, said method also has a following feature: described determine under multiple different condition with system Parameter X2 that transmission cost is relevant is achieved in the following ways:

The Q-value that the bit error rate is corresponding before the error correction that coherent system algorithm chip provides is as parameter X2.

In order to solve the problems referred to above, present invention also offers the device of a kind of optical signal-to-noise ratio monitoring, wherein, Including:

First determines module, for determining parameter X1 relevant to OSNR under multiple different condition；

Second determines module, for determining parameter relevant to system transfers cost under multiple different condition X2；

Acquisition module, for described parameter X1 and X2 as independent variable, OSNR measured value is strain Amount, utilizes multiple regression technical limit spacing OSNR formula；

Monitoring modular, data extracting parameter X1 (i) after input signal is recovered and X2 (i), utilize The OSNR of described OSNR formula monitoring measured signal.

Further, said apparatus also has a following feature:

Described first determines module, determines that parameter X1 relevant to OSNR under multiple different condition is It is accomplished by: calculate the OSNR obtained as parameter X1 by Error Vector Magnitude.

Further, said apparatus also has a following feature:

Described first determines module, determines that parameter X1 relevant to OSNR under multiple different condition is It is accomplished by: after calculating second moment and Fourth-order moment numerical value, utilize formula to obtain carrier-to-noise ratio；Will Described carrier-to-noise ratio is converted into corresponding OSNR, using this OSNR as parameter X1.

Further, said apparatus also has a following feature:

Described first determines module, determines that parameter X1 relevant to OSNR under multiple different condition is It is accomplished by: utilize amplitude and phase information to calculate electricity signal to noise ratio, by described electricity signal to noise ratio Conversion is OSNR, using this OSNR as parameter X1.

Further, said apparatus also has a following feature:

Described second determines module, determines parameter X2 relevant to system transfers cost under multiple different condition It is achieved in the following ways: to describe the Gauss exponent number of signal level probability distribution as parameter X2.

Further, said apparatus also has a following feature:

Described second determines module, determines parameter X2 relevant to system transfers cost under multiple different condition It is achieved in the following ways: with the Q that the bit error rate before the error correction that coherent system algorithm chip provides is corresponding Value is as parameter X2.

To sum up, the present invention provides the method and device of a kind of optical signal-to-noise ratio monitoring to make full use of coherent system Digital Signal Processing, it is achieved take into account hardware cost and OSNR monitoring accuracy.Use of the present invention Method and apparatus, compared with prior art, it is achieved that the electrical domain monitoring of coherent system OSNR, saves Monitoring cost, OSNR monitoring accuracy is higher, improve the reliability of optical communication system.

Accompanying drawing explanation

Fig. 1 is the schematic diagram of the system of the coherent system optical signal-to-noise ratio monitoring of the embodiment of the present invention；

Fig. 2 is the flow chart of the method for the coherent system optical signal-to-noise ratio monitoring of the embodiment of the present invention；

Fig. 3 is the OSNR result of calculation calculated based on EVM and the relation of error of the embodiment of the present invention Figure；

Fig. 4 is parameter X1 of the embodiment of the present invention 1, X2 and OSNR value three-dimensional curve diagram；

Fig. 5 is OSNR result of calculation and the graph of a relation of error of the embodiment of the present invention 1；

Fig. 6 is parameter X1 of the embodiment of the present invention 2, X2 and OSNR value three-dimensional curve diagram；

Fig. 7 is OSNR result of calculation and the graph of a relation of error of the embodiment of the present invention 2；

Fig. 8 is OSNR result of calculation and the graph of a relation of error of the embodiment of the present invention 3；

Fig. 9 is OSNR result of calculation and the graph of a relation of error of the embodiment of the present invention 4；

Figure 10 is OSNR result of calculation and the graph of a relation of error of the embodiment of the present invention 5；

Figure 11 is the schematic diagram of the device of a kind of optical signal-to-noise ratio monitoring of the embodiment of the present invention.

Detailed description of the invention

For making the object, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing Embodiments of the invention are described in detail.It should be noted that in the case of not conflicting, this Shen Embodiment in please and the feature in embodiment can mutual combination in any.

Described in the embodiment of the present invention, the system of coherent system optical signal-to-noise ratio monitoring consists of the following components, phase Stem grafting receives electrooptical device, coherent reception digital signal processing chip and optical signal-to-noise ratio monitoring device.Defeated Optical signal realizes photoelectric signal transformation successively, compensates damage and recovers signal, finally from recovering signal Extract relevant information and realize the monitoring of OSNR.

Wherein, coherent reception electrooptical device and coherent reception digital signal processing chip are existing phase The general of dry systems realizes technology.Coherent reception electrooptical device includes local oscillator light source, frequency mixer, light Electric transducer, high-speed AD converter.Coherent reception digital signal processing chip includes timing and goes time delay, Dispersion compensation, polarization demultiplexing, frequency compensation, the function such as phase recovery.

Optical signal-to-noise ratio monitoring device needs from recovering to extract signal related data information, and analytical data obtains Relevant parameter needed for OSNR calculating.

With several embodiments, the method for the optical signal-to-noise ratio monitoring of the present invention is described in detail below.

Embodiment 1, as in figure 2 it is shown, comprise the following steps:

Step 101, determine parameter X1 relevant to OSNR under multiple different condition；

Parameter X1 is close with true OSNR when system transfers cost is negligible, but in system transfers generation Valency relatively big constantly with the differing greatly of true OSNR.

The present embodiment X1 to calculate the OSNR (OSNR) obtained from Error Vector Magnitude (EVM) Illustrate as a example by X1.

Have according to general knowledge known in this field definition:

${\mathrm{EVM}}_{\mathrm{rms}}=\sqrt{\frac{1}{N}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{|S_{\mathrm{meas}}\left(n\right)-S_{\mathrm{ideal}}\left(n\right)|}^2}$

Wherein, S_measFor AVHRR NDVI value, S_idealFor planisphere reference value.

EVM with the relation of signal to noise ratio (SNR) is:

$\mathrm{SNR}\≈\frac{1}{{\mathrm{EVM}}_{\mathrm{rms}}^2}$

Signal to noise ratio (linear value) can be converted as OSNR (dB value), specific as follows:

OSNR=10*log10 (SNR)+10*log10 (SR/12.5)

Wherein, SR represents input optical signal character rate, and unit is GBd, and 12.5 represent OSNR meter 12.5GHz corresponding for noise power institute specification reference bandwith 0.1nm during calculation.

Fig. 3 gives value of calculation and the curve of ideal value of OSNR based on EVM, it is seen that in ideal In the case of OSNR=15dB, corresponding multiple OSNR value of calculation, different nonlinear effects pair is described The influence degree of OSNR monitoring is different, and especially in the case of big OSNR, error has been even more than 5dB, The most just say that this computational methods do not account for the impact of the factor such as non-linear, it is impossible to directly from single parameter meter Calculate the exact value obtaining OSNR.In the case of there is no system transfers cost, the most such as back-to-back In the case of, the OSNR (parameter X1) herein calculated and the error of preferable OSNR are the least.

Existing coherent system is usually polarisation multiplex system, in the case of being not added with specified otherwise, and this enforcement Relevant parameter in dual-polarization state is done average treatment by example.The phase in each polarization state can also be calculated respectively Answer parameter, the more final parameter that calculates is done average treatment.

Step 102, determine parameter X2 relevant to system transfers cost under multiple different condition；

Parameter X2 is to characterize system transfers effect or the parameter of cost, and system transfers effect includes but do not limits In nonlinear effect and system filter.

Step 101 and step 102 do not have strict sequencing in principle.

The present embodiment is said as a example by parameter X2 using the Gauss exponent number describing signal level probability distribution Bright, it should be noted that to also have additive method can realize parameter X2.

Equation below is to represent the general-purpose indexes function of 1 and 0 probability distribution,

$f_v\left(x\right)=\frac{v}{2\sqrt{2}\mathrm{\σ\Γ}(1/v)}\exp (-{\left(\frac{x-\mathrm{\μ}}{\sqrt{2}\mathrm{\σ}}\right)}^2),\∀x\∈R$

Wherein, μ is the meansigma methods of probability distribution, and σ is the mean square deviation of probability distribution, and ν is Gauss exponent number, Γ is gamma function.Under normal circumstances, when especially nonlinear effect is less, ν close to 2, because of This ν represents the size of nonlinear effect to a certain extent.

For the Setting signal after Digital Signal Processing in coherent system, Likelihood estimation is utilized to obtain The relevant parameter of the general-purpose indexes function of 1 and 0 probability distribution: meansigma methods, mean square deviation and Gauss exponent number. Wherein, Gauss exponent number represents the degree of nonlinear effect.

Such as, in matlab, available mle function realizes the maximal possibility estimation of probability density.

Step 103, utilize multiple regression (Multiple regression) technical limit spacing OSNR formula；

Design multivariate linear equation model, making parameter X1 and X2 is independent variable, and independent variable combination is permissible Comprising cross term and quadratic term, OSNR measured value (i.e. OSNR actual value) is dependent variable.

Can use more independent variable, such as X3 in principle, X4 etc., but from the checking of monitoring accuracy And design complexities considers, 2 independent variables have been capable of the monitoring exact requirements of OSNR.

Coherent system is 10 spans PM-QPSK (palarization multiplexing-QPSK) system, every span 100km standard single-mode fiber, for investigating nonlinear effect, unicast launched power is respectively-3dBm, 0dBm, 2dBm, 5dBm.As shown in table 1, ideal value has multiple identical value, represents to enter in difference By adjusting the OSNR value that noise obtains under fine power, X1 represents the ginseng that the present embodiment first step obtains Number, X2 represents the parameter that the present embodiment second step obtains, and value of calculation represents and utilizes multiple regression technology to obtain OSNR value of calculation, and corresponding OSNR error.

Table 1

Multiple regression typically uses method of least square to realize the coefficient of X β=y, and concrete formula is β=(X^TX)^-1X^Ty.Wherein, X is independent variable, and y is dependent variable (OSNR ideal value), and β is to return Coefficient, footnote^TRepresenting matrix transposition, footnote^-1Representing matrix is inverted.X is multiple regression independent variable matrix, Contain the combination of two independent variables, can be [1 X1 X2 X1.*X2], it is also possible to be [1 X1 X2 X1.*X2 X1.^2 X2.^2], it is also possible to it is can also to be [1 X1 X2 X1.*X2 X1.^2], however, it is also possible to use [1 X1 X2], i.e. binary linear regression, but do not recommend, because Error is bigger.In matlab, available regress function realizes multiple regression, uses linest in excel Function realizes multiple regression, or directly design matrix is inverted and multiplying realizes multivariate regression coefficients Determine.

The OSNR formula obtained in this step is only applicable to the coherent light module that performance is close, performance difference Bigger coherent light module needs independent calibration.

Step 104, input signal is recovered after data extract X1 (i) and X2 (i) parameter, utilize above-mentioned The formula that step obtains detects the OSNR of measured signal.

First three step of above-mentioned steps can be by theoretical simulation or laboratory/dispatch from the factory measurement and analyze and process acquisition The concrete coefficient of OSNR formula, substitutes into actual X1 (i) and X2 (i) when coherent system is properly functioning Parameter, can draw the OSNR of current coherent system.

Fig. 4 is the three-dimensional curve diagram of X1, X2 and the OSNR of the embodiment of the present invention one, and Fig. 5 is this The OSNR result of calculation based on multiple regression of bright embodiment one, it is seen that relative to the result of calculation of Fig. 3 There is bigger lifting.

Embodiment 2:

Step 201, calculate parameter X1 relevant to OSNR under multiple different condition；

With the step 101 in embodiment 1.

Step 202, calculate parameter X2 relevant to system transfers cost under multiple different condition；

Coherent system algorithm chip can provide the bit error rate before error correction, and X2 chooses the Q-value that the bit error rate is corresponding, Concrete formula is:

$Q=20\lg \left(\sqrt{2}\mathrm{erfcinv}\left(2\mathrm{BER}\right)\right)$

Wherein, erfcinv is the inverse function of error function, and BER is the bit error rate before error correction.

It is to be noted that X2 exists multiple implementation method.Such as utilize histogram information, different costs System may have identical SNR value, but in rectangular histogram, the distribution of 0 and 1 information has difference.

Step 203, utilize multiple regression technology obtain OSNR formula；

System is same as in Example 1, and selecting X is [1 X1 X2 X1.*X2], result of calculation such as table Shown in 2.

Table 2

Step 204, input signal is recovered after data extract X1 (i) and X2 (i) parameter, utilize above-mentioned The formula that step obtains calculates the OSNR of measured signal.

Fig. 6 is the three-dimensional curve diagram of X1, X2 and the OSNR of the embodiment of the present invention two, and Fig. 7 is this The OSNR result of calculation based on multiple regression of bright embodiment two, it is seen that relative to the result of calculation of Fig. 3 There is bigger lifting.

Embodiment 3:

Step 301, calculate parameter X1 relevant to OSNR under multiple different condition；

Utilize Moment Methods to calculate OSNR, first calculate second moment and Fourth-order moment numerical value, then use Formula obtains carrier-to-noise ratio (CNR), is converted into corresponding OSNR the most again, and detailed process refers to literary composition Offer " In-band optical to noise ratio estimation from equalized signals in digital Coherent receiver " (IEEE photonics Journal 2014), or " Esitmating OSNR of Equalised QPSK Signals”(ECOC 2011,Tu 6.A.6)。

Moment Methods result is very nearly the same with X1 described in embodiment 1 step 101, but computation complexity is bigger.

Step 302, calculate parameter X2 relevant to system transfers cost under multiple different condition；

With the step 202 in embodiment 2.

Step 303, utilize multiple regression technology obtain OSNR formula；

Selecting X is [1 X1 X2 X1.*X2], and result of calculation is as shown in table 3.

Table 3

Step 304, input signal is recovered after data extract X1 (i) and X2 (i) parameter, utilize above-mentioned The formula that step obtains calculates the OSNR of measured signal.

Fig. 8 is the OSNR result of calculation based on multiple regression of the embodiment of the present invention three, it is seen that relative to The result of calculation of Fig. 3 has had bigger lifting.

Embodiment 4:

Step 401, calculate parameter X1 relevant to OSNR under multiple different condition；

With the step 101 in embodiment 1.

Step 402, calculate parameter X2 relevant to system transfers cost under multiple different condition；

With the step 202 in embodiment 2.

Step 403, utilize multiple regression technology obtain OSNR formula；

System is same as in Example 1, and selecting X is [1 X2 X1.*X2 X1.^2 X2.^2], y Deducting X1 for OSNR ideal value, result of calculation is as shown in table 4.The most directly use X1 conduct Independent variable, but X1 is made as the reference value of OSNR or reference value, multivariate linear equation value For the correction value of OSNR, this correction value generally on the occasion of.

Table 4

Step 404, input signal is recovered after data extract X1 (i) and X2 (i) parameter, utilize above-mentioned The formula that step obtains calculates the OSNR of measured signal.

Fig. 9 is the OSNR result of calculation based on multiple regression of the embodiment of the present invention four, it is seen that relative to The result of calculation of Fig. 3 has had bigger lifting.

Embodiment 5:

Step 501, calculate parameter X1 relevant to OSNR under multiple different condition；

Amplitude and phase information is utilized to calculate SNR.As a example by QPSK (QPSK), first Four constellation point (I+1j*Q) are transformed into first quartile, i.e. X=abs (I)+1j*abs (Q).Do so Benefit be to simplify phase calculation complexity.

Amplitude information is abs (X), and angle information is angle (X).Calculate amplitude information and angle letter respectively The meansigma methods of breath and standard deviation, making Qa is that amplitude information meansigma methods is divided by amplitude information standard deviation；Qp is Angle information meansigma methods is divided by angle information standard deviation.SNR is following formula, and wherein k is amplitude factor and phase The matching constant of location factor, takes according to theoretical simulation and is about worth 1.38, finally utilizes formula to be converted by SNR For OSNR:

$\mathrm{SNR}=\frac{1}{\frac{1}{Q{a}^2}+\frac{1}{Q{p}^2{k}_2}}$

It is to be noted and can obtain X1 by various methods, such as, utilize various telecommunications in radio communication to make an uproar Than (SNR) formula.The OSNR computation complexity of such as patent WO/2015/006981 is relatively big, Error has slightly to be improved, and the feature of this kind of method is bigger in system transfers cost especially nonlinear effect Relatively big with OSNR error during high s/n ratio, therefore only can not ensure that OSNR is under various scenes with X1 Monitoring accuracy.

Step 502, calculate parameter X2 relevant to system transfers cost under multiple different condition；

With the step 202 in embodiment 2.

Step 503, utilize multiple regression technology obtain OSNR formula；

With the step 103 in embodiment 1.

Step 504, input signal is recovered after data extract X1 (i) and X2 (i) parameter, utilize above-mentioned The formula that step obtains calculates the OSNR of measured signal.

Figure 10 is the OSNR result of calculation based on multiple regression of the embodiment of the present invention five, it is seen that relatively Result of calculation in Fig. 3 has had bigger lifting.

Figure 11 is the schematic diagram of the device of a kind of optical signal-to-noise ratio monitoring of the embodiment of the present invention, such as Figure 11 institute Showing, the device of the present embodiment includes:

First determines module, for determining parameter X1 relevant to OSNR under multiple different condition；

Second determines module, for determining parameter relevant to system transfers cost under multiple different condition X2；

Acquisition module, for described parameter X1 and X2 as independent variable, OSNR measured value is strain Amount, utilizes multiple regression technical limit spacing OSNR formula；

Monitoring modular, data extracting parameter X1 (i) after input signal is recovered and X2 (i), utilize The OSNR of described OSNR formula monitoring measured signal.

In a preferred embodiment, described first determines module, determine under multiple different condition with light noise Can be accomplished by than relevant parameter X1: calculate acquisition by Error Vector Magnitude OSNR is as parameter X1.

In a preferred embodiment, described first determines module, determine under multiple different condition with light noise Can be accomplished by than relevant parameter X1: calculate profit after second moment and Fourth-order moment numerical value Carrier-to-noise ratio is obtained with formula；Described carrier-to-noise ratio is converted into corresponding OSNR, this OSNR is made For parameter X1.

In a preferred embodiment, described first determines module, determine under multiple different condition with light noise Can be accomplished by than relevant parameter X1: utilize amplitude and phase information to calculate telecommunications Make an uproar ratio, be OSNR by described electricity signal to noise ratio conversion, using this OSNR as parameter X1.

In a preferred embodiment, described second determines module, determines and passes with system under multiple different condition Parameter X2 that defeated cost is relevant can be accomplished by: to describe signal level probability distribution Gauss exponent number as parameter X2.

In a preferred embodiment, described second determines module, determines and passes with system under multiple different condition Parameter X2 that defeated cost is relevant can be accomplished by: provides with coherent system algorithm chip Error correction before Q-value corresponding to the bit error rate as parameter X2.

One of ordinary skill in the art will appreciate that all or part of step in said method can pass through program Instructing related hardware to complete, described program can be stored in computer-readable recording medium, as read-only Memorizer, disk or CD etc..Alternatively, all or part of step of above-described embodiment can also use One or more integrated circuits realize.Correspondingly, each module/unit in above-described embodiment can use The form of hardware realizes, it would however also be possible to employ the form of software function module realizes.The present invention is not restricted to appoint The combination of the hardware and software of what particular form.

These are only the preferred embodiments of the present invention, certainly, the present invention also can have other various embodiments, In the case of without departing substantially from present invention spirit and essence thereof, those of ordinary skill in the art work as can be according to this Various corresponding change and deformation are made in invention, but these change accordingly and deformation all should belong to the present invention Appended scope of the claims.

Claims (12)

1. a method for optical signal-to-noise ratio monitoring, including:

Determine parameter X1 relevant to OSNR under multiple different condition；

Determine parameter X2 relevant to system transfers cost under multiple different condition；

With described parameter X1 and X2 as independent variable, OSNR measured value is dependent variable, utilizes polynary time Return technical limit spacing OSNR formula；

Data extracting parameter X1 (i) after recovering input signal and X2 (i), utilize described OSNR public The OSNR of formula monitoring measured signal.

2. the method for claim 1, it is characterised in that: described determine under multiple different condition with Parameter X1 that OSNR is relevant is achieved in the following ways:

The OSNR obtained is calculated as parameter X1 by Error Vector Magnitude.

3. the method for claim 1, it is characterised in that: described determine under multiple different condition with Parameter X1 that OSNR is relevant is achieved in the following ways:

Formula is utilized to obtain carrier-to-noise ratio after calculating second moment and Fourth-order moment numerical value；

Described carrier-to-noise ratio is converted into corresponding OSNR, using this OSNR as parameter X1.

4. the method for claim 1, it is characterised in that: described determine under multiple different condition with Parameter X1 that OSNR is relevant is achieved in the following ways:

Utilize amplitude and phase information to calculate electricity signal to noise ratio, be OSNR by described electricity signal to noise ratio conversion, Using this OSNR as parameter X1.

5. the method as described in any one of claim 1-4, it is characterised in that: described determine multiple not Parameter X2 relevant to system transfers cost under the conditions of Tong is achieved in the following ways:

To describe the Gauss exponent number of signal level probability distribution as parameter X2.

6. the method as described in any one of claim 1-4, it is characterised in that: described determine multiple not Parameter X2 relevant to system transfers cost under the conditions of Tong is achieved in the following ways:

The Q-value that the bit error rate is corresponding before the error correction that coherent system algorithm chip provides is as parameter X2.

7. the device of an optical signal-to-noise ratio monitoring, it is characterised in that including:

First determines module, for determining parameter X1 relevant to OSNR under multiple different condition；

Second determines module, for determining parameter relevant to system transfers cost under multiple different condition X2；

Acquisition module, for described parameter X1 and X2 as independent variable, OSNR measured value is strain Amount, utilizes multiple regression technical limit spacing OSNR formula；

Monitoring modular, data extracting parameter X1 (i) after input signal is recovered and X2 (i), utilize The OSNR of described OSNR formula monitoring measured signal.

8. device as claimed in claim 7, it is characterised in that:

Described first determines module, determines that parameter X1 relevant to OSNR under multiple different condition is It is accomplished by: calculate the OSNR obtained as parameter X1 by Error Vector Magnitude.

9. device as claimed in claim 7, it is characterised in that:

Described first determines module, determines that parameter X1 relevant to OSNR under multiple different condition is It is accomplished by: after calculating second moment and Fourth-order moment numerical value, utilize formula to obtain carrier-to-noise ratio；Will Described carrier-to-noise ratio is converted into corresponding OSNR, using this OSNR as parameter X1.

10. device as claimed in claim 7, it is characterised in that:

Described first determines module, determines that parameter X1 relevant to OSNR under multiple different condition is It is accomplished by: utilize amplitude and phase information to calculate electricity signal to noise ratio, by described electricity signal to noise ratio Conversion is OSNR, using this OSNR as parameter X1.

11. devices as described in any one of claim 7-10, it is characterised in that:

Described second determines module, determines parameter X2 relevant to system transfers cost under multiple different condition It is achieved in the following ways: to describe the Gauss exponent number of signal level probability distribution as parameter X2.

12. devices as described in any one of claim 7-10, it is characterised in that:

Described second determines module, determines parameter X2 relevant to system transfers cost under multiple different condition It is achieved in the following ways: with the Q that the bit error rate before the error correction that coherent system algorithm chip provides is corresponding Value is as parameter X2.