WO2016173324A1

WO2016173324A1 - Optical signal to noise ratio monitoring method and device

Info

Publication number: WO2016173324A1
Application number: PCT/CN2016/076069
Authority: WO
Inventors: 沈百林; 廖屏; 杨鸿晋; 武成宾
Original assignee: 中兴通讯股份有限公司
Priority date: 2015-04-30
Filing date: 2016-03-10
Publication date: 2016-11-03
Also published as: CN106209222A

Abstract

An optical signal to noise ratio (OSNR) monitoring method and device. The method comprises: determining a parameter X1 related to the OSNR in a plurality of different conditions; determining a parameter X2 related to a system transmission cost in the plurality of the different conditions; setting the parameters X1 and X2 as independent variables, and an OSNR measured value as a dependent variable, and utilizing a multiple regression technique to obtain an OSNR equation; extracting parameters X1 (i) and X2 (i) from data following input signal recovery, and utilizing the OSNR equation to monitor the OSNR of a signal to be measured. The present invention makes full use of a digital signal processing technique of a coherent system, and achieves both a favorable hardware cost and OSNR monitoring precision. The above technical solution achieves OSNR electrical domain monitoring in a coherent system, thus reducing monitoring cost, and improving an optical communication system reliability due to high OSNR monitoring precision.

Description

Method and device for monitoring optical signal to noise ratio

Technical field

This document relates to, but is not limited to, performance monitoring in the field of optical communications, and more particularly to an optical signal to noise ratio monitoring method and apparatus.

Background technique

The optical signal to noise ratio (OSNR) of the wavelength division multiplexing system is a key parameter for measuring the transmission performance of the wavelength division system. It is defined as the channel signal power divided by the noise power within 0.1 nm at the signal wavelength, which is convenient for use. Generally converted to dB. With the development of the wavelength division multiplexing system to 40Gb/s and above, the OSNR monitoring is becoming more and more difficult.

OSNR optical domain monitoring mainly includes out-of-band monitoring and in-band monitoring. The out-of-band monitoring measures the noise power between the channels, and then uses interpolation to obtain the noise power at the signal wavelength, thereby calculating the OSNR. The defect of out-of-band monitoring is not applicable to wide-spectrum signals and system filtered signals, and is generally used in 10Gb/s wavelength division multiplexing systems. In-band monitoring can be based on polarization methods, as well as spectral comparison methods. The polarization extinction method searches for the maximum and minimum signal powers in various polarization states, but it is not suitable for polarization multiplexing systems. The measurement of optical signal-to-noise ratio is achieved by the principle of polarization measurement, and it is not applicable to polarization multiplexing systems. The spectral comparison method is based on the light monitoring module, and the noise and the signal are simultaneously detected, the detection accuracy is still not ideal, and the system realizes high cost.

OSNR electrical domain monitoring is a research hotspot in recent years. For example, digital signal processing technology is used to analyze optical signal-to-noise ratio by histogram technique, but the monitoring accuracy is poor under large signal-to-noise ratio and system cost. Coherent system is the mainstream technology of optical communication in 100Gb/s long-haul wavelength division system. It uses advanced digital signal technology to compensate for various transmission impairments, including chromatic dispersion compensation, polarization demultiplexing, frequency compensation, phase recovery, and forward error. Error correction and other technologies.

Summary of the invention

The following is an overview of the topics detailed in this document. This summary is not intended to limit the claims The scope of protection.

Embodiments of the present invention provide a method and apparatus for optical signal to noise ratio monitoring, which realizes OSNR monitoring of a coherent system by using digital signal processing technology.

Embodiments of the present invention provide a method for monitoring optical signal to noise ratio, including:

Determining a parameter X1 related to optical signal to noise ratio under a plurality of different conditions;

Determining a parameter X2 related to the system transmission cost under a plurality of different conditions;

Taking the parameters X1 and X2 as independent variables, the optical signal-to-noise ratio measurement is a dependent variable, and the optical signal-to-noise ratio formula is obtained by using multiple regression techniques;

The data extraction parameters X1(i) and X2(i) after the input signal is recovered are used to monitor the optical signal to noise ratio of the signal to be tested by using the optical signal to noise ratio formula.

Optionally, the foregoing method further has the following feature: the determining the parameter X1 related to the optical signal-to-noise ratio under a plurality of different conditions is implemented by:

The optical signal to noise ratio obtained by the error vector magnitude calculation is taken as the parameter X1.

Calculate the second-order moment and the fourth-order moment value and use the formula to obtain the carrier-to-noise ratio;

The carrier-to-noise ratio is calculated as a corresponding optical signal-to-noise ratio, and the optical signal-to-noise ratio is used as the parameter X1.

The telecommunication noise ratio is calculated by using the amplitude and phase information, and the telecommunication noise ratio is converted into an optical signal to noise ratio, and the optical signal to noise ratio is used as the parameter X1.

Optionally, the foregoing method further has the following feature: the determining the parameter X2 related to the system transmission cost under a plurality of different conditions is implemented by:

The Gaussian order describing the probability distribution of the signal level is taken as the parameter X2.

The Q value corresponding to the error rate before error correction provided by the coherent system algorithm chip is taken as the parameter X2.

The embodiment of the invention further provides an apparatus for monitoring optical signal to noise ratio, which comprises:

a first determining module, configured to determine a parameter X1 related to an optical signal to noise ratio under a plurality of different conditions;

a second determining module, configured to determine a parameter X2 related to a system transmission cost under a plurality of different conditions;

Obtaining a module, which is set with the parameters X1 and X2 as independent variables, and the optical signal to noise ratio measurement value is a dependent variable, and the optical signal to noise ratio formula is obtained by using multiple regression techniques;

The monitoring module is configured to extract the parameters X1(i) and X2(i) after the input signal is recovered, and use the optical signal to noise ratio formula to monitor the optical signal to noise ratio of the signal to be tested.

Optionally, the above device also has the following features:

The first determining module is configured to determine a parameter X1 related to an optical signal-to-noise ratio under a plurality of different conditions by using an optical signal-to-noise ratio obtained by calculating an error vector magnitude as the parameter X1.

Optionally, the above device also has the following features:

The first determining module is configured to determine a parameter X1 related to an optical signal-to-noise ratio under a plurality of different conditions by calculating a second-order moment and a fourth-order moment value, and obtaining a carrier-to-noise ratio by using the formula; The carrier-to-noise ratio is calculated as the corresponding optical signal-to-noise ratio, and the optical signal-to-noise ratio is taken as the parameter X1.

Optionally, the above device also has the following features:

The first determining module is configured to determine a parameter X1 related to an optical signal-to-noise ratio under a plurality of different conditions by calculating a telecommunication noise ratio by using amplitude and phase information, and converting the telecommunication noise ratio into The optical signal to noise ratio is taken as the parameter X1.

Optionally, the above device also has the following features:

The second determining module is configured to determine a parameter X2 related to a system transmission cost under a plurality of different conditions by using a Gaussian order describing a signal level probability distribution as the parameter X2.

Optionally, the above device also has the following features:

The second determining module is configured to determine, under different conditions, The system transmission cost-related parameter X2: the Q value corresponding to the error correction error rate provided by the coherent system algorithm chip is taken as the parameter X2.

The embodiment of the invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the above method.

In summary, the embodiments of the present invention provide a method and apparatus for optical signal to noise ratio monitoring that fully utilizes the digital signal processing technology of the coherent system to achieve both hardware cost and OSNR monitoring accuracy. Compared with the related technology, the method and the device according to the embodiment of the invention realize the electrical domain monitoring of the optical signal to noise ratio of the coherent system, save the monitoring cost, and the OSNR monitoring precision is high, and the reliability of the optical communication system is improved.

Other aspects will be apparent upon reading and understanding the drawings and detailed description.

BRIEF abstract

1 is a schematic diagram of a system for monitoring optical signal to noise ratio of a coherent system according to an embodiment of the present invention;

2 is a flow chart of a method for monitoring optical signal to noise ratio of a coherent system according to an embodiment of the present invention;

3 is a relationship diagram of OSNR calculation results and errors based on EVM calculation according to an embodiment of the present invention;

4 is a three-dimensional graph of parameters X1, X2 and OSNR values of Embodiment 1 of the present invention;

Figure 5 is a diagram showing the relationship between the OSNR calculation result and the error in the first embodiment of the present invention;

6 is a three-dimensional graph of parameters X1, X2 and OSNR values of Embodiment 2 of the present invention;

7 is a diagram showing a relationship between an OSNR calculation result and an error according to Embodiment 2 of the present invention;

Figure 8 is a diagram showing the relationship between the OSNR calculation result and the error in the third embodiment of the present invention;

Figure 9 is a diagram showing the relationship between the OSNR calculation result and the error in the fourth embodiment of the present invention;

Figure 10 is a diagram showing the relationship between OSNR calculation results and errors in Embodiment 5 of the present invention;

FIG. 11 is a schematic diagram of an apparatus for optical signal to noise ratio monitoring according to an embodiment of the present invention.

Embodiments of the invention

Embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that, in the case of no conflict, the features in the embodiments and the embodiments in the present application may be arbitrarily combined with each other.

As shown in FIG. 1, the system for detecting optical signal to noise ratio of a coherent system according to an embodiment of the present invention comprises the following parts: a coherent receiving photoelectric conversion device, a coherent receiving digital signal processing chip, and an optical signal to noise ratio monitoring device. The input optical signal sequentially realizes photoelectric signal conversion, compensates for damage and recovers the signal, and finally extracts relevant information from the recovered signal to realize optical signal to noise ratio monitoring.

Among them, the coherent receiving photoelectric conversion device and the coherent receiving digital signal processing chip are common implementation technologies of related coherent systems. The coherent receiving photoelectric conversion device includes a local oscillator light source, a mixer, a photoelectric converter, and a high speed analog to digital converter. The coherent receiving digital signal processing chip includes timing and de-delay, dispersion compensation, polarization demultiplexing, frequency compensation, phase recovery and the like.

The optical signal to noise ratio monitoring device needs to extract relevant data information from the recovered signal, and analyze the data to obtain relevant parameters required for optical signal to noise ratio calculation.

The method of optical signal to noise ratio monitoring of the present invention will be described in detail below in several embodiments.

Embodiment 1, as shown in FIG. 2, includes the following steps:

Step 101: Determine a parameter X1 related to an optical signal to noise ratio under a plurality of different conditions;

The parameter X1 is close to the real OSNR when the system transmission cost is negligible, but the difference from the real OSNR is large when the system transmission cost is large.

The present embodiment X1 is described by taking the optical signal-to-noise ratio (OSNR) obtained from the error vector magnitude (EVM) calculation as X1 as an example.

According to common knowledge in the art, there are:

Where rms represents the root mean square, N is the number of sampled samples, S _meas is the normalized measurement value, and S _ideal is the constellation reference value.

The relationship between EVM and signal-to-noise ratio (SNR) is:

The signal-to-noise ratio (linear value) can be converted into optical signal-to-noise ratio (dB value) as follows:

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

Where SR represents the symbol rate of the input optical signal in GBd, and 12.5 represents 12.5 GHz corresponding to the reference bandwidth of 0.1 nm for the noise power in the OSNR calculation.

Figure 3 shows the calculated and ideal value of the OSNR based on EVM. It can be seen that in the case of ideal OSNR=15dB, corresponding to multiple OSNR calculations, different nonlinear effects have different effects on OSNR monitoring, especially In the case of large OSNR, the error even exceeds 5 dB. That is to say, this calculation method does not consider the influence of nonlinear factors, and the exact value of OSNR cannot be obtained directly from a single parameter calculation. In the absence of a system transmission penalty, especially in the case of back-to-back, the OSNR (parameter X1) and the ideal OSNR calculated here are small.

The relevant coherent system is usually a polarization multiplexing system. In the present embodiment, the corresponding parameter X1 on the dual polarization state is averaged without any special explanation. It is also possible to calculate the corresponding parameter X1 for each polarization state separately, and finally averaging X1.

Step 102: Determine a parameter X2 related to a system transmission cost under a plurality of different conditions;

Parameter X2 is a parameter that characterizes the transmission effect or cost of the system, including but not limited to nonlinear effects and system filtering.

In principle, steps 101 and 102 do not have a strict sequence.

This embodiment is described by taking the Gaussian order of the signal level probability distribution as the parameter X2 as an example. It should be noted that there are other methods for implementing the parameter X2.

The following formula is a general exponential function representing the probability distribution of 1 and 0,

Where μ is the mean of the probability distribution, σ is the mean square of the probability distribution, ν is the Gaussian order, Γ is the gamma function, and R is the domain of the function. Under normal conditions, especially when the nonlinear effect is small, ν is close to 2, so ν represents the magnitude of the nonlinear effect to a certain extent.

For a given signal after digital signal processing in a coherent system, the likelihood estimation method can be used. Relevant parameters of the general exponential function of the probability distributions of 1 and 0: mean, mean squared and Gaussian order. Among them, the Gaussian order represents the degree of nonlinear effects.

For example, the mle function can be used in matlab to achieve maximum likelihood estimation of probability density.

Step 103: Obtain an optical signal to noise ratio formula by using multiple regression techniques;

The multivariate regression calculation model is designed such that the parameters X1 and X2 are independent variables, and the independent variable combination can contain cross terms and quadratic terms, and the OSNR measurement value (ie, the true OSNR value) is the dependent variable.

In principle, more independent variables can be used, such as X3, X4, etc., but from the verification of monitoring accuracy and design complexity, the two independent variables have been able to achieve accurate OSNR monitoring requirements.

The coherent system is a 10-span PM-QPSK (polarization multiplexed-quadrature phase shift keying) system with 100km standard single-mode fiber per span. To investigate the nonlinear effect, the single-wave fiber input power is -3dBm, 0dBm, respectively. 2dBm, 5dBm. As shown in Table 1, the ideal value has a plurality of identical values, indicating the OSNR value obtained by adjusting the noise at different fiber input powers, X1 represents the parameter obtained in the first step of the embodiment, and X2 represents the second step of the embodiment. The obtained parameters, the calculated values represent the calculated OSNR values obtained using multiple regression techniques, and the corresponding OSNR errors.

Table 1

Multivariate regression generally uses the least squares method to achieve the coefficient of Xβ=y. The specific formula is β=(X ^T X) ^-1 X ^T y. Where X is the independent variable, y is the dependent variable (OSNR ideal value, OSNR ideal value = OSNR measured value), β is the regression coefficient, the foot mark ^T indicates the matrix transpose, and the foot mark ^-1 indicates the matrix inversion. X is a multivariate regression independent variable matrix, which contains a combination of two independent variables, which can be [1 X1 X2 X1.*X2] or [1 X1 X2 X1.*X2 X1.^2 X2.^2], It can also be [1 X1 X2 X1.*X2 X1.^2]. In principle, [1 X1 X2] can also be used, that is, binary linear regression, but it is not recommended because the error is slightly larger. In Matlab, you can use the regress function to achieve multiple regression, use the linest function to achieve multiple regression in excel, or directly design the matrix inversion and multiplication to achieve the determination of multiple regression coefficients.

The OSNR formula obtained in this step is only applicable to coherent optical modules with close performance. Coherent optical modules with large performance differences need to be independently scaled.

Step 104: Extract X1(i) and X2(i) parameters from the data after the input signal is recovered, and use the formula obtained in the above step to monitor the optical signal to noise ratio of the signal to be tested.

The first three steps of the above steps can obtain the specific coefficients of the optical signal-to-noise ratio formula through theoretical simulation or laboratory/factory measurement and analysis, and enter the actual X1(i) and X2(i) parameters in the normal operation of the coherent system, ie The OSNR of the current coherent system can be derived.

4 is a three-dimensional graph of X1, X2 and OSNR calculation values according to Embodiment 1 of the present invention, and FIG. 5 is a multi-regression-based OSNR calculation result according to Embodiment 1 of the present invention, and it can be seen that the calculation result is larger than that of FIG. Improvement.

Example 2:

Step 201: Calculate a parameter X1 related to an optical signal to noise ratio under a plurality of different conditions;

Same as step 101 in the embodiment 1.

Step 202: Calculate a parameter X2 related to a system transmission cost under a plurality of different conditions;

The coherent system algorithm chip can provide the error rate before error correction, and X2 selects the Q value corresponding to the bit error rate. The specific formula is:

Where erfcinv is the inverse of the error function and BER is the error rate before error correction.

It should be pointed out that there are multiple implementation methods for X2. For example, using histogram information, systems of different costs may have the same SNR value, but the distribution of 0 and 1 information in the histogram is different.

Step 203: Obtain an optical signal to noise ratio formula by using multiple regression techniques;

The system was the same as in the first embodiment, and X was selected as [1 X1 X2 X1.*X2], and the calculation results are shown in Table 2.

Table 2

Step 204: Extract X1(i) and X2(i) parameters for the data after the input signal is recovered, and calculate an optical signal to noise ratio of the signal to be tested by using the formula obtained in the above step.

6 is a three-dimensional graph of X1, X2 and OSNR calculated values according to Embodiment 2 of the present invention, and FIG. 7 is a multi-regression based OSNR calculation result according to Embodiment 2 of the present invention, and it can be seen that the calculation result is larger than that of FIG. Improvement.

Example 3:

Step 301: Calculate a parameter X1 related to an optical signal to noise ratio under a plurality of different conditions;

The OSNR is calculated by the moment method. Specifically, the second-order moment and the fourth-order moment value are first calculated, and then the carrier-to-noise ratio (CNR) is obtained by the formula. Finally, the corresponding OSNR is calculated. For the specific process, refer to the document “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).

The result of the moment method is similar to that of X1 described in step 101 of Embodiment 1, but the computational complexity is greater.

Step 302: Calculate a parameter X2 related to a system transmission cost under a plurality of different conditions;

Same as step 202 in Embodiment 2.

Step 303, using a multiple regression technique to obtain an optical signal to noise ratio formula;

Select X as [1 X1 X2 X1.*X2], and the calculation results are shown in Table 3.

table 3

Step 304: Extract X1(i) and X2(i) parameters from the data after the input signal is recovered, and calculate an optical signal to noise ratio of the signal to be tested by using the formula obtained in the above step.

FIG. 8 is a multi-regression based OSNR calculation result according to Embodiment 3 of the present invention, and it can be seen that the calculation result with respect to FIG. 3 is greatly improved.

Example 4:

Step 401: Calculate a parameter X1 related to an optical signal to noise ratio under a plurality of different conditions;

Same as step 101 in the embodiment 1.

Step 402: Calculate a parameter X2 related to a system transmission cost under a plurality of different conditions;

Same as step 202 in Embodiment 2.

Step 403, using a multiple regression technique to obtain an optical signal to noise ratio formula;

The system is the same as in the first embodiment, and X is selected as [1 X2 X1.*X2 X1.^2 X2.^2], and y is the OSNR ideal value minus X1, and the calculation result is shown in Table 4. Instead of using X1 as an independent variable directly, X1 is used as a reference value or reference value of OSNR, and the multivariate regression calculation value is used as a correction value of OSNR, and the correction value is generally a positive value.

Table 4

Step 404: Extract X1(i) and X2(i) parameters from the data after the input signal is recovered, and calculate an optical signal to noise ratio of the signal to be tested by using the formula obtained in the above step.

FIG. 9 is a result of OSNR calculation based on multiple regression in the fourth embodiment of the present invention, and it can be seen that the calculation result relative to FIG. 3 is greatly improved.

Example 5:

Step 501: Calculate a parameter X1 related to an optical signal to noise ratio under a plurality of different conditions;

The SNR is calculated using the amplitude and phase information. Taking quadrature phase shift keying (QPSK) as an example, the first four constellation points (I+1j*Q) are first converted to the first quadrant, that is, X=abs(I)+1j*abs(Q). This has the advantage of simplifying phase calculation complexity.

The amplitude information is abs(X) and the angle information is angle(X). The average value and standard deviation of the amplitude information and the angle information are respectively calculated, and Qa is the average of the amplitude information divided by the standard deviation of the amplitude information; Qp is the average value of the angle information divided by the standard deviation of the angle information. The SNR is as follows, where k is the matching constant of the amplitude factor and the phase factor, and the approximate value is 1.38 according to the theoretical simulation. Finally, the SNR is converted into OSNR by the formula;

It should be noted that X1 can be obtained in a variety of ways, for example using a variety of telecommunication noise ratio (SNR) equations in wireless communications. For example, the optical signal-to-noise ratio (SNR) calculation complexity is large and the error is slightly improved. The method is characterized by a large OSNR error in the system transmission cost, especially the nonlinear effect and high signal-to-noise ratio. The X1 cannot guarantee the monitoring accuracy of OSNR in various scenarios.

Step 502: Calculate a parameter X2 related to a system transmission cost under a plurality of different conditions;

Same as step 202 in Embodiment 2.

Step 503, using a multiple regression technique to obtain an optical signal to noise ratio formula;

Same as step 103 in the embodiment 1.

Step 504: Extract X1(i) and X2(i) parameters from the data after the input signal is recovered, and calculate an optical signal to noise ratio of the signal to be tested by using the formula obtained in the above step.

FIG. 10 is a multi-regression based OSNR calculation result according to Embodiment 5 of the present invention, and it can be seen that the calculation result relative to FIG. 3 is greatly improved.

FIG. 11 is a schematic diagram of an apparatus for monitoring optical signal to noise ratio according to an embodiment of the present invention. As shown in FIG. 11, the apparatus of this embodiment includes:

In an optional embodiment, the first determining module is configured to determine a parameter X1 related to an optical signal-to-noise ratio under a plurality of different conditions by using an optical signal-to-noise ratio obtained by calculating an error vector magnitude as Parameter X1.

In an optional embodiment, the first determining module is configured to determine a parameter X1 related to an optical signal-to-noise ratio under a plurality of different conditions by calculating a second-order moment and a fourth-order moment value. Obtaining a carrier-to-noise ratio; calculating the carrier-to-noise ratio to calculate a corresponding optical signal-to-noise ratio, and using the optical signal-to-noise ratio as the parameter X1.

In an optional embodiment, the first determining module is configured to determine a parameter X1 related to an optical signal-to-noise ratio under a plurality of different conditions by calculating a telecommunication noise ratio using the amplitude and phase information, and The telecommunication noise ratio is converted into an optical signal to noise ratio, and the optical signal to noise ratio is taken as a parameter X1.

In an optional embodiment, the second determining module is configured to determine a parameter X2 related to a system transmission cost under a plurality of different conditions by using a Gaussian order describing a signal level probability distribution as a parameter. X2.

In an optional embodiment, the second determining module is configured to determine a parameter X2 related to a system transmission cost under a plurality of different conditions by using a pre-error error rate provided by the coherent system algorithm chip. The corresponding Q value is taken as parameter X2.

One of ordinary skill in the art will appreciate that all or a portion of the steps described above can be accomplished by a program that instructs the associated hardware, such as a read-only memory, a magnetic or optical disk, and the like. Alternatively, all or part of the steps of the above embodiments may also be implemented using one or more integrated circuits. Correspondingly, each module/unit in the foregoing embodiment may be implemented in the form of hardware or in the form of a software function module. The invention is not limited to any specific form of combination of hardware and software.

The above is only an alternative embodiment of the present invention, and of course, the present invention may be embodied in various other embodiments without departing from the spirit and scope of the invention. Corresponding changes and modifications are intended to be included within the scope of the appended claims.

Industrial applicability

The above technical solution realizes the electric domain monitoring of the optical signal-to-noise ratio of the coherent system, saves the monitoring cost, has high OSNR monitoring precision, and improves the reliability of the optical communication system.

Claims

A method of optical signal to noise ratio monitoring, comprising:

Determining a parameter X1 related to optical signal to noise ratio under a plurality of different conditions;

Determining a parameter X2 related to the system transmission cost under a plurality of different conditions;

Taking the parameters X1 and X2 as independent variables, the optical signal-to-noise ratio measurement is a dependent variable, and the optical signal-to-noise ratio formula is obtained by using multiple regression techniques;

The data extraction parameters X1(i) and X2(i) after the input signal is recovered are used to monitor the optical signal to noise ratio of the signal to be tested by using the optical signal to noise ratio formula.
The method of claim 1 wherein said determining a parameter X1 associated with an optical signal to noise ratio under a plurality of different conditions is achieved by:

The optical signal to noise ratio obtained by the error vector magnitude calculation is taken as the parameter X1.
The method of claim 1 wherein said determining a parameter X1 associated with an optical signal to noise ratio under a plurality of different conditions is achieved by:

Calculate the second-order moment and the fourth-order moment value and use the formula to obtain the carrier-to-noise ratio;

The carrier-to-noise ratio is calculated as a corresponding optical signal-to-noise ratio, and the optical signal-to-noise ratio is used as the parameter X1.
The method of claim 1 wherein said determining a parameter X1 associated with an optical signal to noise ratio under a plurality of different conditions is achieved by:

The telecommunication noise ratio is calculated by using the amplitude and phase information, and the telecommunication noise ratio is converted into an optical signal to noise ratio, and the optical signal to noise ratio is taken as the parameter X1.
A method according to any one of claims 1 to 4, wherein said determining a parameter X2 relating to a system transmission cost under a plurality of different conditions is achieved in the following manner:

The Gaussian order describing the probability distribution of the signal level is taken as the parameter X2.
A method according to any one of claims 1 to 4, wherein said determining a parameter X2 relating to a system transmission cost under a plurality of different conditions is achieved in the following manner:

The Q value corresponding to the error rate before error correction provided by the coherent system algorithm chip is taken as the parameter X2.
A device for optical signal to noise ratio monitoring, comprising:

a first determining module, configured to determine a parameter X1 related to an optical signal to noise ratio under a plurality of different conditions;

a second determining module, configured to determine a parameter X2 related to a system transmission cost under a plurality of different conditions;

Obtaining a module, which is set with the parameters X1 and X2 as independent variables, and the optical signal to noise ratio measurement value is a dependent variable, and the optical signal to noise ratio formula is obtained by using multiple regression techniques;

The monitoring module is configured to extract the parameters X1(i) and X2(i) after the input signal is recovered, and use the optical signal to noise ratio formula to monitor the optical signal to noise ratio of the signal to be tested.
The apparatus of claim 7 wherein:

The first determining module is configured to determine a parameter X1 related to an optical signal to noise ratio under a plurality of different conditions by:

The optical signal to noise ratio obtained by the error vector magnitude calculation is taken as the parameter X1.
The apparatus of claim 7 wherein:

The first determining module is configured to determine a parameter X1 related to an optical signal to noise ratio under a plurality of different conditions by:

After calculating the second-order moment and the fourth-order moment value, the carrier-to-noise ratio is obtained by using the formula; the corresponding signal-to-noise ratio is calculated by the corresponding carrier-to-noise ratio, and the optical signal-to-noise ratio is taken as the parameter X1.
The apparatus of claim 7 wherein:

The first determining module is configured to determine a parameter X1 related to an optical signal to noise ratio under a plurality of different conditions by:

The telecommunication noise ratio is calculated by using the amplitude and phase information, and the telecommunication noise ratio is converted into an optical signal to noise ratio, and the optical signal to noise ratio is used as the parameter X1.
A device according to any of claims 7-10, wherein:

The second determining module is configured to determine a parameter X2 related to a system transmission cost under a plurality of different conditions by:

The Gaussian order describing the probability distribution of the signal level is taken as the parameter X2.
A device according to any of claims 7-10, wherein:

The second determining module is configured to determine a parameter X2 related to a system transmission cost under a plurality of different conditions by:

The Q value corresponding to the error rate before error correction provided by the coherent system algorithm chip is taken as the parameter X2.
A computer storage medium having stored therein computer executable instructions for performing the method of any one of claims 1 to 6.