Method and system for estimating MPI interference influence level of optical communication signal

Abstract

The invention provides a method and system for estimating the MPI interference influence level of an optical communication signal, and the method comprises the steps: carrying out the photoelectric conversion of an optical signal passing through an optical fiber, and sampling the optical signal into a digital signal; performing independent calculation to obtain a mean value of each level; calculating a second-order central moment and a fourth-order central moment on each level; the ratio of the second moment to the fourth moment is calculated, and an MPI interference coefficient based on the data statistical characteristics on each level is obtained; and calculating the mean value of the MPI interference coefficients to obtain the MPI interference influence grade value of the received data. According to the invention, the index of the MPI interference influence level in a link can be output, so that the MPI interference intensity in the link can be judged; the method solves the problem of large SNR estimation deviation under MPI interference, has certain adaptability, can be applied to any intensity modulation and direct detection of optical communication systems, and also has corresponding effects on SNR estimation deviation under the influence of high temperature, low temperature and the like.

Description

Technical Field

[0001] The present invention belongs to the field of optical communication, and in particular, relates to a method and system for estimating the level of influence of MPI interference on optical communication signals. Background Art

[0002] Optical communication is a communication technology that uses light waves as a carrier for information transmission. Since the first realization of optical fiber communication in the 1970s, optical communication technology has developed rapidly. In recent years, with the maturity of optical amplifiers, wavelength division multiplexing (WDM) and coherent communication technologies, optical communication has achieved long-distance and high-speed transmission and is widely used in the fields of Internet backbone networks, data center interconnection, 5G networks and submarine communications.

[0003] Signal interference in optical communications can significantly affect the performance and transmission quality of the system, leading to problems such as signal distortion, increased bit error rate, bandwidth limitation, and shortened transmission distance. It directly affects the stability, efficiency, and economy of the optical communication system, and is a key challenge in design optimization.

[0004] MPI is one of the interference factors that need to be paid attention to in high-speed and large-capacity optical communication systems, which can lead to misjudgment of the actual link performance and its changes. Under the assumption that ordinary noise obeys Gaussian distribution characteristics, when MPI interference exists, the data in the link is equalized and non-Gaussian interference is introduced, which leads to the deterioration of the bit error rate (Ber) performance of the received signal under the influence of non-Gaussian and inaccurate SNR measurement.

[0005] There is no good calculation method for estimating MPI interference in the prior art. The impact strength of multipath interference (MPI) can be estimated by fitting and shaping the distribution characteristics of the received data. However, the fitting algorithm itself has poor stability and needs to recalibrate the fitting parameters when the actual environment changes. At the same time, the fitting algorithm itself needs to perform multiple calculations to select the best quality, resulting in very large memory and computing overheads.

[0006] Patent document "Detection method and device of MPI in optical communication system and optical communication system" (CN117917866A) discloses a method of using relevant information of the electrical signal obtained by the optical receiving end and relevant information of the optical communication system to determine the linear correlation between MPI noise and received optical power in the optical communication system, that is, the gradient change relationship between MPI noise and received optical power, and then based on the linear correlation, determine the MPI noise corresponding to each level. However, it uses analog circuits instead of digital circuits, and the estimation method is completely different from the present invention.

[0007] Therefore, there is an urgent need for an estimation method for the degree to which a signal is affected by MPI interference, which has low memory requirements and small computational complexity and can effectively solve the estimation bias problem under MPI interference. Summary of the invention

[0008] In view of the defects in the prior art, an object of the present invention is to provide a method and system for estimating the level of influence of MPI interference on optical communication signals.

[0009] A method for estimating the level of MPI interference affecting an optical communication signal provided by the present invention comprises:

[0010] Step S1: The optical signal passing through the optical fiber is sampled into a digital signal after being photoelectrically converted;

[0011] Step S2: Calculate each digital signal independently to obtain the mean value of each level;

[0012] Step S3: Calculate the second-order central moment and the fourth-order central moment at each level;

[0013] Step S4: Calculate the ratio of the 2nd order central moment to the 4th order central moment to obtain the MPI interference coefficient based on the statistical characteristics of the data at each level;

[0014] Step S5: Calculate the mean value of the MPI interference coefficient to obtain the level of impact of the MPI interference on the received data.

[0015] Preferably, the optical signal in step S1 is a non-return-to-zero code or pulse amplitude modulated optical signal, which is sampled into a digital signal by an analog-to-digital converter.

[0016] The mean value of the level in step S2

[0017] Where i represents the level of the received signal;

[0018] N[i] represents the number of data on the i-th level;

[0019] rcvData[i][j] represents the j-th received data at the i-th level.

[0020] Preferably, the 2nd-order center distance is

[0021] The 4th order center distance is

[0022] Wherein, N[i] represents the number of data at the i-th level;

[0023] rcvData[i][j] represents the jth received data at the i-th level;

[0024] avgLev[i] represents the average value of the i-th level.

[0025] Preferably, the MPI interference coefficient

[0026] Where M2Lev[i] represents the second-order center distance of the i-th level;

[0027] M4Lev[i] represents the 4th-order center distance of the i-th level.

[0028] The level value affected by MPI interference

[0029] Wherein, M represents the total number of levels of the received signal.

[0030] In the step S5, the SNR measurement value newSNR in the system is calibrated simultaneously = SNR-20*log10(avgMPI);

[0031] Wherein, SNR represents the uncalibrated SNR;

[0032] newSNR represents the SNR value that matches the received signal Ber after calibration with the MPI interference impact level value.

[0033] According to the present invention, a system for estimating the level of MPI interference affecting an optical communication signal comprises:

[0034] Module M1: converts the optical signal passing through the optical fiber into a digital signal through photoelectric conversion;

[0035] Module M2: Calculate each digital signal independently to obtain the mean value of each level;

[0036] Module M3: Calculate the second-order central moment and the fourth-order central moment at each level;

[0037] Module M4: Calculate the ratio of the 2nd order central moment to the 4th order central moment to obtain the MPI interference coefficient based on the statistical characteristics of the data at each level;

[0038] Module M5: Calculate the mean value of the MPI interference coefficient to obtain the level of impact of MPI interference on the received data.

[0039] Preferably, the optical signal in the module M1 is a non-return-to-zero code or a pulse amplitude modulated optical signal, which is sampled into a digital signal by an analog-to-digital converter.

[0040] The mean value of the level in the module M2

[0041] Where i represents the level of the received signal;

[0042] N[i] represents the number of data on the i-th level;

[0043] rcvData[i][j] represents the j-th received data at the i-th level.

[0044] Preferably, the 2nd-order center distance is

[0045] The 4th order center distance is

[0046] Wherein, N[i] represents the number of data at the i-th level;

[0047] rcvData[i][j] represents the jth received data at the i-th level;

[0048] avgLev[i] represents the average value of the i-th level.

[0049] Preferably, the MPI interference coefficient

[0050] Where M2Lev[i] represents the second-order center distance of the i-th level;

[0051] M4Lev[i] represents the 4th-order center distance of the i-th level.

[0052] The level value affected by MPI interference

[0053] Wherein, M represents the total number of levels of the received signal.

[0054] The module M6 simultaneously calibrates the SNR measurement value newSNR in the system = SNR-20*log10(avgMPI);

[0055] Wherein, SNR represents the uncalibrated SNR;

[0056] newSNR represents the SNR value that matches the received signal Ber after calibration with the MPI interference impact level value.

[0057] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the method for estimating the level of influence of MPI interference on optical communication signals are implemented.

[0058] An electronic device provided according to the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the method for estimating the level of MPI interference affecting an optical communication signal are implemented.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] 1. The present invention performs quantitative calculations on data distribution in different dimensions, quantitatively describes the degree of non-Gaussianity of the data, and then obtains the interference intensity value of the MPI interference on the data, thereby solving the problem of large SNR estimation deviation under MPI interference.

[0061] 2. The present invention directly quantifies the non-ideal factors on the data from the substantial statistical characteristic changes occurring in the data, has a certain adaptability, can be applied to arbitrary intensity modulation and direct detection optical communication systems, and also has a corresponding effect on the SNR estimation deviation under the influence of high and low temperatures.

[0062] 3. The present invention describes the changes in data to a certain extent through quantitative values, and can help determine the MPI interference intensity in a link by outputting an indicator of the MPI interference impact level in a link. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0064] Figure 1 The flowchart of the method for estimating the level of MPI interference affecting optical communication signals is shown in FIG. DETAILED DESCRIPTION

[0065] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0066] According to the present invention, a method for estimating the level of MPI interference of an optical communication signal can be applied to arbitrary intensity modulation and direct detection optical communication systems. Figure 1 For example, including:

[0067] Step S1: After the non-return-to-zero (NRZ) or pulse amplitude modulation (PAM4) optical signal passing through the optical fiber is converted into a digital signal by an analog-to-digital converter (ADC);

[0068] Step S2: Calculate the sampled digital signals at different levels independently to obtain the mean value of each level.

[0069]

[0070] Wherein, i is 0 to 1 in NRZ and 0 to 3 in PAM4, indicating the level of the received signal; N[i] is the number of data at the i-th level; rcvData is the received data, and rcvData[i][j] is the j-th data at the i-th level.

[0071] Different from the existing analog circuit estimation method of MPI, a digital circuit is used to perform statistical analysis on data sampling and collection. Starting from the unique statistical phenomena presented by the data after being affected by MPI, the statistical information of different dimensions is combined to separate the MPI eigenvalues ​​from the statistical differences between white noise and MPI interference.

[0072] Step S3: Calculate the second-order central moment at each level:

[0073]

[0074] Step S4: Calculate the 4th order central moment at each level:

[0075]

[0076] Compared with the fitting algorithm, which relies on a large number of test parameters to shape the data distribution curve, and cannot clearly distinguish between ordinary noise and MPI interference, it does not have a precise analysis and calculation target. It directly targets the short-tail distribution characteristics of data under MPI interference and uses the ratio parameter of the central moment of different orders, which has never been effectively applied to the estimation of MPI. The calculation of this parameter can eliminate the interference of ordinary noise, thereby solving the problem of accurately and quantitatively analyzing the intensity of the impact of MPI interference on data.

[0077] Step S5: By calculating the ratio of the second-order moment to the fourth-order moment, the influence of common noise on the calculation can be eliminated, and the MPI interference coefficient of the MPI interference intensity based on the statistical characteristics of the data at each level can be obtained:

[0078]

[0079] Step S6: Calculate the average of the MPI interference coefficients at all levels to obtain the level value avgMPI of the MPI interference impact on the received data:

[0080]

[0081] Wherein, M is the total number of levels of the received signal, M=2 for NRZ signal, and M=4 for PAM4 signal.

[0082] By performing quantitative calculations on data distribution in different dimensions and quantitatively describing the degree of data non-Gaussianity, the interference intensity value of the MPI interference on the data is obtained, which is used to judge the quality of the current received signal and calibrate the SNR measurement value in the system, newSNR = SNR-20*log10(avgMPI);

[0083] Among them, SNR is the uncalibrated SNR, and newSNR is the SNR value that matches the received signal Ber after calibration with the MPI interference impact level value.

[0084] The changes in device characteristics caused by high and low temperatures will cause non-ideal factors to affect the statistical characteristics of the data. Currently, there is no good theory to estimate and correct it. Therefore, we do not try to explain how this phenomenon occurs and affects devices and data from a theoretical perspective. We directly quantify the non-ideal factors in the data based on the substantial statistical changes in the data. The quantitative values ​​can describe the changes in the data to a certain extent and provide a reference value for operation and maintenance measurement.

[0085] Outputting the MPI interference impact level indicator in a link solves the problem that operation and maintenance personnel cannot judge the MPI interference intensity in the link. It also has a certain effect on other SNR estimation deviations under the influence of high and low temperatures.

[0086] The present invention also provides a system for estimating the level of impact of MPI interference on optical communication signals. The system for estimating the level of impact of MPI interference on optical communication signals can be implemented by executing the process steps of the method for estimating the level of impact of MPI interference on optical communication signals. That is, those skilled in the art can understand the method for estimating the level of impact of MPI interference on optical communication signals as a preferred implementation of the system for estimating the level of impact of MPI interference on optical communication signals.

[0087] According to the present invention, a system for estimating the level of MPI interference affecting an optical communication signal comprises:

[0088] Module M1: converts the optical signal passing through the optical fiber into a digital signal through photoelectric conversion;

[0089] Module M2: Calculate each digital signal independently to obtain the mean value of each level;

[0090] Module M3: Calculate the second-order central moment and the fourth-order central moment at each level;

[0091] Module M4: Calculate the ratio of the 2nd order central moment to the 4th order central moment to obtain the MPI interference coefficient based on the statistical characteristics of the data at each level;

[0092] Module M5: Calculate the mean value of the MPI interference coefficient to obtain the level of impact of MPI interference on the received data.

[0093] In more preferred examples, the optical signal in the module M1 is a non-return-to-zero code or a pulse amplitude modulated optical signal, which is sampled into a digital signal by an analog-to-digital converter.

[0094] The mean value of the level in the module M2

[0095] Wherein, i represents the level of the received signal;

[0096] N[i] represents the number of data on the i-th level;

[0097] rcvData[i][j] represents the j-th received data at the i-th level.

[0098] In more preferred embodiments, the second-order center distance is

[0099] The 4th order center distance is

[0100] Wherein, N[i] represents the number of data at the i-th level;

[0101] rcvData[i][j] represents the jth received data at the i-th level;

[0102] avgLev[i] represents the average value of the i-th level.

[0103] In more preferred embodiments, the MPI interference coefficient

[0104] Where M2Lev[i] represents the second-order center distance of the i-th level;

[0105] M4Lev[i] represents the 4th-order center distance of the i-th level.

[0106] The level value affected by MPI interference

[0107] Wherein, M represents the total number of levels of the received signal.

[0108] The module M6 simultaneously calibrates the SNR measurement value newSNR in the system = SNR-20*log10(avgMPI);

[0109] Wherein, SNR represents the uncalibrated SNR;

[0110] newSNR represents the SNR value that matches the received signal Ber after calibration with the MPI interference impact level value.

[0111] According to a computer-readable storage medium storing a computer program provided by the present invention, when the computer program is executed by a processor, the steps of the method for estimating the level of influence of MPI interference on optical communication signals are implemented.

[0112] An electronic device provided according to the present invention includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the steps of the method for estimating the level of MPI interference affecting an optical communication signal are implemented.

[0113] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0114] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for estimating the level of MPI interference of an optical communication signal, characterized in that: include: Step S1: The optical signal passing through the optical fiber is sampled into a digital signal after being photoelectrically converted; Step S2: Calculate each digital signal independently to obtain the mean value of each level; Step S3: Calculate the second-order central moment and the fourth-order central moment at each level; Step S4: Calculate the ratio of the 2nd order central moment to the 4th order central moment to obtain the MPI interference coefficient based on the statistical characteristics of the data at each level; Step S5: Calculate the mean value of the MPI interference coefficient to obtain the level of impact of the MPI interference on the received data.

2. The method for estimating the level of MPI interference affecting an optical communication signal according to claim 1, characterized in that: The optical signal in step S1 is a non-return-to-zero code or pulse amplitude modulated optical signal, which is sampled into a digital signal by an analog-to-digital converter; The mean value of the level in step S2 Where i represents the level of the received signal; N[i] represents the number of data on the i-th level; rcvData[i][j] represents the j-th received data at the i-th level.

3. The method for estimating the level of MPI interference affecting an optical communication signal according to claim 1, characterized in that: The second-order center distance is The 4th order center distance is Wherein, N[i] represents the number of data at the i-th level; rcvData[i][j] represents the jth received data at the i-th level; avgLev[i] represents the average value of the i-th level.

4. The method for estimating the level of MPI interference affecting an optical communication signal according to claim 1, characterized in that: The MPI interference coefficient Where M2Lev[i] represents the second-order center distance of the i-th level; M4Lev[i] represents the 4th order center distance of the i-th level; The level value affected by MPI interference Wherein, M represents the total number of levels of the received signal; In the step S5, the SNR measurement value newSNR in the system is calibrated simultaneously = SNR-20*log10(avgMPI); Wherein, SNR represents the uncalibrated SNR; newSNR represents the SNR value that matches the received signal Ber after calibration with the MPI interference impact level value.

5. A system for estimating the level of MPI interference of an optical communication signal, characterized in that: include: Module M1: converts the optical signal passing through the optical fiber into a digital signal through photoelectric conversion; Module M2: Calculate each digital signal independently to obtain the mean value of each level; Module M3: Calculate the second-order central moment and the fourth-order central moment at each level; Module M4: Calculate the ratio of the 2nd order central moment to the 4th order central moment to obtain the MPI interference coefficient based on the statistical characteristics of the data at each level; Module M5: Calculate the mean value of the MPI interference coefficient to obtain the level of impact of MPI interference on the received data.

6. The system for estimating the level of MPI interference affecting an optical communication signal according to claim 5, characterized in that: The optical signal in the module M1 is a non-return-to-zero code or pulse amplitude modulated optical signal, which is sampled into a digital signal by an analog-to-digital converter; The mean value of the level in the module M2 Where i represents the level of the received signal; N[i] represents the number of data on the i-th level; rcvData[i][j] represents the j-th received data at the i-th level.

7. The system for estimating the level of MPI interference of optical communication signals according to claim 5, characterized in that: The second-order center distance is The 4th order center distance is Wherein, N[i] represents the number of data at the i-th level; rcvData[i][j] represents the jth received data at the i-th level; avgLev[i] represents the average value of the i-th level.

8. The system for estimating the level of MPI interference of optical communication signals according to claim 5, characterized in that: The MPI interference coefficient Where M2Lev[i] represents the second-order center distance of the i-th level; M4Lev[i] represents the 4th order center distance of the i-th level; The level value affected by MPI interference Wherein, M represents the total number of levels of the received signal; The module M6 simultaneously calibrates the SNR measurement value newSNR in the system = SNR-20*log10(avgMPI); Wherein, SNR represents the uncalibrated SNR; newSNR represents the SNR value that matches the received signal Ber after calibration with the MPI interference impact level value.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for estimating the level of influence of MPI interference on an optical communication signal according to any one of claims 1 to 4 are implemented.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the computer program is executed by a processor, the steps of the method for estimating the level of influence of MPI interference on an optical communication signal according to any one of claims 1 to 4 are implemented.

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