Multipath interference detection method, optical receiving equipment, system and communication device

Abstract

The invention discloses a multipath interference detection method, an optical receiving device, a system and a communication device, and the method comprises the steps: determining sets of error signals of preset levels corresponding to a modulation format employed by an optical transmitting device based on original signals obtained after the conversion of the optical receiving device, and each preset level corresponds to one set; for at least two sets, calculating a mean value feature of the error signals in each set; a first index value characterizing the MPI intensity is calculated based on the mean feature. Therefore, only simple statistical calculation is needed, complex calculation is not needed, sending signals do not need to be changed, calculation resources and storage resources are reduced, and therefore real-time MPI detection which is low in calculation complexity, low in cost and compatible with service signals is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of optical communication technology, and in particular to a multi-path interference detection method, an optical receiving device, a system and a communication apparatus. BACKGROUND

[0002] In an optical communication system, multi-path interference (MPI) is a common source of signal impairment, which can significantly affect the transmission quality and stability of the system. Therefore, effective detection of MPI is crucial to ensure the reliable operation of optical communication. Currently, existing MPI detection techniques are either computationally complex and costly, or cannot be compatible with service transmission, making it difficult to meet the demand for simple and real-time monitoring of MPI in the operation and maintenance of optical communication systems. SUMMARY

[0003] The present application provides a multi-path interference detection method, an optical receiving device, a system and a communication apparatus, which is simple to calculate, low in cost and compatible with real-time monitoring of service transmission, meeting the demand for simple and real-time monitoring of MPI in the operation and maintenance of optical communication systems.

[0004] The present application adopts the following technical solutions: In a first aspect, the present application provides a multi-path interference detection method, the method comprising the following index calculation operations: based on the original signal obtained after conversion by an optical receiving device, determining a set of error signals corresponding to a preset level of a modulation format adopted by an optical transmitting device, each preset level corresponding to a set; for at least two sets, calculating the mean value feature of the error signals in each set; and based on the mean value feature, calculating a first index value representing the intensity of MPI.

[0005] In this way, by analyzing the error mean value corresponding to different signal levels, the intensity of MPI can be preliminarily estimated. This scheme only requires simple statistical calculation, does not require complex calculation, and does not require modification of the transmitted signal. The calculation resources and storage resources are reduced, thereby realizing real-time MPI detection with low calculation complexity, low cost and compatibility with service signals.

[0006] In combination with the first aspect, in some possible implementations, the index calculation operation further comprises: for at least two sets, calculating the distribution dispersion feature in each set; and based on the distribution dispersion feature, calculating a correction factor, multiplying the first index value by the correction factor to obtain a second index value.

[0007] In this way, by introducing the distribution dispersion feature of the error to calculate a correction factor, and using it to correct the first index value, a more accurate and reliable second index value can be obtained, which especially improves the problem that the first index value may not be accurate when MPI is weak.

[0008] In some possible implementation manners of the first aspect, the method further includes: triggering an alarm when the second index value exceeds a corresponding index threshold; wherein the index threshold is a strength threshold based on the MPI strength, and the mapping relationship between the MPI strength and the second index value is pre-calibrated.

[0009] In this way, the system can automatically and timely issue a warning when the MPI interference reaches a harmful level by judging and triggering the alarm based on the preset index threshold, so as to facilitate the operation and maintenance personnel to respond quickly and improve the maintainability and reliability of the system.

[0010] In some possible implementation manners of the first aspect, the method further includes: estimating the MPI strength based on the obtained second index value and based on the mapping relationship between the MPI strength and the second index value.

[0011] In this way, the MPI strength value can be inversely converted from the calculated abstract second index value by using the calibrated mapping relationship, so as to realize quantitative evaluation of the MPI interference degree and provide data support for accurate network diagnosis and optimization.

[0012] In some possible implementation manners of the first aspect, the method further includes: performing the index calculation operation to obtain a second index value corresponding to each known MPI strength under different known MPI strengths; and constructing the mapping relationship between the MPI strength and the second index value according to the plurality of known MPI strengths and the corresponding second index values.

[0013] In this way, the mapping relationship can be pre-established for different fiber link systems by testing and calibration under different known MPI strengths, so as to ensure the accuracy and adaptability of the present application in different actual application environments.

[0014] In some possible implementation manners of the first aspect, the first index value is calculated based on a mean value feature, including: calculating a first difference value of the mean value feature of the error signal between two sets corresponding to two preset levels with the same amplitude and opposite polarity, to eliminate a component of Gaussian white noise irrelevant to the level and a component dependent on the MPI strength in the second order in the error signal, and to retain a component dependent on the MPI strength in the first order; calculating a second difference value of the mean value feature of the error signal between two sets corresponding to two preset levels with different amplitudes, to eliminate the component of Gaussian white noise irrelevant to the level in the error signal, and to retain components dependent on the MPI strength in the first and second orders; calculating a third difference value based on the first difference value and the second difference value, to eliminate the component dependent on the MPI strength in the first order and retain only the component dependent on the MPI strength in the second order; and calculating the first index value based on a ratio of the third difference value to the first difference value.

[0015] Thus, by first using the same amplitude and opposite sign level pair to calculate the first difference value of the mean square mean, the same amplitude and opposite sign difference can effectively offset the Gaussian noise irrelevant to the level, so that the first difference value mainly reflects the linear influence of the MPI on the error energy, as a stable "reference quantity"; then using the different amplitude level pair to calculate the second difference value of the mean square mean, the different amplitude difference retains the linear and nonlinear (linear + quadratic) effects of the MPI, providing information sources for subsequent separation of the quadratic term; by combining the first difference value and the second difference value, the linear correlation component is removed, and the third difference value containing only the quadratic correlation component is obtained, the third difference value is constructed to "remove the linear term", and finally the first index value is obtained by taking the ratio of the first difference value to the third difference value, which is equivalent to normalizing the quadratic term with the linear reference.

[0016] In combination with the first aspect, the mean value feature is the mean square mean. The first difference value is calculated as follows: ff1 = f2-f1. The second difference value is calculated as follows: ff2 =f1'-f0. The third difference value is calculated as follows: ff3 =ff1-K1 ff2. The first index value is calculated as follows: Amp_mpi = K2 ff3 / ff1. Wherein, ff1 represents the first difference value, ff2 represents the second difference value, ff3 represents the third difference value, Amp_mpi represents the first index value, f1 and f2 are the mean square means of the error signals of two sets corresponding to the preset levels with the same amplitude and opposite polarity, f1' and f0 are the mean square means of the error signals of two sets corresponding to the preset levels with different amplitudes, f1' corresponds to the same or different preset level as f1, the preset level corresponding to any of f1, f2, f1' is the same as any preset level corresponding to the calculation of the correction factor, K1 and K2 are coefficients related to the preset levels corresponding to f1, f2, f1'.

[0017] Thus, the mean square mean is used as the basis for statistics, the contrast of the MPI dependent term is improved through difference combination and ratio form, and the estimation stability is enhanced.

[0018] In combination with the first aspect, in some possible implementations, the modulation format is N-order pulse amplitude modulation PAM-N, N>2, the preset level corresponding to f1' is the same preset level with the smallest amplitude among the N preset levels, and the preset level corresponding to f0 is one preset level with the largest amplitude among the N preset levels.

[0019] In conjunction with the first aspect, for example, the modulation format is fourth-order pulse amplitude modulation (PAM-4), where the preset level corresponding to f1' and f1 is the preset level with the smallest amplitude among the four preset levels, and the preset level corresponding to f0 is the preset level with the largest amplitude among the four preset levels.

[0020] In this way, it can be directly applied to common PAM-4 scenarios. By selecting the level pair with the largest amplitude and opposite polarity in the variance ratio of the correction factor, the distribution changes caused by MPI can be distinguished to the greatest extent, making the correction amount more reliable.

[0021] In conjunction with the first aspect, in some possible implementations, the correction factor is calculated based on the distribution dispersion characteristics, including: for two sets corresponding to two preset levels with the same amplitude and opposite polarity, the correction factor is calculated based on the ratio of the distribution dispersion characteristics of the error signals between the sets.

[0022] In this way, using the same amplitude but different signs allows components that are independent of the level, such as the background Gaussian white noise, to be better canceled out, while only the distribution differences related to MPI are amplified.

[0023] In conjunction with the first aspect, for example, the distribution dispersion characteristic is variance, and the correction factor is calculated as follows: Comp=v3 / v0-1, where v3 and v0 are the variances of two preset levels with the same amplitude and opposite polarities.

[0024] Using variance directly is simple to calculate and suitable for real-time implementation. Subtracting 1 from the ratio makes Comp approach 0. Therefore, even if the first index value calculated based on the mean characteristic may be distorted near the zero point when MPI approaches zero (for example, when the third difference and the first difference approach zero at the same time, the ratio of the two will approach 1, resulting in distorted results), this application can also use Comp to pull the second index value to 0, ensuring the reliability of the second index value calculated when MPI is very weak.

[0025] In conjunction with the first aspect, for example, the modulation format is N-order pulse amplitude modulation (PAM-N), where N > 2. The preset level corresponding to the distribution dispersion characteristics when calculating the correction factor is the two preset levels with the largest amplitude and opposite polarities among the N preset levels.

[0026] In conjunction with the first aspect, for example, the mean feature is the mean squared mean. Calculating the mean feature of the error signals within each set includes: squaring each error signal within the set to obtain the squared error value, and then summing all the squared error values ​​and averaging them to obtain the mean squared mean of the set.

[0027] In conjunction with the first aspect, for example, the distribution dispersion feature is variance. Calculating the distribution dispersion feature within each set includes: calculating the mean of all error signals within each set, calculating the deviation of each error signal relative to the mean, squaring all deviations to obtain the squared deviation value, and then summing all the squared deviation values ​​and averaging them to obtain the variance of the set.

[0028] In conjunction with the first aspect, in some possible implementations, based on the original signal obtained after conversion by the optical receiving device, an error signal corresponding to a preset level of the optical transmitting device is determined, and all error signals of the same preset level are treated as a set. This includes: acquiring the original signal obtained after conversion by the optical receiving device; determining the target signal based on all preset levels corresponding to the optical transmitting device; calculating the error signal between the original signal and the target signal; and classifying the error signal into the set of preset levels to which the target signal belongs.

[0029] Secondly, this application provides an optical receiving device for performing the method in the first aspect or any optional implementation of the first aspect. The optical receiving device may include modules for performing the method in the first aspect or any optional implementation of the first aspect. For example, the optical receiving device includes: The error acquisition module is used to determine a set of error signals with preset levels corresponding to the modulation format adopted by the optical transmitting device based on the original signal obtained after conversion by the optical receiving device. Each preset level corresponds to one set. The mean feature calculation module is used to calculate the mean feature of the error signal in each of at least two sets. The first index value calculation module is used to calculate the first index value representing the MPI intensity based on the mean characteristic.

[0030] Thirdly, this application also provides an optical communication system, including an optical receiving device, an optical transmitting device, and an optical fiber link; wherein, Optical transmitting equipment is used to send optical signals to optical receiving equipment via an optical fiber link; An optical receiving device for performing the method as described in the first aspect or any possible implementation thereof.

[0031] Fourthly, this application also provides a communication device, including at least one processor and a memory; At least one processor is coupled to memory and a communication interface; The memory is used to store instructions, the processor is used to execute instructions, and the communication interface is used to communicate with other communication devices under the control of at least one processor. When executed by at least one processor, the instruction causes at least one processor to perform the method of the first aspect or any possible implementation thereof.

[0032] Fifthly, this application also provides a chip system including a processor and a memory, the memory and the processor being interconnected by a circuit, the memory storing computer programs or instructions, and the processor executing the computer programs or instructions to implement the method in the first aspect or any possible implementation of the first aspect.

[0033] Sixthly, this application also provides a computer-readable storage medium, characterized in that the storage medium stores a computer program or instructions, which, when executed by a processor, implement the method in the first aspect or any possible implementation of the first aspect.

[0034] In a seventh aspect, this application also provides a computer program product, which includes a computer program or instructions that, when executed by a processor, implement the method in the first aspect or any possible implementation of the first aspect.

[0035] The beneficial effects of aspects two through seven above can be referred to in the first aspect or any possible implementation of the first aspect, and will not be elaborated here. Based on the implementations provided in the above aspects, this application can also be further combined to provide more implementations.

[0036] Other advantages, objectives and features of this application will be partly apparent from the description below, and partly understood by those skilled in the art through study and practice of this application. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0038] Figure 1 This is a schematic diagram of the structure of an optical communication system provided in an embodiment of this application; Figure 2 This is one of the flowcharts of the multipath interference detection method provided in the embodiments of this application; Figure 3 This is the second flowchart of the multipath interference detection method provided in the embodiments of this application; Figure 4 This is a schematic diagram of the sub-steps of step S201; Figure 5 This is a schematic diagram of the sub-steps of step S205; Figure 6 This is the third flowchart of the multipath interference detection method provided in the embodiments of this application; Figure 7 This is a flowchart illustrating the mapping relationship between MPI intensity and the second index value. Figure 8 This is the fourth flowchart of the multipath interference detection method provided in the embodiments of this application; Figure 9a This is the time-domain distribution diagram of the original signal output by the equalizer; Figure 9b It is a statistical histogram of the original signal output by the equalizer; Figure 10a It is a statistical histogram of the original signal output by the equalizer without MPI; Figure 10b This is a statistical histogram of the raw signal output by the equalizer at an MPI intensity of -30.5dB. Figure 10c This is a statistical histogram of the original signal output by the equalizer at an MPI of -24.4 dB. Figure 11 This is a schematic diagram showing the mapping relationship between MPI intensity and the second index value MPIratio when Rop = -4dBm; Figure 12a This is one of the structural schematic diagrams of an optical receiving device; Figure 12b This is the second schematic diagram of the structure of an optical receiving device; Figure 12c This is the third schematic diagram of the optical receiving device; Figure 12d This is the fourth schematic diagram of the structure of an optical receiving device; Figure 12e This is the fifth schematic diagram of the structure of an optical receiving device; Figure 13 This is a schematic diagram of the communication device of this application. Detailed Implementation

[0039] It should be noted that, in this application, the terms "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0040] The term "and / or" as used in this application includes any and all combinations of one or more of the associated listed items. In this application, "at least one" means one or more, and "more than one" means two or more. The terms "first," "second," and other ordinal terms used in this application may be used to describe various constituent elements, but these constituent elements are not limited by these terms. The purpose of using these terms is solely to distinguish one constituent element from others and should not be construed as indicating or implying relative importance. For example, without departing from the scope of this application, a first constituent element may be named a second constituent element, and similarly, a second constituent element may be named a first constituent element.

[0041] Before introducing the embodiments of this application, the technical terms involved in this application will be introduced first.

[0042] Multipath interference (MPI) refers to the phenomenon in optical communication systems where reflections between fiber optic connectors, joints, or components cause optical signals to propagate along multiple paths during transmission. These signal copies arriving at the receiver at different times superimpose with the main signal, creating interference and introducing signal strength-related noise that degrades signal quality and affects system transmission performance.

[0043] Modulation format: refers to the encoding rules used to carry digital information onto an optical carrier. This application's embodiments particularly relate to the PAM-N (Pulse Amplitude Modulation-N) format, where N represents the number of different signal levels; for example, PAM-4 has four different levels.

[0044] Error signal: refers to the difference between the actual received signal (original signal) before passing through the decision unit at the receiver and the ideal signal (target signal) recovered after passing through the decision unit. This signal contains noise and distortion information introduced by the channel.

[0045] Calibration: This refers to the process of establishing the correspondence between MPI intensity and the final detection index (such as the second index value) proposed in this invention through experimental means before the actual application of this method. This process ensures the accuracy and reliability of the monitoring results.

[0046] Before introducing the embodiments of this application, the relevant technologies involved in this application will be introduced first.

[0047] In optical communication systems, multipath interference (MPI) is a common source of signal impairment, significantly affecting the system's transmission quality and stability. Therefore, effective MPI detection is crucial for ensuring the reliable operation of optical communication. Currently, existing MPI detection technologies mainly employ two approaches: The first technique is based on cross-correlation calculations, which estimates the MPI intensity by calculating the cross-correlation between the error signal and the target signal. However, this approach requires complex mathematical operations, placing high demands on hardware storage resources and computing power, resulting in high implementation costs and making it difficult to apply to real-time monitoring scenarios that require low cost and low power consumption. The second technique involves inserting a specific zero-power gap into the transmitted signal and evaluating the MPI by comparing the power difference inside and outside the gap. The drawback of this method is that it alters the normal transmitted signal format, making it incompatible with actual service data transmission and thus unable to achieve real-time monitoring without interrupting services.

[0048] In summary, the existing technologies are either computationally complex and costly, or incompatible with service transmission, making it difficult to meet the need for simple, real-time monitoring of MPI in the operation and maintenance of optical communication systems. Therefore, this application provides a multipath interference detection method, an optical receiving device, a system, and a communication apparatus, offering a computationally simple, low-cost, and service-transmission-compatible real-time monitoring solution that meets the needs of simple, real-time monitoring of MPI in the operation and maintenance of optical communication systems.

[0049] The following first describes one or more exemplary operating environments to make it easier and clearer to understand the role and intent of the various implementation methods in the embodiments of this application.

[0050] The method provided in this application embodiment can be applied to an optical communication system. The optical communication system includes at least one optical transmitting device, at least one optical receiving device, and an optical fiber link. The optical fiber link includes multiple optical fiber segments and multiple optical fiber connectors. The optical fiber connectors are used to connect the optical transmitting device, the optical receiving device, and the optical fibers. Figure 1 The optical communication system 100 includes an optical transmitting device 101, an optical receiving device 103, and an optical fiber link 102. The optical fiber link 102 includes multiple optical fiber segments AN and multiple optical fiber connectors AN. Optical fiber connector A connects the optical transmitting device 101 and the first optical fiber segment A, optical fiber connector B connects the first optical fiber segment A and the second optical fiber segment B, and so on. Optical fiber connector N connects the last optical fiber segment N and the optical receiving device 103.

[0051] In optical communication systems, optical transmitting equipment modulates information onto an optical signal according to a predetermined modulation format and transmits this optical signal to an optical receiving equipment via an optical fiber link. The optical receiving equipment receives the optical signal and demodulates it back into the original information. It should be noted that the optical receiving equipment and the optical transmitting equipment are collectively referred to as optical network terminals (ONTs). An ONT can possess both optical receiving and optical transmitting capabilities. For a single instance of transmitting and receiving optical signals, the optical network device transmitting the optical signal is the optical transmitting equipment, and the optical network device receiving the optical signal is the optical receiving equipment. (Reference) Figure 1 The optical transmitting device 101 modulates information onto an optical signal and transmits it sequentially through fiber optic connectors A, B, ... N-1, N, and N to the optical receiving device 103. The receiving device 103 receives the optical signal and demodulates the original information. Reflection often occurs when the optical signal passes through fiber optic connectors. When some fiber optic connectors are contaminated or loose, excessive reflection can cause the optical signal to reflect back and forth between the connectors. Even-numbered reflections of the optical signal will superimpose on the directly transmitted optical signal, generating MPI noise that affects the directly transmitted signal. This noise leads to bit errors and performance degradation, resulting in a poor user experience. Figure 1 As shown, after the optical transmitting device 101 transmits optical signal X1 to the optical receiving device 103 via the optical fiber link 102, a portion of the optical signal is directly transmitted from the optical transmitting device 101 to the optical receiving device 103; the other portion of the optical signal is reflected in the optical fiber link 102, resulting in a reflected optical signal X2. The reflected optical signal X2 is superimposed on the optical signal X1, forming MPI noise on the optical signal X1. This application aims to perform simple, real-time monitoring of MPI.

[0052] It should be noted that the method in this application is for an independent path. If a system contains multiple paths, the method of this application can be implemented separately for each path. For example, this application can be used in a direct-modulation and direct-detection optical communication system.

[0053] The technical solutions of this application are described below through several embodiments. It should be understood that these embodiments can be implemented in many different forms and should not be construed as being limited to the embodiments set forth herein.

[0054] refer to Figure 2 Firstly, embodiments of this application provide a multipath interferometry detection method, wherein the subject executing the method may be... Figure 1 The optical receiving device mentioned can also be other devices that can obtain the data required by the method from the optical receiving device. The method in this application embodiment includes the following index calculation operations: S201: Based on the original signal obtained after conversion by the optical receiving device, determine the set of error signals corresponding to the preset level of the modulation format adopted by the optical transmitting device, with each preset level corresponding to a set; S203: For at least two sets, calculate the mean characteristic of the error signal within each set; S205: The first index value representing the intensity of MPI is calculated based on the mean characteristic.

[0055] Thus, by analyzing the mean error corresponding to different signal levels, the strength of MPI can be preliminarily estimated. This scheme only requires simple statistical calculations, without complex calculations or modifications to the transmitted signal, reducing computational and storage resources. As a result, it achieves real-time MPI detection with low computational complexity, low cost, and compatibility with business signals.

[0056] refer to Figure 3 Optionally, in this application, the indicator calculation operation may also include: S301: For at least two sets, calculate the distribution dispersion characteristics within each set; S303: Calculate the correction factor based on the distribution dispersion characteristics; S305: Multiply the first index value by the correction factor to obtain the second index value.

[0057] Thus, by introducing the dispersion characteristics of the error distribution to calculate a correction factor and using it to correct the first index value, a more accurate and reliable second index value can be obtained. This particularly improves the problem that the first index value may be inaccurate when the MPI is very weak.

[0058] The following combination Figures 2-11 The steps in steps S201-S205 and other optional steps are described in detail.

[0059] Regarding step S201 Based on the original signal obtained after conversion by the optical receiving device, a set of error signals corresponding to the preset level of the modulation format adopted by the optical transmitting device is determined, and each preset level corresponds to a set.

[0060] Preset level corresponding to the modulation format: In modulation formats such as PAM-N, this is used to represent a specific signal state of a digital symbol. Each level corresponds to a nominal amplitude and a polarity. For ease of description, in the embodiments of this application, algebraic values ​​(such as -3, -1, +1, +3 in PAM-4) may be used to refer to each level, where the absolute value of the value represents the amplitude of the level, and the sign represents its polarity. For example, "the level with the largest amplitude" refers to the level with the largest absolute value.

[0061] An optical transmitting device can modulate information onto an optical signal and transmit that optical signal to an optical receiving device via an optical fiber link. For example, the optical transmitting device converts the information into an electrical signal according to a predetermined modulation format, then performs electro-optical conversion to obtain an optical signal, and finally transmits the optical signal over the optical fiber link. The modulation format is N-order pulse amplitude modulation (PAM-N), where N > 2, corresponding to N preset levels, each preset level corresponding to one n bits of data (N = ...). For example, PAM-4 uses 2 bits, PAM-8 uses 3 bits, and so on. Converting information into an electrical signal according to a predetermined modulation format maps the information to a preset level that matches its value. For instance, in fourth-order pulse amplitude modulation (PAM-4), the four preset levels are -3, -1, +1, and +3, each corresponding to a 2-bit data. For example, -3, -1, +1, and +3 correspond to 00, 01, 10, and 11 respectively. Therefore: if the information to be transmitted is binary data "00", it is mapped to level "-3"; "01" is mapped to "-1"; "10" is mapped to "+1"; and "11" is mapped to "+3". The mapped levels are then converted to optical signals via electro-optical conversion and sent to the fiber optic link. When the optical receiving device receives the optical signal, it can convert it to an electrical signal via photoelectric conversion, which serves as the original signal. There is an error between the original signal and the level initially mapped by the optical transmitting device; this error is represented by the error signal mentioned in this application. Step S201 is to determine the set of error signals for each preset level based on the original signal.

[0062] refer to Figure 4 In some embodiments, step S201 involves determining an error signal at a preset level corresponding to the optical transmitting device based on the original signal obtained after conversion by the optical receiving device, including steps S401-S407: S401: Acquire the original signal obtained after conversion by the optical receiving device; In some possible implementations, the optical receiving device can perform equalization processing on the electrical signal using an optical digital signal processor (oDSP) to obtain the original signal, which can be stored in the RAM of the oDSP. In this step, this part of the original signal can be read directly from the RAM.

[0063] For example, the original signal is generally a series, denoted by P, which represents a series of original signals obtained by the optical receiving device over a period of time after conversion. This is actually a sequence of level values ​​(after equalization), which can be represented as: P = {P[0], P[1], P[2], ..., P[n-1]}, where P[i] (i = 0, 1, 2, ..., n) represents a level value of P (i is the index). For example, if n = 1000, then P is a sequence with 1000 level values.

[0064] S403: Based on all preset levels corresponding to the optical transmitting device, the original signal is judged to obtain the target signal; The target signal can be understood as the preset level that the original signal should theoretically correspond to on the optical transmitting device side. In some embodiments, the preset level that is closest to the original signal among all the preset levels configured by the optical transmitting device can be determined as the target signal corresponding to the original signal. Since the optical receiving device obtains a series of original signals, denoted as P, the result after the decision is also a series of target signals, denoted as P'={P[0]',P[1]',P[2]'}. As mentioned above, when an optical transmitting device transmits information, it maps the information to one of N preset adjustment levels. For example, the modulation format is fourth-order pulse amplitude modulation (PAM-4), and the four preset levels are -3, -1, +1, and +3. Assuming the information to be transmitted is binary data "00", "01", "10", and "11", the corresponding levels on the optical transmitting device side are "-3", "-1", "+1", and "+3". However, due to interference from noise in the optical fiber link (such as MPI noise, RIN noise, etc.), the original signal obtained by the optical receiving device is not "-3", "-1", "+1", and "+3". For example, it may be P = {"-3.2", "-0.8", "0.4", "3.9"}. Therefore, in this embodiment, it is necessary to determine the original signal to restore it to the correct level and obtain the target signal. For example, "-3.2" is closest to "-3", "-0.8" is closest to "-1", "0.4" is closest to "+1", and "3.9" is closest to "+3". Therefore, the target signals obtained by judging "-3.2", "-0.8", "0.4", and "3.9" are P'={"-3", "-1", "+1", and "+3"} respectively. It is understood that the specific method of judgment here is only for illustrative purposes; other methods may be used in some possible implementations, and this is not limited here.

[0065] S405: Calculate the error signal between the original signal and the target signal; In some embodiments, the error signal may be specifically the original signal minus the target signal; in other embodiments, the error signal may also be the target signal minus the original signal.

[0066] As mentioned earlier, both the original signal and the target signal are a series of level sequences. Therefore, the resulting error signal is also a sequence, denoted as err. Then: err={P[0]-P[0]',P[1]-P[1]',P[2]-P[2]',…,P[n-1]-P[n-1]'}.

[0067] S407: Divide the error signal into the set of preset levels to which the target signal belongs.

[0068] Each preset level corresponds to a set for placing error signals. For example, when the modulation format is N-order pulse amplitude modulation (PAM-N), there are N sets, assuming these N sets are Err(0), Err(1), ..., Err(N-1). This means that the n elements in err in step S405 are to be assigned to these N sets.

[0069] As mentioned earlier, the target signal can be understood as the preset level that the original signal should theoretically correspond to on the optical transmitting device side. Therefore, when the target signal is determined, its preset level can be determined. Since the error signal is obtained from the target signal, the error signal can be directly placed into the set corresponding to the preset level of the target signal. For example, for an original signal, if it is found in S403 that a certain original signal is closest to the k-th preset level during the decision, then in addition to determining that the target signal is the i-th preset level in S403, in S407, the error signal calculated in step S405 will also be placed into the set corresponding to the i-th preset level, that is, into Err(k). Taking the PAM-4 example mentioned earlier, the four preset levels are -3, -1, +1, and +3, corresponding to the sets Err(0), Err(1), Err(2), and Err(3), respectively: the original signal is "-3.2", the target signal obtained by the decision is "-3", and the error signal is "-0.2", which will be placed in the set Err(0) corresponding to "-3"; the original signal is "-0.8", the target signal obtained by the decision is "-1", and the error signal is... The error signal “0.2” will be placed in the set Err(1) corresponding to “-1”; the original signal is “0.4”, the target signal obtained by the decision is “+1”, the error signal is “0.6”, the error signal “0.6” will be placed in the set Err(2) corresponding to “+1”; the original signal is “3.9”, the target signal obtained by the decision is “+3”, and the resulting error signal is “0.9”, the error signal “0.9” will be placed in the set Err(3) corresponding to “+3”.

[0070] It is understandable that the error signals mentioned above include various noises in the system, including MPI noise, relative intensity noise (RIN), Gaussian white noise, etc., which are of interest in this application.

[0071] Regarding step S203 For at least two sets, calculate the mean characteristic of the error signal within each set; Mean value characteristics refer to the characteristic values ​​obtained by statistically averaging the error signal. In this application, the mean squared mean is preferably used, that is, the error signal is first squared and then the average value is calculated, which helps to highlight the power information of the noise.

[0072] For example, calculating the mean characteristic of the error signals within each set includes: squaring each error signal within the set to obtain the squared error value, and then summing all the squared error values ​​and averaging them to obtain the mean square of the set.

[0073] Taking the set Err(i) as an example, assuming that the set consists of M error signals err_i1, err_i2, ..., err_iM, the mean square of the M error signals in the set Err(i) is calculated as follows: (1); Regarding step S301 For at least two sets, calculate the distribution dispersion characteristics within each set; Distribution dispersion characteristics are statistics used to measure the degree to which an error signal fluctuates or disperses around its mean. In this application, variance is preferably used, which calculates the average of the squares of the differences between each error signal and the average error, and can effectively characterize the intensity of noise fluctuations.

[0074] For example, calculating the distribution dispersion characteristics within each set includes: calculating the mean of all error signals within each set, calculating the deviation of each error signal relative to the mean, squaring all deviations to obtain the squared deviation value, and then summing all the squared deviation values ​​and averaging them to obtain the variance of the set.

[0075] Taking the set Err(i) as an example, assuming that the set consists of M error signals err_i1, err_i2, ..., err_iM, the variance of the M error signals in the set Err(i) is calculated as follows: Vi: (2); (3); Regarding step S205 The first index value representing the intensity of MPI is calculated based on the mean characteristic.

[0076] refer to Figure 5 In some embodiments, the first index value is calculated based on the mean characteristic, including S501-S507: S501: For two preset levels with the same amplitude and opposite polarity, calculate the first difference of the mean characteristics of the error signal between the sets to eliminate the Gaussian white noise component that is independent of the level and the component that is quadratically dependent on the MPI intensity in the error signal, and retain the component that is linearly dependent on the MPI intensity. In some embodiments, the mean feature is the mean squared mean.

[0077] MPI noise exhibits a certain intensity-dependent characteristic in causing damage, thus allowing for approximate quantization of the noise based on this characteristic. For example, assuming the i-th preset level is G, which includes both the level amplitude and polarity, the mean square value corresponding to the set of G is: (4); Where 'a' represents the intensity of MPI, This represents intensity-dependent noise, which is a component that is linearly dependent on the MPI intensity. The system is Gaussian white noise. Taking PAM-4 as an example, assuming G is its first modulation level -3, i.e. G=-3, then substituting G into (4) yields the mean square value corresponding to the first preset level -3 in the case of PAM-4: (5); For the set corresponding to two preset levels with the same amplitude and opposite polarity, assuming that the two preset levels are +B and -B respectively, substituting G into equation (4), we can obtain the mean square values ​​of +B and -B respectively: (6); (7); Subtracting (7) from equation (6) yields the difference between the mean square values ​​of +B and -B, i.e., the first difference ff1, as follows: (8); It can be seen that calculating ff1 can eliminate the quadratic terms corresponding to Gaussian white noise that is independent of the level in the error signal. And components that are quadratically dependent on MPI intensity Only the component a, which is linearly dependent on the MPI intensity, is retained.

[0078] Among them, the specific values ​​of the mean square average on the left side of equations (6), (7), and (8), namely the specific values ​​of the mean square average of +B and -B, f1 and f2, are actually obtained through equation (1), that is: ff1=f2-f1. f1 and f2 are the mean square average of the error signals of the sets corresponding to two preset levels with the same amplitude and opposite polarity, obtained through equation (1).

[0079] In some embodiments, the preset level corresponding to f1 is the preset level with the smallest amplitude among the N preset levels of PAM-N.

[0080] S503: For two sets corresponding to two preset levels with different amplitudes, calculate the second difference of the mean characteristics of the error signal between the sets, eliminate the Gaussian white noise component in the error signal that is independent of the level, and retain the components that are dependent on the MPI intensity in the first and second order. For the set corresponding to two preset levels with different amplitudes, assuming that the two preset levels are -C and -D respectively, substituting G into equation (4), we can obtain the mean square values ​​of -C and -D respectively: (9); (10); It is understandable that the specific values ​​of the mean square on the left side of equations (9) and (10), namely the specific values ​​of the mean square of -C and -D, are actually obtained through equation (1).

[0081] Subtracting (10) from equation (9) yields the difference between the mean square values ​​of -C and -D, i.e., the second difference ff2, as follows: (11); It can be seen that calculating ff2 can eliminate the quadratic term of Gaussian white noise in the error signal that is independent of the level. And retain the component that is quadratically dependent on the MPI intensity. , and component a which is linearly dependent on MPI intensity.

[0082] Among them, the specific values ​​of the mean square average on the left side of equations (9), (10), and (11), namely the specific values ​​of the mean square average of -C and -D, f1' and f0, are actually obtained through equation (1), i.e., ff2 = f1' - f0. f1' and f0 are the mean square average values ​​of the error signals of the two sets corresponding to two preset levels with different amplitudes, obtained through equation (1). Here, f1' and f1 can be the same or different preset levels.

[0083] In some embodiments, the preset level corresponding to f1' and f1 is the same preset level with the smallest amplitude among the N preset levels of PAM-N, and the preset level corresponding to f0 is the preset level with the largest amplitude among the N preset levels.

[0084] S505: The third difference is calculated based on the first difference and the second difference, so that the components that are linearly dependent on the MPI intensity are eliminated and only the components that are quadratically dependent on the MPI intensity are retained. For example, the third difference ff3 is calculated based on the first difference and the second difference, specifically based on the following formula: ff3 = ff1 - K1 ff2 (12); K1 is a coefficient related to the preset levels corresponding to f1, f2, and f1', with the aim of eliminating B from the result obtained based on (12). Z a The term (Z+Z1). Combining the previous equations (8) and (11), we can see that if we want to eliminate B... Z a For the term (Z+Z1), we only need to design a coefficient K1 such that 4B in equation (8) is... Z a (Z+Z1) and 2 in equation (11) (DC) Z As long as a(Z+Z1) is equal, that is, 4B Z a (Z+Z1)=2 (DC) Z a(Z+Z1), from which we obtain: K1 = 2B / (DC) (13); Substituting equations (13), (8), and (11) into equation (12), we obtain: (14); It is evident that the calculated ff3 only retains the components that exhibit a quadratic dependence on the MPI intensity. .

[0085] S507: The first index value is calculated based on the ratio of the third difference to the first difference.

[0086] For example, the ratio of the third difference to the first difference can be multiplied by a coefficient to obtain the first index value, Amp_mpi: Amp_mpi = K2 ff3 / ff1 (15); K2 is a coefficient related to the preset levels corresponding to f1, f2, and f1', with the aim of correcting the coefficients based on (15) to be as close to 1 as possible. For example, substituting equations (8) and (14) into (15) yields: Amp_mpi =K2 (4B) (Z+Z1) )(16); The purpose of K2 is to make K2 in (16) / 4B=1, that is: K2=4B / (17); Substituting equations (17), (8), and (14) into equation (15), we obtain: Amp_mpi= (Z+Z1)(18); It can be seen that the calculated Amp_mpi and It is positively correlated and can characterize the MPI intensity.

[0087] Thus, this embodiment first calculates the first difference in the mean squared values ​​using pairs of levels with the same amplitude but different signs. This difference effectively cancels Gaussian noise unrelated to the level, allowing the first difference to primarily reflect the linear influence of MPI on error energy, serving as a stable "benchmark quantity." Then, it calculates the second difference in the mean squared values ​​using pairs of levels with different amplitudes. These differences preserve both linear and nonlinear (first-order + second-order) effects of MPI, providing information for subsequent separation of the second-order term. By combining the first and second differences, the first-order correlation component is eliminated, resulting in a third difference containing only the second-order correlation component. This third difference is used to "eliminate the first-order term." Finally, the ratio of the third difference to the first difference is taken, which is equivalent to normalizing the second-order term using a linear benchmark, ultimately yielding the first index value. Furthermore, specifically, the mean squared value is used as the basic statistical basis. Through difference combinations and ratios, the contrast of the MPI dependency term is improved, enhancing the estimation stability.

[0088] In some embodiments, the modulation format is fourth-order pulse amplitude modulation (PAM-4), and the preset level corresponding to f1' and f1 is the preset level with the smallest amplitude among the four preset levels, while the preset level corresponding to f0 is the preset level with the largest amplitude among the four preset levels.

[0089] For example, the four preset levels are "-3", "-1", "+1", and "+3" levels respectively; f1' and f1 represent the mean square value of the set corresponding to the "-1" level; f0 represents the mean square value of the set corresponding to the "-3" level; f2 represents the mean square value of the set corresponding to the "+1" level; K1 is 1, and K2 is 1 / 2.

[0090] Regarding step S303 Calculate the correction factor based on the distribution dispersion characteristics.

[0091] Since when MPI is very small, the numerator and denominator of the ratio corresponding to the first index both tend to 0, so the calculated first index may actually be close to 1. Step S203 is to correct this situation.

[0092] The correction factor is calculated based on the distribution dispersion characteristics, including: for two sets corresponding to two preset levels with the same amplitude and opposite polarity, the correction factor is calculated based on the ratio of the distribution dispersion characteristics of the error signals between the sets.

[0093] For example, the correction factor is calculated as follows: Comp=v3 / v0-1(19) Wherein, v3 and v0 are the variances of two preset levels with the same amplitude but opposite polarities.

[0094] In some embodiments, the modulation format is N-order pulse amplitude modulation (PAM-N), where N > 2. The preset levels corresponding to the distribution dispersion characteristics v3 and v0 when calculating the correction factor are the two preset levels with the largest amplitude and opposite polarities among the N preset levels. The preset level corresponding to any one of f1, f2, and f1' when calculating the first index value is the same as any preset level corresponding to the calculation of the correction factor.

[0095] For example, the modulation format is fourth-order pulse amplitude modulation (PAM-4), and the four preset levels are "-3", "-1", "+1", and "+3" levels respectively; v3 represents the distribution dispersion characteristics of the set corresponding to the "+3" level, and v0 represents the distribution dispersion characteristics of the set corresponding to the "-3" level.

[0096] like Figure 9a and Figure 9b As shown, Figure 9a This is a time-domain distribution diagram of the original signal output by the equalizer (FFE). The horizontal axis represents time, and the vertical axis represents the level. Each point in the diagram represents the original signal before a decision. This diagram intuitively reflects the real-time interference pattern of MPI noise on each signal in the time domain. As can be seen, with the influence of MPI, the signal points at each level are no longer stably clustered on the ideal level line, but rather spread in the vertical direction. Figure 9b This is a statistical histogram of the raw signal output by the equalizer (FFE), with the horizontal axis representing the level and the vertical axis representing the frequency of occurrence. This graph reveals the impact of MPI noise on the overall signal distribution from a statistical perspective. The ratio v3 / v0 can be intuitively understood geometrically as the relative difference in the height of the histogram vertices corresponding to the preset levels v3 and v0.

[0097] As the MPI intensity increases, the intensity-related distribution of the signal and noise can be compared through... Figure 10a , 10b The 10c embodiment, among which, Figure 10a , 10b Figures 1 and 10c are statistical histograms of the original signals output by the equalizer when there is no MPI, and when the MPI intensity is -30.5dB and -24.4dB, respectively. It can be seen that the intensity correlation distribution corresponding to different MPI intensities gradually becomes more obvious: when MPI is absent, the distributions of the two levels are symmetrical, with similar peak heights, and v3 / v0 approaches 1; when MPI is increased, the distribution of the +3 level broadens more drastically, and its peak height is significantly lower than that of the -3 level, resulting in an increase in the v3 / v0 ratio. Therefore, Comp = v3 / v0 - 1 essentially captures and quantifies this asymmetry caused by MPI from the statistical distribution pattern.

[0098] Regarding step S305The second index value is obtained by multiplying the first index value by the correction factor.

[0099] After obtaining the correction factor, the first index value is multiplied by the correction factor to obtain the second index value. The formula for calculating the final second index value MPIratio is as follows: MPIratio=Amp_mpi Comp= K2 (ff3 / ff1) (v3 / v0-1)(20); Since the correction factor (v3 / v0 - 1) tends to 0 when MPI is very weak, even if the first index value calculated based on the mean characteristic may be distorted near the zero point when MPI approaches zero (for example, when the third difference and the first difference approach zero at the same time, the ratio of the two will approach 1, resulting in a distorted result), this application can also use Comp to pull the second index value MPIratio back to zero, ensuring the reliability of the second index value MPIratio calculated when MPI is very weak.

[0100] It is understandable that the steps of indicator calculation are performed periodically, and the above only describes the specific process of indicator calculation operation more than once.

[0101] The following uses PAM-4 as an example to briefly illustrate the calculation process of the second indicator in this application. Assume that the four preset levels corresponding to PAM-4 are -3, -1, +1, and +3, which correspond to four sets Err(0), Err(1), Err(2), and Err(3). Throughout the monitoring process, the following process is executed periodically: (1) Obtain a series of raw signals to be processed in the current cycle from the RAM of the optical receiving device. Assume there are 1000 raw signals P = {0.9, 0.7, 2.5, -2.6, -2.3, -1.2, -0.4, ...}.

[0102] (2) Make a decision on each original signal to obtain the corresponding target signal; The original signal in P is compared one by one with the four levels "-3, -1, +1, +3", and the original signal is mapped to one of these four levels. After the decision, P'={1,1,3,-3,-3,-1,-1,......} is obtained.

[0103] (3) Calculate the error signal between the original signal and the target signal, and put the error signal into the set to which the target signal belongs.

[0104] Calculate the difference between P and P' to obtain err = {0.1, 0.3, 0.5, 0.4, 0.7, -0.2, 0.6, ...}. Place each element of err into four sets Err(0), Err(1), Err(2), and Err(3), resulting in: The set of -3 level levels Err(0) = {0.4, 0.7, ...}; The set of -1 levels is Err(1) = {-0.2, 0.6, ...}; The set of +1 levels is Err(2) = {0.1, 0.3, ...}; The set of +3 levels is Err(3) = {0.5, ...}; (4) Select sets Err(0), Err(1), and Err(2), and calculate the mean square value of the error signal within each set. The mean square value of the error signal within Err(0) is denoted as f0, the mean square value of the error signal within Err(1) is denoted as f1, and the mean square value of the error signal within Err(2) is denoted as f2. ; ; ; Where N0 represents the number of error signals inside Err(0), N1 represents the number of error signals inside Err(1), and N2 represents the number of error signals inside Err(2).

[0105] (5) Select sets Err(0) and Err(3), and calculate the variance of the error signal within each set. The variance of the error signal within Err(0) is denoted as v0, and the variance of the error signal within Err(3) is denoted as v3: ; ; ; ; Where N3 represents the number of error signals inside Err(3). , This represents the mean of the error signals within Err(0) and Err(3).

[0106] (6) Calculate the first index Amp_mpi. The specific calculation process is as follows: ff1 = f2 - f1; ff2 = f1 - f0; Amp_mpi = (ff1-ff2) / (2 ff1); (7) Calculate the correction factor Comp: Comp=v3 / v0-1; (8) Calculate the second index MPIratio: MPIratio=Amp_mpi Comp; Thus, this application can "extract" the MPI noise component with intensity-related characteristics from the mixed noise through the above calculations. Amp_mpi provides a preliminary estimate of the MPI intensity, but to improve accuracy, especially when the MPI is weak, a variance ratio (specifically v3 / v0 - 1) is introduced for correction. This is because the presence of MPI makes the asymmetry in the noise distribution between high (+3) and low (-3) levels more pronounced, and the variance ratio can capture this change. Since (v3 / v0 - 1) tends to 0 when the MPI is weak, the MPIratio can be pulled back to zero, ensuring the reliability of the calculated final index when the MPI intensity is weak.

[0107] Because intensity-dependent RIN noise also exists in the optical link, and the MPI intensity is directly related to the SNR (Signal-to-Noise Ratio) and laser linewidth, a software solution for real-time monitoring of MPI intensity can be implemented by pre-calibrating the actual optical transmission system and setting an MPI intensity alarm value to assist the operation of the alarm system. Therefore, in some embodiments, reference is made to... Figure 6 The methods also include: S601: An alarm is triggered when the value of the second indicator exceeds the corresponding indicator threshold; In this way, by judging and triggering alarms through preset indicator thresholds, the system can automatically and promptly issue warnings when MPI interference reaches a harmful level, which facilitates rapid response by operation and maintenance personnel and improves the maintainability and reliability of the system.

[0108] In some embodiments, testing and calibration under different known MPI intensities can also establish a dedicated and accurate mapping relationship for different fiber optic link systems in advance, ensuring the accuracy and adaptability of the proposed solution in different practical application environments. (Refer to...) Figure 7 The pre-calibration process specifically includes: S701: Under multiple known MPI intensities, perform index calculation operations to obtain a second index value corresponding to each known MPI intensity; The specific process is as follows: First, configure the initial MPI strength of the optical transmitting device. Each MPI strength corresponds to one test (the test can also be implemented based on simulation software, where a model of the actual link to be monitored is designed, and then the MPI strength is changed through the simulation software). For each test, the optical receiving device performs an index calculation operation: that is, it executes steps S401-S407 to generate error signals and puts them into a set, and based on the error signals in the set, it calculates the mean and variance and then calculates the second index value (see details). Figure 3 (Steps S203, S301, S205, S303, S305). After obtaining the second index value in each test, the MPI intensity of the optical transmitting device is changed, and the next test is performed again, and so on, until multiple second index values ​​are obtained.

[0109] S703: Based on multiple known MPI intensities and their corresponding second index values, a mapping relationship between MPI intensities and second index values ​​is constructed.

[0110] Based on the data pairs (MPI intensity + second index value) from each test in step S701, a mapping relationship between MPI intensity and the second index value can be constructed. For example, with MPI intensity as the horizontal axis (e.g., Figure 11 (As shown in mpi), the second index value is the vertical axis (e.g., Figure 11 As shown in MPIratio, a curve can be obtained to represent this mapping relationship.

[0111] like Figure 11 As shown in the figure, this graph illustrates the mapping relationship between MPI intensity and the second index value when the average optical power received at the receiver is set to Rop = -4 dBm in the simulation test. It demonstrates the second index value MPIratio corresponding to different MPI values. Figure 11 A strong, approximately linear, positive correlation was found between the MPI_ratio value and the actual MPI intensity. This figure also demonstrates that the proposed MPI_ratio can effectively characterize the increase in MPI intensity. Therefore, the scheme proposed in this application can provide MPI intensity alerts in different real-world links, enabling real-time MPI monitoring in business scenarios.

[0112] Furthermore, in step S601, the indicator threshold is a strength threshold based on MPI strength, and the mapping relationship between MPI strength and the second indicator value is pre-calibrated. For example, when the method of this application needs to be applied to a certain business scenario, the system's MPI resistance capability can be determined according to the application scenario and system operation and maintenance requirements. The MPI strength threshold MPI_th reflects the system's MPI resistance capability. Therefore, the business side only needs to set the strength threshold MPI_th, and then compare it with the MPI_th value. Figure 11The corresponding second indicator value is determined as the indicator threshold MPIratio_th. Then, during subsequent formal MPI monitoring, it is only necessary to compare the real-time calculated second indicator value with MPIratio_th. When the real-time calculated MPI_ratio exceeds MPIratio_th, it is considered that the MPI intensity has become so high as to affect communication quality, and an alarm will be triggered.

[0113] In some business scenarios, a specific MPI intensity value is required. This can be obtained by further converting the MPI intensity using a second indicator value calculated in real time. Therefore, refer to... Figure 8 In other embodiments, the method further includes: S801: Estimate the MPI intensity based on the obtained second index value and the mapping relationship between MPI intensity and the second index value.

[0114] For example, the second indicator value obtained in real time is compared with... Figure 11 The relationship shown can be used to directly determine the corresponding MPI intensity.

[0115] In this way, through the established mapping relationship, the calculated abstract second index value can be converted back into a specific MPI intensity value, thereby realizing a quantitative assessment of the degree of MPI interference and providing data support for accurate network diagnosis and optimization.

[0116] In summary, the embodiments of this application have the following beneficial effects: 1) It can be compatible with various business scenarios to achieve real-time monitoring of MPI intensity; 2) The calculation scheme is simple, requiring only the calculation of the mean and variance of the noise of the equalized signal, which is easy to implement in software.

[0117] Compared to MPI detection schemes based on cross-correlation operations, the embodiments of this application avoid complex multiplication and accumulation and large amounts of storage operations through simple statistical operations (such as calculating the mean and variance) and algebraic combinations, thereby significantly reducing computational complexity and hardware resource consumption, and making it easier to implement real-time or near-real-time monitoring functions in existing optical receiving devices.

[0118] 3) The MPI intensity has a good linear correlation with the calculated value, and different MPI intensity warnings can be set for different scenarios; 4) The pre-calibration of the fiber optic system can be adapted to different fiber optic links, resulting in better alarm performance.

[0119] It should be noted that this specification provides the method operation steps as shown in the embodiments or flowcharts. The order of steps listed in the embodiments is only one of many possible execution orders and does not represent the only execution order. In practice, when the method program is executed, it can be executed in the order shown in the embodiments or drawings or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0120] Based on the same technical concept, in the second aspect, refer to... Figure 12a This application also provides an optical receiving device 1200, comprising: The error acquisition module 1201 is used to determine a set of error signals with preset levels corresponding to the modulation format adopted by the optical transmitting device based on the original signal obtained after conversion by the optical receiving device. Each preset level corresponds to one set. The mean feature calculation module 1202 is used to calculate the mean feature of the error signal in each of at least two sets. The first index value calculation module 1203 is used to calculate the first index value representing the MPI intensity based on the mean characteristics.

[0121] In some embodiments, reference Figure 12b The optical receiving device 1200 also includes: The distribution feature calculation module 1204 is used to calculate the distribution dispersion feature within each of the at least two sets. The correction factor calculation module 1205 is used to calculate the correction factor based on the distribution dispersion characteristics. The second index value calculation module 1206 is used to multiply the first index value by the correction factor to obtain the second index value.

[0122] In some embodiments, the correction factor calculation module 1205 is specifically used to calculate the correction factor for two sets corresponding to two preset levels with the same amplitude and opposite polarity, based on the ratio of the distribution dispersion characteristics of the error signals between the sets.

[0123] In some embodiments, the distribution dispersion feature is variance, and the correction factor calculation module 1205 calculates the correction factor as follows: Comp=v3 / v0-1; where v3 and v0 are the variances of two preset levels with the same amplitude and opposite polarity.

[0124] In some embodiments, reference Figure 12c The first indicator value calculation module 1203 includes: The first difference calculation submodule 12031 is used to calculate the first difference of the mean characteristics of the error signal between two sets corresponding to two preset levels with the same amplitude and opposite polarity, so as to eliminate the Gaussian white noise component that is independent of the level and the component that is quadratically dependent on the MPI intensity in the error signal, and retain the component that is linearly dependent on the MPI intensity. The second difference calculation submodule 12032 is used to calculate the second difference of the mean characteristics of the error signal between two sets corresponding to two preset levels with different amplitudes, eliminate the Gaussian white noise component in the error signal that is independent of the level, and retain the component that is dependent on the MPI intensity in the first and second order. The third difference calculation submodule 12033 is used to calculate a third difference based on the first difference and the second difference, so as to eliminate the components that are linearly dependent on the MPI intensity and retain only the components that are linearly dependent on the MPI intensity. The first index value calculation submodule 12034 is used to calculate the first index value based on the ratio of the third difference to the first difference.

[0125] Specifically, the mean characteristic is the mean squared mean; The first difference calculation submodule 12031 calculates the first difference as follows: ff1 = f2 - f1; The second difference calculation submodule 12032 calculates the second difference as follows: ff2 = f1' - f0; The third difference calculation submodule 12033 calculates the third difference as follows: ff3 = ff1 - K1 ff2; The first indicator value calculation submodule 12034 calculates the first indicator value as follows: Amp_mpi=K2 ff3 / ff1; Wherein, ff1 represents the first difference, ff2 represents the second difference, ff3 represents the third difference, Amp_mpi represents the first index value, f1 and f2 are the mean square averages of the error signals of the sets corresponding to two preset levels with the same amplitude and opposite polarity, f1' and f0 are the mean square averages of the error signals of the two sets corresponding to two preset levels with different amplitudes, f1' corresponds to the same or different preset levels as f1, and the preset level corresponding to any one of f1, f2, and f1' is the same as any preset level corresponding to the calculation of the correction factor, and K1 and K2 are coefficients related to the preset levels corresponding to f1, f2, and f1'.

[0126] In some embodiments, reference Figure 12dThe optical receiving device 1200 also includes: Alarm module 1207 is used to trigger an alarm when the second indicator value exceeds the corresponding indicator threshold; The index threshold is obtained by pre-calibrating the intensity threshold based on MPI intensity and the mapping relationship between MPI intensity and the second index value.

[0127] In some embodiments, reference Figure 12e The optical receiving device 1200 also includes: MPI intensity conversion module 1208 is used to estimate MPI intensity based on the obtained second index value and the mapping relationship between MPI intensity and the second index value.

[0128] The actions performed by each module of the device 1200 of the second aspect of this application correspond to the steps in the method of the embodiment of the first aspect of this application. For the detailed functions of each module of the device 1200 and other optional modules, please refer to the description in the method embodiment of the first aspect above, which will not be repeated here.

[0129] It should be noted that the various modules described herein are divided into modules for clarity. However, in actual implementation, the boundaries between modules may be blurred. For example, any or all functional modules in this application may share various hardware and / or software elements. As another example, any and / or all functional modules in this application may be wholly or partially implemented by a shared processor executing software instructions. Furthermore, various software sub-modules executed by one or more processors may be shared among various software modules. Accordingly, unless expressly required, the scope of this application is not limited by mandatory boundaries between various hardware and / or software elements.

[0130] Based on the same technical concept, in the third aspect, refer to Figure 13 This application also provides a communication device 1300, including at least one processor and a memory; The at least one processor is coupled to the memory and the communication interface; The memory is used to store instructions, the processor is used to execute the instructions, and the communication interface is used to communicate with other communication devices under the control of the at least one processor; When the instructions are executed by the at least one processor, the at least one processor causes the at least one processor to perform the method steps of the first aspect.

[0131] In some embodiments of this application, the communication interface, processor, and memory may be connected via a bus or other means. Memory may include read-only memory and random access memory, providing instructions and data to the processor. A portion of the memory may also include non-volatile random access memory (NVRAM). Memory stores the operating system and operating instructions, executable modules, or data structures, or subsets thereof, or extended sets thereof. Operating instructions may include various operation instructions used to implement various operations. The operating system may include various system programs used to implement various basic business processes and handle hardware-based tasks. The processor controls the operation of the communication device; it can also be called the central processing unit (CPU). In specific applications, the various components of the communication device are coupled together through a bus system. This bus system includes not only the data bus but also power buses, control buses, and status signal buses. However, for clarity, all buses in the diagram are referred to as the bus system. The methods disclosed in the embodiments of this application can be applied to a processor or implemented by a processor. The processor can be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. In this embodiment of the application, the processor is used to execute the method steps performed by the aforementioned optical receiving device. In another possible design, when the optical receiving device is a chip, it includes a processing unit and a communication unit. The processing unit may be, for example, a processor, and the communication unit may be, for example, an input / output interface, pins, or circuits. The processing unit can execute computer execution instructions stored in the storage unit to cause the chip within the terminal to execute the wireless reporting information transmission method described in any of the first aspects above. Optionally, the storage unit is a storage unit within the chip, such as a register or cache. The storage unit can also be a storage unit located outside the chip within the terminal, such as a read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, such as random access memory (RAM). The processor mentioned above can be a general-purpose central processing unit, a microprocessor, an ASIC, or one or more integrated circuits used to control the execution of the program described above. It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the device embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines. Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application. In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. Based on the same technical concept, in a fourth aspect, embodiments of this application also provide an optical communication system, as referenced. Figure 1 The system includes an optical receiving device, an optical transmitting device, and an optical fiber link; wherein the optical transmitting device is used to transmit an optical signal to the optical receiving device via the optical fiber link; and the optical receiving device is used to perform the method as described in the first aspect embodiment.

[0132] Based on the same technical concept, in a fifth aspect, embodiments of this application also provide a computer program product, including one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state disk (SSD)).

[0133] Based on the same technical concept, in a sixth aspect, embodiments of this application also provide a computer-readable storage medium storing a computer program or instructions. When the computer program or instructions are executed by a processing device, they implement the method steps in any of the method embodiments of the first aspect. Further details can be found in the method embodiments, which will not be repeated here. In this embodiment, the computer-readable storage medium can be non-volatile or volatile. Computer-readable storage media include flash memory, hard disks, multimedia cards, random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), magnetic disks, optical disks, etc. In some embodiments, the computer-readable storage medium can be an internal storage unit of a computing device, such as the hard disk or memory of the computing device. In other embodiments, the computer-readable storage medium can also be an external storage device of the computing device, such as a plug-in hard disk, a secure digital card (SD card), a flash memory card, etc., equipped on the computing device. Of course, the computer-readable storage medium can also include both internal storage units and external storage devices of the computing device. In this embodiment, the computer-readable storage medium is typically used to store software installed on the computing device, such as program code of the methods of the embodiments of the first or second aspects. In addition, computer-readable storage media can also be used to temporarily store various types of data that have been output or will be output.

[0134] It should be noted that the order in which the embodiments are described in this application is not intended to limit the priority of the embodiments. The reference to "embodiment" herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. Those skilled in the art will explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0135] Unless otherwise defined, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this application and in its specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0136] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many forms under the guidance of this application without departing from the spirit and scope of protection of the claims. All equivalent transformations made under the inventive concept of this application using the content of this application's specification and drawings, or direct / indirect applications in other related technical fields, are included within the patent protection scope of this application.

Claims

1. A multipath interferometry detection method, characterized in that, The method includes the following indicator calculation operations: Based on the original signal obtained after conversion by the optical receiving device, a set of error signals corresponding to preset levels of the modulation format adopted by the optical transmitting device is determined, and each preset level corresponds to one set. For at least two of the said sets, the mean characteristic of the error signal within each of the said sets is calculated; The first index value characterizing the MPI intensity is calculated based on the mean characteristic.

2. The method according to claim 1, characterized in that, The indicator calculation operation also includes: For at least two of the sets, calculate the distribution dispersion characteristics within each set; Calculate the correction factor based on the aforementioned distribution dispersion characteristics; The second index value is obtained by multiplying the first index value by the correction factor.

3. The method according to claim 2, characterized in that, The method further includes: triggering an alarm when the second indicator value exceeds the corresponding indicator threshold; The index threshold is obtained by pre-calibrating the intensity threshold based on MPI intensity and the mapping relationship between MPI intensity and the second index value.

4. The method according to claim 2, characterized in that, The method further includes: Based on the obtained second index value and the mapping relationship between MPI intensity and the second index value, the MPI intensity is estimated.

5. The method according to claim 3 or 4, characterized in that, The method further includes: Under different known MPI intensities, the index calculation operation is performed to obtain the second index value corresponding to each known MPI intensity; Based on multiple known MPI intensities and their corresponding second index values, the mapping relationship between MPI intensities and the second index values ​​is constructed.

6. The method according to any one of claims 1-5, characterized in that, The calculation of the first index value based on the mean characteristic includes: For a set of two preset levels with the same amplitude and opposite polarity, calculate the first difference of the mean characteristic of the error signal between the sets to eliminate the Gaussian white noise component that is independent of the level and the component that is quadratically dependent on the MPI intensity in the error signal, and retain the component that is linearly dependent on the MPI intensity. For two sets corresponding to two preset levels with different amplitudes, calculate the second difference of the mean characteristics of the error signal between the sets, eliminate the Gaussian white noise component in the error signal that is independent of the level, and retain the components that are dependent on the MPI intensity in the first and second order. A third difference is calculated based on the first difference and the second difference, so that the components that are linearly dependent on the MPI intensity are eliminated and only the components that are quadratically dependent on the MPI intensity are retained. The first index value is calculated based on the ratio of the third difference to the first difference.

7. The method according to claim 6, characterized in that, The mean characteristic is the mean squared mean; The first difference is calculated as follows: ff1 = f2 - f1; The second difference is calculated as follows: ff2 = f1' - f0; The third difference is calculated as follows: ff3 = ff1 - K1 ff2; The first index value is calculated as follows: Amp_mpi = K2 ff3 / ff1; Wherein, ff1 represents the first difference, ff2 represents the second difference, ff3 represents the third difference, Amp_mpi represents the first index value, f1 and f2 are the mean square values ​​of the error signals of the sets corresponding to two preset levels with the same amplitude and opposite polarity, f1' corresponds to the same or different preset level as f1, f1' and f0 are the mean square values ​​of the error signals of the two sets corresponding to two preset levels with different amplitudes, the preset level corresponding to any one of f1, f2, and f1' is the same as any preset level corresponding to the calculation of the correction factor, and K1 and K2 are coefficients related to the preset levels corresponding to f1, f2, and f1'.

8. The method according to claim 7, characterized in that, The modulation format is N-order pulse amplitude modulation (PAM-N), where N > 2. The preset levels corresponding to f1' and f1 are the same preset level with the smallest amplitude among the N preset levels, and the preset level corresponding to f0 is the preset level with the largest amplitude among the N preset levels.

9. The method according to claim 7, characterized in that, The modulation format is fourth-order pulse amplitude modulation (PAM-4). The preset level corresponding to f1' and f1 is the preset level with the smallest amplitude among the four preset levels, and the preset level corresponding to f0 is the preset level with the largest amplitude among the four preset levels.

10. The method according to claim 9, characterized in that, The four preset levels are "-3", "-1", "+1", and "+3" levels, respectively. f0 represents the mean square value of the set corresponding to the "-3" level; f1' and f1 represent the mean square value of the set corresponding to the "-1" level; f2 represents the mean square value of the set corresponding to the "+1" level; K1 is 1, and K2 is 1 / 2.

11. The method according to any one of claims 1-10, characterized in that, The calculation of the correction factor based on the distribution dispersion characteristics includes: For two sets corresponding to two preset levels with the same amplitude and opposite polarity, the correction factor is calculated based on the ratio of the distribution dispersion characteristics of the error signal between the sets.

12. The method according to claim 11, characterized in that, The distribution dispersion characteristic is variance, and the correction factor is calculated as follows: Comp=v3 / v0-1, where v3 and v0 are the variances of two preset levels with the same amplitude and opposite polarity.

13. The method according to claim 12, characterized in that, The modulation format is N-order pulse amplitude modulation (PAM-N), where N > 2. The preset level corresponding to the distribution dispersion characteristics when calculating the correction factor is the two preset levels with the largest amplitude and opposite polarities among the N preset levels.

14. The method according to claim 12, characterized in that, The modulation format is fourth-order pulse amplitude modulation (PAM-4), and the four preset levels are "-3", "-1", "+1", and "+3" levels respectively; v3 represents the distribution dispersion characteristics of the set corresponding to the "+3" level, and v0 represents the distribution dispersion characteristics of the set corresponding to the "-3" level.

15. The method according to any one of claims 1-14, characterized in that, The mean feature is the mean squared mean, and calculating the mean feature of the error signal within each set includes: The error square value is obtained by squaring each error signal in the set, and then the average of all the error square values ​​is obtained by summing them up.

16. The method according to any one of claims 2-14, characterized in that, The distribution dispersion feature is variance, and the calculation of the distribution dispersion feature within each set includes: Calculate the mean of all error signals within each set, calculate the deviation of each error signal relative to the mean, square all deviations to obtain the squared deviation value, and then sum and average all the squared deviation values ​​to obtain the variance of the set.

17. The method according to any one of claims 1-14, characterized in that, The error signal for determining the preset level corresponding to the optical transmitting device based on the original signal obtained after conversion by the optical receiving device includes: Acquire the original signal obtained after conversion by the optical receiving device; The target signal is obtained by judging the original signal based on all preset levels corresponding to the optical transmitting device; Calculate the error signal between the original signal and the target signal; The error signal is assigned to a set of preset levels belonging to the target signal.

18. An optical receiving device, characterized in that, include: The error acquisition module is used to determine a set of error signals with preset levels corresponding to the modulation format adopted by the optical transmitting device based on the original signal obtained after conversion by the optical receiving device. Each preset level corresponds to one set. The mean feature calculation module is used to calculate the mean feature of the error signal in each of at least two sets. The first index value calculation module is used to calculate the first index value representing the MPI intensity based on the mean characteristic.

19. The device according to claim 18, characterized in that, Also includes: The distribution feature calculation module is used to calculate the distribution dispersion feature within each of at least two sets. The correction factor calculation module is used to calculate the correction factor based on the distribution dispersion characteristics. The second indicator value calculation module is used to multiply the first indicator value by the correction factor to obtain the second indicator value.

20. The device according to claim 19, characterized in that, Also includes: The alarm module is used to trigger an alarm when the second indicator value exceeds the corresponding indicator threshold. The index threshold is obtained by pre-calibrating the intensity threshold based on MPI intensity and the mapping relationship between MPI intensity and the second index value.

21. The device according to any one of claims 18-20, characterized in that, The first indicator value calculation module includes: The first difference calculation submodule is used to calculate the first difference of the mean characteristics of the error signal between two sets corresponding to two preset levels with the same amplitude and opposite polarity, so as to eliminate the Gaussian white noise component that is independent of the level and the component that is quadratically dependent on the MPI intensity in the error signal, and retain the component that is linearly dependent on the MPI intensity. The second difference calculation submodule is used to calculate the second difference of the mean characteristics of the error signal between two sets corresponding to two preset levels with different amplitudes, eliminate the Gaussian white noise component in the error signal that is independent of the level, and retain the components that are dependent on the MPI intensity in the first and second order. The third difference calculation submodule is used to calculate the third difference based on the first difference and the second difference, so as to eliminate the components that are linearly dependent on the MPI intensity and retain only the components that are linearly dependent on the MPI intensity. The first index value calculation submodule is used to calculate the first index value based on the ratio of the third difference to the first difference.

22. The device according to any one of claims 19-21, characterized in that, The correction factor calculation module is used to calculate the correction factor based on the ratio of the distribution dispersion characteristics of the error signal between two sets corresponding to two preset levels with the same amplitude and opposite polarity.

23. An optical communication system, characterized in that, This includes optical receiving equipment, optical transmitting equipment, and optical fiber links; among which, The optical transmitting device is used to transmit optical signals to the optical receiving device through the optical fiber link; The optical receiving device is used to perform the method as described in any one of claims 1-17.

24. A communication device, characterized in that, Includes at least one processor and memory; The at least one processor is coupled to the memory and the communication interface; The memory is used to store instructions, the processor is used to execute the instructions, and the communication interface is used to communicate with other communication devices under the control of the at least one processor; When the instruction is executed by the at least one processor, it causes the at least one processor to perform the method as described in any one of claims 1-17.

25. A computer-readable storage medium, characterized in that, The storage medium stores a computer program or instructions, which, when executed by a processor, implement the method of any one of claims 1-17.

26. A computer program product, characterized in that, The computer program product includes a computer program or instructions that, when executed by a processor, implement the method of any one of claims 1-17.

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