Signal-to-noise ratio and mode coupling joint estimation method and device for mode division multiplexing optical fiber communication and storage medium

Abstract

The invention discloses a signal-to-noise ratio and mode coupling joint estimation method and device for mode division multiplexing optical fiber communication and a storage medium, and the method comprises the steps: obtaining a plurality of groups of communication signals of the mode division multiplexing optical fiber communication, and obtaining a spectrum correlation function of the communication signals, determining a cyclic correlation function according to the spectrum correlation function, determining a signal-to-noise ratio and an optical fiber length according to the cyclic correlation function, and determining a power coupling coefficient value according to the signal-to-noise ratio and the optical fiber length corresponding to each group of communication signals. According to the method, the signal-to-noise ratio and mode coupling can be monitored at the same time, the communication quality can be evaluated more comprehensively through the combined monitoring capacity, and a complex data acquisition or synthesis process is not needed, so that implementation and operation of a monitoring system are simplified, real-time monitoring can be achieved, and reliability and timely detection of the communication system can be guaranteed. The method is widely applied to the technical field of optical communication.

Description

Technical Field

[0001] The present invention relates to the field of optical communication technology, and in particular to a method, a device and a storage medium for jointly estimating a signal-to-noise ratio and mode coupling in mode division multiplexing optical fiber communication. Background Art

[0002] With the explosive growth of Internet and data communication demand, optical communication systems have become the backbone of modern communication networks due to their advantages such as high bandwidth, low loss and anti-electromagnetic interference. In particular, in high-speed coherent optical communication systems, ultra-high-speed data transmission can be achieved by using advanced modulation formats and digital signal processing technologies.

[0003] Coherent detection technology in coherent optical communication systems can provide higher signal detection sensitivity and can accurately measure the amplitude and phase of optical signals, which is essential for achieving high-speed transmission and improving signal quality. Mode multiplexing (MDM) technology was developed to solve the problem of limited bandwidth in single-mode fiber (SMF) networks. MDM technology provides additional information transmission channels by using multiple orthogonal modes.

[0004] In coherent transmission systems, the transmitted optical signal is susceptible to dynamic optical impairments such as amplified spontaneous emission (ASE), chromatic dispersion (CD), and polarization mode dispersion (PMD). In MDM systems, the mode coupling effect (MC) makes the monitoring process more complicated than that of single-mode fiber (SMF). Therefore, it is difficult to monitor the signal-to-noise ratio and mode coupling parameters in mode division multiplexing optical fiber communications using coherent transmission. Summary of the invention

[0005] In view of the technical problem that it is currently difficult to monitor the signal-to-noise ratio and mode coupling parameters of mode division multiplexing optical fiber communications using coherent transmission, the purpose of the present invention is to provide a method, device and storage medium for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communications.

[0006] On the one hand, an embodiment of the present invention includes a method for jointly estimating a signal-to-noise ratio and a mode coupling of a mode-division multiplexed optical fiber communication, wherein the method for jointly estimating a signal-to-noise ratio and a mode coupling of a mode-division multiplexed optical fiber communication includes the following steps:

[0007] Acquire multiple groups of communication signals of mode division multiplexing optical fiber communication;

[0008] For any group of the communication signals, obtaining a spectrum correlation function of the communication signals, determining a cyclic correlation function according to the spectrum correlation function, and determining a signal-to-noise ratio and an optical fiber length according to the cyclic correlation function;

[0009] The power coupling coefficient value is determined according to the signal-to-noise ratio and the optical fiber length corresponding to each group of the communication signals.

[0010] Further, the obtaining of multiple groups of communication signals of mode division multiplexing optical fiber communication includes:

[0011] Receiving signals of mode division multiplexing optical fiber communication through a coherent receiver under various channel environment conditions respectively;

[0012] The signals received under each of the channel environment states form a group of communication signals.

[0013] Further, the acquiring the spectrum correlation function of the communication signal includes:

[0014] For any group of the communication signals, a plurality of discrete digital signal components corresponding to the communication signals are obtained; each of the discrete digital signal components has a corresponding polarization multiplexing dimension and a mode multiplexing dimension;

[0015] For any group of the communication signals, the discrete digital signal components are respectively intercepted according to the same time length, and a plurality of cycle period graphs are determined according to the intercepted signals;

[0016] For any group of the communication signals, the spectrum correlation function in matrix form is determined using the corresponding plurality of the cyclic periodograms as elements in a matrix.

[0017] Further, determining the cyclic correlation function according to the spectrum correlation function comprises:

[0018] Performing inverse Fourier transform on the elements in the spectrum correlation function respectively;

[0019] The cyclic correlation function in matrix form is determined by using the results of inverse Fourier transformation of the elements in the spectrum correlation function as elements in a matrix.

[0020] Further, determining the signal-to-noise ratio and the optical fiber length according to the cyclic correlation function comprises:

[0021] Determining a maximum correlation strength value according to the cyclic correlation function;

[0022] Obtaining an upper sideband average power and a lower sideband average power of each of the discrete digital signal components;

[0023] Determining a normalized correlation coefficient according to the maximum value of the correlation strength, the upper sideband average power, and the lower sideband average power;

[0024] The signal-to-noise ratio is determined according to the normalized correlation coefficient.

[0025] Further, the normalized correlation coefficient is determined according to the maximum value of the correlation strength, the upper sideband average power and the lower sideband average power, according to the following formula:

[0026]

[0027] Wherein, δ is the normalized correlation coefficient, R sum is the maximum value of the correlation strength, P1 is the upper sideband average power, and P2 is the lower sideband average power;

[0028] The signal-to-noise ratio is determined according to the normalized correlation coefficient according to the following formula:

[0029]

[0030] Wherein, SNR is the signal-to-noise ratio.

[0031] Further, determining the signal-to-noise ratio and the optical fiber length according to the cyclic correlation function comprises:

[0032] The fiber length is determined using the CAF-4CDE algorithm.

[0033] Further, determining the power coupling coefficient value according to the signal-to-noise ratio and the optical fiber length corresponding to each group of the communication signals includes:

[0034] Performing quadratic fitting or linear fitting according to each of the signal-to-noise ratios and each of the optical fiber lengths;

[0035] The coefficient value determined by fitting is used as the power coupling coefficient value.

[0036] On the other hand, an embodiment of the present invention also includes a computer device including a memory and a processor, the memory being used to store at least one program, and the processor being used to load at least one program to execute the method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication in the embodiment.

[0037] On the other hand, an embodiment of the present invention also includes a computer-readable storage medium, which stores a program executable by a processor. When the program executable by the processor is executed by the processor, it is used to execute the method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication in the embodiment.

[0038] The beneficial effects of the present invention are as follows: the signal-to-noise ratio and mode coupling joint estimation method of mode division multiplexing optical fiber communication in the embodiment can simultaneously monitor the signal-to-noise ratio (SNR) and mode coupling (MC). This joint monitoring capability can more comprehensively evaluate the communication quality and does not require complex data acquisition or synthesis processes, thereby simplifying the implementation and operation of the monitoring system, and can achieve real-time monitoring, ensuring the reliability and timely detection of the communication system. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 Schematic diagram of a mode division multiplexing optical fiber communication system to which a method for jointly estimating a signal-to-noise ratio and mode coupling in mode division multiplexing optical fiber communication can be applied in an embodiment;

[0040] Figure 2 Schematic diagram of the steps of the method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication in the embodiment;

[0041] Figure 3 It is a flow chart of a method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication in an embodiment;

[0042] Figure 4 Schematic diagram of SNR estimation performance under different channel environment conditions obtained for numerical simulation verification;

[0043] Figure 5 Schematic diagram of the estimated curve of the power coupling coefficient h at different optical fiber lengths obtained for numerical simulation verification. DETAILED DESCRIPTION

[0044] Terminology explanation:

[0045] 1. Coherent Optical Communication: Coherent optical communication is an advanced optical communication technology that uses lasers as light sources and uses coherent detection technology to improve signal reception sensitivity and transmission quality. In a coherent optical communication system, the signal at the transmitter modulates the optical carrier of the laser, while the receiver uses a local laser synchronized with the transmitter for coherent mixing to detect the amplitude and phase information of the transmitted signal. This technology significantly improves the signal transmission distance and system capacity.

[0046] 2. Chromatic Dispersion (CD): Chromatic dispersion refers to the phenomenon that the optical signal transmitted in the optical fiber is pulse-broadened due to the different light speeds of different wavelengths. Dispersion will distort the time domain waveform of the signal, affect the integrity of the signal, and thus reduce the performance of the communication system. The dispersion effect includes material dispersion and waveguide dispersion, and is one of the damage factors that need to be considered and compensated in long-distance optical fiber communication systems.

[0047] 3. Nyquist System: Nyquist system refers to a signal sampling system that satisfies the Nyquist sampling theorem. According to the Nyquist sampling theorem, in order to avoid aliasing, the sampling frequency of the signal should be at least twice the highest frequency of the signal. In optical fiber communications, Nyquist systems usually refer to digital signal processing systems that can meet this condition and can accurately reconstruct the original analog signal from the sampled data.

[0048] 4. Timing Error Estimation: Timing error estimation refers to the process of estimating the deviation between the sampling clock of the received signal and the actual clock of the signal in a digital communication system. Accurate timing error estimation is crucial for synchronous demodulation of the signal. It can ensure that the signal is sampled at the optimal time, thereby improving the accuracy of signal demodulation and the overall performance of the system.

[0049] 5. DSP technology (Digital Signal Processing Technology, DSP): DSP technology refers to the technology of using digital circuits or computers to process signals. In optical fiber communication systems, DSP technology is widely used in key links such as signal modulation, demodulation, equalization, dispersion compensation, and timing recovery. Through DSP technology, efficient signal processing can be achieved, system performance can be optimized, and transmission quality can be improved.

[0050] 6.Signal-to-Noise Ratio (SNR): Signal-to-noise ratio is a measure of signal strength relative to background noise.

[0051] 7. Mode Coupling (MC): Mode coupling refers to the signal exchange between different modes due to reasons such as optical fiber bending.

[0052] 8.Optical Performance Monitoring (OPM): used to monitor the signal quality in fiber optic communication systems in real time.

[0053] 9. Polarization Mode Dispersion (PMD): Pulse broadening caused by changes in polarization state in optical fiber.

[0054] 10. Mode Division Multiplexing (MDM): Also known as mode multiplexing, it is a method of increasing transmission capacity in optical fiber communications. It increases transmission bandwidth by transmitting multiple spatial modes simultaneously in the optical fiber. Traditional single-mode optical fiber communications only use one spatial mode in the optical fiber, while mode division multiplexing technology precisely controls the optical signal of each mode so that they can be transmitted independently in the optical fiber without interfering with each other, thereby greatly increasing the transmission capacity of the optical fiber.

[0055] 11. Few Mode Fiber (FMF): Optical fiber that can transmit a limited number of modes.

[0056] 12. Single Mode Fiber (SMF): Fiber that can only transmit a single mode.

[0057] 13. Amplified Spontaneous Emission (ASE): A source of noise in fiber amplifiers.

[0058] 14. Deep Learning (DL): A machine learning technique used to process large amounts of data.

[0059] 15. Machine Learning (ML): An artificial intelligence technique used to learn patterns from data.

[0060] Current optical performance monitoring (OPM) techniques mainly rely on statistical features extracted from received signals. These methods are usually suitable for direct detection methods, but they are not applicable to coherent communication systems due to their wider application scenarios and greater monitoring difficulties. Deep learning (DL)-based OPM techniques require a large data set to achieve good performance, and obtaining diverse data sets is very difficult and time-consuming. The shortcomings of current related technologies can be summarized as follows:

[0061] 1. Difficulty in obtaining datasets: Deep learning (DL) requires a large amount of datasets, which are very difficult and time-consuming to obtain.

[0062] 2. Monitoring methods are not applicable: Existing machine learning-based OPM technologies are not applicable to coherent communication systems because these systems have a wider range of application scenarios and are more difficult to monitor.

[0063] 3. Mode coupling effect: The mode coupling effect (MC) in the MDM system makes the monitoring process more complicated and the relevant technologies are difficult to monitor accurately.

[0064] That is to say, for coherent communication systems that apply mode multiplexing (MDM), it is necessary to address the challenges faced by integrated sensing and communication in the MDM system under weak coupling conditions, especially the accurate monitoring of signal-to-noise ratio (SNR) and mode coupling (MC).

[0065] Based on the above principle, in this embodiment, a method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication is provided. The method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication can be used to estimate the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication. Figure 1 The mode division multiplexing optical fiber communication system shown in the figure performs joint estimation of signal-to-noise ratio and mode coupling. Figure 1 The mode division multiplexing optical fiber communication system uses coherent optical communication and mode division multiplexing technology for communication.

[0066] In this embodiment, refer to Figure 2The method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication comprises the following steps:

[0067] S1. Obtain multiple groups of communication signals for mode division multiplexing optical fiber communication;

[0068] S2. For any group of communication signals, obtaining a spectrum correlation function of the communication signal, determining a cyclic correlation function according to the spectrum correlation function, and determining a signal-to-noise ratio and an optical fiber length according to the cyclic correlation function;

[0069] S3. Determine the power coupling coefficient value according to the signal-to-noise ratio and optical fiber length corresponding to each group of communication signals.

[0070] In this embodiment, steps S1-S3 can be performed by DSP. DSP technology plays a core role in coherent optical communication systems. It can perform necessary processing on received optical signals, including symbol rate estimation, carrier frequency offset correction, dispersion compensation and adaptive equalization of signals.

[0071] In this embodiment, a specific execution process of steps S1-S3 is as follows: Figure 3 See Figure 3 The specific implementation of steps S1-S3 applies two technologies: "SNR estimation" and "mode coupling estimation". The principle of SNR estimation is that in a coherent optical communication system, each polarization and mode can be modeled using a random process, and the SNR can be estimated through an extended circulant matrix and circulant autocorrelation function (CAF); the principle of mode coupling estimation is that by analyzing the radiation loss and the power exchange of mode coupling, the fiber laying environment can be estimated. The details of these two technologies include:

[0072] A. SNR estimation

[0073] In a coherent optical communication system, each polarization and mode can be modeled using a random process. In this embodiment, the cyclic frequency characteristics of the signal are first analyzed by an extended cyclic matrix. In this way, the cyclic autocorrelation function (CAF) of the signal can be calculated, and then the signal-to-noise ratio (SNR) can be estimated. The specific steps are as follows:

[0074] 1. Signal model: First, the signal is modeled, taking into account the effects of polarization dependent loss (PDL) and mode dependent loss (MDL).

[0075] 2. Circulant Matrix: An extended circulant matrix is ​​constructed to describe the cyclic frequency characteristics of the signal.

[0076] 3. Cyclic Autocorrelation Function (CAF): By performing an inverse Fourier transform on the signal, we get CAF, which can be used to estimate the time delay and phase change of the signal.

[0077] 4. SNR estimation: A new normalized correlation coefficient δ is proposed to correct the SNR estimator, thereby obtaining a more accurate SNR estimation.

[0078] B. Mode Coupling Estimation

[0079] In an MDM system, mode coupling (MC) is an important influencing factor, which causes power exchange between different modes of a signal. This embodiment proposes a method for estimating mode coupling, and the specific steps are as follows:

[0080] 1. Power coupling model: A model is established to describe the power exchange between random coupling modes caused by factors such as fiber bending.

[0081] 2. Distributed Mode Crosstalk (DMC) and Inter-Mode Interference (IMI): DMC and IMI are considered as additional noises, which will have an impact on the system performance.

[0082] 3. Mode coupling estimation: A method is proposed to estimate the fiber laying environment by estimating the system SNR and performing quadratic or linear fitting.

[0083] In this embodiment, Figure 1 The few-mode optical fiber is exposed to vibration and other influences in the field, experimental environment or during the laying process.

[0084] When executing steps S1-S3, the arbitrary waveform generator can generate a communication signal, and the communication signal is transmitted along the few-mode optical fiber to the coherent receiver to perform sensing monitoring on the optical fiber laying environment. When executing step S1, the DSP reads the communication signal received from the coherent receiver.

[0085] In this embodiment, when executing step S1, the DSP can read the communication signals received by the coherent receiver at different time periods, and the communication signals read by the DSP in each time period form a group of communication signals. Figure 1 The few-mode optical fiber is exposed to the influence of vibration and other factors. The channel environment conditions such as the vibration intensity and bending degree of the few-mode optical fiber generally change. Therefore, at different time periods, the few-mode optical fiber generally faces different vibration intensities and different bending degrees and other channel environment conditions. A group of communication signals read by the DSP in a certain time period are transmitted under the channel environment conditions of the few-mode optical fiber in that time period.

[0086] For the multiple communication signals obtained in step S1, each communication signal is processed in step S2. Since the principle of executing step S2 for each communication signal is the same, the process of executing step S2 for any one communication signal is taken as an example for description.

[0087] In this embodiment, when executing the step of acquiring the spectrum correlation function of the communication signal in step S2, the following steps may be specifically performed:

[0088] S201. Acquire multiple discrete digital signal components corresponding to the communication signal;

[0089] S202. Each discrete digital signal component is intercepted according to the same time period, and multiple cycle period diagrams are determined according to the intercepted signals;

[0090] S203. Using the corresponding plurality of cyclic periodograms as elements in a matrix, determine a spectrum correlation function in matrix form.

[0091] In step S201, for Figure 1 In the mode division multiplexing optical fiber communication system shown, a group of communication signals received by it can be decomposed from two orthogonal polarization direction dimensions, namely the first polarization direction and the second polarization direction, or can be decomposed from two mode multiplexing dimensions, namely +I and -I, thereby obtaining multiple discrete digital signal components. For example, for a group of communication signals, the discrete digital signal component with the first polarization direction and the +I component is recorded as x, the discrete digital signal component with the first polarization direction and the -I component is recorded as x1, the discrete digital signal component with the second polarization direction and the +I component is recorded as y, and the discrete digital signal component with the second polarization direction and the -I component is recorded as y1, thereby obtaining four discrete digital signal components, namely x, x1, y and y1.

[0092] In step S202, taking discrete digital signal components x and y as an example, x and y are preprocessed by digital signal processing (DSP) such as matched filtering and resampling, and then the preprocessed x and y are intercepted at the same time length W. By using the data after resampling and matched filtering, MDM channel effects such as CD, PMD and MC can be resisted. Among them, the signal intercepted from x is X W , the signal intercepted from y is Y W Next, set the cycle frequency α, and then calculate the cycle period diagram according to the following formula:

[0093]

[0094] In formulas (1) and (2), Represents X W is the conjugate of , and f is the frequency variable.

[0095] By using formulas (1) and (2), we can get the frequency domain periodogram P xx , P xy , P yx and P yy wait.

[0096] According to the principles of formulas (1) and (2), the four discrete digital signal components x, x1, y and y1 can be processed in pairs to obtain other periodic diagrams. For example, when processing the two discrete digital signal components x and x1, specifically, when applying formulas (1) and (2), replace the variable y in formulas (1) and (2) with x1, so as to obtain P xx , and Isocyclic period diagram.

[0097] Based on the above principle, by executing step S202, P can be obtained. xx , P xy , P yx , P yy , and And so on 16 cycle diagrams.

[0098] The cyclic periodogram obtained by executing step S202 can be regarded as an estimation of the spectrum correlation function SCF of the communication signal. In this embodiment, the cyclic periodogram obtained in step S202 can be directly used as the spectrum correlation function SCF.

[0099] Specifically, in this embodiment, it is assumed that Figure 1 The mode division multiplexing optical fiber communication system shown is a weakly coupled MDM system. When PDL and MDL are ignored, its spectrum correlation function SCF can be written as a 4×4 matrix containing and And other elements.

[0100] Since the cyclic periodogram can be regarded as an estimation of the spectrum correlation function SCF of the communication signal, and the cyclic periodogram can be directly used as the spectrum correlation function SCF, in this embodiment, let and Equal to P xx , P xy , P yx , P yy , and Right now Thus, the value of each element in the spectrum correlation function SCF is determined.

[0101] In step S203, the specific form of the obtained spectrum correlation function SCF is:

[0102]

[0103] The spectrum correlation function (SCF) includes the modeling results of polarization rotation, PMD and MC effects.

[0104] After executing steps S201-S203 to obtain the spectrum correlation function SCF(f), the cyclic correlation function CAF can be further obtained. There are two feasible methods for calculating the cyclic correlation function CAF. The first method is to obtain it by performing an inverse Fourier transform on the spectrum correlation function SCF(f). The other method is to directly calculate in the time domain according to the definition of the cyclic correlation function CAF to obtain a CAF sequence. After the CAF sequence is generated, the delay n is determined according to the peak position of a specific formula, and then the CAF matrix is ​​constructed with the first value of the delayed CAF sequence.

[0105] In this embodiment, the first method is used to obtain the cyclic correlation function CAF. In this embodiment, when the step of determining the cyclic correlation function according to the spectrum correlation function in step S2 is performed, the following steps may be performed:

[0106] S204. Perform inverse Fourier transform on the elements in the spectrum correlation function respectively;

[0107] S205. Using the results of inverse Fourier transformation of the elements in the spectrum correlation function as the elements in the matrix, a cyclic correlation function in matrix form is determined.

[0108] In step S204, an inverse Fourier transform is performed on each element in SCF(f), for example, Perform an inverse Fourier transform to obtain the time domain For frequency domain Perform an inverse Fourier transform to obtain the time domain ...for frequency domain Perform an inverse Fourier transform to obtain the time domain

[0109] In step S205, for the inverse Fourier transform obtained Elements such as ……right The relative positions of the elements in SCF(f) remain unchanged, thus forming a circular correlation function CAF(τ) in matrix form:

[0110]

[0111] Among them, τ is the time variable.

[0112] In this embodiment, by using the matrix-form spectrum correlation function SCF(f) and the cyclic correlation function CAF(τ), the spectrum response H corresponding to the dispersion effect can be obtained byjkf2 The impact on single SCF and CAF is studied, as well as the impact of polarization effects on SCF and CAF.

[0113] After executing steps S204-S205 to obtain the cyclic correlation function CAF, the signal-to-noise ratio and the optical fiber length can be further obtained. In this embodiment, when executing the step of determining the signal-to-noise ratio and the optical fiber length according to the cyclic correlation function in step S2, the following steps can be specifically performed:

[0114] S206. Determine the maximum value of the correlation strength according to the cyclic correlation function;

[0115] S207. Obtaining the upper sideband average power and the lower sideband average power of each discrete digital signal component;

[0116] S208. Determine a normalized correlation coefficient based on the maximum correlation strength, the upper sideband average power, and the lower sideband average power;

[0117] S209. Determine the signal-to-noise ratio according to the normalized correlation coefficient;

[0118] S210. Use CAF-4CDE algorithm to determine the optical fiber length.

[0119] In step S206, the nth element in the cyclic correlation function CAF(τ) is recorded as R n (τ), R n (τ) is a function of time τ. Figure 1 In the case of chromatic dispersion (CD) in the mode division multiplexing optical fiber communication system shown in FIG, the time τ = τ CD Time R n The value of (τ) determines the maximum correlation strength R sum .

[0120] Specifically, τ CD satisfy

[0121]

[0122] In determining τ CD After that, the maximum correlation strength R can be calculated by the following formula: sum :

[0123]

[0124] Since in an actual optical fiber link, uncompensated or any residual channel effect will significantly affect the estimation accuracy of the signal-to-noise ratio SNR, this embodiment proposes to use a normalized correlation coefficient to correct the SNR estimation. Specifically, when the ASE noise is linear, in step S207, the upper sideband average power P1 and the lower sideband average power P2 of all discrete digital signal components such as x, x1, y and y1 are obtained, and in step S208, the normalized correlation coefficient δ is calculated according to the following formula:

[0125]

[0126] In step S209, the signal-to-noise ratio SNR is calculated according to the following formula:

[0127]

[0128] In step S210, the cyclic correlation function CAF(τ) is processed using the CAF-4CDE algorithm to estimate Figure 1 The fiber length L of the few-mode fiber when transmitting this group of communication signals in the mode division multiplexing optical fiber communication system shown.

[0129] By executing step S2, the signal-to-noise ratio SNR and the corresponding optical fiber length L of any group of communication signals can be obtained, that is, each group of communication signals can obtain the corresponding signal-to-noise ratio SNR and optical fiber length L by executing step S2.

[0130] Due to the radiation loss caused by the random bending of the optical fiber laid on site, the power exchange between the random coupling modes can be described by power coupling. In the sparse MDM system, distributed modal crosstalk (DMC) and inter-mode interference (IMI) may be the two main damages of the sparse MDM system accompanied by multi-mode coupling crosstalk. At the same time, the impact of IMI and DMC effects on the sparse MDM system can be regarded as an additive noise. When there is severe vibration in the external environment, when the degree of fiber bending is stronger, the power coupling coefficient is larger, which will cause additional SNR damage. Therefore, in step S3, the monitored power coupling coefficient value can be obtained by performing quadratic or linear fitting on the optical fiber length.

[0131] Specifically, taking quadratic fitting as an example, the fitting formula can be expressed as:

[0132]

[0133] Since the corresponding signal-to-noise ratio SNR and fiber length L can be obtained by executing step S2 for each group of communication signals, multiple groups of communication signals can be monitored and multiple signal-to-noise ratios SNR and fiber lengths L can be obtained as the channel environment state changes, the power coupling coefficient h can be obtained by fitting the fitting formula, which specifically includes the quadratic term coefficient h caused by inter-mode interference (IMI)IMI and the first-order coefficient h caused by distributed modal crosstalk (DMC) DMC , and the constant term SNR0 is obtained by fitting. In the fitting formula, the signal-to-noise ratio SNR can use a linear value instead of a logarithmic value.

[0134] The method for jointly estimating the signal-to-noise ratio and mode coupling of mode-division multiplexing optical fiber communication in this embodiment can simultaneously monitor the signal-to-noise ratio (SNR) and mode coupling (MC), providing an effective monitoring method for integrated sensing and communication systems; the following new technical means are applied:

[0135] 1. Application of extended circulant matrix:

[0136] The extended circulant matrix is ​​used to model the cyclic frequency characteristics of the signal, which is an innovative application of the existing technology and improves the accuracy of signal processing.

[0137] 2. Innovative calculation of cyclic autocorrelation function (CAF):

[0138] Using CAF to estimate the signal's time delay and phase change is an innovation in signal processing technology, which improves the understanding of signal characteristics.

[0139] 3. The proposal of normalized correlation coefficient δ:

[0140] It is proposed to use the normalized correlation coefficient δ to correct the SNR estimation, which improves the accuracy of SNR estimation.

[0141] 5. Power coupling model of mode coupling:

[0142] A model is established to describe the power exchange between random coupling modes caused by factors such as fiber bending, and the mode coupling effect is studied in depth.

[0143] 6. Resistance to random polarization effects: By using an extended circulant matrix, it is possible to resist random polarization effects and improve the robustness of the system.

[0144] 7. Tolerance to polarization effects: The system is specially designed to have high tolerance to chromatic dispersion (CD), polarization mode dispersion (PMD) and (DGD) in the optical fiber channel. This is particularly important for practical optical communication systems because these effects will seriously affect the integrity of the signal and the accurate estimation of the signal-to-noise ratio.

[0145] In summary, the method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication in this embodiment can achieve the following effects:

[0146] 1. Joint monitoring capabilities:

[0147] Able to monitor both signal-to-noise ratio (SNR) and mode coupling (MC) simultaneously, this joint monitoring capability enables the system to more comprehensively assess communication quality.

[0148] 2. Higher accuracy:

[0149] By using the extended circulant matrix and circulant autocorrelation function (CAF), the signal-to-noise ratio (SNR) can be estimated more accurately, especially in the presence of polarization mode dispersion (PMD), chromatic dispersion (CD) and mode coupling effects.

[0150] 3. Stronger robustness:

[0151] Greater resistance to random polarization effects means more stable performance in the face of various perturbations common in fiber-optic communication systems.

[0152] 4. Simplified data requirements:

[0153] Compared with deep learning methods that require large data sets, the method for jointly estimating the signal-to-noise ratio and mode coupling of mode-division multiplexed optical fiber communications in the embodiment does not require complex data acquisition or synthesis processes, thereby simplifying the implementation and operation of the monitoring system.

[0154] 5. Real-time monitoring capability:

[0155] It enables real-time monitoring, which is critical to ensuring the reliability of communication systems and detecting problems in a timely manner.

[0156] The SNR and mode coupling joint estimation method of mode division multiplexing optical fiber communication in this embodiment is verified by numerical simulation, and the SNR estimation performance under different channel environment conditions is obtained as follows: Figure 4 As shown in the figure, the estimated curve of power coupling coefficient h under different fiber lengths is as follows Figure 5 As shown. Figure 4 and Figure 5 It can be seen that the signal-to-noise ratio and mode coupling joint estimation method of mode division multiplexing optical fiber communication can jointly estimate the signal-to-noise ratio and the power coupling coefficient of mode coupling of the mode division multiplexing optical fiber communication system.

[0157] A computer program for executing the method for jointly estimating the signal-to-noise ratio and mode coupling of mode-division multiplexed optical fiber communication in the present embodiment can be written and written into a computer device or a storage medium. When the computer program is read out and executed, the method for jointly estimating the signal-to-noise ratio and mode coupling of mode-division multiplexed optical fiber communication in the present embodiment is executed, thereby achieving the same technical effect as the method for jointly estimating the signal-to-noise ratio and mode coupling of mode-division multiplexed optical fiber communication in the embodiment.

[0158] It should be noted that, unless otherwise specified, when a feature is referred to as being "fixed" or "connected" to another feature, it may be directly fixed or connected to the other feature, or it may be indirectly fixed or connected to the other feature. In addition, the descriptions of up, down, left, right, etc. used in the present disclosure are only relative to the relative positional relationship of the components of the present disclosure in the accompanying drawings. The singular forms of "a", "" and "the" used in the present disclosure are also intended to include the plural forms, unless the context clearly indicates other meanings. In addition, unless otherwise defined, all technical and scientific terms used in this embodiment have the same meaning as those generally understood by those skilled in the art. The terms used in the specification of this embodiment are only for describing specific embodiments and are not intended to limit the present invention. The term "and / or" used in this embodiment includes any combination of one or more related listed items.

[0159] It should be understood that, although the term first, second, third etc. may be adopted to describe various elements in the present disclosure, these elements should not be limited to these terms. These terms are only used to distinguish the same type of elements from each other. For example, without departing from the scope of the present disclosure, the first element may also be referred to as the second element, and similarly, the second element may also be referred to as the first element. The use of any and all examples or exemplary language ("for example", "such as" etc.) provided by the present embodiment is only intended to better illustrate embodiments of the present invention, and unless otherwise required, the scope of the present invention will not be limited.

[0160] It should be appreciated that embodiments of the present invention may be implemented or enforced by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The method may be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the methods and drawings described in the specific embodiments. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program may be implemented in assembly or machine language. In any case, the language may be a compiled or interpreted language. In addition, the program may be run on a programmed dedicated integrated circuit for this purpose.

[0161] In addition, the operations of the process described in this embodiment may be performed in any suitable order, unless otherwise indicated in this embodiment or otherwise clearly contradicted by the context. The process described in this embodiment (or variations and / or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as a code (e.g., executable instructions, one or more computer programs, or one or more applications) executed on one or more processors in common, by hardware or a combination thereof. A computer program includes a plurality of instructions that may be executed by one or more processors.

[0162] Further, the method can be implemented in any type of computing platform that is operably connected to a suitable computer, including but not limited to a personal computer, a minicomputer, a mainframe, a workstation, a network or distributed computing environment, a separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, etc. Various aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, an optical read and / or write storage medium, a RAM, a ROM, etc., so that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the process described herein. In addition, the machine-readable code, or part thereof, can be transmitted via a wired or wireless network. When such media includes instructions or programs that implement the above steps in conjunction with a microprocessor or other data processor, the invention of this embodiment includes these and other different types of non-transitory computer-readable storage media. When programmed according to the methods and techniques of the present invention, the present invention also includes the computer itself.

[0163] The computer program can be applied to input data to perform the functions of the present embodiment, thereby converting the input data to generate output data stored in a non-volatile memory. The output information can also be applied to one or more output devices such as a display. In a preferred embodiment of the present invention, the converted data represents a physical and tangible object, including a specific visual depiction of the physical and tangible object produced on the display.

[0164] The above are only preferred embodiments of the present invention. The present invention is not limited to the above embodiments. As long as the technical effects of the present invention are achieved by the same means, any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention. Within the scope of protection of the present invention, its technical solutions and / or implementation methods may have various modifications and changes.

Claims

1. A method for jointly estimating signal-to-noise ratio and mode coupling in mode division multiplexing optical fiber communication, characterized in that: The method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication comprises: Acquire multiple groups of communication signals of mode division multiplexing optical fiber communication; For any group of the communication signals, obtaining a spectrum correlation function of the communication signals, determining a cyclic correlation function according to the spectrum correlation function, and determining a signal-to-noise ratio and an optical fiber length according to the cyclic correlation function; The power coupling coefficient value is determined according to the signal-to-noise ratio and the optical fiber length corresponding to each group of the communication signals.

2. The method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication according to claim 1, characterized in that: The method of obtaining multiple groups of communication signals of mode division multiplexing optical fiber communication comprises: Receiving signals of mode division multiplexing optical fiber communication through a coherent receiver under various channel environment conditions respectively; The signals received under each of the channel environment states form a group of communication signals.

3. The method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication according to claim 2, characterized in that: The acquiring of the spectrum correlation function of the communication signal comprises: For any group of the communication signals, a plurality of discrete digital signal components corresponding to the communication signals are obtained; each of the discrete digital signal components has a corresponding polarization multiplexing dimension and a mode multiplexing dimension; For any group of the communication signals, the discrete digital signal components are respectively intercepted according to the same time length, and a plurality of cycle period graphs are determined according to the intercepted signals; For any group of the communication signals, the spectrum correlation function in matrix form is determined using the corresponding plurality of the cyclic periodograms as elements in a matrix.

4. The method for jointly estimating signal-to-noise ratio and mode coupling in mode division multiplexing optical fiber communication according to claim 3, characterized in that: The determining of the cyclic correlation function according to the spectrum correlation function comprises: Performing inverse Fourier transform on the elements in the spectrum correlation function respectively; The cyclic correlation function in matrix form is determined by using the results of inverse Fourier transformation of the elements in the spectrum correlation function as elements in a matrix.

5. The method for jointly estimating signal-to-noise ratio and mode coupling in mode division multiplexing optical fiber communication according to claim 3, characterized in that: Determining the signal-to-noise ratio and the optical fiber length according to the cyclic correlation function comprises: Determining a maximum correlation strength value according to the cyclic correlation function; Obtaining an upper sideband average power and a lower sideband average power of each of the discrete digital signal components; Determining a normalized correlation coefficient according to the maximum value of the correlation strength, the upper sideband average power, and the lower sideband average power; The signal-to-noise ratio is determined according to the normalized correlation coefficient.

6. The method for jointly estimating signal-to-noise ratio and mode coupling in mode division multiplexing optical fiber communication according to claim 5, characterized in that: The normalized correlation coefficient is determined according to the maximum value of the correlation strength, the upper sideband average power and the lower sideband average power, according to the following formula: Wherein, δ is the normalized correlation coefficient, R sum is the maximum value of the correlation strength, P1 is the upper sideband average power, and P2 is the lower sideband average power; The signal-to-noise ratio is determined according to the normalized correlation coefficient according to the following formula: Wherein, SNR is the signal-to-noise ratio.

7. The method for jointly estimating signal-to-noise ratio and mode coupling in mode division multiplexing optical fiber communication according to claim 3, characterized in that: Determining the signal-to-noise ratio and the optical fiber length according to the cyclic correlation function comprises: The fiber length is determined using the CAF-4CDE algorithm.

8. The method for jointly estimating the signal-to-noise ratio and mode coupling in mode division multiplexing optical fiber communication according to any one of claims 1 to 7, characterized in that: Determining the power coupling coefficient value according to the signal-to-noise ratio and the optical fiber length corresponding to each group of the communication signals includes: Performing quadratic fitting or linear fitting according to each of the signal-to-noise ratios and each of the optical fiber lengths; The coefficient value determined by fitting is used as the power coupling coefficient value.

9. A computer device, characterized in that: It comprises a memory and a processor, the memory is used to store at least one program, and the processor is used to load at least one program to execute the method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication as described in any one of claims 1-8.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to execute the method for jointly estimating the signal-to-noise ratio and mode coupling of mode division multiplexing optical fiber communication as described in any one of claims 1 to 8 when executed by the processor.

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