Optical fiber communication signal quality improvement method and system based on adaptive compensation

Abstract

This invention relates to the field of optical fiber communication technology, and more particularly to a method and system for improving the signal quality of optical fiber communication based on adaptive compensation. The method performs joint time-domain and frequency-domain analysis on the optical signal to be processed, extracts distortion characteristic parameters, and maps them to a set of compensation coefficients to construct a compensation function for inverse signal compensation. By evaluating the quality of the compensated signal and comparing it with a preset benchmark, the mapping rules of the compensation coefficients are dynamically adjusted, achieving adaptive and precise compensation for the nonlinearity and dispersion effects of the transmission medium, effectively improving signal quality and system performance.

Description

Technical Field

[0001] This invention relates to the field of optical fiber communication technology, and in particular to a method and system for improving the quality of optical fiber communication signals based on adaptive compensation. Background Technology

[0002] In fiber optic communication systems, signals are affected by both nonlinear and dispersion effects of the transmission medium during long-distance transmission, leading to signal waveform distortion and consequently increased bit error rate and degraded system performance. To address this issue, existing technologies typically employ fixed or pre-configured compensation schemes. A common approach is to deploy digital signal processing modules at the transmitter or receiver, utilizing pre-distortion or post-equalization algorithms based on fixed models to combat known link impairments. For example, applying compensation opposite to the predicted distortion using lookup tables or fixed digital filters can attempt to recover the original signal waveform. These methods rely on prior knowledge of link characteristics or statistical models of typical parameters.

[0003] However, such conventional practices have significant drawbacks. The transmission characteristics of fiber optic links are not static; they are affected by various dynamic factors such as ambient temperature fluctuations, equipment aging, link reconfiguration, and changes in service load, causing their nonlinear and dispersion characteristics to drift over time. Compensation schemes based on fixed models cannot track these dynamic changes, and their compensation coefficients, once set, are difficult to adjust adaptively. When the link state deviates from the preset model, the fixed compensation function becomes inaccurate and may even introduce additional compensation errors, leading to further degradation of signal quality. This not only limits long-term stability and transmission capacity in complex and variable environments but also increases the cost and difficulty of manual adjustment and optimization in network operation and maintenance. Summary of the Invention

[0004] The embodiments of the present invention provide a method and system for improving the quality of optical fiber communication signals based on adaptive compensation, which can solve the problems in the prior art.

[0005] A first aspect of the present invention provides a method for improving the quality of optical fiber communication signals based on adaptive compensation, comprising: Acquire the optical signal to be processed transmitted through the fiber optic communication link; The optical signal to be processed is subjected to joint time-domain and frequency-domain analysis to extract distortion characteristic parameters representing the nonlinear and dispersion effects of the transmission medium; The distortion characteristic parameters are mapped to a set of compensation coefficients to obtain a compensation function relationship representing the signal degradation process. The set of compensation coefficients is set separately for different distortion types. The compensation coefficient set is applied to the optical signal to be processed, and the signal waveform is subjected to inverse compensation processing to obtain the compensated optical signal. The bit error rate and signal-to-noise ratio of the compensated optical signal are jointly evaluated to generate a quality evaluation result characterizing the compensation effect. Based on the deviation between the quality assessment result and the preset quality benchmark, an update instruction is generated to adjust the set of compensation coefficients in the compensation function relationship. Based on the update instruction, the mapping rule from the distortion feature parameters to the set of compensation coefficients is dynamically corrected.

[0006] The optical signal to be processed is subjected to joint time-domain and frequency-domain analysis to extract distortion characteristic parameters representing the nonlinear and dispersion effects of the transmission medium, including: The time-domain waveform of the optical signal to be processed is sampled, and the amplitude change rate and phase jump between adjacent sampling points are calculated to determine the waveform distortion location caused by the nonlinear effect of the transmission medium, and the time-domain distortion feature components corresponding to the waveform distortion location are extracted; The optical signal to be processed is subjected to frequency domain transformation to obtain the spectral distribution. By analyzing the offset and spread of each frequency component in the spectral distribution relative to the reference spectrum, the spectral spread region caused by the dispersion effect of the transmission medium is determined, and the frequency domain distortion feature components corresponding to the spectral spread region are extracted. The correspondence between the time-domain distortion feature components and the frequency-domain distortion feature components is determined, and a joint distortion feature vector is generated by cross-mapping the distribution of the waveform distortion position on the time axis with the distribution of the spectral spread region on the frequency axis. Based on the relative weights of the temporal distortion feature components and the frequency-domain distortion feature components in the joint distortion feature vector, the dominant distortion type of the optical signal to be processed is determined, and the distortion feature parameters are obtained based on the temporal distortion feature components, the frequency-domain distortion feature components, and the dominant distortion type.

[0007] Mapping the distortion characteristic parameters to a set of compensation coefficients yields a compensation function relationship representing the signal degradation process, including: The distortion feature parameters are decomposed into nonlinear distortion components and dispersion distortion components based on the dominant distortion type identifier in the distortion feature parameters; A first set of compensation coefficients is calculated for the nonlinear distortion component to counteract the nonlinear effect, and a second set of compensation coefficients is calculated for the dispersion distortion component to counteract the dispersion effect. The compensation coefficient set is obtained based on the first set of compensation coefficients and the second set of compensation coefficients. Each compensation coefficient in the compensation coefficient set is constrained by limiting the gradient of the phase difference change between adjacent compensation coefficients to be less than the phase continuity threshold, and limiting the range of the ratio between the amplitude adjustment factors corresponding to each compensation coefficient to satisfy the amplitude consistency constraint, thus obtaining a constrained compensation coefficient set that satisfies the phase continuity threshold and the amplitude consistency constraint; Based on the constrained set of compensation coefficients, a nonlinear compensation mapping function is generated to map the nonlinear distortion component to the first set of compensation coefficients, and a dispersion compensation mapping function is generated to map the dispersion distortion component to the second set of compensation coefficients. The relationship between the compensation functions is obtained based on the nonlinear compensation mapping function and the dispersion compensation mapping function.

[0008] A first set of compensation coefficients is calculated for the nonlinear distortion component to counteract the nonlinear effect, and a second set of compensation coefficients is calculated for the dispersion distortion component to counteract the dispersion effect. The compensation coefficient set is obtained based on the first and second compensation coefficient sets, including: The amplitude distortion parameter and the apparent phase distortion parameter are extracted from the nonlinear distortion component, and the delay distortion parameter and the spectral distortion parameter are extracted from the dispersion distortion component. Based on the coupling relationship between the amplitude distortion parameter and the phase distortion parameter, an amplitude compensation coefficient for canceling the amplitude distortion parameter and a phase compensation coefficient for canceling the phase distortion parameter are determined, and the amplitude compensation coefficient and the phase compensation coefficient are combined to obtain the first compensation coefficient group; Based on the correlation between the delay distortion parameter and the spectral distortion parameter, a delay compensation coefficient for compensating the delay distortion parameter and a spectral compensation coefficient for compensating the spectral distortion parameter are determined, and the delay compensation coefficient and the spectral compensation coefficient are combined to obtain the second compensation coefficient group; The first set of compensation coefficients is marked as a nonlinear compensation channel, and the second set of compensation coefficients is marked as a dispersion compensation channel. The compensation coefficient set is obtained based on the nonlinear compensation channel and the dispersion compensation channel.

[0009] The compensation coefficient set is applied to the optical signal to be processed, and the signal waveform is subjected to inverse compensation processing to obtain a compensated optical signal. The bit error rate and signal-to-noise ratio of the compensated optical signal are jointly evaluated to generate a quality evaluation result characterizing the compensation effect, including: The first compensation coefficient group in the compensation coefficient set is applied to the time-domain waveform of the optical signal to be processed, and the amplitude is reversed and the phase is reversed to generate a nonlinear compensation intermediate signal. The second set of compensation coefficients in the compensation coefficient set is applied to the frequency domain representation of the nonlinear compensation intermediate signal, and the frequency domain representation is subjected to delay inverse compensation and spectrum inverse convergence to generate the compensated optical signal; The compensated optical signal is demodulated to obtain a demodulation result. Based on the demodulation result and a preset reference sequence, a bit error rate index characterizing the reliability of signal transmission is obtained. The signal power and noise power of the compensated optical signal are measured, and the ratio of the signal power to the noise power is calculated to obtain the signal-to-noise ratio (SNR) index, which characterizes the signal clarity. Determine the joint evaluation relationship between the bit error rate index and the signal-to-noise ratio index, and generate a quality evaluation result that comprehensively characterizes the quality of the compensated optical signal based on the joint evaluation relationship.

[0010] Determine the joint evaluation relationship between the bit error rate index and the signal-to-noise ratio index, and generate a quality evaluation result that comprehensively characterizes the quality of the compensated optical signal based on the joint evaluation relationship, including: Based on the bit error rate index, determine the bit error distribution parameter reflecting the characteristics of the transmission error distribution and the noise interference parameter reflecting the degree of noise interference in the signal-to-noise ratio index; The joint evaluation relationship is generated based on the correlation between the bit error distribution parameters and the noise interference parameters; Based on the joint evaluation relationship, the impact of the bit error rate (BER) index on signal transmission reliability and the impact of the signal-to-noise ratio (SNR) index on signal reception clarity are analyzed to determine the BER weighting coefficient and the SNR weighting coefficient used to quantify the importance of the BER index. A transmission reliability score is generated based on the bit error rate index and the bit error rate weighting coefficient, and a reception clarity score is generated based on the signal-to-noise ratio index and the signal-to-noise ratio weighting coefficient. The transmission reliability score and the reception clarity score are fused based on the joint evaluation relationship to generate the quality evaluation result.

[0011] Based on the deviation between the quality assessment result and the preset quality benchmark, an update instruction is generated to adjust the set of compensation coefficients in the compensation function relationship. Based on the update instruction, the mapping rule from the distortion characteristic parameters to the set of compensation coefficients is dynamically corrected, including: The quality assessment result is compared with the preset quality benchmark, and the deviation of the quality assessment result relative to the preset quality benchmark is calculated. Based on the deviation value, a bit error rate deviation component and a signal-to-noise ratio deviation component are determined, and a deviation quantification index is generated based on the bit error rate deviation component and the signal-to-noise ratio deviation component. Based on the relationship between the deviation quantification index and each compensation coefficient in the compensation coefficient set, the first target compensation coefficient that needs to be adjusted for the bit error rate deviation component and the second target compensation coefficient that needs to be adjusted for the signal-to-noise ratio deviation component are determined. The adjustment range of the first target compensation coefficient and the adjustment range of the second target compensation coefficient are calculated based on the deviation quantification index. The first target compensation coefficient and the adjustment range are used as the first update instruction for nonlinear compensation, and the second target compensation coefficient and the adjustment range are used as the second update instruction for dispersion compensation. The mapping rule is updated based on the first update instruction and the second update instruction.

[0012] A second aspect of the present invention provides an optical fiber communication signal quality improvement system based on adaptive compensation, comprising: The signal acquisition unit is used to acquire the optical signal to be processed transmitted through the optical fiber communication link. The feature extraction unit is used to perform joint time-domain and frequency-domain analysis on the optical signal to be processed, and extract distortion feature parameters that represent the nonlinear effects and dispersion effects of the transmission medium. The compensation mapping unit is used to map the distortion feature parameters to a set of compensation coefficients to obtain a compensation function relationship representing the signal degradation process. The set of compensation coefficients is set separately for different distortion types. The signal compensation unit is used to apply the compensation coefficient set to the optical signal to be processed, perform inverse compensation processing on the signal waveform to obtain the compensated optical signal, perform joint evaluation of the bit error rate and signal-to-noise ratio on the compensated optical signal, and generate a quality evaluation result characterizing the compensation effect. The dynamic adjustment unit is used to generate an update instruction for adjusting the set of compensation coefficients in the compensation function relationship based on the deviation between the quality assessment result and the preset quality benchmark, and to dynamically correct the mapping rule of the distortion feature parameters to the set of compensation coefficients based on the update instruction.

[0013] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0014] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0015] This invention significantly improves the signal transmission quality and system adaptability of optical fiber communication systems. Through joint time-domain and frequency-domain analysis, it can comprehensively and accurately extract distortion characteristic parameters caused by nonlinear and dispersion effects of the transmission medium, providing accurate quantitative basis for subsequent compensation. By mapping the distortion characteristic parameters to sets of compensation coefficients set for different distortion types, a compensation function relationship that accurately characterizes the signal degradation process is constructed, enabling targeted modeling of complex mixed damage.

[0016] This invention utilizes the compensation function relationship to perform inverse compensation processing on the optical signal waveform, effectively offsetting or reducing the distortion accumulated during signal transmission and directly improving the waveform integrity of the received signal. A joint evaluation of the bit error rate and signal-to-noise ratio of the compensated signal generates a comprehensive quality assessment result characterizing the compensation effect, providing an objective, multi-dimensional, real-time measurement of system performance.

[0017] This invention dynamically generates compensation coefficient update instructions based on the deviation between quality assessment results and preset benchmarks, and corrects the mapping rules from distortion features to compensation coefficients accordingly, achieving closed-loop online optimization of the compensation strategy. This mechanism enables automatic adaptation to changes and aging of fiber optic link parameters, as well as dynamic adjustments to network service modes, continuously maintaining optimal compensation effects. The entire solution forms a complete technical closed loop from feature extraction, compensation modeling, effect evaluation to parameter adaptation, improving signal quality while enhancing the long-term stability and intelligent operation and maintenance level of the communication system. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the optical fiber communication signal quality improvement method based on adaptive compensation according to an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram of the process for generating quality assessment results according to an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0022] Figure 1 This is a flowchart illustrating the optical fiber communication signal quality improvement method based on adaptive compensation, according to an embodiment of the present invention. Figure 1 As shown, the method includes: Acquire the optical signal to be processed transmitted through the fiber optic communication link; The optical signal to be processed is subjected to joint time-domain and frequency-domain analysis to extract distortion characteristic parameters representing the nonlinear and dispersion effects of the transmission medium; The distortion characteristic parameters are mapped to a set of compensation coefficients to obtain a compensation function relationship representing the signal degradation process. The set of compensation coefficients is set separately for different distortion types. The compensation coefficient set is applied to the optical signal to be processed, and the signal waveform is subjected to inverse compensation processing to obtain the compensated optical signal. The bit error rate and signal-to-noise ratio of the compensated optical signal are jointly evaluated to generate a quality evaluation result characterizing the compensation effect. Based on the deviation between the quality assessment result and the preset quality benchmark, an update instruction is generated to adjust the set of compensation coefficients in the compensation function relationship. Based on the update instruction, the mapping rule from the distortion feature parameters to the set of compensation coefficients is dynamically corrected.

[0023] The optical signal to be processed is subjected to joint time-domain and frequency-domain analysis to extract distortion characteristic parameters representing the nonlinear and dispersion effects of the transmission medium, including: The time-domain waveform of the optical signal to be processed is sampled, and the amplitude change rate and phase jump between adjacent sampling points are calculated to determine the waveform distortion location caused by the nonlinear effect of the transmission medium, and the time-domain distortion feature components corresponding to the waveform distortion location are extracted; The optical signal to be processed is subjected to frequency domain transformation to obtain the spectral distribution. By analyzing the offset and spread of each frequency component in the spectral distribution relative to the reference spectrum, the spectral spread region caused by the dispersion effect of the transmission medium is determined, and the frequency domain distortion feature components corresponding to the spectral spread region are extracted. The correspondence between the time-domain distortion feature components and the frequency-domain distortion feature components is determined, and a joint distortion feature vector is generated by cross-mapping the distribution of the waveform distortion position on the time axis with the distribution of the spectral spread region on the frequency axis. Based on the relative weights of the temporal distortion feature components and the frequency-domain distortion feature components in the joint distortion feature vector, the dominant distortion type of the optical signal to be processed is determined, and the distortion feature parameters are obtained based on the temporal distortion feature components, the frequency-domain distortion feature components, and the dominant distortion type.

[0024] After acquiring the optical signal to be processed in the fiber optic communication link, a high-speed analog-to-digital converter is used to sample the time-domain waveform of the optical signal. The sampling frequency is set to more than four times the signal symbol rate to ensure complete waveform details are captured. For the acquired discrete sampling point sequence, the amplitude change rate between adjacent sampling points is calculated. Specifically, the instantaneous change rate is obtained by dividing the difference between the amplitude value of the current sampling point and the amplitude value of the previous sampling point by the sampling time interval. At the same time, the phase jump variable between adjacent sampling points is extracted. The phase difference value is calculated by performing a phase unwrapping operation on the complex domain optical field signal. When the amplitude change rate exceeds a preset threshold or the phase jump variable exceeds a certain threshold within a single sampling period... When the waveform is measured in radians, this location is marked as a waveform distortion location. These distortion locations reflect the effects of signal self-phase modulation and cross-phase modulation caused by nonlinear phenomena such as the fiber Kerr effect. At the marked distortion location, the amplitude and phase sequences of five consecutive sampling points are extracted to constitute the time-domain distortion characteristic components of that location.

[0025] A Fast Fourier Transform (FFT) is performed on the same optical signal to convert the time-domain signal to the frequency domain, obtaining the spectral distribution. The measured spectrum is compared frequency-by-frequency with a reference spectrum under ideal transmission conditions. The reference spectrum is calculated using the theoretical bandwidth of the modulation format at the transmitting end and pulse shaping parameters. For each frequency component in the spectrum, the offset of its center frequency relative to the corresponding component in the reference spectrum is calculated. This offset quantifies the degree of frequency drift caused by dispersion. Simultaneously, the 3dB bandwidth spread of each frequency component is measured, and the spectral spread caused by dispersion is quantified by the ratio of the measured bandwidth to the reference bandwidth. When the frequency offset exceeds 5% of the symbol rate, or the bandwidth spread exceeds 1.2 times the reference value, the frequency band is marked as a spectral spread region. Within the marked region, the frequency coordinates, power spectral density values, and phase response curves are extracted to form the frequency domain distortion characteristic components.

[0026] A correlation mechanism is established between the time-domain waveform distortion location and the frequency-domain spectral spread region. The time coordinates of the time-domain distortion location are converted into frequency-domain characteristic frequencies through the duality of Fourier transform, and the frequency coordinates of the frequency-domain spread region are mapped back to the time-domain characteristic time points through inverse transform. By calculating the distribution density function of the time-domain distortion location throughout the sampling window and the proportion of the spectral spread region within the Nyquist bandwidth, a dual-domain cross-mapping matrix is ​​constructed. The rows of this matrix correspond to the time-domain features, the columns correspond to the frequency-domain features, and the matrix element values ​​represent the correlation strength between the two. The time-domain distortion feature components and the frequency-domain distortion feature components are weighted and concatenated according to the correlation strength to form a joint distortion feature vector containing the time-domain amplitude sequence, the time-domain phase sequence, the frequency-domain offset sequence, and the frequency-domain spread sequence.

[0027] The energy proportions of the time-domain and frequency-domain components in the joint distortion feature vector are calculated. The time-domain component energy is calculated by summing the squares of the amplitude deviations at the distortion locations, and the frequency-domain component energy is obtained by integrating the power spectral density in the spectral spread region. When the time-domain component energy proportion exceeds 60% of the total energy, the dominant distortion type is determined to be nonlinear effect-dominated; when the frequency-domain component energy proportion exceeds 60%, it is determined to be dispersion effect-dominated; when both energy proportions are between 40% and 60%, it is determined to be a mixed distortion type. The extracted time-domain distortion feature components, frequency-domain distortion feature components, and the determined dominant distortion type are encapsulated into structured distortion feature parameters. These parameters contain numerical arrays and type identifiers for use in subsequent compensation coefficient mapping.

[0028] Mapping the distortion characteristic parameters to a set of compensation coefficients yields a compensation function relationship representing the signal degradation process, including: The distortion feature parameters are decomposed into nonlinear distortion components and dispersion distortion components based on the dominant distortion type identifier in the distortion feature parameters; A first set of compensation coefficients is calculated for the nonlinear distortion component to counteract the nonlinear effect, and a second set of compensation coefficients is calculated for the dispersion distortion component to counteract the dispersion effect. The compensation coefficient set is obtained based on the first set of compensation coefficients and the second set of compensation coefficients. Each compensation coefficient in the compensation coefficient set is constrained by limiting the gradient of the phase difference change between adjacent compensation coefficients to be less than the phase continuity threshold, and limiting the range of the ratio between the amplitude adjustment factors corresponding to each compensation coefficient to satisfy the amplitude consistency constraint, thus obtaining a constrained compensation coefficient set that satisfies the phase continuity threshold and the amplitude consistency constraint; Based on the constrained set of compensation coefficients, a nonlinear compensation mapping function is generated to map the nonlinear distortion component to the first set of compensation coefficients, and a dispersion compensation mapping function is generated to map the dispersion distortion component to the second set of compensation coefficients. The relationship between the compensation functions is obtained based on the nonlinear compensation mapping function and the dispersion compensation mapping function.

[0029] After obtaining the distortion characteristic parameters, a distortion type identification operation is performed. This involves analyzing the spectral distortion mode and time-domain waveform distortion characteristics within the distortion characteristic parameters to extract the dominant distortion type identifier. When asymmetric broadening of high-frequency components is detected, accompanied by power-dependent distortion, it is marked as nonlinear distortion dominant; when a linear phase shift is detected in the frequency components and the group velocity dispersion coefficient exceeds a threshold, it is marked as dispersion distortion dominant. Based on this dominant distortion type identifier, the distortion characteristic parameters are decomposed into two independent components: the nonlinear distortion component includes parameters such as self-phase modulation depth, cross-phase modulation coefficient, and four-wave mixing intensity; the dispersion distortion component includes dispersion accumulation, polarization mode dispersion value, and higher-order dispersion term coefficients.

[0030] To address the nonlinear distortion component, a correlation model between nonlinear phase shift and optical power is established. When calculating the first set of compensation coefficients, a phase compensation amount is set for each frequency point. This phase compensation amount is the negative of the nonlinear phase shift, and the amplitude compensation factor is set according to the degree of power loss. Specifically, when the self-phase modulation depth is... When, the phase part of the corresponding compensation coefficient is set to The gain value for the amplitude component is determined based on the transmission distance and fiber loss coefficient. For the dispersion component, the dispersion compensation is constructed by multiplying the cumulative dispersion by the transmission distance. When calculating the second set of compensation coefficients, a phase correction proportional to the square of the frequency is applied to each frequency component; the correction amount is determined by both the dispersion coefficient and the fiber length. The first and second sets of compensation coefficients are then aligned by frequency index and merged to form the initial set of compensation coefficients.

[0031] Constraint processing is performed on the initial set of compensation coefficients. First, the phase difference between corresponding compensation coefficients at adjacent frequency points is checked, and the phase change gradient is calculated. If the absolute value of the phase difference between two adjacent compensation coefficients exceeds a preset phase continuity threshold, for example, exceeding... For radians, linear interpolation is used to smooth the interval, ensuring a gradual phase transition. Next, the consistency of the amplitude adjustment factors is checked. The amplitude adjustment factors corresponding to all compensation coefficients are extracted, and the ratio between adjacent factors is calculated. This ratio is required to fall within the amplitude consistency constraint range, for example, limited to between 0.8 and 1.2. If a ratio is detected to be outside this range, abnormal amplitude adjustment factors are either smoothed or boosted to meet the constraints. After these constraint processes, a set of constrained compensation coefficients is obtained, where each coefficient exhibits smooth and continuous characteristics in both the phase and amplitude dimensions.

[0032] A mapping function is constructed based on a constrained set of compensation coefficients. The nonlinear compensation mapping function represents the correspondence from the nonlinear distortion component to the first set of compensation coefficients, established using a piecewise linear function or polynomial fitting method. When the self-phase modulation depth in the nonlinear distortion component is within a specific interval, the mapping function outputs the first set of compensation coefficients for that interval. The dispersion compensation mapping function represents the correspondence from the dispersion distortion component to the second set of compensation coefficients, typically using a frequency domain transfer function, whose coefficients are directly determined by the dispersion accumulation. The nonlinear and dispersion compensation mapping functions are cascaded to form a complete compensation function relationship. This compensation function relationship receives distortion characteristic parameters as input and outputs a complete set of compensation coefficients containing phase compensation and amplitude compensation terms, used for subsequent inverse compensation operations on the optical signal to be processed.

[0033] A first set of compensation coefficients is calculated for the nonlinear distortion component to counteract the nonlinear effect, and a second set of compensation coefficients is calculated for the dispersion distortion component to counteract the dispersion effect. The compensation coefficient set is obtained based on the first and second compensation coefficient sets, including: The amplitude distortion parameter and the apparent phase distortion parameter are extracted from the nonlinear distortion component, and the delay distortion parameter and the spectral distortion parameter are extracted from the dispersion distortion component. Based on the coupling relationship between the amplitude distortion parameter and the phase distortion parameter, an amplitude compensation coefficient for canceling the amplitude distortion parameter and a phase compensation coefficient for canceling the phase distortion parameter are determined, and the amplitude compensation coefficient and the phase compensation coefficient are combined to obtain the first compensation coefficient group; Based on the correlation between the delay distortion parameter and the spectral distortion parameter, a delay compensation coefficient for compensating the delay distortion parameter and a spectral compensation coefficient for compensating the spectral distortion parameter are determined, and the delay compensation coefficient and the spectral compensation coefficient are combined to obtain the second compensation coefficient group; The first set of compensation coefficients is marked as a nonlinear compensation channel, and the second set of compensation coefficients is marked as a dispersion compensation channel. The compensation coefficient set is obtained based on the nonlinear compensation channel and the dispersion compensation channel.

[0034] After obtaining the nonlinear distortion and dispersion distortion components, corresponding compensation coefficients need to be calculated for each distortion type. For the nonlinear distortion component, the amplitude distortion parameter is first extracted. This parameter reflects the degree of amplitude distortion of the signal envelope caused by the nonlinear Kerr effect of the optical fiber during transmission. Specifically, the extraction method involves statistically analyzing the constellation diagram of the received signal and calculating the radial offset between the actual received symbol and the ideal symbol position. This offset is the amplitude distortion parameter. Simultaneously, the phase distortion parameter is extracted, which characterizes the rotation angle deviation of the signal carrier phase caused by self-phase modulation and cross-phase modulation. This is obtained by calculating the angle deviation between the received symbol and the ideal symbol.

[0035] There is a coupling relationship between amplitude distortion parameters and phase distortion parameters, stemming from the physical nature of nonlinear effects in optical fibers. In single-mode fibers, changes in signal power simultaneously cause changes in both the real and imaginary parts of the refractive index; the former leads to phase shift, while the latter causes amplitude attenuation. Therefore, this coupling effect needs to be considered when determining the compensation coefficients. The amplitude compensation coefficient is calculated by multiplying the negative reciprocal of the amplitude distortion parameter by a correction factor, which is dynamically adjusted based on the current signal power. The phase compensation coefficient uses the negative value of the phase distortion parameter as its base value and is superimposed with a coupling correction term calculated based on the amplitude distortion parameter. The coefficient of the correction term is determined by offline measurement of the fiber's nonlinearity coefficient. The amplitude and phase compensation coefficients are combined in the order of compensating for amplitude first, then phase, to form the first set of compensation coefficients.

[0036] For the dispersion distortion component, the delay distortion parameter is extracted. This parameter quantifies the difference in transmission delay caused by dispersion effects among different frequency components. The extraction method involves performing a Fourier transform on the received signal and calculating the relative delay of each frequency component with respect to the center frequency. The distribution characteristics of the delay difference are the delay distortion parameter. The spectral distortion parameter reflects the spectral broadening and energy distribution changes caused by dispersion. It is extracted by comparing the differences between the received signal spectrum and the transmitted signal spectrum.

[0037] There is a definite correlation between delay distortion parameters and spectral distortion parameters. This correlation is determined by both the fiber dispersion coefficient and the transmission distance. The delay compensation coefficient is calculated using the design method of a dispersion compensation filter. Digital filter coefficients with opposite dispersion characteristics are constructed based on the delay distortion parameters, and the filter order is adaptively selected according to the magnitude of the dispersion. The spectral compensation coefficient is obtained through frequency domain equalization. The ratio of the ideal spectrum to the actual spectrum is calculated at each frequency point; this ratio is the spectral compensation coefficient for that frequency point. The delay compensation coefficient and the spectral compensation coefficient are combined according to the frequency domain processing flow to form a second set of compensation coefficients.

[0038] To facilitate selective application in subsequent signal processing, the first set of compensation coefficients is designated as the nonlinear compensation channel, specifically designed to handle signal distortion caused by fiber nonlinearity. The second set of compensation coefficients is designated as the dispersion compensation channel, specifically designed to handle signal broadening and inter-symbol interference caused by dispersion effects. The compensation coefficient sets of the two channels constitute a complete compensation coefficient set. In practical applications, the corresponding channel can be activated based on the main type of distortion detected, or the two channels can be cascaded in the order of dispersion compensation followed by nonlinear compensation to achieve comprehensive compensation for complex transmission impairments.

[0039] Figure 2 This is a schematic diagram illustrating the process of generating quality assessment results according to an embodiment of the present invention. Figure 2 As shown, the compensation coefficient set is applied to the optical signal to be processed, and the signal waveform is subjected to inverse compensation processing to obtain a compensated optical signal. The bit error rate and signal-to-noise ratio of the compensated optical signal are jointly evaluated to generate a quality assessment result characterizing the compensation effect, including: The first compensation coefficient group in the compensation coefficient set is applied to the time-domain waveform of the optical signal to be processed, and the amplitude is reversed and the phase is reversed to generate a nonlinear compensation intermediate signal. The second set of compensation coefficients in the compensation coefficient set is applied to the frequency domain representation of the nonlinear compensation intermediate signal, and the frequency domain representation is subjected to delay inverse compensation and spectrum inverse convergence to generate the compensated optical signal; The compensated optical signal is demodulated to obtain a demodulation result. Based on the demodulation result and a preset reference sequence, a bit error rate index characterizing the reliability of signal transmission is obtained. The signal power and noise power of the compensated optical signal are measured, and the ratio of the signal power to the noise power is calculated to obtain the signal-to-noise ratio (SNR) index, which characterizes the signal clarity. Determine the joint evaluation relationship between the bit error rate index and the signal-to-noise ratio index, and generate a quality evaluation result that comprehensively characterizes the quality of the compensated optical signal based on the joint evaluation relationship.

[0040] After acquiring the optical signal to be processed, the first set of compensation coefficients is extracted from the compensation coefficient set. This set of coefficients is specifically designed for the nonlinear Kerr effect and self-phase modulation phenomena in optical fiber transmission. The first set of compensation coefficients includes the amplitude compensation factor. and phase compensation factor The subscript i represents the discrete sampling point number. The time-domain waveform of the optical signal to be processed is represented in complex form. ,in For amplitude components, The phase component. The amplitude reverse adjustment process is achieved through calculation. Achieve, compensation factor Based on pre-calibration of transmission distance and signal power, the typical value range is 0.85 to 1.15. Phase inversion correction is performed through calculation. Completed, phase compensation amount The ratio of dispersion length to nonlinear length is used to determine this value, which can reach over 0.5 radians in long-distance transmission scenarios. After time-domain compensation, the nonlinear compensated intermediate signal is obtained. .

[0041] Perform a Fast Fourier Transform on the nonlinear compensation intermediate signal to convert it to the frequency domain and obtain its spectral representation. Extract the second set of compensation coefficients from the set of compensation coefficients; this set contains the group delay compensation parameters. and spectral shaping coefficients Delay inverse compensation is achieved by applying phase correction to each frequency component. Implementation, in which The frequency-dependent delay characterizes the dispersion-induced delay; this parameter is calculated based on the fiber dispersion coefficient D and the transmission distance L. The inverse spectral convergence process multiplies the frequency domain representation by a shaping coefficient. Shaping coefficient This coefficient is used to suppress spectral broadening and exhibits Gaussian attenuation characteristics in the edge regions of the signal bandwidth. After frequency domain compensation is completed, the signal is converted back to the time domain using an inverse fast Fourier transform to obtain the compensated optical signal.

[0042] After compensation, the optical signal is sent to the coherent demodulation module, where it undergoes coherent mixing using a local oscillator. Digital sampling is then performed via an analog-to-digital converter. Demodulation processing includes two stages: carrier phase recovery and symbol decision. Phase recovery uses the Viterbi-Viterbi algorithm to eliminate residual phase noise, while symbol decision determines the received symbol sequence based on constellation mapping rules. The received symbol sequence is compared bit-by-bit with a known pseudo-random reference sequence from the transmitter, and the number of inconsistent bits is counted. The bit error rate (BER) is calculated as the ratio of erroneous bits to the total number of bits. Typical optical communication systems require this BER to be below a certain value. .

[0043] Signal power measurement is achieved by time averaging the squared amplitude of the compensated optical signal. The measurement window length is set to an integer multiple of the symbol period to ensure statistical validity. Noise power measurement utilizes signal idle time slots or pilot symbol intervals; the power values ​​collected within these intervals primarily reflect amplifier spontaneous emission noise and receiver thermal noise. The signal-to-noise ratio (SNR) is defined as the signal power... With noise power The ratio is usually expressed in decibels. For a high-quality optical communication link, this indicator should be greater than 20 decibels.

[0044] When establishing a joint evaluation relationship, a weighted fusion mechanism is introduced, and a bit error rate weight is set. With signal-to-noise ratio weight ,satisfy The bit error rate (BER) metric is normalized and then weighted and summed with the normalized signal-to-noise ratio (SNR) metric to generate a comprehensive quality score. ,in and This is the normalization function. The quality assessment results are output in numerical form, which directly reflects the transmission performance of the compensated optical signal and provides a quantitative basis for subsequent adaptive adjustment of compensation parameters.

[0045] Determine the joint evaluation relationship between the bit error rate index and the signal-to-noise ratio index, and generate a quality evaluation result that comprehensively characterizes the quality of the compensated optical signal based on the joint evaluation relationship, including: Based on the bit error rate index, determine the bit error distribution parameter reflecting the characteristics of the transmission error distribution and the noise interference parameter reflecting the degree of noise interference in the signal-to-noise ratio index; The joint evaluation relationship is generated based on the correlation between the bit error distribution parameters and the noise interference parameters; Based on the joint evaluation relationship, the impact of the bit error rate (BER) index on signal transmission reliability and the impact of the signal-to-noise ratio (SNR) index on signal reception clarity are analyzed to determine the BER weighting coefficient and the SNR weighting coefficient used to quantify the importance of the BER index. A transmission reliability score is generated based on the bit error rate index and the bit error rate weighting coefficient, and a reception clarity score is generated based on the signal-to-noise ratio index and the signal-to-noise ratio weighting coefficient. The transmission reliability score and the reception clarity score are fused based on the joint evaluation relationship to generate the quality evaluation result.

[0046] When evaluating the quality of compensated optical signals, a joint evaluation mechanism needs to be established from two dimensions: bit error rate (BER) and signal-to-noise ratio (SNR). After obtaining the BER of the compensated optical signal, the time interval sequence of bit error occurrences is calculated by statistically analyzing the distribution of erroneous symbols within a continuous time window. Probability density analysis is then performed on this time interval sequence to extract the proportion of time periods where bit errors occur in clusters and the variance of the discrete distribution. These two factors together constitute the bit error distribution parameter. This parameter reflects whether the bit errors occur in a bursty, concentrated manner or are randomly distributed. Burst-type bit errors usually indicate that the compensation algorithm does not adequately handle distortion in a specific frequency band.

[0047] Simultaneously, regarding the signal-to-noise ratio (SNR) metric, the signal power spectral density and noise power spectral density are sampled at the receiver. Local SNR values ​​at different frequency components are calculated, and the number of frequency bands below a set threshold and their corresponding power percentages are statistically analyzed to generate noise interference parameters. This parameter quantifies the degree to which noise penetrates the effective signal. When noise is mainly concentrated in the high-frequency band, it indicates that dispersion compensation introduces additional high-frequency noise.

[0048] A correlation analysis model was established between the bit error rate distribution parameter and the noise interference parameter. The Pearson correlation coefficients of the two parameters were calculated under different transmission distances and modulation formats. When the absolute value of the correlation coefficient exceeds 0.6, a strong coupling relationship is considered to exist between the two parameters. This coupling relationship constitutes the mathematical basis for the joint evaluation relationship, indicating that the deterioration of the bit error rate and the decrease in the signal-to-noise ratio are often caused by the same compensation defects.

[0049] Based on this joint evaluation relationship, the impact of bit error rate (BER) on system transmission reliability is analyzed. For fiber optic links carrying critical business data, even a single bit error can trigger data retransmission. Therefore, the impact of the BER is quantified as the probability of transmission interruption. Signal-to-noise ratio (SNR) directly affects the stability of the receiver's decision threshold. For every 3 dB decrease in SNR, the symbol decision error rate approximately doubles. This relationship quantifies the impact of SNR on reception clarity. The normalized transmission interruption probability is used as the BER weighting coefficient, with a value ranging from 0.4 to 0.7. The reciprocal of the increase factor of the decision error rate is used as the SNR weighting coefficient, with a value ranging from 0.3 to 0.6. The sum of the two weighting coefficients is normalized to 1 to ensure the balance of the evaluation system.

[0050] When calculating the transmission reliability score, the current bit error rate is compared with the industry standard value. If the measured bit error rate is... The order of magnitude, the standard requirement is If the magnitude is small, the initial reliability score is 75 points. This score is multiplied by the bit error rate weighting coefficient to obtain the weighted reliability score. The receive sharpness score is based on the signal-to-noise ratio (SNR) in decibels. A linear mapping is used to convert the SNR into a percentage score, with each 1 dB increase in SNR corresponding to an additional 5 points. This score is multiplied by the SNR weighting coefficient to form the weighted sharpness score.

[0051] During the fusion operation, the fusion strategy is adjusted based on the correlation coefficient in the joint evaluation relationship. When the correlation coefficient is positive, a weighted summation method is used, and the quality evaluation result equals the weighted sum of the transmission reliability score and the reception clarity score. When the correlation coefficient is negative, it indicates that the improvement in bit error rate comes at the cost of signal-to-noise ratio. In this case, the harmonic mean is used for fusion to avoid over-optimization of individual indicators masking overall performance defects. The final quality evaluation result is output in numerical form, ranging from 0 to 100, with higher values ​​indicating better compensation effects.

[0052] Based on the deviation between the quality assessment result and the preset quality benchmark, an update instruction is generated to adjust the set of compensation coefficients in the compensation function relationship. Based on the update instruction, the mapping rule from the distortion characteristic parameters to the set of compensation coefficients is dynamically corrected, including: The quality assessment result is compared with the preset quality benchmark, and the deviation of the quality assessment result relative to the preset quality benchmark is calculated. Based on the deviation value, a bit error rate deviation component and a signal-to-noise ratio deviation component are determined, and a deviation quantification index is generated based on the bit error rate deviation component and the signal-to-noise ratio deviation component. Based on the relationship between the deviation quantification index and each compensation coefficient in the compensation coefficient set, the first target compensation coefficient that needs to be adjusted for the bit error rate deviation component and the second target compensation coefficient that needs to be adjusted for the signal-to-noise ratio deviation component are determined. The adjustment range of the first target compensation coefficient and the adjustment range of the second target compensation coefficient are calculated based on the deviation quantification index. The first target compensation coefficient and the adjustment range are used as the first update instruction for nonlinear compensation, and the second target compensation coefficient and the adjustment range are used as the second update instruction for dispersion compensation. The mapping rule is updated based on the first update instruction and the second update instruction.

[0053] During the operation of an optical fiber communication system, by monitoring the quality indicators of the compensated optical signal in real time, the accuracy of the current compensation coefficient set can be determined. When comparing the quality assessment results with a preset quality benchmark, the deviation value is determined by calculating the difference. The preset quality benchmark is usually set according to the design requirements of the communication system; for example, the bit error rate benchmark can be set to... The signal-to-noise ratio (SNR) baseline can be set to 20 dB. The actual measured quality assessment results include the current bit error rate (BER) measurement and the SNR measurement. By calculating the difference between the actual measurement and the baseline value, a deviation value reflecting the degree of deviation in the compensation effect is obtained.

[0054] After obtaining the deviation value, it needs to be decomposed into a bit error rate (BER) deviation component and a signal-to-noise ratio (SNR) deviation component. The BER deviation component is calculated by the difference between the actual BER and the BER benchmark, and the SNR deviation component is calculated by the difference between the actual SNR and the SNR benchmark. To facilitate subsequent adjustment of the compensation coefficient, the two deviation components are normalized and weighted to generate a deviation quantization index. This index uses a quantization method with a value range of 0 to 1. When the deviation quantization index is close to 0, it indicates that the compensation effect is close to the ideal state; when the deviation quantization index is close to 1, it indicates that the compensation effect deviates significantly from expectations.

[0055] The compensation coefficient set contains multiple coefficients for different distortion types, such as nonlinear compensation coefficients for self-phase modulation effects and dispersion compensation coefficients for dispersion effects. By analyzing the sensitivity relationship between the bit error rate (BER) deviation component and each compensation coefficient, the first target compensation coefficient with the most significant impact on the BER is determined. Generally, the nonlinear compensation coefficient has a more direct impact on the BER; when the BER deviation component exceeds a set threshold, the nonlinear compensation coefficient is determined as the first target compensation coefficient. Similarly, by analyzing the correlation between the signal-to-noise ratio (SNR) deviation component and each compensation coefficient, the second target compensation coefficient with the most significant impact on the SNR is determined. The dispersion compensation coefficient has a more pronounced impact on the SNR; when the SNR deviation component exceeds a set threshold, the dispersion compensation coefficient is determined as the second target compensation coefficient.

[0056] The adjustment range for the first target compensation coefficient is calculated by multiplying the deviation quantization index by the adjustment step size of the compensation coefficient. The adjustment step size is preset according to the system stability requirements, typically ranging from 5% to 15% of the current compensation coefficient. When the deviation quantization index is large, the adjustment range is increased accordingly to accelerate convergence; when the deviation quantization index is small, the adjustment range is decreased accordingly to improve adjustment accuracy. The adjustment range for the second target compensation coefficient is calculated using the same method, but different adjustment step size parameters can be set according to the sensitivity of dispersion compensation to signal quality.

[0057] When generating the first update instruction, the determined first target compensation coefficient identifier and its corresponding adjustment range are encapsulated into an instruction data structure. This instruction is specifically used to correct the mapping rules related to nonlinear compensation. When generating the second update instruction, the determined second target compensation coefficient identifier and its corresponding adjustment range are encapsulated into another instruction data structure. This instruction is specifically used to correct the mapping rules related to dispersion compensation. Based on the first and second update instructions, the mapping rules from distortion feature parameters to the compensation coefficient set are updated. The specific adjustment method is as follows: Regarding the adjustment of the first target compensation coefficient, the adjustment direction is determined based on the direction of the bit error rate deviation component: when the actual bit error rate is higher than the bit error rate benchmark, the bit error rate deviation component is positive, indicating that the current nonlinear compensation is insufficient. Therefore, the first target compensation coefficient is increased positively by the adjustment magnitude. The adjustment range Q is a quantitative indicator of deviation. The step size for adjusting the preset nonlinear compensation coefficient is set; when the actual bit error rate is lower than the bit error rate benchmark, the bit error rate deviation component is negative, indicating that the current nonlinear compensation is overcompensated. Therefore, the first target compensation coefficient is decreased negatively by the adjustment magnitude. .

[0058] Regarding the adjustment of the second target compensation coefficient, the adjustment direction is determined based on the direction of the signal-to-noise ratio (SNR) deviation component: when the actual SNR is lower than the SNR reference, the SNR deviation component is negative, indicating insufficient dispersion compensation. Therefore, the second target compensation coefficient is increased positively by the adjustment increment. The adjustment range The step size for adjusting the preset dispersion compensation coefficient is set; when the actual signal-to-noise ratio is higher than the signal-to-noise ratio reference, the signal-to-noise ratio deviation component is positive, indicating that the current dispersion compensation is overcompensated. In this case, the second target compensation coefficient is decreased negatively by the adjustment range. .

[0059] After completing the above calculations, the storage locations of the compensation coefficients for the first and second targets in the original mapping rules are replaced with the following: and The remaining compensation coefficients remain unchanged, forming a new mapping table. The updated mapping rules take effect immediately in subsequent compensation processing, enabling dynamic adaptive adjustment of the compensation parameters.

[0060] The optical fiber communication signal quality improvement system based on adaptive compensation according to an embodiment of the present invention includes: The signal acquisition unit is used to acquire the optical signal to be processed transmitted through the optical fiber communication link. The feature extraction unit is used to perform joint time-domain and frequency-domain analysis on the optical signal to be processed, and extract distortion feature parameters that represent the nonlinear effects and dispersion effects of the transmission medium. The compensation mapping unit is used to map the distortion feature parameters to a set of compensation coefficients to obtain a compensation function relationship representing the signal degradation process. The set of compensation coefficients is set separately for different distortion types. The signal compensation unit is used to apply the compensation coefficient set to the optical signal to be processed, perform inverse compensation processing on the signal waveform to obtain the compensated optical signal, perform joint evaluation of the bit error rate and signal-to-noise ratio on the compensated optical signal, and generate a quality evaluation result characterizing the compensation effect. The dynamic adjustment unit is used to generate an update instruction for adjusting the set of compensation coefficients in the compensation function relationship based on the deviation between the quality assessment result and the preset quality benchmark, and to dynamically correct the mapping rule of the distortion feature parameters to the set of compensation coefficients based on the update instruction.

[0061] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0062] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0063] This invention can be a method, apparatus, system, and / or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of the invention.

[0064] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for improving the quality of optical fiber communication signals based on adaptive compensation, characterized in that, include: Acquire the optical signal to be processed transmitted through the fiber optic communication link; The optical signal to be processed is subjected to joint time-domain and frequency-domain analysis to extract distortion characteristic parameters representing the nonlinear and dispersion effects of the transmission medium; The distortion characteristic parameters are mapped to a set of compensation coefficients to obtain a compensation function relationship representing the signal degradation process. The set of compensation coefficients is set separately for different distortion types. The compensation coefficient set is applied to the optical signal to be processed, and the signal waveform is subjected to inverse compensation processing to obtain the compensated optical signal. The bit error rate and signal-to-noise ratio of the compensated optical signal are jointly evaluated to generate a quality evaluation result characterizing the compensation effect. Based on the deviation between the quality assessment result and the preset quality benchmark, an update instruction is generated to adjust the set of compensation coefficients in the compensation function relationship. Based on the update instruction, the mapping rule from the distortion feature parameters to the set of compensation coefficients is dynamically corrected.

2. The method according to claim 1, characterized in that, The optical signal to be processed is subjected to joint time-domain and frequency-domain analysis to extract distortion characteristic parameters representing the nonlinear and dispersion effects of the transmission medium, including: The time-domain waveform of the optical signal to be processed is sampled, and the amplitude change rate and phase jump between adjacent sampling points are calculated to determine the waveform distortion location caused by the nonlinear effect of the transmission medium, and the time-domain distortion feature components corresponding to the waveform distortion location are extracted; The optical signal to be processed is subjected to frequency domain transformation to obtain the spectral distribution. By analyzing the offset and spread of each frequency component in the spectral distribution relative to the reference spectrum, the spectral spread region caused by the dispersion effect of the transmission medium is determined, and the frequency domain distortion feature components corresponding to the spectral spread region are extracted. The correspondence between the time-domain distortion feature components and the frequency-domain distortion feature components is determined, and a joint distortion feature vector is generated by cross-mapping the distribution of the waveform distortion position on the time axis with the distribution of the spectral spread region on the frequency axis. Based on the relative weights of the temporal distortion feature components and the frequency-domain distortion feature components in the joint distortion feature vector, the dominant distortion type of the optical signal to be processed is determined, and the distortion feature parameters are obtained based on the temporal distortion feature components, the frequency-domain distortion feature components, and the dominant distortion type.

3. The method according to claim 1, characterized in that, Mapping the distortion characteristic parameters to a set of compensation coefficients yields a compensation function relationship representing the signal degradation process, including: The distortion feature parameters are decomposed into nonlinear distortion components and dispersion distortion components based on the dominant distortion type identifier in the distortion feature parameters; A first set of compensation coefficients is calculated for the nonlinear distortion component to counteract the nonlinear effect, and a second set of compensation coefficients is calculated for the dispersion distortion component to counteract the dispersion effect. The compensation coefficient set is obtained based on the first set of compensation coefficients and the second set of compensation coefficients. Each compensation coefficient in the compensation coefficient set is constrained by limiting the gradient of the phase difference change between adjacent compensation coefficients to be less than the phase continuity threshold, and limiting the range of the ratio between the amplitude adjustment factors corresponding to each compensation coefficient to satisfy the amplitude consistency constraint, thus obtaining a constrained compensation coefficient set that satisfies the phase continuity threshold and the amplitude consistency constraint; Based on the constrained set of compensation coefficients, a nonlinear compensation mapping function is generated to map the nonlinear distortion component to the first set of compensation coefficients, and a dispersion compensation mapping function is generated to map the dispersion distortion component to the second set of compensation coefficients. The relationship between the compensation functions is obtained based on the nonlinear compensation mapping function and the dispersion compensation mapping function.

4. The method according to claim 3, characterized in that, A first set of compensation coefficients is calculated for the nonlinear distortion component to counteract the nonlinear effect, and a second set of compensation coefficients is calculated for the dispersion distortion component to counteract the dispersion effect. The compensation coefficient set is obtained based on the first and second compensation coefficient sets, including: The amplitude distortion parameter and the apparent phase distortion parameter are extracted from the nonlinear distortion component, and the delay distortion parameter and the spectral distortion parameter are extracted from the dispersion distortion component. Based on the coupling relationship between the amplitude distortion parameter and the phase distortion parameter, an amplitude compensation coefficient for canceling the amplitude distortion parameter and a phase compensation coefficient for canceling the phase distortion parameter are determined, and the amplitude compensation coefficient and the phase compensation coefficient are combined to obtain the first compensation coefficient group; Based on the correlation between the delay distortion parameter and the spectral distortion parameter, a delay compensation coefficient for compensating the delay distortion parameter and a spectral compensation coefficient for compensating the spectral distortion parameter are determined, and the delay compensation coefficient and the spectral compensation coefficient are combined to obtain the second compensation coefficient group; The first set of compensation coefficients is marked as a nonlinear compensation channel, and the second set of compensation coefficients is marked as a dispersion compensation channel. The compensation coefficient set is obtained based on the nonlinear compensation channel and the dispersion compensation channel.

5. The method according to claim 1, characterized in that, The compensation coefficient set is applied to the optical signal to be processed, and the signal waveform is subjected to inverse compensation processing to obtain a compensated optical signal. The bit error rate and signal-to-noise ratio of the compensated optical signal are jointly evaluated to generate a quality evaluation result characterizing the compensation effect, including: The first compensation coefficient group in the compensation coefficient set is applied to the time-domain waveform of the optical signal to be processed, and the amplitude is reversed and the phase is reversed to generate a nonlinear compensation intermediate signal. The second set of compensation coefficients in the compensation coefficient set is applied to the frequency domain representation of the nonlinear compensation intermediate signal, and the frequency domain representation is subjected to delay inverse compensation and spectrum inverse convergence to generate the compensated optical signal; The compensated optical signal is demodulated to obtain a demodulation result. Based on the demodulation result and a preset reference sequence, a bit error rate index characterizing the reliability of signal transmission is obtained. The signal power and noise power of the compensated optical signal are measured, and the ratio of the signal power to the noise power is calculated to obtain the signal-to-noise ratio (SNR) index, which characterizes the signal clarity. Determine the joint evaluation relationship between the bit error rate index and the signal-to-noise ratio index, and generate a quality evaluation result that comprehensively characterizes the quality of the compensated optical signal based on the joint evaluation relationship.

6. The method according to claim 5, characterized in that, Determine the joint evaluation relationship between the bit error rate index and the signal-to-noise ratio index, and generate a quality evaluation result that comprehensively characterizes the quality of the compensated optical signal based on the joint evaluation relationship, including: Based on the bit error rate index, determine the bit error distribution parameter reflecting the characteristics of the transmission error distribution and the noise interference parameter reflecting the degree of noise interference in the signal-to-noise ratio index; The joint evaluation relationship is generated based on the correlation between the bit error distribution parameters and the noise interference parameters; Based on the joint evaluation relationship, the impact of the bit error rate (BER) index on signal transmission reliability and the impact of the signal-to-noise ratio (SNR) index on signal reception clarity are analyzed to determine the BER weighting coefficient and the SNR weighting coefficient used to quantify the importance of the BER index. A transmission reliability score is generated based on the bit error rate index and the bit error rate weighting coefficient, and a reception clarity score is generated based on the signal-to-noise ratio index and the signal-to-noise ratio weighting coefficient. The transmission reliability score and the reception clarity score are fused based on the joint evaluation relationship to generate the quality evaluation result.

7. The method according to claim 1, characterized in that, Based on the deviation between the quality assessment result and the preset quality benchmark, an update instruction is generated to adjust the set of compensation coefficients in the compensation function relationship. Based on the update instruction, the mapping rule from the distortion characteristic parameters to the set of compensation coefficients is dynamically corrected, including: The quality assessment result is compared with the preset quality benchmark, and the deviation of the quality assessment result relative to the preset quality benchmark is calculated. Based on the deviation value, a bit error rate deviation component and a signal-to-noise ratio deviation component are determined, and a deviation quantification index is generated based on the bit error rate deviation component and the signal-to-noise ratio deviation component. Based on the relationship between the deviation quantification index and each compensation coefficient in the compensation coefficient set, the first target compensation coefficient that needs to be adjusted for the bit error rate deviation component and the second target compensation coefficient that needs to be adjusted for the signal-to-noise ratio deviation component are determined. The adjustment range of the first target compensation coefficient and the adjustment range of the second target compensation coefficient are calculated based on the deviation quantification index. The first target compensation coefficient and the adjustment range are used as the first update instruction for nonlinear compensation, and the second target compensation coefficient and the adjustment range are used as the second update instruction for dispersion compensation. The mapping rule is updated based on the first update instruction and the second update instruction.

8. An optical fiber communication signal quality improvement system based on adaptive compensation, used to implement the method as described in any one of claims 1-7, characterized in that, include: The signal acquisition unit is used to acquire the optical signal to be processed transmitted through the optical fiber communication link. The feature extraction unit is used to perform joint time-domain and frequency-domain analysis on the optical signal to be processed, and extract distortion feature parameters that represent the nonlinear effects and dispersion effects of the transmission medium. The compensation mapping unit is used to map the distortion feature parameters to a set of compensation coefficients to obtain a compensation function relationship representing the signal degradation process. The set of compensation coefficients is set separately for different distortion types. The signal compensation unit is used to apply the compensation coefficient set to the optical signal to be processed, perform inverse compensation processing on the signal waveform to obtain the compensated optical signal, perform joint evaluation of the bit error rate and signal-to-noise ratio on the compensated optical signal, and generate a quality evaluation result characterizing the compensation effect. The dynamic adjustment unit is used to generate an update instruction for adjusting the set of compensation coefficients in the compensation function relationship based on the deviation between the quality assessment result and the preset quality benchmark, and to dynamically correct the mapping rule of the distortion feature parameters to the set of compensation coefficients based on the update instruction.

9. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 7.

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