A method and system for high-speed signal reception of a protocol signal processing module

Abstract

This application provides a high-speed signal receiving method and system for a protocol signal processing module, relating to the field of high-speed signal receiving. The method includes: acquiring an initial signal; determining the spectral distribution characteristics of the high-speed signal based on the initial signal; determining an interference frequency band range based on the spectral distribution characteristics; and judging the dynamic change trend of the interference signal based on the interference frequency band range. If the power value of the interference signal exceeds a power threshold range under the dynamic change trend within a predetermined time, adaptively updating the filtering parameters of the interference frequency band range to obtain a first set of filtering parameters. The first set of filtering parameters is applied to an adaptive filtering processing module to perform interference suppression on the high-speed signal, obtaining a suppressed first high-speed signal. Thus, the method provided in this application can adaptively update the filtering parameters when the power value of the interference signal exceeds a power threshold range under the dynamic change trend within a predetermined time, improving the interference suppression effect.

Description

Technical Field

[0001] This application relates to the field of high-speed signal reception, specifically to a high-speed signal reception method and system for a protocol signal processing module. Background Technology

[0002] In modern communication systems, the performance of high-speed signal reception and processing directly affects the quality and efficiency of information transmission. With the rapid development of wireless communication technology, the communication environment is becoming increasingly complex, and signal interference problems are becoming more and more prominent. Especially in application scenarios such as 5G, Internet of Things (IoT), and satellite communication, interference signals may come from multiple frequency bands and have dynamic changing characteristics, which poses a severe challenge to traditional interference suppression technologies.

[0003] Traditional signal interference suppression methods primarily rely on filters with fixed parameters, such as band-stop filters or notch filters. These filters are typically designed for known interference frequency bands. However, in real-world communication environments, the frequency, intensity, and time characteristics of interference signals are often dynamically changing. Filters with fixed parameters cannot be adjusted, resulting in poor interference suppression performance. For example, when the interference frequency band shifts or new interference sources appear, traditional filters may fail to effectively suppress interference or even mistakenly filter out useful signals, affecting the reliability of the communication system.

[0004] Therefore, there is an urgent need for an interference suppression technology that can analyze signal characteristics, dynamically adjust filtering parameters, and protect useful signals, so as to improve the stability and reliability of high-speed signal reception. Summary of the Invention

[0005] In view of the above problems, the present application provides a high-speed signal receiving method and system for a protocol signal processing module, which overcomes or at least partially solves the problems of the prior art being unable to dynamically adjust filtering parameters and having poor interference suppression effect.

[0006] A first aspect of this application provides a high-speed signal receiving method for a protocol signal processing module, comprising: acquiring an initial signal; determining the spectral distribution characteristics of the high-speed signal based on the initial signal; determining an interference frequency band range based on the spectral distribution characteristics; and judging the dynamic change trend of the interference signal based on the interference frequency band range. If the power value of the interference signal under the dynamic change trend exceeds a power threshold range within a predetermined time, adaptively updating the filtering parameters of the interference frequency band range to obtain a first set of filtering parameters. Applying the first set of filtering parameters to an adaptive filtering processing module to perform interference suppression operation on the high-speed signal to obtain a suppressed first high-speed signal.

[0007] In this embodiment, the spectral distribution characteristics of the high-speed signal can be determined based on the initial signal. Based on the spectral distribution characteristics, the frequency band range of the initial signal can be segmented using a preset frequency band division rule. Energy data for each segmented frequency band is obtained. Based on the energy data, the interference frequency band range is determined, and then the dynamic change trend of the interference signal is judged. If the power value of the interference signal exceeds the power threshold range under the dynamic change trend within a predetermined time, the filtering parameters of the interference frequency band range are adaptively updated to obtain a first set of filtering parameters. The first set of filtering parameters is applied to the adaptive filtering processing module to perform interference suppression on the high-speed signal, obtaining a suppressed first high-speed signal. Thus, the high-speed signal receiving method of the protocol signal processing module provided in this application can adaptively update the filtering parameters when the power value of the interference signal exceeds the power threshold range under the dynamic change trend within a predetermined time, improving the interference suppression effect.

[0008] In one alternative approach, the first set of filtering parameters is applied to the adaptive filtering processing module to perform interference suppression on the high-speed signal. After obtaining the suppressed first high-speed signal, the method further includes: determining, based on the suppressed first high-speed signal, whether there is excessive suppression of the useful signal.

[0009] In one alternative approach, after determining whether there is excessive suppression of the useful signal based on the suppressed first high-speed signal, the method includes: if there is excessive suppression of the useful signal, performing a second fine-tuning process on the first set of filtering parameters to obtain a second set of filtering parameters.

[0010] In this way, the filtering parameters can be further updated to improve the interference suppression effect.

[0011] In one alternative approach, if there is excessive suppression of the useful signal, after performing secondary fine-tuning on the first set of filtering parameters to obtain the second set of filtering parameters, the method further includes: applying the second set of filtering parameters to an adaptive filtering processing module to perform interference suppression operation on the high-speed signal and obtain the suppressed second high-speed signal.

[0012] In one alternative approach, if there is excessive suppression of the useful signal, a second fine-tuning process is performed on the first set of filtering parameters to obtain a second set of filtering parameters. This includes: if there is excessive suppression of the useful signal, calculating the distortion of the first high-speed signal, and using an adaptive adjustment mechanism based on gradient descent to calculate the partial derivatives of the distortion with respect to each parameter in the first set of filtering parameters, and determining the adjustment direction to obtain the second set of filtering parameters.

[0013] In one alternative approach, determining the interference frequency band range based on spectral distribution characteristics includes: segmenting the frequency band range of the initial signal according to a preset frequency band division rule based on the spectral distribution characteristics; acquiring energy data for each segmented frequency band; and determining the interference frequency band range based on the energy data.

[0014] In one alternative approach, the interference frequency band range is determined based on energy data, including: comparing the energy of each frequency band with the energy threshold, and initially determining the frequency band with the largest energy exceeding the energy threshold as the potential interference frequency band range; calculating the ratio between the potential interference frequency band range and the energy of the remaining frequency bands, and if each ratio is higher than the empirical ratio threshold and has a peak feature within the potential interference frequency band range, then the potential interference frequency band range is the interference frequency band range.

[0015] In one alternative approach, based on the interference frequency band range, the dynamic trend of the interference signal is determined, including: performing time-frequency analysis of the signal using short-time Fourier transform; inputting the time-frequency characteristic parameters obtained from the time-frequency analysis into an autoregressive moving average model to predict the possible dynamic trend of the interference signal using time series analysis methods; calculating the power change rate of the interference signal; and determining the dynamic trend of the interference signal based on the power change rate and the possible dynamic trend.

[0016] In one alternative approach, determining whether there is excessive suppression of the useful signal based on the suppressed first high-speed signal includes: comparing the first high-speed signal with an ideal signal, calculating the root mean square error (RMSE), and comparing the RMS error with a preset error threshold, where the ideal signal refers to the signal transmitted in an ideal environment with no noise, no distortion, and infinite bandwidth. If the RMS error is greater than the preset error threshold, calculating the signal-to-noise ratio (SNR) change and the amplitude suppression ratio of the signal before and after suppression. Determining whether there is excessive suppression of the useful signal based on the SNR change and amplitude suppression ratio of the signal before and after suppression.

[0017] A second aspect of this application provides a high-speed signal receiving system with a protocol signal processing module. The system includes: an acquisition module for acquiring an initial signal; a first determination module for determining the spectral distribution characteristics of the high-speed signal based on the initial signal; a second determination module for determining an interference frequency band range based on the spectral distribution characteristics; a judgment module for judging the dynamic change trend of the interference signal based on the interference frequency band range; an update module for adaptively updating the filtering parameters of the interference frequency band range to obtain a first set of filtering parameters if the power value of the interference signal exceeds a power threshold range under the dynamic change trend within a predetermined time; and a suppression module for applying the first set of filtering parameters to the adaptive filtering processing module to perform interference suppression operation on the high-speed signal and obtain a suppressed first high-speed signal.

[0018] The above description is merely an overview of the technical solutions of the embodiments of this application. In order to better understand the technical means of the embodiments of this application and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of this application more obvious and understandable, specific implementation methods of this application are described below. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating a high-speed signal receiving method for a protocol signal processing module provided in some embodiments of this application.

[0021] Figure 2 Another flowchart of a high-speed signal receiving method for a protocol signal processing module provided in some embodiments of this application.

[0022] Figure 3 A high-speed signal receiving system for a protocol signal processing module is provided as another embodiment of this application.

[0023] Figure 4 This is a schematic diagram of a high-speed signal receiver provided for some embodiments of this application.

[0024] Figure 5 This is a schematic diagram of high-speed signal transmission provided for some embodiments of this application.

[0025] Figure 6 This is a partially enlarged schematic diagram of the D group difference pairs provided in some embodiments of this application. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0028] The terms "comprising" and "having," and any variations thereof, used in the specification, claims, and drawings of this application are intended to cover without excluding other meanings. The words "a" or "an" do not exclude the presence of multiples.

[0029] The term "embodiment" as used herein means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of the phrase "embodiment" in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0030] Furthermore, the terms "first," "second," etc., in the specification and claims of this application or in the aforementioned drawings are used to distinguish different objects rather than to describe a specific order, and may explicitly or implicitly include one or more of the features.

[0031] In the description of this application, unless otherwise stated, "multiple" means two or more (including two), and similarly, "multiple groups" means two or more (including two groups).

[0032] In the description of this application, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linkage" should be interpreted broadly. For example, "connection" or "linkage" in mechanical structures can refer to a physical connection, such as a fixed connection, for example, a connection fixed by fasteners, such as a connection fixed by screws, bolts, or other fasteners; a physical connection can also be a detachable connection, such as a snap-fit ​​or interlocking connection; a physical connection can also be an integral connection, such as a connection formed by welding, bonding, or integral molding. In circuit structures, "connection" or "linkage" can refer not only to a physical connection but also to an electrical connection or a signal connection. For example, it can be a direct connection, i.e., a physical connection, or an indirect connection through at least one intermediate component, as long as the circuit is connected; it can also refer to the internal connection of two components. Signal connection can refer not only to signal connection through a circuit but also to signal connection through a media, such as radio waves. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0033] This application provides a high-speed signal reception method for a protocol signal processing module. Please refer to [link / reference]. Figure 1 , Figure 1 This is a flowchart illustrating a high-speed signal receiving method for a protocol signal processing module provided in some embodiments of this application.

[0034] like Figure 1 As shown, the high-speed signal receiving method of the protocol signal processing module provided in this application embodiment includes the following steps 101 to 106:

[0035] Step 101: Obtain the initial signal.

[0036] In practical applications, the method also includes sampling the input high-speed signal before acquiring the initial signal.

[0037] Specifically, the high-speed input signal can be initially sampled using a high-speed analog-to-digital converter. For example, the sampling rate can be set to 20 million samples per second (MSa / s), which conforms to the Nyquist sampling theorem and ensures that the signal is not distorted. The sampling duration is 1 millisecond, resulting in 20,000 sampling points, which constitute the initial signal.

[0038] Step 102: Determine the spectral distribution characteristics of the high-speed signal based on the initial signal.

[0039] Specifically, determining the spectral distribution characteristics of a high-speed signal based on an initial signal includes: performing a frequency domain transformation on the initial signal to determine the spectral distribution characteristics of the high-speed signal.

[0040] For example, the Fast Fourier Transform (FFT) algorithm can be used to convert the time-domain signal into a frequency-domain signal to obtain spectral data and form a spectral characteristic curve. For instance, the spectral distribution characteristics of a determined high-speed signal can be a frequency range of 0 to 22.05 kHz with a resolution of 0.1 Hz.

[0041] Step 103: Determine the range of interference frequency bands based on the spectral distribution characteristics.

[0042] Specifically, determining the interference frequency band range based on spectral distribution characteristics includes: segmenting the initial signal's frequency band range according to preset frequency band division rules based on spectral distribution characteristics; acquiring energy data for each segmented frequency band; and determining the interference frequency band range based on the energy data.

[0043] Specifically, based on energy data, the interference frequency band range is determined, including: comparing the energy of each frequency band with the energy threshold, and initially identifying the frequency band with the largest energy exceeding the energy threshold as the potential interference frequency band range. The potential interference frequency band range is then compared with the energy of the remaining frequency bands. If all the obtained ratios are higher than the empirical ratio threshold and exhibit peak characteristics within the potential interference frequency band range, then the potential interference frequency band range is considered the interference frequency band range.

[0044] For example, assuming the frequency range determined based on spectral distribution characteristics is 0 to 22.05 kHz with a resolution of 0.1 Hz, the frequency range is divided into multiple sub-bands using a preset frequency band division rule. For instance, five bands are defined: 0-500 Hz, 500-2000 Hz, 2000-5000 Hz, 5000-10000 Hz, and 10000-22050 Hz. The energy data for each band is calculated. The calculated results are assumed to be: 0-500 Hz energy is 120.5 units, 500-2000 Hz energy is 350.2 units, 2000-5000 Hz energy is 800.7 units, 5000-10000 Hz energy is 200.3 units, and 10000-22050 Hz energy is 90.1 units. Analyzing the energy data, assuming the energy threshold is the total energy of 1561.8 units divided by 5 frequency bands, i.e., the energy threshold is 312.36 units, it was found that the energy of 800.7 units in the 2000-5000Hz frequency band far exceeds the energy threshold, and it was preliminarily determined that this is the potential interference frequency band range.

[0045] In some embodiments, for further verification, the energy ratios of this frequency band and other frequency bands can be calculated separately. The ratio of 2000-5000Hz to the adjacent frequency band 500-2000Hz is 2.29, and the ratio to 5000-10000Hz is 4.0. Both are significantly higher than the empirical ratio threshold of 1.5. Combining the presence of peak features in the spectral curve within this frequency band, and assuming that multiple peaks with amplitudes exceeding three times the average value are detected, the 2000-5000Hz frequency band is finally confirmed as the interference frequency band range.

[0046] It should be noted that the process of calculating the energy data for each frequency band is as follows:

[0047] The energy of the spectrum X[k] is the square of the real part plus the square of the imaginary part of the spectrum X[k] obtained by the fast Fourier transform of the initial signal x[n]. Taking the 0-500Hz frequency band as an example, the starting frequency kstart is equal to the lowest frequency / resolution in the band, i.e., 0 Hz / 0.1 Hz, which is 0. The ending frequency kend is equal to the highest frequency / resolution in the band, i.e., 500 Hz / 0.1 Hz, which is 5000. Therefore, there are a total of 5001 frequency points (including 0 Hz).

[0048] The energy data for each frequency band is the sum of the energy from the starting frequency kstart to the ending frequency kend. For example, the energy data for the 0-500Hz frequency band is the sum of the energy from the starting frequency 0 to the ending frequency 5000, i.e., Eband1 = 120.5 units.

[0049] It should also be noted that the empirical ratio threshold of 1.5 can be determined by the typical ratio range of the interference frequency band in historical data.

[0050] Step 104: Based on the interference frequency band range, determine the dynamic change trend of the interference signal.

[0051] Specifically, based on the interference frequency band range, the dynamic change trend of the interference signal is determined, including: performing time-frequency analysis of the signal using short-time Fourier transform; inputting the time-frequency characteristic parameters obtained from the time-frequency analysis into an autoregressive moving average model to predict the possible dynamic change trend of the interference signal using time series analysis methods; calculating the power change rate of the interference signal; and determining the dynamic change trend of the interference signal based on the power change rate and the possible dynamic change trend.

[0052] For example, assuming the interference frequency range is 2000-5000Hz, a time-frequency analysis of the signal is performed using Short Time Fourier Transform (STFT). The time window length is set to 10ms, the window function is a Hanning window, and the overlap rate is 50%. After obtaining the time-frequency diagram, the center frequency of the interference signal is extracted as 2500Hz. Simultaneously, the modulation characteristics of the signal are calculated, revealing that its frequency exhibits periodic jumps over time with a period of approximately 50ms, indicating that it may be a frequency-hopping interference signal.

[0053] Using time series analysis, the time-frequency characteristic parameters obtained from time-frequency analysis were input into an autoregressive moving average (ARMA) model. The model order was set to (2,1). The possible dynamic change trend of the interference signal was predicted by fitting the results. The analysis showed that the frequency may fluctuate between 2000Hz and 3000Hz in the next 100ms, with a change range of approximately ±50Hz. By comparing with historical data, it was found that the frequency hopping rate of the interference signal increased by 10% in the past hour, indicating that the possible dynamic change trend is increasing.

[0054] To further verify the dynamic trend, the power change rate of the interference signal can be calculated. It was found that the power increased from -35dBm to -30dBm in the last 10 minutes, an increase of 14.3%. Based on the power change rate and the possible dynamic change trend, the dynamic change trend of the interference signal is determined to be a dynamic enhancement trend.

[0055] Step 105: If the power value of the interference signal exceeds the power threshold range under the dynamic change trend within a predetermined time, the filtering parameters of the interference frequency band range are adaptively updated to obtain the first set of filtering parameters.

[0056] For example, suppose the normal signal power threshold range for a certain frequency band is set to -80 dBm to -50 dBm, and the predetermined time is 10 minutes. The power of the interfering signal increases from -35 dBm to -30 dBm within the last 10 minutes, showing a dynamic increasing trend. If the power value of the interfering signal at -30 dBm within the predetermined time period significantly exceeds the upper limit of the power threshold range (-50 dBm), then an adaptive update mechanism is automatically triggered. This mechanism calls a preset filter parameter adjustment algorithm to adaptively update the filter parameters for the interfering frequency band, obtaining a first set of filter parameters.

[0057] For example, the preset filter parameter adjustment algorithm can be an adaptive filtering algorithm based on minimum mean square error. Assuming the initial filter parameters have a cutoff frequency of 10MHz and a bandwidth of 2MHz, the error value in the adaptive filtering algorithm with minimum mean square error is calculated based on the spectral characteristics of the interference signal. Assuming the calculated error value e is 0.05 and the target error value is 0.01, the filter coefficients are iteratively updated based on the error value of 0.05 to obtain the updated first set of filter parameters, including a new cutoff frequency fc of 10.5MHz, a bandwidth of 1.8MHz, and a gain adjustment value of -3dB.

[0058] For example, the process of changing the initial cutoff frequency of the filter parameters from 10MHz to a new cutoff frequency fc of 10.5MHz is as follows:

[0059] Slightly increase the cutoff frequency fc to 10.01 MHz and recalculate the error e′=0.048. Assuming the calculated ∂e / ∂fc is −0.2 / MHz and the step size is 0.1, the change in cutoff frequency Δ after one iteration is... fc The product of the step size, the error value of 0.05, and ∂e / ∂fc−0.2 is +0.001MHz, meaning the updated cutoff frequency fc is 10.001 MHz. The error value is recalculated. If the error value drops below 0.01 after one iteration, the first set of filter parameters includes the new cutoff frequency fc of 10.001MHz. If the error value does not drop below 0.01, iteration continues until the error value drops below 0.01. The cutoff frequency fc at which the error value first drops below 0.01 is determined as the new cutoff frequency fc included in the first set of filter parameters. The adjustment process for the bandwidth B (1.9MHz) and the gain G adjustment value of -3.15dB is the same as the adjustment process for the cutoff frequency fc, and will not be described again in this application.

[0060] In some embodiments, the updated first set of filtering parameters can also be verified. For example, simulation analysis might determine that the signal suppression effect in this frequency band is improved by 15% based on the first set of filtering parameters, confirming that the first set of filtering parameters meets expectations. If the verification results do not meet expectations, further optimization can be achieved by combining historical data, such as referencing processing records of similar interference signals over the past 24 hours to extract the optimal parameter combination for readjustment. Furthermore, to ensure stability, the readjusted parameters will be compared and analyzed with the filtering settings of adjacent frequency bands to avoid parameter conflicts. For example, it will be ensured that the cutoff frequency difference between adjacent frequency bands is not less than 0.2MHz, thereby maintaining the overall spectrum balance.

[0061] Step 106: Apply the first set of filtering parameters to the adaptive filtering processing module to perform interference suppression on the high-speed signal and obtain the suppressed first high-speed signal.

[0062] In this embodiment, the spectral distribution characteristics of the high-speed signal can be determined based on the initial signal. Based on the spectral distribution characteristics, the frequency band range of the initial signal can be segmented using a preset frequency band division rule. Energy data for each segmented frequency band is obtained. Based on the energy data, the interference frequency band range is determined, and then the dynamic change trend of the interference signal is judged. If the power value of the interference signal exceeds the power threshold range under the dynamic change trend within a predetermined time, the filtering parameters of the interference frequency band range are adaptively updated to obtain a first set of filtering parameters. The first set of filtering parameters is applied to the adaptive filtering processing module to perform interference suppression on the high-speed signal, obtaining a suppressed first high-speed signal. Thus, the high-speed signal receiving method of the protocol signal processing module provided in this application can adaptively update the filtering parameters when the power value of the interference signal exceeds the power threshold range under the dynamic change trend within a predetermined time, improving the interference suppression effect.

[0063] refer to Figure 2 , Figure 2 This is another flowchart illustrating a high-speed signal receiving method for a protocol signal processing module provided in some embodiments of this application. In this embodiment, steps 107-109 may be included after step 106.

[0064] Step 107: Based on the suppressed first high-speed signal, determine whether there is excessive suppression of the useful signal.

[0065] Specifically, based on the suppressed first high-speed signal, it is determined whether there is excessive suppression of the useful signal. This includes: comparing the first high-speed signal with an ideal signal, calculating the root mean square error (RMSE), and comparing the RMS error with a preset error threshold. The ideal signal refers to the high-speed signal transmitted in an ideal environment with no noise, no distortion, and unlimited bandwidth. If the RMS error is greater than the preset error threshold, the signal-to-noise ratio (SNR) change and the amplitude suppression ratio before and after suppression are calculated. Based on the SNR change and amplitude suppression ratio before and after suppression, it is determined whether there is excessive suppression of the useful signal.

[0066] For example, the first high-speed signal is compared with an ideal signal. Assuming the ideal signal is a sine wave, the root mean square error (RMSE) is calculated. This is obtained by summing the squares of the actual signal values ​​from the 0th to the (N-1th)th sampling points, subtracting the squares of the ideal signal values, dividing by the total number of sampling points, and then taking the square root. Assuming the calculated RMSE is 0.15V and the preset error threshold is 0.1V, the signal-to-noise ratio (SNR) before and after suppression is calculated. Assuming the SNR before suppression is 25 dB and after suppression is 18 dB, a significant decrease, the amplitude suppression ratio is calculated. The amplitude suppression ratio before and after suppression is calculated. Assuming the amplitude decreases from 1.5V to 0.8V, the amplitude suppression ratio is 46.7%. If the preset amplitude suppression ratio threshold is 30%, 46.7% exceeds the 30% threshold. Considering the RMSE being greater than the preset error threshold, the significant decrease in SNR after suppression, and the amplitude suppression ratio exceeding the preset threshold, over-suppression is determined.

[0067] Understandably, if the root mean square error is not greater than the preset error threshold or the SNR does not decrease significantly after suppression (e.g., not more than 3 dB), or the amplitude suppression ratio of the signal before and after suppression does not exceed the preset amplitude suppression ratio threshold, it is determined that there is no over-suppression.

[0068] Step 108: If there is excessive suppression of the useful signal, perform secondary fine-tuning on the first set of filter parameters to obtain the second set of filter parameters.

[0069] In practical applications, if there is excessive suppression of the useful signal, a second fine-tuning process is performed on the first set of filter parameters to obtain a second set of filter parameters. This includes: if there is excessive suppression of the useful signal, calculating the distortion of the first high-speed signal; using an adaptive adjustment mechanism based on gradient descent, calculating the partial derivatives of the distortion with respect to each parameter in the first set of filter parameters; and determining the adjustment direction to obtain the second set of filter parameters. Assuming the iteration step size is set to 0.01, the goal is to reduce the distortion to below a distortion threshold, for example, a distortion threshold of 5.0%.

[0070] For example, the distortion D is the square root of the sum of the squares of the effective values ​​of the second harmonic to the squares of the effective values ​​of the nth (n≥2) harmonics, multiplied by 100%, and then divided by the effective value (RMS) of the fundamental frequency. Assuming the calculated distortion D is 6.8%, the first set of filter parameters includes a new cutoff frequency fc of 10.5MHz, a bandwidth B of 1.8MHz, and a gain G adjustment value of -3dB.

[0071] Assuming ∂D / ∂fc is +20% / kHz, it indicates that the higher the cutoff frequency, the higher the distortion. Assuming ∂D / ∂G is +15% / dB, it indicates that the higher the gain, the higher the distortion. Assuming ∂D / ∂B is −10% / MHz, it indicates that the higher the bandwidth, the lower the distortion. Based on the partial derivatives of the distortion D with respect to each parameter, the adjustment direction is determined. That is, the cutoff frequency after each iteration is the cutoff frequency before each iteration minus the iteration step size multiplied by the partial derivative of the distortion with respect to the cutoff frequency; the bandwidth after each iteration is the bandwidth before each iteration minus the iteration step size multiplied by the partial derivative of the distortion with respect to the bandwidth; and the gain after each iteration is the gain before each iteration minus the iteration step size multiplied by the partial derivative of the distortion with respect to the gain. This process is repeated until the distortion drops below the distortion threshold. The set of filter parameters whose distortion first drops below the distortion threshold is then determined as the second set of filter parameters. For example, if the iteration step size is set to 0.01, after one iteration, fc is the cutoff frequency 10.5 minus the step size 0.01 multiplied by ∂D / ∂fc = 20, which is 10.3MHz; G is the gain -3 minus the step size 0.01 multiplied by ∂D / ∂G = 15, which is -3.15 dB; and B is the bandwidth 1.8 minus the step size 0.01 multiplied by ∂D / ∂B = -10, which is 1.9MHz. The distortion is recalculated. If the distortion drops below 5.0% after one iteration, the second filter parameter set includes the new cutoff frequency fc 10.3MHz, bandwidth B 1.9MHz, and a gain G adjustment of -3.15dB. If the distortion does not drop below 5.0%, the iteration continues until the distortion drops below 5.0%. The filter parameter set whose distortion first drops below 5.0% is determined as the second filter parameter set.

[0072] Step 109: Apply the second set of filtering parameters to the adaptive filtering processing module to perform interference suppression on the high-speed signal and obtain the suppressed second high-speed signal.

[0073] In practical applications, the output of the second high-speed signal can be monitored in real time to obtain signal quality feedback data and determine whether further adjustments are needed to the filter parameters in the subsequent signal stream.

[0074] For example, the process of real-time monitoring of the second high-speed signal output is as follows:

[0075] Suppose we monitor the output of an audio signal with a signal-to-noise ratio (SNR) of 15.2 dB, which is below a preset threshold of 20 dB. Automatic analysis of the spectral distribution characteristics of a second high-speed signal reveals that the main noise is concentrated in the 2 kHz to 3 kHz frequency band, accounting for approximately 12.5% ​​of the total energy. This signal quality feedback data is input into a machine learning-based adaptive parameter adjustment model. This model, trained on historical data, determines that when the noise proportion exceeds 10% of the total energy and is concentrated in a specific frequency band, the cutoff frequency of the filter in the subsequent signal stream should be adjusted to 2.5 kHz, and the gain parameter reduced by 0.8 dB to reduce noise amplification. After this adjustment, monitoring the output signal again shows, for example, an SNR improvement to 21.3 dB, meeting the quality standard.

[0076] Furthermore, the adjusted filtering parameters can be correlated with the signal transmission delay to ensure that the delay is controlled within 50 milliseconds. The current delay is calculated to be 42 milliseconds, which meets the real-time requirements. If the delay exceeds 50 milliseconds, the filtering algorithm in the aforementioned embodiment is further optimized to reduce computational complexity and thus reduce the delay. Through the above process, the signal quality is continuously optimized.

[0077] Another embodiment of this application provides a high-speed signal receiving system for a protocol signal processing module. Figure 3 A high-speed signal receiving system for a protocol signal processing module is provided in another embodiment of this application, referenced to... Figure 3 A high-speed signal receiving system 3 with a protocol signal processing module includes: an acquisition module 31 for acquiring an initial signal; a first determination module 32 for determining the spectral distribution characteristics of the high-speed signal based on the initial signal; a second determination module 33 for determining the interference frequency band range based on the spectral distribution characteristics; a judgment module 34 for judging the dynamic change trend of the interference signal based on the interference frequency band range; an update module 35 for adaptively updating the filtering parameters of the interference frequency band range to obtain a first set of filtering parameters if the power value of the interference signal exceeds a power threshold range under the dynamic change trend within a predetermined time; and a suppression module 36 for applying the first set of filtering parameters to the adaptive filtering processing module to perform interference suppression operation on the high-speed signal and obtain a suppressed first high-speed signal.

[0078] In some embodiments, the first determining module 32 is specifically used to: perform a frequency domain transformation operation on the initial signal to determine the spectral distribution characteristics of the high-speed signal. The second determining module 33 is specifically used to: segment the frequency range of the initial signal according to a preset frequency band division rule based on the spectral distribution characteristics; acquire energy data for each segmented frequency band; and determine the interference frequency band range based on the energy data. The judging module 34 is specifically used to: perform time-frequency analysis on the signal using short-time Fourier transform; input the time-frequency characteristic parameters obtained from the time-frequency analysis into an autoregressive moving average model using a time series analysis method to predict the possible dynamic change trend of the interference signal; and calculate the power change rate of the interference signal. The dynamic change trend of the interference signal is determined based on the power change rate and the possible dynamic change trend.

[0079] In some embodiments, the determination module 34 is further configured to determine, based on the suppressed first high-speed signal, whether there is excessive suppression of the useful signal.

[0080] In some embodiments, a high-speed signal receiving system 3 of a protocol signal processing module may further include a fine-tuning module for: if there is excessive suppression of the useful signal, performing secondary fine-tuning on the first set of filtering parameters to obtain a second set of filtering parameters.

[0081] In some embodiments, the suppression module 36 is further configured to apply the second set of filtering parameters to the adaptive filtering processing module to perform interference suppression operation on the high-speed signal and obtain the suppressed second high-speed signal.

[0082] In some embodiments, the judgment module 34 is further specifically configured to: compare the first high-speed signal with an ideal signal, calculate the root mean square error (RMSE), and compare the RMS error with a preset error threshold, wherein the ideal signal refers to the signal transmitted by the high-speed signal in an ideal environment with no noise, no distortion, and infinite bandwidth. If the RMS error is greater than the preset error threshold, calculate the signal-to-noise ratio (SNR) change of the signal before and after suppression and the amplitude suppression ratio of the signal before and after suppression. Based on the SNR change of the signal before and after suppression and the amplitude suppression ratio of the signal before and after suppression, determine whether there is excessive suppression of the useful signal.

[0083] In some embodiments, another embodiment of this application further improves the high-speed signal receiving end of the protocol signal processing module. Figure 4 This is a schematic diagram of a high-speed signal receiver provided for some embodiments of this application. (See reference) Figure 4Since the high-speed signal rate is as high as 3.125 gigabits per second (Gbps), in this embodiment, a 0.1 microfarad 0402 coupling capacitor 41 is designed at the receiving end of each high-speed signal to isolate the DC bias generated during transmission. Furthermore, this coupling capacitor is not placed at a distance of 1 / 4 wavelength from the driving end to avoid standing wave effects. Here, the driving end refers to the signal source end, i.e., the chip or device that transmits the high-speed signal.

[0084] In some embodiments, to reduce common-mode signal interference, the high-speed signal in this embodiment is transmitted in the form of differential pairs. Figure 5 This is a schematic diagram illustrating the transmission of a high-speed signal according to some embodiments of this application. (Reference) Figure 5 , Figure 5 In the diagram, A, B, C, and D are four differential pairs. During PCB layout and routing, the length difference between the two signal lines within each differential pair should be controlled within 50 mils to avoid timing deviations. The distance between any two differential pairs in A, B, C, and D must be greater than three times the signal line width. Figure 6 This is a partially enlarged schematic diagram of the D-group difference pairs provided in some embodiments of this application. (See reference) Figure 6 The internal spacing S1 of the differential pair needs to be less than twice the signal line width S to ensure tight coupling.

[0085] Those skilled in the art will understand that although some embodiments herein include certain features included in other embodiments, combinations of features from different embodiments are intended to be within the scope of this application and form different embodiments. For example, in the claims, any of the claimed embodiments can be used in any combination.

[0086] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application 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 of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A high-speed signal receiving method for a protocol signal processing module, characterized in that, The method includes: acquiring an initial signal; determining the spectral distribution characteristics of the high-speed signal based on the initial signal; determining the interference frequency band range based on the spectral distribution characteristics; judging the dynamic change trend of the interference signal based on the interference frequency band range; if the power value of the interference signal under the dynamic change trend exceeds a power threshold range within a predetermined time, adaptively updating the filtering parameters of the interference frequency band range to obtain a first set of filtering parameters; applying the first set of filtering parameters to an adaptive filtering processing module to perform interference suppression operation on the high-speed signal and obtain a suppressed first high-speed signal; after applying the first set of filtering parameters to the adaptive filtering processing module to perform interference suppression operation on the high-speed signal and obtain a suppressed first high-speed signal, the method further includes: based on The method involves determining whether there is excessive suppression of the useful signal in the first high-speed signal. If excessive suppression of the useful signal exists, a second fine-tuning process is performed on the first set of filtering parameters to obtain a second set of filtering parameters. This includes: if there is excessive suppression of the useful signal, calculating the distortion of the first high-speed signal, and using an adaptive adjustment mechanism based on gradient descent to calculate the partial derivatives of the distortion with respect to each parameter in the first set of filtering parameters, determining the adjustment direction, and obtaining the second set of filtering parameters. After obtaining the second set of filtering parameters by performing the second fine-tuning process on the first set of filtering parameters, the method further includes: applying the second set of filtering parameters to an adaptive filtering processing module to perform interference suppression on the high-speed signal and obtain a suppressed second high-speed signal.

2. The method according to claim 1, characterized in that, The step of determining the interference frequency band range based on the spectral distribution characteristics includes: segmenting the frequency band range of the initial signal according to the spectral distribution characteristics using a preset frequency band division rule; obtaining energy data for each frequency band after segmentation; and determining the interference frequency band range based on the energy data.

3. The method according to claim 2, characterized in that, The step of determining the interference frequency band range based on the energy data includes: comparing the energy of each frequency band with the energy threshold, and initially determining the frequency band with the largest energy exceeding the energy threshold as the potential interference frequency band range; calculating the ratio between the potential interference frequency band range and the energy of the other frequency bands respectively, and if each ratio obtained is higher than the empirical ratio threshold and there is a peak feature in the potential interference frequency band range, then the potential interference frequency band range is the interference frequency band range.

4. The method according to claim 1, characterized in that, The step of determining the dynamic change trend of the interference signal based on the interference frequency band range includes: performing time-frequency analysis on the signal using short-time Fourier transform; inputting the time-frequency characteristic parameters obtained from the time-frequency analysis into an autoregressive moving average model using a time series analysis method to predict the possible dynamic change trend of the interference signal; calculating the power change rate of the interference signal; and determining the dynamic change trend of the interference signal based on the power change rate and the possible dynamic change trend.

5. The method according to claim 1, characterized in that, The determination of whether there is excessive suppression of the useful signal based on the suppressed first high-speed signal includes: comparing the first high-speed signal with an ideal signal, calculating the root mean square error (RMSE), comparing the RMS error with a preset error threshold, wherein the ideal signal refers to the signal after the high-speed signal is transmitted in an ideal environment with no noise, no distortion, and infinite bandwidth; if the RMS error is greater than the preset error threshold, calculating the signal-to-noise ratio (SNR) change of the signal before and after suppression and the amplitude suppression ratio of the signal before and after suppression; and determining whether there is excessive suppression of the useful signal based on the SNR change of the signal before and after suppression and the amplitude suppression ratio of the signal before and after suppression.

6. A high-speed signal receiving system for a protocol signal processing module, characterized in that, The system includes: an acquisition module for acquiring an initial signal; a first determination module for determining the spectral distribution characteristics of the high-speed signal based on the initial signal; a second determination module for determining the interference frequency band range based on the spectral distribution characteristics; a judgment module for judging the dynamic change trend of the interference signal based on the interference frequency band range; an update module for adaptively updating the filtering parameters of the interference frequency band range to obtain a first set of filtering parameters if the power value of the interference signal under the dynamic change trend exceeds a power threshold range within a predetermined time; and a suppression module for applying the first set of filtering parameters to the adaptive filtering processing module to perform interference suppression operation on the high-speed signal and obtain a suppressed first high-speed signal. After acquiring the suppressed first high-speed signal, the method further includes: based on the suppressed first high-speed signal, determining whether there is excessive suppression of the useful signal; if there is excessive suppression of the useful signal, performing secondary fine-tuning on the first set of filtering parameters to obtain a second set of filtering parameters, including: if there is excessive suppression of the useful signal, calculating the distortion of the first high-speed signal, and based on the adaptive adjustment mechanism of gradient descent, calculating the partial derivative of the distortion with respect to each parameter in the first set of filtering parameters, determining the adjustment direction, and obtaining the second set of filtering parameters; after performing secondary fine-tuning on the first set of filtering parameters to obtain the second set of filtering parameters, the method further includes: applying the second set of filtering parameters to an adaptive filtering processing module to perform interference suppression operation on the high-speed signal, and acquiring the suppressed second high-speed signal.

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