Digital signal analysis method and device, terminal and storage medium

Abstract

The invention discloses a digital signal analysis method and device, a terminal and a storage medium. The method comprises the following steps: eliminating data related jitter corresponding to a target digital signal from time interval error data corresponding to the target digital signal; obtaining a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal; obtaining an error rate curve corresponding to the target digital signal based on data related jitter corresponding to the target digital signal, the random jitter histogram and the periodic jitter histogram; generating a bathtub curve corresponding to the target digital signal according to the error rate curve corresponding to the target digital signal; and obtaining a target analysis result based on the bathtub curve. The invention aims to accurately and efficiently complete the jitter analysis of the digital signal so as to judge the stability of a digital signal system.

Description

Technical Field

[0001] The present application relates to the technical field of digital signal processing, and in particular to a digital signal analysis method, device, terminal and storage medium. Background Art

[0002] Jitter is the deviation of the edge of a signal from its ideal position. It is a key indicator for the signal integrity test of a digital system. For clock and serial signals, jitter directly affects performance. Excessive jitter may cause data reception errors and increase the bit error rate (BER) of digital products, thereby affecting system performance. In order to ensure the stability of high-speed digital systems, test and measurement instruments such as oscilloscopes are usually required to perform jitter analysis on the signal, identify and separate different types of jitter components, and analyze the total jitter at a specific bit error rate to ensure that the device can meet the relevant bit error performance standards.

[0003] However, the existing signal jitter analysis methods have the following problems: In traditional signal jitter analysis, the inverse error function usually used is highly dependent on mathematical tools or data analysis software. Summary of the invention

[0004] The main purpose of the present application is to provide a digital signal analysis method, device, terminal and storage medium, aiming to accurately and efficiently complete the jitter analysis of digital signals in order to determine the stability of the digital signal system when traditional mathematical tools or data analysis software packages cannot be used.

[0005] To achieve the above object, the present application provides a digital signal analysis method, the method comprising:

[0006] Eliminating data-related jitter corresponding to the target digital signal from the time interval error data corresponding to the target digital signal to obtain residual jitter time interval error data, wherein the data-related jitter is used to characterize the jitter caused by the change of the input data pattern during the transmission of the target digital signal, and the residual jitter time interval error data is used to characterize the jitter time interval error related to the random jitter of the target digital signal and the periodic jitter of the target digital signal;

[0007] Processing the residual jitter time interval error data to obtain a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal;

[0008] Obtaining a bit error rate curve corresponding to the target digital signal based on the data-dependent jitter corresponding to the target digital signal, the random jitter histogram, and the periodic jitter histogram;

[0009] Generate a bathtub curve corresponding to the target digital signal according to the bit error rate curve corresponding to the target digital signal by using a preset mathematical model;

[0010] Based on the bathtub curve corresponding to the target digital signal, a target analysis result is obtained, wherein the target analysis result is used to characterize the jitter characteristics of the target digital signal.

[0011] Specifically, before removing the data-related jitter in the time interval error data corresponding to the target digital signal to obtain the remaining jitter time interval error data, the method further includes:

[0012] Performing clock recovery processing on the target digital signal to obtain a reference clock corresponding to the target digital signal;

[0013] Based on the reference clock, calculate and obtain time interval error data corresponding to the target digital signal;

[0014] Performing autocorrelation processing on the bit stream corresponding to the target digital signal to obtain the pattern length of the repetitive sequence in the bit stream corresponding to the target digital signal;

[0015] Based on the pattern length of the repetitive sequence and the time interval error data corresponding to the target digital signal, the data-dependent jitter corresponding to the target digital signal is obtained.

[0016] Specifically, obtaining the data-dependent jitter corresponding to the target digital signal based on the pattern length of the repetitive sequence and the time interval error data corresponding to the target digital signal includes:

[0017] Based on the pattern length of the repetitive sequence, the time interval error data corresponding to the target digital signal is divided into at least one time interval error data group, wherein the bit stream corresponding to the target digital signal includes at least one repetitive sequence, and the repetitive sequence corresponds to the time interval error data group one by one;

[0018] Calculate and obtain the average value corresponding to each time interval error data group;

[0019] Based on the average values ​​corresponding to the respective time interval error data groups, the standard deviation of the average values ​​corresponding to the respective time interval error data groups is calculated, wherein the average values ​​corresponding to the respective time interval error data groups correspond to the standard deviation of the average values ​​corresponding to the respective time interval error data groups in a one-to-one manner, and the standard deviation of the average values ​​corresponding to the respective time interval error data groups is used to characterize a repetitive sequence;

[0020] The standard deviations of the mean values ​​corresponding to the respective time interval error data groups are combined to obtain the data-dependent jitter corresponding to the target digital signal.

[0021] Specifically, the processing of the residual jitter time interval error data to obtain a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal includes:

[0022] Performing fast Fourier transform processing on the residual jitter time interval error data to obtain a frequency spectrum diagram corresponding to the residual jitter time interval error data;

[0023] Based on a preset threshold, extracting a random jitter frequency component and a periodic jitter frequency component from a frequency spectrum corresponding to the residual jitter time interval error data;

[0024] A random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal are generated based on the random jitter frequency component and the periodic jitter frequency component through a preset data statistical tool library.

[0025] Specifically, obtaining a bit error rate curve corresponding to the target digital signal based on the data-dependent jitter corresponding to the target digital signal, the random jitter histogram, and the periodic jitter histogram includes:

[0026] Based on the data-dependent jitter corresponding to the target digital signal, generating a data-dependent jitter histogram corresponding to the data-dependent jitter;

[0027] Performing convolution calculation processing on the data-dependent jitter histogram, the random jitter histogram, and the periodic jitter histogram to obtain an overall jitter histogram corresponding to the target digital signal;

[0028] Based on the overall jitter histogram, a total jitter probability density function corresponding to the target digital signal is calculated, wherein the overall jitter probability density function is used to characterize the distribution of the signal jitter of the target digital signal around the timing center of the target digital signal;

[0029] Performing an integral calculation process on the overall jitter probability density function to obtain an integral calculation result corresponding to the overall jitter probability density function;

[0030] Based on the integral calculation result, a bit error rate curve corresponding to the target digital signal is generated.

[0031] Specifically, the preset mathematical model includes a dual Dirac model;

[0032] The method of generating a bathtub curve corresponding to the target digital signal by using a preset mathematical model according to a bit error rate curve corresponding to the target digital signal comprises:

[0033] The bit error rate curve corresponding to the target digital signal is extrapolated by the dual Dirac model to obtain a bathtub curve corresponding to the target digital signal.

[0034] Specifically, the target analysis result includes target total jitter data, wherein the target total jitter data includes the signal total jitter values ​​corresponding to the target digital signal at different bit error rates;

[0035] The step of obtaining a target analysis result based on a bathtub curve corresponding to the target digital signal includes:

[0036] The target total jitter data is calculated based on the bathtub curve by using a spectrum method or a tail fitting method.

[0037] To achieve the above object, the present application also provides a digital signal analysis device, the device comprising:

[0038] The first unit is used to remove data-related jitter corresponding to the target digital signal from the time interval error data corresponding to the target digital signal to obtain residual jitter time interval error data, wherein the data-related jitter is used to characterize the jitter caused by the change of the input data pattern during the transmission of the target digital signal, and the residual jitter time interval error data is used to characterize the jitter time interval error related to the random jitter of the target digital signal and the periodic jitter of the target digital signal;

[0039] The second unit is used to process the residual jitter time interval error data to obtain a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal;

[0040] A third unit is used to obtain a bit error rate curve corresponding to the target digital signal based on the data-dependent jitter corresponding to the target digital signal, the random jitter histogram and the periodic jitter histogram;

[0041] A fourth unit is used to generate a bathtub curve corresponding to the target digital signal according to the bit error rate curve corresponding to the target digital signal by using a preset mathematical model;

[0042] The fifth unit is used to obtain a target analysis result based on the bathtub curve corresponding to the target digital signal, wherein the target analysis result is used to characterize the jitter characteristics of the target digital signal.

[0043] To achieve the above-mentioned purpose, the present application also provides a terminal, including a memory storing multiple instructions; the processor loads instructions from the memory to execute the steps in any one of the methods provided in the present application.

[0044] To achieve the above objectives, the present application also provides a storage medium, which stores multiple instructions, and the instructions are suitable for a processor to load to execute the steps in any method provided in the present application.

[0045] The present application provides a digital signal analysis method, device, terminal and storage medium. First, the data-related jitter corresponding to the target digital signal can be eliminated from the time interval error data corresponding to the target digital signal to obtain the jitter time interval error related to the random jitter of the target digital signal and the periodic jitter of the target digital signal, wherein the data-related jitter is used to characterize the jitter of the target digital signal caused by the change of the input data pattern during the transmission process; then, the remaining jitter time interval error data is processed to obtain the random jitter histogram corresponding to the target digital signal and the periodic jitter histogram corresponding to the target digital signal; then, based on the data-related jitter corresponding to the target digital signal, the random jitter histogram and the periodic jitter histogram, the bit error rate curve corresponding to the target digital signal is obtained; then, through a preset mathematical model, according to the bit error rate curve corresponding to the target digital signal, a bathtub curve corresponding to the target digital signal is generated; finally, based on the bathtub curve corresponding to the target digital signal, the target analysis result is accurately calculated, wherein the target analysis result is used to characterize the jitter characteristics of the target digital signal.

[0046] It can be seen that the present application provides a new digital signal analysis method. Compared with the existing signal jitter analysis means, it can accurately and efficiently complete the jitter analysis of digital signals without relying on traditional mathematical tools or data analysis software to determine the stability of the digital signal system. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic diagram of a process flow provided for an embodiment of the present application;

[0048] Figure 2 A schematic diagram of the relationship between bit error rate and jitter provided in an embodiment of the present application;

[0049] Figure 3 A schematic diagram of a bathtub curve provided in an embodiment of the present application;

[0050] Figure 4 A schematic diagram of the Q value error provided in the embodiment of the present application;

[0051] Figure 5 A schematic diagram of the structure of a digital signal analysis device provided in an embodiment of the present application;

[0052] Figure 6 A schematic diagram of the structure of a terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0054] In traditional signal jitter analysis, the inverse error function usually used relies heavily on mathematical tools or data analysis software; and conventional signal jitter analysis methods cannot accurately quantify the various components of jitter, and it is difficult to distinguish different types of jitter in the total jitter of the signal. Therefore, the embodiments of the present application provide a digital signal analysis method, device, terminal and storage medium to solve practical technical problems.

[0055] The embodiment of the present application provides a digital signal analysis method, which can accurately and efficiently complete the jitter analysis of digital signals to determine the stability of the digital signal system when traditional mathematical tools or data analysis software packages cannot be used. The following specifically describes how to implement the jitter analysis of digital signals.

[0056] like Figure 1 As shown, the specific process of the method can be as follows:

[0057] S110. Eliminate data-related jitter corresponding to the target digital signal from the time interval error data corresponding to the target digital signal to obtain residual jitter time interval error data, wherein the data-related jitter is used to characterize jitter caused by changes in the input data pattern during the transmission of the target digital signal, and the residual jitter time interval error data is used to characterize jitter time interval errors related to random jitter of the target digital signal and periodic jitter of the target digital signal.

[0058] The target digital signal may be a digital signal, which refers to a signal that is discrete in time and amplitude and is usually used in digital communication and digital signal processing, wherein information is encoded as a series of binary digits (0 and 1).

[0059] The time interval error data may be a time interval error, a time interval error (TIE). In a communication system, TIE refers to the deviation of each active edge of a signal from its ideal position. TIE is critical to the stability and reliability of the system. A high-precision signal source usually requires a low TIE to ensure the quality of data transmission.

[0060] The data-dependent jitter may be data-dependent jitter (DDJ), which refers to a phenomenon in which the jitter of a signal is related to the data pattern of the transmission in a digital communication system. Data-dependent jitter is usually caused by nonlinear characteristics in the circuit, which produce different responses depending on the input data. Data-dependent jitter is a component of the total jitter and affects the timing performance of the signal and the overall performance of the system.

[0061] In some embodiments, data-related jitter corresponding to the target digital signal is removed from the time interval error data corresponding to the target digital signal to obtain a jitter time interval error related to the random jitter of the target digital signal and the periodic jitter of the target digital signal.

[0062] Random jitter (RJ) refers to an unpredictable and randomly distributed jitter that occurs in digital signals. It is not caused by a specific data pattern, but by various random noises and uncertainties in the signal transmission path. Random jitter is a component of total jitter and has a significant impact on signal quality and system performance.

[0063] Periodic jitter (PJ) refers to a repetitive and predictable jitter in digital signals. Periodic jitter is usually caused by periodic changes in the signal transmission path. These changes may be caused by factors such as resonance in the circuit, power supply ripple, mechanical vibration, or instability of the clock signal. Unlike random jitter, periodic jitter is predictable and usually appears as discrete spectral lines in the frequency domain.

[0064] In some embodiments, before removing the data-related jitter in the time interval error data corresponding to the target digital signal to obtain the remaining jitter time interval error data, the method further includes steps A1 to A4 as shown below:

[0065] A1. Perform clock recovery processing on the target digital signal to obtain a reference clock corresponding to the target digital signal.

[0066] In some embodiments, clock recovery is an important step in digital signal processing, especially in high-speed data communication systems, the purpose of which is to extract a stable clock signal from a received digital signal so that the signal can be sampled and decoded correctly.

[0067] Specifically, the reference clock can be obtained through the following specific implementation process:

[0068] Preprocessing: Use a bandpass filter to remove unwanted noise; amplify the signal appropriately to ensure sufficient amplitude;

[0069] Design clock recovery circuit: Choose DPLL, which is suitable for high-speed data communication and easy to integrate;

[0070] Implement clock recovery: Connect the received signal to the input of the DPLL; configure the DPLL parameters, such as loop bandwidth, to accommodate the specific data rate; start the clock recovery process, and the DPLL will automatically adjust the frequency and phase of its internal VCO or DCO to synchronize with the input signal;

[0071] Lock detection: When the DPLL successfully locks onto the signal, the lock indicator will give feedback, indicating that clock recovery is complete;

[0072] Clock signal output: DPLL outputs a clean and stable clock signal, the reference clock, which is synchronized with the input data stream.

[0073] A2. Based on the reference clock, calculate and obtain time interval error data corresponding to the target digital signal.

[0074] In some embodiments, the time interval error data corresponding to the target digital signal may be calculated by the following specific implementation process:

[0075] Align signal: Align the target digital signal with the signal corresponding to the reference clock to ensure that the time axes of the two signals are consistent;

[0076] Extract edges: Identify rising or falling edges in the target digital signal and record the position of each edge relative to the reference clock;

[0077] Calculate time deviation: For each edge, calculate its actual time deviation relative to the nearest reference clock edge. This actual time deviation can be positive (signal advance) or negative (signal lag);

[0078] Record deviation: record the time deviation of each edge to form a series of values;

[0079] Calculate TIE: For each measured time deviation, calculate the deviation value relative to the ideal position; define TIE as the maximum absolute value of these deviations to obtain the time interval error data.

[0080] A3. Perform an autocorrelation operation on the bit stream corresponding to the target digital signal to obtain a pattern length of a repeated sequence in the bit stream corresponding to the target digital signal.

[0081] A bit stream refers to data transmitted in a communication system represented as a series of binary bits. Usually, these bits are encoded according to certain rules. A bit stream is the basic form of a digital signal, consisting of a series of 0s and 1s, representing a digital representation of the original information.

[0082] Autocorrelation is a mathematical tool used to measure how similar a signal is to itself at different time offsets. In digital signal processing, autocorrelation is often used to detect repetitive patterns in a signal.

[0083] In some embodiments, for a given bit stream x[n], all possible autocorrelation functions Rxx[τ] are calculated. Typically, τ ranges from 0 to N-1. A peak in the autocorrelation function is found. The peak appears at τ, which means that there is a repeating pattern in the bit stream, and its length is τ. Typically, the largest peak corresponds to the longest repeating pattern, thereby obtaining the pattern length of the repeating sequence in the bit stream corresponding to the target digital signal.

[0084] A4. Obtain data-dependent jitter corresponding to the target digital signal based on the pattern length of the repetitive sequence and the time interval error data corresponding to the target digital signal.

[0085] In some embodiments, obtaining the data-dependent jitter corresponding to the target digital signal based on the pattern length of the repetitive sequence and the time interval error data corresponding to the target digital signal includes steps A401 to A404 as shown below:

[0086] A401. Based on the pattern length of the repetitive sequence, the time interval error data corresponding to the target digital signal is divided into at least one time interval error data group, wherein the bit stream corresponding to the target digital signal includes at least one repetitive sequence, and the repetitive sequence corresponds to the time interval error data group one by one.

[0087] A402. Calculate and obtain the average value corresponding to each time interval error data group.

[0088] A403. Based on the average values ​​corresponding to the various time interval error data groups, calculate the standard deviation of the average values ​​corresponding to the various time interval error data groups, wherein the average values ​​corresponding to the various time interval error data groups correspond one to one with the standard deviation of the average values ​​corresponding to the various time interval error data groups, and the standard deviation of the average values ​​corresponding to the various time interval error data groups is used to characterize a repetitive sequence.

[0089] A404 , combining the standard deviations of the mean values ​​corresponding to the various time interval error data groups to obtain data-dependent jitter corresponding to the target digital signal.

[0090] S120: Process the remaining jitter time interval error data to obtain a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal.

[0091] In some embodiments, the processing of the residual jitter time interval error data to obtain a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal includes the following steps S121 to S123:

[0092] S121. Perform fast Fourier transform processing on the residual jitter time interval error data to obtain a frequency spectrum corresponding to the residual jitter time interval error data.

[0093] Fast Fourier Transform (FFT) is an efficient algorithm for calculating Discrete Fourier Transform (DFT). DFT is a method for converting signals from the time domain to the frequency domain, and FFT is an efficient way to achieve this conversion.

[0094] In some embodiments, the residual jitter time interval error data is processed using a fast Fourier transform (FFT) to obtain its frequency domain representation. FFT converts the time domain data into the frequency domain, which makes it easier to identify the contribution of different frequency components. An amplitude spectrum is calculated from the FFT result, which will give the amplitude of each frequency component. The amplitude spectrum is usually represented as part of a spectrogram. The spectrum is drawn using the amplitude spectrum to visualize the contribution of different frequency components. The spectrum diagram usually shows the relationship between frequency (abscissa) and amplitude (ordinate).

[0095] S122: Based on a preset threshold, extract a random jitter frequency component and a periodic jitter frequency component from a frequency spectrum corresponding to the remaining jitter time interval error data.

[0096] In some embodiments, in order to distinguish between random jitter and periodic jitter, the preset threshold needs to be set, and the preset threshold can be determined based on statistical characteristics of data or domain knowledge.

[0097] Specifically, in the spectrum diagram, periodic jitter appears as a significant peak, while random jitter appears as a relatively smooth background noise. By comparing the amplitude in the spectrum with the preset threshold, the random jitter frequency component and the periodic jitter frequency component can be extracted.

[0098] S123. Generate a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal based on the random jitter frequency component and the periodic jitter frequency component by using a preset data statistical tool library.

[0099] In some embodiments, the preset data statistics tool library can be matplotlib, which is a widely used Python 2D drawing library that can generate publication-quality graphics. Matplotlib is very flexible and compatible with a variety of operating systems and graphics backends. The core module of matplotlib is pyplot, which provides a MATLAB-style interface that makes drawing simple and intuitive.

[0100] Specifically, the number of bins of the histogram (bins=20) can be adjusted to accommodate the input data range and distribution. If the input data range is large or small, this parameter may need to be adjusted, while the color, transparency, and other parameters may also be adjusted to improve the visualization effect.

[0101] S130 , obtaining a bit error rate curve corresponding to the target digital signal based on the data-dependent jitter corresponding to the target digital signal, the random jitter histogram, and the periodic jitter histogram.

[0102] In some embodiments, the bit error rate curve corresponding to the target digital signal is obtained based on the data-dependent jitter corresponding to the target digital signal, the random jitter histogram, and the periodic jitter histogram, including the steps S131 to S135 as shown below:

[0103] S131. Generate a data-dependent jitter histogram corresponding to the data-dependent jitter based on the data-dependent jitter corresponding to the target digital signal.

[0104] S132: Perform convolution calculation processing on the data-dependent jitter histogram, the random jitter histogram, and the periodic jitter histogram to obtain an overall jitter histogram corresponding to the target digital signal.

[0105] In some embodiments, three independent histogram data sets may be established according to the data-dependent jitter histogram, the random jitter histogram, and the periodic jitter histogram, and convolution calculations may be performed on the histogram data sets to obtain an overall jitter data set, and the overall jitter data set may be converted into the overall jitter histogram.

[0106] S133. Based on the overall jitter histogram, calculate and obtain an overall jitter probability density function corresponding to the target digital signal, wherein the overall jitter probability density function is used to characterize a distribution of the signal jitter of the target digital signal around a timing center of the target digital signal.

[0107] The probability density function (PDF) is a way of describing the probability distribution of a continuous random variable, describing the relative likelihood of the random variable taking a value near a certain value. The probability density function is usually represented by f(x), where x is the value that the random variable can take.

[0108] In some embodiments, the total frequency can be calculated based on the overall jitter histogram, and the total frequency is the sum of all frequencies; the overall jitter probability density is calculated according to probability density = frequency / (total frequency*interval width), and finally a function graph is drawn using the calculated overall jitter probability density, and the function graph is used to characterize the overall jitter probability density function corresponding to the target digital signal.

[0109] In some embodiments, the probability density function (PDF) mathematical model of DJ and RJ is expressed as follows:

[0110]

[0111] Where x represents the amplitude of the jitter, μ L Indicates the peak value on the left side of DJ, μ R Indicates the peak value on the right side of DJ.

[0112] The random and deterministic components in jitter are uncorrelated, and the PDF of the total jitter TJ can be obtained by convolving the two:

[0113] TJ(x)=DJ δδ (x)*RJ(x)

[0114] S134: Performing an integral calculation process on the overall jitter probability density function to obtain an integral calculation result corresponding to the overall jitter probability density function.

[0115] S135. Generate a bit error rate curve corresponding to the target digital signal based on the integral calculation result.

[0116] The bit error rate (BER) is an important indicator for measuring the quality of data transmission in digital communication systems. It indicates the ratio of the number of bits received in error to the total number of bits transmitted during the transmission process. The lower the BER, the better the system performance; otherwise, it means that the system performance is poor or there is more interference.

[0117] In some embodiments, the relationship between bit error rate and jitter can be understood by the sampling time of the eye diagram, which is graphically represented by the bathtub curve. Figure 2 As shown, the closer the sampling time x is to the 0 / 1 change edge, the greater the bit error rate.

[0118] The mathematical expression of bit error rate is:

[0119] BER L (x) = ρ T ∫0 x TJ(x)dx

[0120]

[0121] Among them, for the clock signal ρ T =1; for random code PRBS, ρ T =0.5, the above two expressions can be used to obtain the bit error rate curves on the left and right sides. The bit error rate curve on the left represents the integral from time 0 to x; the bit error rate curve on the right represents the integral from x to time T. The size of T is determined by UI (unit interval).

[0122] In some embodiments, Q space is a mathematical transformation of the probability axis of the cumulative distribution function (CDF), so that the Gaussian distribution is represented as a straight line with a slope inversely related to the standard deviation. Taking the standard normal distribution as an example, its cumulative distribution function (CDF), or Gaussian integral function, can be expressed by an error function (Error Function) as:

[0123]

[0124] Its complementary error function is defined as follows:

[0125]

[0126] The bit error rate can be expressed by the erfc function as:

[0127]

[0128] definition Where μ is the mean of the normal distribution and σ is the standard deviation of the normal distribution. It can be obtained that in the case of ordinary normal distribution, the relationship between Q(x) and the erfc function is:

[0129]

[0130] Where β(x) is the bit error rate corresponding to the sampling time x, where β(x) = BER L (x) = 1-BERR (x).

[0131] S140. Generate a bathtub curve corresponding to the target digital signal according to a bit error rate curve corresponding to the target digital signal by using a preset mathematical model.

[0132] In some embodiments, the preset mathematical model includes a dual Dirac model, and the generating of a bathtub curve corresponding to the target digital signal by using the preset mathematical model according to the bit error rate curve corresponding to the target digital signal includes the following specific implementation process:

[0133] The bit error rate curve corresponding to the target digital signal is extrapolated by the dual Dirac model to obtain a bathtub curve corresponding to the target digital signal.

[0134] The Bathtub Curve is a graphical representation used to describe the failure rate of a product or system over time. It is named because of its bathtub-like shape. The Bathtub Curve is usually divided into three different stages, each of which represents a different failure rate characteristic in the life cycle of a product or system.

[0135] The Dual-Dirac Model is a method for analyzing and describing signal jitter in digital communication systems, especially for high-speed serial data links such as PCI Express, SATA, USB and other high-speed interfaces. The Dual-Dirac Model can help engineers quantify and understand the impact of different types of jitter on system performance, especially for the evaluation of bit error rate (BER).

[0136] Continuing with the above-mentioned embodiment, combined with the above-mentioned expression, the relationship between the bathtub curve and the sampling time in the Q space can be obtained as follows:

[0137]

[0138] It can be seen that the tail of the Q-space bathtub curve has linear characteristics.

[0139] S150. Obtain a target analysis result based on a bathtub curve corresponding to the target digital signal, wherein the target analysis result is used to characterize a jitter characteristic of the target digital signal.

[0140] In some embodiments, the target analysis result includes target total jitter data, wherein the target total jitter data includes the signal total jitter values ​​corresponding to the target digital signal at different bit error rates, and the target analysis result is obtained based on the bathtub curve corresponding to the target digital signal, including the specific implementation process shown below:

[0141] The target total jitter data is calculated based on the bathtub curve by using a spectrum method or a tail fitting method. The bathtub curve is as follows: Figure 3 shown.

[0142] In some embodiments, according to the characteristics of the dual Dirac model, RJrms, DJ can be obtained by the following expressions: δδ and TJ(β), TJ(β) is also TJ@BER, that is, the target total jitter data.

[0143]

[0144] DJ δδ =(μ R +μ L )

[0145] TJ(β)=DJ δδ +2Q(β)*RJrms

[0146] Among them, DJ δδ It represents a specific part of deterministic jitter (DJ), which is represented by two Greek letters δ (delta). It can be a deterministic jitter component between two specific points, or a specific type of deterministic jitter. RJrms represents the root mean square (RMS) value of random jitter (RJ), which is an important parameter used to describe random jitter in the dual Dirac model.

[0147] DJ can be obtained by spectrum method or tail fitting method. δδ and RJrms, and then derive TJ@BER based on the above expression, that is, TJ corresponding to different bit error rates.

[0148] In combination with the above method, the embodiment of the present application also proposes a specific testing process to verify the technical effect of the embodiment of the present application:

[0149] From the relationship between bit error rate and overall jitter mentioned above, we can know that:

[0150] The bit error rate can be obtained by integrating the overall jitter PDF. The bit error rate can be expressed in Q space, that is, if the bit error rate is known, the Q value can be converted; if the Q value is known, the bit error rate can be inverted. The inverse error function erfc-1 is required to transform the bit error rate into Q space.

[0151] Therefore, referring to the above findings, the effect test was carried out through the following specific test process:

[0152] Test conditions and contents:

[0153] The PRBS random code waveform is transmitted through an arbitrary waveform generator with a baud rate of 1 Gbps. The waveform is collected by an oscilloscope, and then the jitter analysis method based on the inverse error function lookup table proposed in the present invention is used to perform offline jitter analysis, and the jitter analysis results when the inverse error function (erfcinv) of Matlab is used are compared;

[0154] Test result analysis:

[0155] Reference Figure 4 , "Q value Error" is the Q value error, which refers to the difference between the estimated Q value and the actual (or target) Q value in reinforcement learning, especially when using Q-learning or Deep Q-Networks (DQN) methods. This error is used to measure the accuracy of the value estimate of state-action pairs during the agent learning process.

[0156] "q value fitting error" is a measure of the difference between the estimated Q value and the target Q value in reinforcement learning, especially when using Q-learning or Deep Q-Networks (DQN) methods. This error is often used to measure the accuracy of Q value estimation during agent learning.

[0157] The Q value obtained by the method proposed in the embodiment of the present application is compared with the Q value calculated by the inverse error function (erfcinv) of Matlab, and its error is less than 10E-5 when the BER is less than 10E-2. When the BER gradually approaches 0.5 from 10E-2, the error gradually increases, and the maximum error is about 0.15. Therefore, the method proposed in the embodiment of the present application is mainly used for Q value transformation when the BER is small (less than 10E-2). In the scope of jitter analysis, it is easy to obtain a BER less than 10E-4 through measurement data, and the extrapolation of the bathtub curve and the estimation of TJ@BER will not result in a situation where the BER is less than 10E-2; when jitter analysis is performed by the method, the bathtub curve obtained is compared with the jitter analysis performed using Matlab erfcinv, and the TJ error corresponding to the same BER is about 10E-9UI (1UI=1ns). For different TJ@BERs that users are interested in, there may be error situations as shown in Table 1:

[0158]

[0159] Table 1 Error table

[0160] The error of the calculated result of TJ@BER is in the order of 10E-7ps, which is almost negligible. Therefore, the method is accurate and effective for signal jitter analysis.

[0161] As can be seen from the above, the embodiment of the present application can first remove the data-related jitter corresponding to the target digital signal from the time interval error data corresponding to the target digital signal, and obtain the jitter time interval error related to the random jitter of the target digital signal and the periodic jitter of the target digital signal, wherein the data-related jitter is used to characterize the jitter caused by the change of the input data pattern during the transmission of the target digital signal; then, the remaining jitter time interval error data is processed to obtain the random jitter histogram corresponding to the target digital signal and the periodic jitter histogram corresponding to the target digital signal; then, based on the data-related jitter corresponding to the target digital signal, the random jitter histogram and the periodic jitter histogram, the bit error rate curve corresponding to the target digital signal is calculated; then, through a preset mathematical model, according to the bit error rate curve corresponding to the target digital signal, a bathtub curve corresponding to the target digital signal is generated; finally, based on the bathtub curve corresponding to the target digital signal, the target analysis result is accurately calculated, wherein the target analysis result is used to characterize the jitter characteristics of the target digital signal.

[0162] In summary, compared with the existing signal jitter analysis method, the embodiment of the present application can accurately and efficiently complete the jitter analysis of digital signals to determine the stability of the digital signal system without relying on traditional mathematical tools or data analysis software.

[0163] In order to better implement the above method, the embodiment of the present application also provides a digital signal analysis device, which can be integrated in an electronic device, and the electronic device can be a terminal, a server, etc. Among them, the terminal can be a mobile phone, a tablet computer, a smart Bluetooth device, a laptop, a personal computer, etc.; the server can be a single server or a server cluster composed of multiple servers.

[0164] For example, in this embodiment, the method of the embodiment of the present application is described in detail by taking the digital signal analysis device being specifically integrated in the terminal as an example.

[0165] For example, Figure 5 As shown, the digital signal analysis device may include a first unit 501, a second unit 502, a third unit 503, a fourth unit 504 and a fifth unit 505, and the device includes:

[0166] The first unit 501 is used to remove data-related jitter corresponding to the target digital signal from the time interval error data corresponding to the target digital signal to obtain residual jitter time interval error data, wherein the data-related jitter is used to characterize the jitter caused by the change of the input data pattern during the transmission of the target digital signal, and the residual jitter time interval error data is used to characterize the jitter time interval error related to the random jitter of the target digital signal and the periodic jitter of the target digital signal;

[0167] The second unit 502 is used to process the residual jitter time interval error data to obtain a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal;

[0168] The third unit 503 is used to obtain a bit error rate curve corresponding to the target digital signal based on the data-dependent jitter corresponding to the target digital signal, the random jitter histogram and the periodic jitter histogram;

[0169] The fourth unit 504 is used to generate a bathtub curve corresponding to the target digital signal according to the bit error rate curve corresponding to the target digital signal by using a preset mathematical model;

[0170] The fifth unit 505 is used to obtain a target analysis result based on the bathtub curve corresponding to the target digital signal, wherein the target analysis result is used to characterize the jitter characteristics of the target digital signal.

[0171] In specific implementation, the above units can be implemented as independent entities, or can be arbitrarily combined to be implemented as the same or several entities. The specific implementation of the above units can refer to the previous method embodiments, which will not be repeated here.

[0172] It can be seen from the above that the embodiments of the present application can accurately and efficiently complete the jitter analysis of digital signals to determine the stability of the digital signal system.

[0173] The embodiment of the present application also provides an electronic device, which can be a terminal, a server, etc. The terminal can be a mobile phone, a tablet computer, a smart Bluetooth device, a laptop, a personal computer, etc. The server can be a single server or a server cluster composed of multiple servers, etc.

[0174] In some embodiments, the digital signal analysis device may also be integrated into multiple electronic devices. For example, the digital signal analysis device may be integrated into multiple servers, and the digital signal analysis method of the present application may be implemented by multiple servers.

[0175] In this embodiment, the electronic device of this embodiment is a terminal as an example for detailed description, for example, Figure 6 As shown, it shows a schematic diagram of the structure of the terminal involved in the embodiment of the present application, specifically:

[0176] The terminal may include one or more processing core processors 601, one or more storage media memories 602, a power supply 603, an input module 604, and a communication module 605. Those skilled in the art will appreciate that Figure 6 The terminal structure shown in the figure does not constitute a limitation on the terminal, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0177] The processor 601 is the control center of the terminal. It uses various interfaces and lines to connect various parts of the entire terminal. It executes various functions of the terminal and processes data by running or executing software programs and / or modules stored in the memory 602, and calling data stored in the memory 602, so as to monitor the terminal as a whole. In some embodiments, the processor 601 may include one or more processing cores; in some embodiments, the processor 601 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 601.

[0178] The memory 602 can be used to store software programs and modules. The processor 601 executes various functional applications and data processing by running the software programs and modules stored in the memory 602. The memory 602 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 602 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 602 may also include a memory controller to provide the processor 601 with access to the memory 602.

[0179] The terminal also includes a power supply 603 for supplying power to various components. In some embodiments, the power supply 603 can be logically connected to the processor 601 through a power management system, so as to manage charging, discharging, and power consumption through the power management system. The power supply 603 can also include any components such as one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators.

[0180] The terminal may further include an input module 604, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball digital signal input related to user settings and function control.

[0181] The terminal may also include a communication module 605. In some embodiments, the communication module 605 may include a wireless module. The terminal may perform short-range wireless transmission through the wireless module of the communication module 605, thereby providing the user with wireless broadband Internet access. For example, the communication module 605 may be used to help the user send and receive emails, browse web pages, and access streaming media.

[0182] Although not shown, the terminal may also include a display unit, etc., which will not be described in detail here. Specifically in this embodiment, the processor 601 in the terminal will load the executable files corresponding to the processes of one or more applications into the memory 602 according to the following instructions, and the processor 601 will run the application stored in the memory 602 to implement various functions, as follows:

[0183] Eliminating data-related jitter corresponding to the target digital signal from the time interval error data corresponding to the target digital signal to obtain residual jitter time interval error data, wherein the data-related jitter is used to characterize the jitter caused by the change of the input data pattern during the transmission of the target digital signal, and the residual jitter time interval error data is used to characterize the jitter time interval error related to the random jitter of the target digital signal and the periodic jitter of the target digital signal;

[0184] Processing the residual jitter time interval error data to obtain a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal;

[0185] Obtaining a bit error rate curve corresponding to the target digital signal based on the data-dependent jitter corresponding to the target digital signal, the random jitter histogram, and the periodic jitter histogram;

[0186] Generate a bathtub curve corresponding to the target digital signal according to the bit error rate curve corresponding to the target digital signal by using a preset mathematical model;

[0187] Based on the bathtub curve corresponding to the target digital signal, a target analysis result is obtained, wherein the target analysis result is used to characterize the jitter characteristics of the target digital signal.

[0188] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0189] It can be seen from the above that the embodiments of the present application can accurately and efficiently complete the jitter analysis of digital signals to determine the stability of the digital signal system.

[0190] A person skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a storage medium and loaded and executed by a processor.

[0191] To this end, an embodiment of the present application provides a storage medium in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any one of the digital signal analysis methods provided in the embodiments of the present application. For example, the instructions can execute the following steps:

[0192] Eliminating data-related jitter corresponding to the target digital signal from the time interval error data corresponding to the target digital signal to obtain residual jitter time interval error data, wherein the data-related jitter is used to characterize the jitter caused by the change of the input data pattern during the transmission of the target digital signal, and the residual jitter time interval error data is used to characterize the jitter time interval error related to the random jitter of the target digital signal and the periodic jitter of the target digital signal;

[0193] Processing the residual jitter time interval error data to obtain a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal;

[0194] Obtaining a bit error rate curve corresponding to the target digital signal based on the data-dependent jitter corresponding to the target digital signal, the random jitter histogram, and the periodic jitter histogram;

[0195] Generate a bathtub curve corresponding to the target digital signal according to the bit error rate curve corresponding to the target digital signal by using a preset mathematical model;

[0196] Based on the bathtub curve corresponding to the target digital signal, a target analysis result is obtained, wherein the target analysis result is used to characterize the jitter characteristics of the target digital signal.

[0197] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0198] According to one aspect of the present application, a computer program product or a computer program is provided, the computer program product or the computer program includes computer instructions, the computer instructions are stored in a storage medium. A processor of a computer device reads the computer instructions from the storage medium, and the processor executes the computer instructions, so that the computer device executes the method provided in various optional implementations provided in the above embodiments.

[0199] Since the instructions stored in the storage medium can execute the steps in any digital signal analysis method provided in the embodiments of the present application, the beneficial effects that can be achieved by any digital signal analysis method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0200] The above is a detailed introduction to a digital signal analysis method, device, terminal and storage medium provided in the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the ideas of the present application, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A digital signal analysis method, characterized in that: The method comprises: Eliminating data-related jitter corresponding to the target digital signal from the time interval error data corresponding to the target digital signal to obtain residual jitter time interval error data, wherein the data-related jitter is used to characterize the jitter caused by the change of the input data pattern during the transmission of the target digital signal, and the residual jitter time interval error data is used to characterize the jitter time interval error related to the random jitter of the target digital signal and the periodic jitter of the target digital signal; Processing the residual jitter time interval error data to obtain a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal; Obtaining a bit error rate curve corresponding to the target digital signal based on the data-dependent jitter corresponding to the target digital signal, the random jitter histogram, and the periodic jitter histogram; Generate a bathtub curve corresponding to the target digital signal according to the bit error rate curve corresponding to the target digital signal by using a preset mathematical model; Based on the bathtub curve corresponding to the target digital signal, a target analysis result is obtained, wherein the target analysis result is used to characterize the jitter characteristics of the target digital signal.

2. The method according to claim 1, characterized in that Before removing the data-related jitter in the time interval error data corresponding to the target digital signal to obtain the remaining jitter time interval error data, the method further includes: Performing clock recovery processing on the target digital signal to obtain a reference clock corresponding to the target digital signal; Based on the reference clock, calculate and obtain time interval error data corresponding to the target digital signal; Performing autocorrelation processing on the bit stream corresponding to the target digital signal to obtain the pattern length of the repetitive sequence in the bit stream corresponding to the target digital signal; Based on the pattern length of the repetitive sequence and the time interval error data corresponding to the target digital signal, the data-dependent jitter corresponding to the target digital signal is obtained.

3. The method according to claim 2, characterized in that The obtaining of data-dependent jitter corresponding to the target digital signal based on the pattern length of the repetitive sequence and the time interval error data corresponding to the target digital signal comprises: Based on the pattern length of the repetitive sequence, the time interval error data corresponding to the target digital signal is divided into at least one time interval error data group, wherein the bit stream corresponding to the target digital signal includes at least one repetitive sequence, and the repetitive sequence corresponds to the time interval error data group one by one; Calculate and obtain the average value corresponding to each time interval error data group; Based on the average values ​​corresponding to the respective time interval error data groups, the standard deviation of the average values ​​corresponding to the respective time interval error data groups is calculated, wherein the average values ​​corresponding to the respective time interval error data groups correspond to the standard deviation of the average values ​​corresponding to the respective time interval error data groups in a one-to-one manner, and the standard deviation of the average values ​​corresponding to the respective time interval error data groups is used to characterize a repetitive sequence; The standard deviations of the mean values ​​corresponding to the respective time interval error data groups are combined to obtain the data-dependent jitter corresponding to the target digital signal.

4. The method according to claim 1, characterized in that The processing of the residual jitter time interval error data to obtain a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal includes: Performing fast Fourier transform processing on the residual jitter time interval error data to obtain a frequency spectrum diagram corresponding to the residual jitter time interval error data; Based on a preset threshold, extracting a random jitter frequency component and a periodic jitter frequency component from a frequency spectrum corresponding to the residual jitter time interval error data; A random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal are generated based on the random jitter frequency component and the periodic jitter frequency component through a preset data statistical tool library.

5. The method according to claim 1, characterized in that The step of obtaining a bit error rate curve corresponding to the target digital signal based on the data-dependent jitter corresponding to the target digital signal, the random jitter histogram, and the periodic jitter histogram comprises: Based on the data-dependent jitter corresponding to the target digital signal, generating a data-dependent jitter histogram corresponding to the data-dependent jitter; Performing convolution calculation processing on the data-dependent jitter histogram, the random jitter histogram, and the periodic jitter histogram to obtain an overall jitter histogram corresponding to the target digital signal; Based on the overall jitter histogram, a total jitter probability density function corresponding to the target digital signal is calculated, wherein the overall jitter probability density function is used to characterize the distribution of the signal jitter of the target digital signal around the timing center of the target digital signal; Performing an integral calculation process on the overall jitter probability density function to obtain an integral calculation result corresponding to the overall jitter probability density function; Based on the integral calculation result, a bit error rate curve corresponding to the target digital signal is generated.

6. The method according to claim 1, characterized in that The preset mathematical model includes a dual Dirac model; The method of generating a bathtub curve corresponding to the target digital signal by using a preset mathematical model according to a bit error rate curve corresponding to the target digital signal includes: The bit error rate curve corresponding to the target digital signal is extrapolated by the dual Dirac model to obtain a bathtub curve corresponding to the target digital signal.

7. The method according to claim 1, characterized in that The target analysis result includes target total jitter data, wherein the target total jitter data includes the signal total jitter values ​​corresponding to the target digital signal at different bit error rates; The step of obtaining a target analysis result based on a bathtub curve corresponding to the target digital signal includes: The target total jitter data is calculated based on the bathtub curve by using a spectrum method or a tail fitting method.

8. A digital signal analysis device, characterized in that: The device comprises: The first unit is used to remove data-related jitter corresponding to the target digital signal from the time interval error data corresponding to the target digital signal to obtain residual jitter time interval error data, wherein the data-related jitter is used to characterize the jitter caused by the change of the input data pattern during the transmission of the target digital signal, and the residual jitter time interval error data is used to characterize the jitter time interval error related to the random jitter of the target digital signal and the periodic jitter of the target digital signal; The second unit is used to process the residual jitter time interval error data to obtain a random jitter histogram corresponding to the target digital signal and a periodic jitter histogram corresponding to the target digital signal; A third unit is used to obtain a bit error rate curve corresponding to the target digital signal based on the data-dependent jitter corresponding to the target digital signal, the random jitter histogram and the periodic jitter histogram; A fourth unit is used to generate a bathtub curve corresponding to the target digital signal according to the bit error rate curve corresponding to the target digital signal by using a preset mathematical model; The fifth unit is used to obtain a target analysis result based on the bathtub curve corresponding to the target digital signal, wherein the target analysis result is used to characterize the jitter characteristics of the target digital signal.

9. A terminal, characterized in that: The method comprises a processor and a memory, wherein the memory stores a plurality of instructions; the processor loads instructions from the memory to execute the steps in the method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to execute the steps in the method according to any one of claims 1 to 7.

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