Statistical eye diagram generation method and apparatus, and storage medium

Abstract

The application discloses a statistical eye diagram generation method and device and a storage medium. The method comprises the following steps: inputting a step signal at a transmitting end of a channel, determining a step response function based on the step signal; introducing a jitter signal at the transmitting end, determining a jitter probability model based on the jitter signal; determining a jitter value set and a jitter probability set based on the jitter probability model; determining a state transition probability matrix between a first time and a second time in the input step signal; establishing an equivalent response distribution kernel for a target sampling time based on the state transition probability matrix and the step response function; performing convolution operation on the voltage probability distribution of the last sampling time of the target sampling time and the equivalent response distribution kernel to determine the voltage probability distribution of the target sampling time, and determining the voltage probability distribution of multiple sampling times; and generating a statistical eye diagram based on the voltage probability distribution of the multiple sampling times. The application has the technical effect of assisting in improving the reliability of simulation evaluation.

Description

TECHNICAL FIELD

[0001] Embodiments of the present disclosure relate to the technical field of electronic design automation simulation, and particularly, to a statistical eye diagram generation method and device, and a storage medium. BACKGROUND

[0002] With the data communication rate of integrated circuits entering the gigabit per second (Gb / s) level, the signal integrity of on-chip and off-chip links becomes the key to the success or failure of integrated circuit design. Many interconnection and device coupling effects that can be ignored at low-speed transmission must be included in modeling and evaluation under high-speed transmission conditions. In addition, system-level behaviors such as amplification and cancellation of jitter have also evolved into typical problems affecting signal integrity. The current electronic design automation simulation process does not adequately consider the jitter amplification caused by the channel, and often simply equates the jitter at the transmitting end to the jitter at the receiving end, which can easily lead to serious misjudgments. Because the jitter at the transmitting end is "colored" and amplified by the step response under the action of the channel, neglecting this effect will make the signal integrity evaluation overly optimistic. Therefore, the problem of improving the reliability of simulation evaluation is worth attention. SUMMARY

[0003] Therefore, embodiments of the present disclosure provide a statistical eye diagram generation method and device, and a storage medium, to assist in improving the reliability of simulation evaluation. In a first aspect, a statistical eye diagram generation method is provided, including: inputting a step signal at the transmitting end of a channel, and determining a step response function based on the step signal; introducing a jitter signal at the transmitting end, and determining a jitter probability model based on the jitter signal, the jitter probability model including: a continuous probability density function or a discrete probability distribution; determining a jitter value set and a jitter probability set based on the jitter probability model, wherein the jitter values in the jitter value set correspond to the jitter probabilities in the jitter probability set; determining a state transition probability matrix between a first time and a second time in the input step signal based on the jitter value set and the jitter probability set, wherein the first time and the second time are separated by one bit period; establishing an equivalent response distribution kernel for a target sampling time based on the state transition probability matrix and the step response function; performing convolution operation on the voltage probability distribution of the last sampling time of the target sampling time and the equivalent response distribution kernel to determine the voltage probability distribution of the target sampling time, and repeatedly performing convolution operation at continuous sampling times to determine the voltage probability distributions of multiple sampling times; and generating a statistical eye diagram based on the voltage probability distributions of the multiple sampling times.

[0004] Optionally, when the jitter probability model is a continuous probability density function, the jitter signal is divided into a plurality of first jitter value subsets based on a preset jitter value segmentation; a second jitter value of a jitter value subset is taken as the median of a plurality of first jitter values in the first jitter value subset; and a second jitter probability of the second jitter value is determined based on a first jitter probability of the plurality of first jitter values.

[0005] Optionally, the matrix elements of the state transition probability matrix comprise joint probabilities of second jitter probabilities between a plurality of second jitter values.

[0006] Optionally, the step signal is a single-edge step signal, and the step response function is a single-edge step response function.

[0007] Optionally, the statistical eye diagram is generated based on the voltage probability distribution of the plurality of sampling instants, comprising: folding the plurality of sampling instants to the same unit interval on a phase axis according to a bit period; superimposing voltage probability distributions of the same or adjacent phases to obtain a first voltage-phase two-dimensional probability distribution, wherein the phase is a relative position of the sampling instant with respect to the bit period; performing normalization processing on the first voltage-phase two-dimensional probability distribution to determine a second voltage-phase two-dimensional probability distribution; and mapping the second voltage-phase two-dimensional probability distribution with a preset color to generate the statistical eye diagram.

[0008] Optionally, the superimposing voltage probability distributions of the same or adjacent phases comprises: summing or averaging voltage probability distributions from different bit periods within the same phase unit; and smoothing voltage probability distributions of adjacent phase units according to a preset weight.

[0009] Optionally, the equivalent response distribution kernel is established for the target sampling instant, comprising: time-shifting the step response function based on the set of jitter values to form a plurality of shifted responses; and weighting and superimposing the shifted responses according to the matrix elements of the state transition probability matrix to obtain the equivalent response distribution kernel for the target sampling instant, wherein the equivalent response distribution kernel is used to represent the influence of the channel on the jitter of the transmitting end, and the weighting and superimposing are used to represent the amplification effect or the colorization effect of the channel on the jitter of the transmitting end.

[0010] Optionally, the first time corresponds to a target sampling phase in a current bit period, and the second time corresponds to a corresponding sampling phase separated from the target sampling phase by one bit period.

[0011] In a second aspect, a statistical eye diagram generation apparatus is provided, comprising: a step signal input unit configured to input a step signal at a transmitting end of a channel, and determine a step response function based on the step signal; a jitter introduction unit configured to introduce a jitter signal at the transmitting end, and determine a jitter probability model based on the jitter signal, the jitter probability model comprising: a continuous probability density function or a discrete probability distribution; a determination unit configured to determine a jitter value set and a jitter probability set based on the jitter probability model, wherein a jitter value in the jitter value set corresponds to a jitter probability in the jitter probability set, and determine a state transition probability matrix between a first time and a second time in the input step signal based on the jitter value set and the jitter probability set, wherein the first time and the second time are separated by one bit period; a convolution unit configured to establish an equivalent response distribution kernel for a target sampling time based on the state transition probability matrix and the step response function, and perform convolution operation on a voltage probability distribution of a previous sampling time of the target sampling time and the equivalent response distribution kernel to determine the voltage probability distribution of the target sampling time, and repeatedly perform the convolution operation at continuous sampling times to determine voltage probability distributions of a plurality of sampling times; and a generation unit configured to generate a statistical eye diagram based on the voltage probability distributions of the plurality of sampling times.

[0012] In a third aspect, a computer readable storage medium is provided, comprising: a memory having instructions stored thereon; and a processor configured to implement the statistical eye diagram generation method provided in the first aspect when reading the memory. BRIEF DESCRIPTION OF DRAWINGS

[0013] The accompanying drawings for use in the description of embodiments of the present disclosure are briefly described as follows:

[0014] Figure 1 A flowchart of a statistical eye diagram generation method provided in some embodiments of the present application is shown;

[0015] Figure 2 A structural diagram of a statistical eye diagram generation apparatus provided in some embodiments of the present application is shown. DETAILED DESCRIPTION

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following will explain the embodiments of the present disclosure with reference to the accompanying drawings. The accompanying drawings in the following description are only some embodiments of the present disclosure, and for those skilled in the art, other drawings can be obtained from these drawings without creative labor, and other embodiments can be obtained without departing from the concept of the present disclosure, and the adjustments and improvements made are within the protection scope of the present disclosure.

[0017] For the purpose of simplicity and brevity of the drawings, only the parts related to the embodiments are shown schematically and these do not necessarily represent the actual structure of the product. In addition, in order to make the drawings simple and easy to understand, in some drawings, only some of the parts with the same structure or function are schematically shown, and there can be more or less parts with the same structure or function in practice.

[0018] In the present disclosure, unless otherwise explicitly specified and limited, ordinal words such as "first", "second", etc. are only used to distinguish the description of the associated objects, and cannot be understood as indicating or implying the relative importance or order between the associated objects; in addition, it also does not represent the number of the associated objects. "Multiple" includes two or more, and other quantifiers are similar. " / " is used to describe the relationship between the associated objects, which represents the "or" relationship between the associated objects. "And / or" is used to describe the relationship between the associated objects, which includes any combination relationship between the associated objects, for example, "a and / or b" includes: "a alone", "b alone", or "a and b". "One or more" or "at least one" of a plurality of objects means any object or any combination of a plurality of objects, for example, "one or more of a1, a2, a3" or "at least one of a1, a2, a3" includes: "a1 alone", "a2 alone", "a3 alone", "a1 and a2", "a1 and a3", "a2 and a3", or "a1, a2 and a3".

[0019] High-speed interconnect designs are moving from low Gb / s to multi-Gb / s and beyond. In this context, physical effects such as dispersion, loss, crosstalk of the wire interconnect, and electromagnetic coupling between devices, directly reshape the edge shape and the inter-symbol interference. Details that were once negligible in low-speed scenarios must now be addressed in modeling and verification. At the same time, system-level behaviors such as amplification, cancellation, and redistribution of different source jitters in the channel and receive chain, significantly change the error code risk and margin evaluation, and have become an indispensable part of signal integrity analysis. However, the consideration of the transmission end jitter amplification effect caused by the channel in the existing electronic design automation simulation process is still insufficient, and there are cases of directly treating the transmission end jitter as the receive end jitter, or adding a noise model decoupled from the channel on the output side. This approach is prone to systematic bias, such as the time disturbance of the transmission end being colored by the time response of the channel when passing through the channel and being converted into equivalent noise in the amplitude domain. The coupling of amplitude and phase causes the estimation of eye opening and error code probability to be overestimated, resulting in overly optimistic integrated circuit link design conclusions. Therefore, the amplification effect of the channel on the transmission end disturbance is included in the simulation calculation, so that the statistical eye diagram obtained by simulation can truly reflect the risk brought by the channel amplification effect, thereby providing more reliable basis for electronic automation design simulation and verification of high-speed transmission applications.

[0020] The following will be described with reference to the drawings:

[0021] Figure 1 A flowchart of a statistical eye diagram generation method provided in some embodiments of the present application is shown. The generation method comprises at least the following steps:

[0022] S110: inputting a step signal at the transmitting end of a channel, and determining a step response function based on the step signal;

[0023] S120: introducing a jitter signal at the transmitting end, and determining a jitter probability model based on the jitter signal, the jitter probability model comprising a continuous probability density function or a discrete probability distribution;

[0024] S130: determining a jitter value set and a jitter probability set based on the jitter probability model, wherein the jitter values in the jitter value set correspond to the jitter probabilities in the jitter probability set;

[0025] S140: determining a state transition probability matrix between a first time and a second time in the input step signal based on the jitter value set and the jitter probability set, wherein the first time and the second time are separated by one bit period;

[0026] S150: establishing an equivalent response distribution kernel for a target sampling time based on the state transition probability matrix and the step response function;

[0027] S160: performing convolution operation on the voltage probability distribution of a previous sampling time of the target sampling time and the equivalent response distribution kernel to determine the voltage probability distribution of the target sampling time, and repeatedly performing convolution operation at continuous sampling times to determine the voltage probability distributions of multiple sampling times;

[0028] S170: generating a statistical eye diagram based on the voltage probability distributions of the multiple sampling times.

[0029] In the above statistical eye diagram generation method, the channel can be a transmission path of a signal, the signal passes through the channel from the transmitting end to the receiving end, and the channel can be a transmission line or a group of circuit paths, which is not limited herein. A step signal is input at the transmitting end of the channel to obtain the edge template of the channel, the step signal refers to a driving form in which the level is suddenly changed from a low steady state to a high steady state and remains unchanged for a long enough time, for example, a long step signal whose duration covers the effective memory length of the channel can be used, the duration of the step signal can be set according to the channel loss, so that the time domain response observed at the receiving end completely contains the rising and falling edge shapes, and the step response function can be determined according to the response of the step signal at the receiving end. Then, a jitter signal is introduced at the transmitting end and a jitter probability model is established, the jitter probability model can be expressed as a continuous probability density function or a discrete probability distribution, and the jitter is manifested as the uncertainty of the timing at the transmitting end, such as the early or late fluctuation of the edge arrival time. When the jitter probability model is expressed as a continuous probability density function, the jitter probability model can be discretized into a plurality of jitter values and a plurality of jitter probabilities to form a one-to-one corresponding jitter value set and jitter probability set; when the jitter probability model is already in a discrete form, the discrete jitter values and the corresponding jitter probabilities can be directly taken as set elements. At the first time and the second time, a state transition probability matrix of the jitter state of the phase at the two times is constructed, which can be used to describe the joint occurrence probability of the jitter value of the current sampling phase and the jitter value of the same phase in the previous bit period. Further, at any target sampling phase, an equivalent response distribution kernel can be established based on the state transition probability matrix and the step response function. At the target sampling phase, the step response function is time-shifted according to the jitter values of the current and previous bit periods corresponding to the phase, and the state transition probability matrix is used to probabilistically weight different time-shifted cases to obtain the equivalent response distribution kernel corresponding to the phase, thereby reflecting the voltage change trend and its weight that can occur at the current phase under the combined action of the edge shape and the jitter. The edge template is time-shifted according to the jitter values of the current and previous bit periods corresponding to the phase, and each time-shifted case is weighted and superimposed according to the state transition probability, thereby determining the result that can reflect the amplification / colorization effect of the channel on the jitter of the transmitting end. Subsequently, the voltage probability distribution can be calculated in a recursive manner, the voltage probability distribution obtained at the previous sampling phase is convolved with the equivalent response distribution kernel to obtain the voltage probability distribution at the target sampling phase, and the recursive process is repeated point by point along the multiple sampling phases of one bit period until the distribution result of all phases is obtained. Finally, the voltage probability distributions of the sampling phases in one bit period are folded to a unified phase axis and superimposed and visually mapped to generate a statistical eye diagram. In some embodiments, the original probability distribution data of each phase can also be output simultaneously to provide a basis for engineering decisions such as bit error rate estimation, equalization parameter, sampling phase, decision threshold setting, etc.

[0030] In some embodiments of the present application, the step signal is a single-edge step signal, and the step response function is a single-edge step response function.

[0031] Taking an example of inputting a single-edge step signal with a rising edge at the transmitting end of the channel, the length of the single-edge step signal can be determined according to the quality of the channel, and the response signal waveform received at the receiving end of the channel is the single-edge step response function of the channel. For example, a single-edge step signal with a length of 60 bits can be input, and the code type is set to a square wave signal of 011111111111… (59 ones), and the period is T. The obtained single-edge step response function is denoted as f(x).

[0032] In some embodiments of the present application, when the jitter probability model is a continuous probability density function, the jitter signal is divided into a plurality of first jitter value subsets based on preset jitter value segmentation; the median of the plurality of first jitter values in the first jitter value subset is taken as a second jitter value of the jitter value subset; and the second jitter probability of the second jitter value is determined based on the first jitter probability of the plurality of first jitter values.

[0033] The jitter introduced at the transmitting end in the present application can not be limited to a specific jitter type, and the jitter probability model can be a continuous probability density function or a discrete probability distribution. Taking a random jitter RJ (Random jitter) that is the most common and unavoidable in a channel as an example, the continuous probability density function of the jitter can conform to a standard normal distribution, as shown in the following formula 1:

[0034] Formula 1

[0035] If the jitter probability model is an analytically continuous probability density function, the continuous probability density function can be discretized, and the segmentation based on preset jitter values can be performed, for example, 1 million points can be generated using the normal distribution of the above formula 1, and the jitter values of the 1 million points can be divided into 200 segments (i.e., 200 first jitter value subsets). The median of the plurality of first jitter values in each segment is taken as the jitter value (i.e., the second jitter value) of the segment, and the sum of the first jitter probability values corresponding to all first jitter values in each segment is taken as the jitter probability value (i.e., the second jitter probability) corresponding to the first jitter value subset. The probability distribution of the jitter is calculated, and the jitter values of the 200 points are denoted as second jitter values , and the corresponding second jitter probability is denoted as . Wherein, {0, 1, …, 200}.

[0036] In some embodiments of the present application, the matrix elements of the state transition probability matrix include the joint probability of the second jitter probabilities between the plurality of second jitter values.

[0037] Without adding jitter at the transmitting end, the value of the step response function at a certain time t has only one possibility f(t), and the corresponding probability value is 1. However, after adding jitter, the value of the step response function at a certain time t has multiple possibilities, and the probability values of the values correspond to the jitter probabilities of the jitter values. Taking the jitter probability model described above as an example, the value of the step response function at a certain time t has 200 possible values, that is, , and the corresponding probability value is . For two time points t and t-T separated by a period T, a state transition probability matrix AP of the two points can be established. The number of rows and columns of the matrix is the number of the second jitter values. In the state transition probability matrix, the value of each element is the multiplication of the corresponding second jitter probability, so that becomes The probability. Since the jitter signal is independent and identically distributed at each time point, the state transition probability matrix that can be established is a 200x200 matrix, where the matrix elements include the joint probability of the second jitter probabilities between multiple second jitter values, that is, the matrix element . Corresponding is the probability that the response value at time t is and the response value at time t-T is .

[0038] In some embodiments of the present application, the statistical eye diagram is generated based on the voltage probability distribution of multiple sampling time points, including: folding the multiple sampling time points to the same unit interval phase axis according to the bit period; superimposing and calculating the voltage probability distributions of the same or adjacent phases to obtain a first voltage-phase two-dimensional probability distribution, wherein the phase is the relative position of the sampling time point relative to the bit period; performing normalization processing on the first voltage-phase two-dimensional probability distribution to determine a second voltage-phase two-dimensional probability distribution; mapping the second voltage-phase two-dimensional probability distribution with a preset color to generate a statistical eye diagram.

[0039] In some embodiments of the present application, the superimposition and calculation of the voltage probability distributions of the same or adjacent phases includes: summing or averaging the voltage probability distributions from different bit periods within the same phase unit; and smoothing the voltage probability distributions of adjacent phase units according to a preset weight.

[0040] In some embodiments of the present application, an equivalent response distribution kernel is established for the target sampling time point, including:

[0041] Time-shifting the step response function based on the jitter value set to form multiple shifted responses;

[0042] The translation responses are weighted and superimposed according to the matrix elements of the state transition probability matrix to obtain an equivalent response distribution kernel for the target sampling moment, wherein the equivalent response distribution kernel is used to represent the influence of the channel on the jitter of the transmitting end, and the weighted superimposition is used to represent the amplification effect or the colorization effect of the channel on the jitter of the transmitting end.

[0043] In the above embodiment, the equivalent response distribution kernel can be established at any target sampling moment, and the purpose is to convert the joint values of the edge template of the channel and the jitter of the transmitting end in the adjacent two bit periods into the statistical response at the moment. Specifically, first, a single-edge step response is taken as the edge template, and for the bit period in which the target sampling moment is located and the corresponding sampling phase separated by one bit period, the corresponding current jitter value and the last period jitter value are taken from the jitter value set, respectively, and the edge template is translated on the time axis according to the two values. Since jitter is a statistical quantity, different jitter value combinations correspond to different jitter probabilities, and the state transition probability matrix determined in step S140 is used as the weight in this embodiment. Based on the single-edge step response function, the jitter values in the jitter value set can be used to time-shift the channel response to form a translation response, and the state transition matrix is used to weight and combine multiple translation responses to obtain an equivalent response distribution kernel for the sampling moment. The equivalent response distribution kernel reflects the influence of the channel on the jitter of the transmitting end, and the contributions of different translation combinations are amplified or inhibited through the aforementioned weight, thereby reflecting the amplification (colorization) effect of the channel on the jitter. For example, the formula for calculating the voltage probability distribution at the target sampling moment k is as follows:

[0044] Formula 2

[0045] Taking the single-edge step signal as an example in this application, the voltage b j ∈ (0, 1), P b-1b0 is the probability of the code type changing from b -1 to b0, is the code type b -m-1 b -m b -m+1 ……b -1 , the corresponding translation response is is the probability value of the code type b -m-1 b -m b -m+1 ……b -1 at the last sampling moment k-1 of the target sampling moment k, and ⊙ is the convolution symbol. Through formula 2, the probability values of all code types at all times can be calculated from time 0 of the single-edge step signal, thereby determining the voltage probability distribution of the eye diagram. In this application, since the single-edge response is used, the above formula 2 is simplified to formula 3:

[0046] Formula 3

[0047] i.e. P b-1b0 =1 / 2, SBR is a single-bit response, the shift response S1 of the code type 1 is δ(v-SBR(t-KT)), the shift response S0 of the code type 0 is δ(v), wherein SBR(t-KT)=f(t-KT)-f(t-T-KT). Since the jitter is introduced at the transmitting end, the value of SBR(t-KT) changes from only one kind to multiple kinds, i.e. SBR(t-KT)=f(t-KT-Pi)-f(t-T-KT-Pj), thus the voltage probability distribution at the target sampling time can be determined by Formula 4:

[0048] Formula 4

[0049] In some embodiments of the present application, the first time corresponds to a target sampling phase in a current bit period, and the second time corresponds to a corresponding sampling phase separated by one bit period from the target sampling phase.

[0050] Figure 2 A structure diagram of a statistical eye diagram generation apparatus provided in some embodiments of the present application is shown. The generation apparatus 200 comprises: a step signal input unit 210 configured to input a step signal at a transmitting end of a channel, and determine a step response function based on the step signal; a jitter introduction unit 220 configured to introduce a jitter signal at the transmitting end, and determine a jitter probability model based on the jitter signal, the jitter probability model comprising: a continuous probability density function or a discrete probability distribution; a determination unit 230 configured to determine a jitter value set and a jitter probability set based on the jitter probability model, wherein the jitter values in the jitter value set correspond to the jitter probabilities in the jitter probability set, and determine a state transition probability matrix between a first time and a second time in the input step signal based on the jitter value set and the jitter probability set, wherein the first time and the second time are separated by one bit period; a convolution unit 240 configured to establish an equivalent response distribution kernel at a target sampling time based on the state transition probability matrix and the step response function, and perform convolution operation on the voltage probability distribution at a previous sampling time of the target sampling time and the equivalent response distribution kernel to determine the voltage probability distribution at the target sampling time, and repeatedly perform the convolution operation at continuous sampling times to determine the voltage probability distributions at multiple sampling times; and a generation unit 250 configured to generate a statistical eye diagram based on the voltage probability distributions at the multiple sampling times.

[0051] Based on the same technical concept, the application further provides a computer readable storage medium, comprising: a memory having instructions stored thereon; and a processor configured to implement the statistical eye diagram generation method provided in the above embodiments when reading the memory.

[0052] In the above embodiments, the description of each embodiment has its own focus, and the parts not described or recorded in detail in a certain embodiment can be referred to the related description of other embodiments. In addition, the above embodiments can be freely combined as needed.

Claims

1. A method for generating statistical eye diagrams, characterized in that, include: A step signal is input at the transmitting end of the channel, and a step response function is determined based on the step signal; A jitter signal is introduced at the transmitting end, and a jitter probability model is determined based on the jitter signal. The jitter probability model includes a continuous probability density function or a discrete probability distribution. Based on the jitter probability model, a jitter value set and a jitter probability set are determined, wherein the jitter values ​​in the jitter value set correspond to the jitter probabilities in the jitter probability set; At the first and second moments of the input step signal, based on the jitter value set and the jitter probability set, a state transition probability matrix between the first and second moments is determined, wherein the first and second moments are separated by one bit period. Based on the state transition probability matrix and the step response function, an equivalent response distribution kernel is established for the target sampling time, including: time-shifting the step response function based on the jitter value set to form multiple shifted responses; weighting and superimposing the shifted responses according to the matrix elements of the state transition probability matrix to obtain the equivalent response distribution kernel for the target sampling time, wherein the equivalent response distribution kernel is used to characterize the influence of the channel on the transmitter jitter, and the weighted superposition is used to characterize the amplification effect of the channel on the transmitter jitter; The voltage probability distribution at the previous sampling time of the target sampling time is convolved with the equivalent response distribution kernel to determine the voltage probability distribution at the target sampling time. The convolution operation is repeated at consecutive sampling times to determine the voltage probability distribution at multiple sampling times. A statistical eye diagram is generated based on the voltage probability distribution at multiple sampling times.

2. The method for generating statistical eye diagrams according to claim 1, characterized in that, When the jitter probability model is a continuous probability density function, the jitter signal is divided into multiple first jitter value subsets based on a preset jitter value segmentation. The median of multiple first jitter values ​​in the first jitter value subset is taken as the second jitter value of the jitter value subset; A second jitter probability of the second jitter value is determined based on a first jitter probability of multiple first jitter values.

3. The method for generating statistical eye diagrams according to claim 2, characterized in that, The matrix elements of the state transition probability matrix include the joint probability of the second jitter probabilities among multiple second jitter values.

4. The method for generating statistical eye diagrams according to claim 3, characterized in that, The step signal is a single-edge step signal, and the step response function is a single-edge step response function.

5. The method for generating a statistical eye diagram according to claim 4, characterized in that, The generation of the statistical eye diagram based on the voltage probability distribution at multiple sampling times includes: The multiple sampling times are folded onto the same unit interval phase axis according to the bit period; The voltage probability distributions with the same or adjacent phases are superimposed to obtain a first voltage-phase two-dimensional probability distribution, wherein the phase is the relative position of the sampling time with respect to the bit period; The first voltage-phase two-dimensional probability distribution is normalized to determine the second voltage-phase two-dimensional probability distribution. The statistical eye diagram is generated by mapping the second voltage-phase two-dimensional probability distribution to a preset color.

6. The method for generating a statistical eye diagram according to claim 5, characterized in that, The superposition calculation of the voltage probability distributions of the same or adjacent phases includes: Sum or average the voltage probability distributions from different bit periods within the same phase unit; The voltage probability distribution of adjacent phase units is smoothed according to a preset weight.

7. The method for generating statistical eye diagrams according to claim 1, characterized in that, The first moment corresponds to the target sampling phase within the current bit period; The second moment corresponds to the sampling phase that is one bit period apart from the target sampling phase.

8. A device for generating statistical eye diagrams, characterized in that, include: A step signal input unit is used to input a step signal at the transmitting end of the channel and determine a step response function based on the step signal; A jitter introduction unit introduces a jitter signal at the transmitting end and determines a jitter probability model based on the jitter signal. The jitter probability model includes a continuous probability density function or a discrete probability distribution. The determining unit is configured to determine a jitter value set and a jitter probability set based on the jitter probability model, wherein the jitter values ​​in the jitter value set correspond to the jitter probabilities in the jitter probability set, and to determine a state transition probability matrix between the first time and the second time based on the jitter value set and the jitter probability set at a first time and a second time in the input step signal, wherein the first time and the second time are separated by one bit period; A convolutional unit is used to establish an equivalent response distribution kernel for a target sampling time based on the state transition probability matrix and the step response function. This includes: time-shifting the step response function based on the jitter value set to form multiple shifted responses; weighting and superimposing the shifted responses according to the matrix elements of the state transition probability matrix to obtain the equivalent response distribution kernel for the target sampling time, wherein the equivalent response distribution kernel characterizes the influence of the channel on the transmitter jitter, and the weighted superposition characterizes the amplification effect of the channel on the transmitter jitter; and performing a convolution operation between the voltage probability distribution of the previous sampling time and the equivalent response distribution kernel to determine the voltage probability distribution of the target sampling time, and repeating the convolution operation at consecutive sampling times to determine the voltage probability distribution of multiple sampling times. The generation unit is used to generate a statistical eye diagram based on the voltage probability distribution at multiple sampling times.

9. A computer-readable storage medium, characterized in that, include: A memory that stores instructions; The processor is configured to, when reading the memory, implement the method for generating a statistical eye diagram as described in any one of claims 1 to 7.

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