Interference jamming separation method based on derivative sparsity and cyclostationary characteristics

Abstract

The application discloses an inter-symbol interference jitter separation method based on derivative sparsity and cyclostationary characteristics, belongs to the jitter analysis technical field in high-speed serial communication, and directly obtains remaining jitter information without inter-symbol interference from sampling data by constructing a derivative sparsity function and utilizing the cyclostationary characteristics of the function, so that the purpose of separating inter-symbol interference jitter from total jitter is achieved; compared with a traditional method, the method of the application is not limited by data code types, can separate ISI jitter from data of any code type, is not limited by the amount of collected data, does not need to recover a clock signal from data, does not need to determine a threshold level from data, and does not need to accurately solve the cross time of measured data or the recovered clock and the threshold level by an interpolation module; and the method of the application is simple in overall implementation and low in calculation complexity.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of jitter analysis in high-speed serial communication, and particularly relates to an inter-symbol interference jitter separation method based on derivative sparsity and cyclostationarity. BACKGROUND

[0002] In a high-speed serial communication system, jitter analysis is a key link for evaluating link performance and guiding system design, and accurate jitter decomposition is the basis for bit error rate (BER) prediction and extrapolation. With the continuous improvement of communication rate, the inter-symbol interference (ISI) caused by limited transmission channel bandwidth is becoming more and more serious, and the ISI jitter generated thereby significantly compresses the timing margin at the receiving end. However, due to the ambiguous boundary between ISI jitter and random jitter (RJ), the existing analysis method often incorrectly divides the ISI jitter into RJ jitter, thereby leading to overestimation of the BER extrapolation result. This overestimation will cause excessive margin design at the system level, resulting in additional hardware cost, power consumption overhead and system complexity, and affecting the optimal implementation of link performance.

[0003] To meet the compliance test requirements of the new generation of high-speed interface standards, more stringent stress tests and longer data patterns, such as PRBS31, need to be introduced to stimulate the worst-case response of the channel. However, for such long code pattern signals, the main bottleneck of jitter decomposition is the characterization and separation of ISI jitter. Therefore, how to implement an efficient, accurate and non-specific code pattern-dependent ISI jitter separation method is still a key research problem in current high-speed link jitter analysis.

[0004] The repetitive code pattern measurement algorithm is the most commonly used ISI jitter separation algorithm at present, and is mainly suitable for measuring data patterns with a length of PRBS15 and below. This method analyzes the time distribution of each transition in the data pattern, usually 10 times or even more, and averages the same transition position, thereby effectively filtering out the effects of random jitter and periodic jitter, extracting stable ISI jitter, and subtracting ISI jitter from the total jitter for subsequent jitter decomposition.

[0005] The existing ISI jitter separation steps are as follows:

[0006] Confirming threshold level reference, according to the measured data voltage value, the threshold level is obtained by histogram statistics method; Clock recovery, the clock information embedded in the data is extracted from the measured data; The code type search is carried out on the measured data, and the code type repetition period of the measured data is determined; In multiple repetitions, usually 10 times or more, each transition in the measured data mode is checked, and the average time of each transition is calculated to measure the ISI jitter, and the average value of the histogram corresponding to each transition is measured according to the recovered clock; The total TIE jitter is obtained by interpolation operation; The ISI jitter is subtracted from the total TIE jitter, and subsequent jitter decomposition is carried out to obtain more accurate random jitter, and the more accurate bit error rate value is extrapolated.

[0007] Defects of prior art:

[0008] Firstly, whether all other forms of jitter are averaged out; The exact length of the data mode is unknown, and the repetition period obtained by the above search method will consume a large amount of computing resources, and even an incorrect repetition period may be obtained;

[0009] Secondly, the existing method is only suitable for short data code type mode, such as PRBS7, and for long data code type, such as PRBS21 and above, due to the need for more than 10 times of repetition period, a large number of waveform sampling points must be collected, which is far higher than the storage depth of the actual oscilloscope. SUMMARY

[0010] The purpose of the present application is to solve the above problems, based on the derivative sparsity and the cyclic stationary characteristic of the code interference jitter separation method, by constructing the derivative sparsity function, the remaining jitter information without code interference can be directly obtained from the sampling data by using the cyclic stationary characteristic of the function, so as to separate the code interference jitter from the total jitter.

[0011] The technical scheme adopted by the present application is as follows:

[0012] The code interference jitter separation method based on derivative sparsity and cyclic stationary characteristic, the method comprises:

[0013] Based on the transmission model of high-speed serial link with jitter, the extreme point data of each code element is determined by derivative;

[0014] The derivative sparse function is constructed by the extreme point data, and the jitter information without code interference is extracted by using the derivative sparse function.

[0015] Further, the transmission model of high-speed serial link with jitter is as follows:

[0016] (1)

[0017] In the formula, is a transmission symbol, is a symbol time width, is a jitter of the th symbol, is a shaped square wave with a width of , and is a channel impulse response;

[0018] In order to quantify the influence of the time offset of the derivative extreme value caused by the inter-symbol interference on formula (1), the derivative of formula (1) is taken, and the extreme point data of each symbol is determined.

[0019] Further, the time offset of the derivative extreme value caused by the inter-symbol interference is specifically as follows:

[0020] In a high-speed serial link, for the sake of simplicity and clarity, it is usually assumed that is zero, and both start from zero, and the derivative is obtained as follows:

[0021] (2)

[0022] In the formula, it is defined that indicates the influence of the inter-symbol interference on the amplitude of the derivative, and the time offset of the derivative extreme value caused by the inter-symbol interference is , then at the time of th symbol jump, , the maximum value is obtained, and the second derivative is 0, as follows:

[0023] (3)

[0024] The Taylor expansion of formula (3) is performed, and the time offset of the derivative extreme value caused by the inter-symbol interference is as follows:

[0025] (4).

[0026] Further, the determination of the extreme point data is specifically as follows:

[0027] By analyzing the time offset, specifically, the channel impulse response is a low-pass filter, the tail of which decreases exponentially, and the derivative also decreases, and the amplitude quickly approaches 0 at a position far away from the main symbol, is a relatively large constant, reflecting the curvature of the channel impulse response at the maximum value, so is approximately 0, and thus the position of the derivative extreme point is determined by the jitter ​​Decision, i.e. .

[0028] Further, in order to reduce data operation amount, a time domain sparse function is constructed according to the determined extreme point data, and the function is specifically as follows:

[0029] (5).

[0030] In summary, due to the adoption of the above technical solutions, the present application has the following beneficial effects:

[0031] The method of the present application is based on the construction of a derivative sparse function, and the remaining jitter information without inter-symbol interference can be directly obtained from the sampling data by using the cyclostationary characteristics of the function, so as to separate the inter-symbol interference jitter from the total jitter, solve the problem that the traditional inter-symbol interference jitter separation method is seriously dependent on repeated code type or data reconstruction and is not completely separated, thereby leading to an excessively high random jitter result when the bit error rate is extrapolated from the random jitter, and causing an overestimation that will cause an excessive margin design at the system level, resulting in additional hardware cost, power consumption and system complexity, and affecting the optimal implementation of link performance. Compared with the existing method, the method of the present application does not need a complex histogram statistics module, a threshold preset value module and a clock recovery module, and has the advantages of simple implementation and low computational complexity. In particular, the existing method depends on the data code type and needs a large amount of collected data, which is difficult to cope with long memory channels, while the method of the present application is not limited by the data code type and is suitable for any length of collected data. BRIEF DESCRIPTION OF DRAWINGS

[0032] Figure 1 A flowchart of the inter-symbol interference jitter separation method of the present application based on derivative sparsity and cyclostationary characteristics;

[0033] Figure 2 A time domain comparison chart of the total jitter obtained after the ISI jitter is separated by the method of the present application and the traditional method in the verification example;

[0034] Figure 3 A frequency domain comparison chart of the total jitter obtained after the ISI jitter is separated by the method of the present application and the traditional method in the verification example;

[0035] Figure 4 A histogram comparison of the total jitter obtained after the ISI jitter is separated by the method of the present application and the traditional method in the verification example. DETAILED DESCRIPTION

[0036] The present application will be described in detail below with reference to the accompanying drawings.

[0037] In order to make the objects, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and not used to limit the present application.

[0038] Embodiment 1

[0039] The embodiment provides an ISI jitter separation method based on derivative sparsity and cyclostationary characteristics, as shown in the following formula, specifically comprising constructing a derivative sparse function and extracting jitter based on cyclostationary characteristics. Figure 1

[0040] (1) The derivative sparse function is constructed as follows:

[0041] The transmission model of the high-speed serial link with jitter is as follows:

[0042] (1)

[0043] In the formula, s n is a transmission symbol, T s is a symbol time width, τ n is jitter of the n th symbol, p (t) is a shaped square wave with a width of T s, h (t) is a channel impulse response, for convenience of calculation, h (t) is set to be zero, for convenience of mathematical processing, both h (0) and h (T s ) are set to be zero, that is, the influence of channel delay is not considered.

[0044] For an ideal square wave p (t), at the time of signal jump, there is an impulse, and the derivative of p (t) is as follows:

[0045] (2)

[0046] In the formula, represents the influence of intersymbol interference on the derivative amplitude, and the time offset of the intersymbol interference on the derivative extreme value is set to be τ I, then at the time of the n th symbol jump,

[0047] (3)

[0048] Taylor expansion is performed on the above formula, and the following formula is obtained:

[0049] ​​​​​​​​​​​​​​​​​​​(4)

[0050] In the above formula, the channel impulse response Typically a low-pass filter, its tail decreases at an exponential rate, and its derivative... It will decrease much faster at a rate that is multiple of the time constant of the low-pass filter, and its amplitude will rapidly approach 0 at positions far from the main symbol. It is usually a relatively large constant, reflecting the curvature of the channel impulse response at its maximum value, therefore The value of can be approximated as 0, meaning that the offset caused by ISI to the extreme points of the derivative is negligible, and the position of the extreme points is mainly determined by the jitter of each sign. Decision, that is The extreme point data has been determined.

[0051] After determining the extreme point data, construct the time-domain sparse derivative signal:

[0052] (5)

[0053] In the formula, It has stable cyclic characteristics, and the cycle period is ,Right now It is a cycle period of It is a stationary random process, and the sparse function does not contain the effects of ISI jitter.

[0054] (2) Extracting jitter based on cyclic stability characteristics:

[0055] The method for extracting jitter in a high-speed serial link based on cyclic stationary characteristics, disclosed in ZL202411885558.2, is used to extract total jitter. This includes dividing the acquired sparse function according to the sampling multiple N and calculating the cyclic autocorrelation function of the sparse function at the symbol rate; obtaining the phase of the cyclic autocorrelation function, which contains only other jitter information of each symbol, thereby achieving the purpose of separating inter-symbol interference jitter in the high-speed serial link. The total jitter does not contain ISI jitter, that is, ISI jitter is separated from the total jitter.

[0056] Verification Example

[0057] To verify the effectiveness of the embodiments of the present invention, the following experimental platform was built. A SerDes signal was simulated using MATLAB 2024b with a symbol rate of 1Gbps, 128 sampling points per symbol, a total of 4096 symbols, a data code of PRBS7, and a modulation scheme of PAM2-NRZ. Random jitter RJ=0.05UI was added to the signal, along with sinusoidal jitter at a frequency of 200kHz and an amplitude of 0.2UI. The ISI jitter information was: channel attenuation of 3dB and frequency of 0.5GHz.

[0058] As shown in Figure 2 , the traditional method removes the random jitter and the periodic sinusoidal jitter by averaging, while in the method of the present application, the period of the sinusoidal jitter is less than one, so the traditional method cannot remove the influence of the sinusoidal jitter by averaging, resulting in a large deviation of the time-domain diagram after removing the ISI jitter, and as shown in Figure 3 and Figure 4 , it can be seen that the frequency and the jitter width of the obtained sinusoidal jitter are both greatly deviated, which will lead to the system being unable to accurately locate the fault frequency.

[0059] In summary, the method of the present application can correctly identify the low-frequency jitter even in the case of non-integer period sinusoidal jitter, can well remove the ISI jitter, retain the non-data-related periodic jitter, and is more accurate for system fault location.

[0060] The principles and implementation manners of the present application are described by applying specific embodiments in the present article, and the above embodiment descriptions are only used to help understand the method of the present application and its core idea. It should be noted that, for the ordinary skilled in the art, some improvements and modifications can be made to the present application without departing from the principles of the present application, and these improvements and modifications also fall within the protection scope of the claims of the present application.

Claims

1. A method for intersymbol interference jitter separation based on derivative sparsity and cyclostationarity, characterized by, The method comprises: Determine the extreme point data of each symbol based on the transmission model of the high-speed serial link with jitter, and the model is specifically as follows: （1） wherein is the transmitted symbol, is the symbol time width, is the jitter of the th symbol, is a shaped square wave of width , and is the channel impulse response; The time offset of the derivative extreme value of the inter-symbol interference is obtained by derivation on the above formula (1), and the extreme point data of each symbol is determined, specifically: by analyzing the time offset, the time offset of the derivative extreme value of the inter-symbol interference is approximately 0, and the position of the extreme point is determined by the jitter of each symbol , that is ; Construct a derivative sparse function through the extreme point data, and use the derivative sparse function to extract jitter information for inter-symbol interference elimination; Divide the obtained derivative sparse function according to a sampling multiple N, and calculate a cyclic autocorrelation function of the derivative sparse function at a symbol rate; obtain a phase of the cyclic autocorrelation function, the phase only contains other jitter information of each symbol, and complete jitter separation.

2. The method for inter-symbol interference jitter separation based on derivative sparsity and cyclostationarity according to claim 1, characterized in that, The time offset of the derivative extreme value caused by the inter-symbol interference is specifically as follows: Let be zero, and both start from zero, and after derivation, the following formula is obtained: （2） where represents the influence of the intersymbol interference on the derivative amplitude, assuming a time shift of the intersymbol interference on the derivative maximum of then the maximum is reached at the symbol jump , its second derivative is 0 at , as follows: （3） Taylor expand the above formula (3) to obtain the time offset of the derivative extreme value caused by the inter-symbol interference as follows: （4）。 3. The method for inter-symbol interference jitter separation based on derivative sparsity and cyclostationarity according to claim 1, characterized in that, Construct a time-domain sparse function according to the determined extreme point data, and the specific formula is as follows: （5）。

Images