CN101149410B - Jitter analysis method based on eye diagram and bit error rate relation - Google Patents

Abstract

This invention provides a kind of dither signal measure method, firstly, calculate the dither sequence of the digital signals data bit, and count them, then exports the relation of eye image and errorrate, ensures that the Gauss frequency curve infinitely near according to the up-down tail of the J(x) frequency curve as well as its analytical RJ(x) and DJ(x), analyzes the dither into random dither and deterministic dither to know the system in farther. English abbreviation: total dither J(x), random dither RJ(x), deterministic dither DJ(x), error rate BER(x).

Description

A kind of jitter analysis method based on eye pattern and bit error rate relation

Technical field:

Present invention relates in general to the jitter measurement field, propose a kind of measuring-signal dither method, be specially adapted to the technical field of shaking analytic system by decomposing.

Background technology:

Shake is a term well-known in the art, be to use voltage transitions to represent unwelcome accompaniment in all electronic systems of timing information, the short term variations of ideal time position is departed from the effective edge edge that can be defined as in the digital signal data bit sequence, and shake may cause the error in data of receiving end.Therefore, the definite amount and type that may appear at signal is very important.And shake comprises two kinds of different types, i.e. deterministic jitter DJ (x) and randomness shake RJ (x).Wherein unbounded on amplitude and be assumed to be the randomized jitter of seeing as of gaussian shaped profile, on the contrary, be not at random, the bounded above deterministic jitter of seeing as of amplitude.

The final scale of weighing systemic-function is an error rate BER, the method that wherein can measure the bit error rate is to rely on eye pattern, and the method for observing eye pattern is: the output terminal that is connected across receiving filter with an oscillograph, adjust the scope sweep cycle then, make the cycle synchronisation of scope horizontal sweep cycle and receiving symbol, the figure that see on the oscillograph screen this moment is " eye pattern ".The target of jitter analysis is to determine the influence of shake to BER, and guarantees that the BER of system is lower than certain maximal value, normally 10 ^-12

Summary of the invention:

Technical matters:

The present invention proposes a kind of signal jitter measuring method, comprise: obtain the shake of each, and the total shake J (x) that is surveyed added up, construct the bimodal model of total shake J (x), relation according to the determined shake of eye pattern and the bit error rate, make the last lower tail of total shake J (x) distribution curve be infinitely close to randomness shake RJ (x) and the determined Gaussian distribution curve of deterministic jitter DJ (x), be decomposed into randomness shake RJ (x) and deterministic jitter DJ (x) thereby will always shake J (x).Referring to Fig. 1.

Technical scheme:

To comprising any signal of some Gauss's shake, if the time long enough of accumulative total sample, eye pattern should be able to close fully.This can cause such notion: opening eye pattern as a comparison, the basis is otiose.And if eye pattern is opened the application degree of confidence, then can recover the use of eye pattern.Scale is placed on the center of eye pattern always in the horizontal direction, suppose if any waveform strides across this scale, then be considered as error code, and rise or descend no matter be, by using a series of scales, can examine and determine the relation of the eye pattern stretching degree and the bit error rate comprehensively, and the descriptive figure of this relation is called bathtub figure.Referring to Fig. 2.

After having gathered enough points, the probability density function of shake or distribution function can be measured by the histogram at place, eye pattern point of crossing.J (x) can be divided into RJ (x) and DJ (x), promptly

J(x)＝RJ(x)*DJ(x) (1)

Wherein: $\mathrm{RJ}\left(x\right)=\frac{1}{\sqrt{2\mathrm{\π}}\mathrm{\σ}}\exp [-\frac{x^2}{{2\mathrm{\σ}}^2}]---\left(2\right)$

So can get: $J\left(x\right)=\frac{1}{\sqrt{2\mathrm{\π}}\mathrm{\σ}}\∫\mathrm{DJ}\left(x^{\′}\right)\exp [-\frac{{(x-x^{\′})}^2}{2{\mathrm{\σ}}^2}]d{x}^{\′}---\left(3\right)$

And draw important basis of the present invention thus, promptly total bimodal pattern of shaking, infinitely approaching in the afterbody and the Gaussian distribution curve of its distribution:

$\underset{x\→+\∞}{\lim }J\left(x\right)\→\mathrm{Aexp}[-\frac{{(x-{\mathrm{\ξ}}_L)}^2}{{2\mathrm{\σ}}^2}]$

(4)

$\underset{x\→+\∞}{\lim }J\left(x\right)\→\mathrm{Aexp}[-\frac{{(x-{\mathrm{\ξ}}_R)}^2}{{2\mathrm{\σ}}^2}]$

So, be 10 reaching the bit error rate by bathtub figure ^-12The figure place, promptly can obtain σ and ξ in the following formula _L, ξ _RValue, promptly obtained (δ δ) value of RJ (x) and DJ (x).

Beneficial effect:

According to the signal data that measures, this method can be decomposed into nearly all shake J (x) randomness shake RJ (x) and deterministic jitter DJ (x).So just the shake of complexity is decomposed into the shake of notable feature, thereby analyzes this two kinds of shakes, find the reason that produces signal jitter, determine the method for erasure signal shake with notable feature.Further the analytic signal system determines the ability to bear of system to shake, also can infer owing to measure the oversize performance that causes directly measuring the system of difficulty consuming time.

Description of drawings:

Fig. 1 is the principle schematic that J (x) decomposes.

Fig. 2 is the tub curve synoptic diagram.

Fig. 3 asks RJ (x) and DJ (x) synoptic diagram by the BER graph of a relation.

Embodiment:

Enforcement of the present invention can be divided into the measurement statistics of two part: J (x) and defining of concrete numerical value.Wherein, the measurement of J (x) statistics needs to gather lot of data adds up, and determines the desirable figure of original signal, changes the x value of eye size, the BER (x) of statistics under this x.And the defining of concrete numerical value, x that obtains according to the first step and the corresponding relation of BER (x) utilize

Relation is obtained the relation of Q (x) and x, and then can be obtained BER 10 ^-12, that is Q (x) is the tangent line of the Q (x) 6,7 near at numerical value: its slope is represented the σ among the RJ; Can determine the ξ of DJ with the intersection point at top _LAnd ξ _R

Experiment:, obtain the σ of RJ (x) and (the δ δ) of DJ (x) at a resulting string data.The concrete steps of algorithm are as follows:

The measurement statistics of J (x):

Step 1:, obtain the ideal position at logical transition edge by given data.

Step 2: the difference between statistic logic edge ideal position and the physical location is the numerical value of each data bit shake, determines the distribution of J (x).

Step 3: two point of crossing of the corresponding eye pattern of difference, according to the transformational relation of eye pattern and bathtub figure, obtain the two-part BER in the left and right sides (x):

${\mathrm{BER}}_L\left(x\right)=\mathrm{\ρ}{\∫}_x^{+\mathrm{\ω}}J\left(x^{\′}\right){\mathrm{dx}}^{\′}$

${\mathrm{BER}}_R\left(x\right)=\mathrm{\ρ}{\∫}_{-\∞}^{x}J\left(x^{\′}\right){\mathrm{dx}}^{\′}---\left(5\right)$

Wherein, ρ is the figure place ratio of edge logical transition in the total bit.At this moment, BER _L(x) can be statistics begins J (x) number to+∞, BER from some x _R(x) can be that statistics begins J (x) number to x from some-∞.Promptly count two numerical value.

Defining of concrete numerical value:

Step 1:, formula 5 can be converted to according to the bimodal model of J (x)

${\mathrm{BER}}_I\left(x\right)=\mathrm{\ρ}\frac{1}{\sqrt{2\mathrm{\π}}\mathrm{\σ}}{\∫}_x^{\∞}\exp [-\frac{{(u_1-x^{\′})}^2}{{2\mathrm{\σ}}^2}]{\mathrm{dx}}^{\′}---\left(6\right)$

Step 2: wherein, get

Then

${\mathrm{BER}}_I\left(Q\right)=\mathrm{\ρ}{\∫}_Q^{\∞}\exp [-\frac{Q^{\′2}}{2}]d{Q}^{\′}---\left(7\right)$

Step 3: according to the error complementary function

Obtain the corresponding relation of Q (x) and BER (x)

Step 4: BER (x) that obtains according to first and the relation of x, in conjunction with the Q (x) and the BER (x) of second portion, can be referring to table 1.

Table 1

Step 5: if be that 2,3 places make tangent line at Q (x), then will obtain 1/ smaller σ, promptly can make the randomized jitter that obtains at last become big, then eye pattern can very fast closure, and BER (x) does not reach 10 ^-12So (promptly Dui Ying BER (x) is 10 at Q (x) the chances are 6,7 places ^-12About) make tangent line, obtain slope and be 1/ σ, left side σ _L, the right σ _R, and σ=(σ _L+ σ _R)/2.Can be referring to Fig. 3.Two intersection points of the right and left tangent line and Q (x) are ξ _LAnd ξ _R

Step 6: according to resulting σ, utilize formula (2), promptly can obtain RJ (x); According to resulting ξ _LAnd ξ _R, promptly can obtain DJ (x) (δ δ).

Claims (6)

1. the method for measuring-signal shake, it is characterized in that: obtain the shake of each, and the total shake J (x) that is surveyed added up, construct the bimodal model of total shake J (x), relation according to the determined shake of eye pattern and the bit error rate, make the last lower tail of total shake J (x) distribution curve be infinitely close to randomness shake RJ (x) and the determined Gaussian distribution curve of deterministic jitter DJ (x), thereby will always shake J (x) and be decomposed into randomness shake RJ (x) and deterministic jitter DJ (x), the distribution of total shake J (x) is obtained by the histogram at place, eye pattern point of crossing, and its bimodal position is by the ξ of deterministic jitter DJ (x) _LAnd ξ _RDetermine; And the distribution of its afterbody left side bit error rate With the right bit error rate

Randomness shake RJ (x) by two Gaussian distribution determines respectively; The error rate BER of obtaining (x) continues according to formula

Corresponding relation, obtain the relation of Q (x) and x again, wherein ρ is total

The figure place ratio of edge logical transition in the figure place will reach 10 to the error rate BER (x) that requires of signal ^-12, corresponding Q (x) is about 7, so determined the σ of left side Gaussian distribution in the bimodal pattern by near 7 tangent slopes _Lσ with the right Gaussian distribution _R, and finally obtain σ=(σ _L+ σ _R)/2, and then the ξ of definite deterministic jitter DJ (x) _LAnd ξ _R

2. according to the method for the described measuring-signal shake of claim 1, it is characterized in that further comprising: data bit shake statistics can draw by eye pattern.

3. according to the method for the described measuring-signal of claim 1 shake, it is characterized in that further comprising: from eye pattern ask error rate BER (x) thus during the derivation tub curve, left error rate BER _L(x) statistics begins to the number of total shake J (x) of+∞, right error rate BER from some x _R(x) statistics begins to the number of total shake J (x) of some x from-∞.

4. according to the method for the described measuring-signal of claim 3 shake, it is characterized in that further comprising: from the eye pattern left error rate BER of deriving _L(x) time, it is to be equivalent to x place in the middle of eye pattern in essence, has placed a horizontal line, after after a while, crosses over this horizontal edge in every case, no matter rising edge or negative edge all be can be regarded as an error code, and right error rate BER _R(x) the class of algorithms seemingly.

5. according to the method for the described measuring-signal of claim 1 shake, it is characterized in that further comprising: always shake J (x) and be decomposed into randomness shake RJ (x) and deterministic jitter DJ (x), and J (x)=RJ (x) * DJ (x), the distribution of always shaking J (x) is obtained by the histogram at place, eye pattern point of crossing.

6. according to the method for the described measuring-signal shake of claim 1, it is characterized in that further comprising: obtained randomness shake RJ (x) and deterministic jitter DJ (x), further analytic system is determined the ability to bear of system to shake.

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