8413S12 Datasheet, PDF (17/33 Pages) Integrated Device Technology – Selectable external crystal or differential

8413S12 DATA SHEET
Peak-to-Peak Jitter Calculations
A standard deviation of a statistical population or data set is the
square root of its variance. A standard deviation is used to calculate
the probability of an anomaly or to predict a failure. Many times, the
term “root mean square” (RMS) is used synonymously for standard
deviation. This is accurate when referring to the square root of the
mean squared deviation of a signal from a given baseline and when
the data set contains a Gaussian distribution with no deterministic
components. A low standard deviation indicates that the data set is
close to the mean with little variation. A large standard deviation
indicates that the data set is spread out and has a large variation from
the mean.
A standard deviation is required when calculating peak-to-peak jitter.
Since true peak-to-peak jitter is random and unbounded, it is
important to always associate a bit error ratio (BER) when specifying
a peak-to-peak jitter limit. Without it, the specification does not have
a boundary and will continue get larger with sample size. Given that
a BER is application specific, many frequency timing devices specify
jitter as an RMS. This allows the peak-to-peak jitter to be calculated
for the specific application and BER requirement. Because a
standard deviation is the variation from the mean of the data set, it is
important to always calculate the peak-to-peak jitter using the typical
RMS value.
The Table 8 shows the BER with its appropriate RMS Multiplier.
There are two columns for the RMS multiplier, one should be used if
your signal is data and the other should be used if the signal is a
repetitive clock signal. The difference between the two is the data
transition density (DTD). The DTD is the number of rising or falling
transitions divided by the total number of bits. For a clock signal, they
are equal, hence the DTD is 1. For Data, on average, most common
encoding standards have a 0.5 DTD.
Table 8. BER Table
BER
RMS Multiplier Data,
“DTD = 0.5”
10^-3
6.180
10^-4
7.438
10^-5
8.530
10^-6
9.507
10^-7
10.399
10^-8
11.224
10^-9
11.996
10^-10
10^-11
12.723
13.412
10^-12
14.069
10^-13
14.698
10^-14
10^-15
15.301
15.883
RMS Multiplier Clock,
“DTD = 1”
6.582
7.782
8.834
9.784
10.654
11.462
12.218
12.934
13.614
14.260
14.882
15.478
16.028
Once the BER is chosen, there are two circumstances to consider. Is
the data set purely Gaussian or does it contains any deterministic
component? If it is Gaussian, then the peak to peak jitter can be
calculated by simply multiplying the RMS multiplier with the typical
RMS specification. For example, if a 10^-12 BER is required for a clock
signal, multiply 14.260 times the typical jitter specification.
Jitter (peak-to-peak) = RMS Multiplier * RMS (typical)
If the datasheet contains deterministic components, then the random
jitter (R_J) and deterministic jitter (D_J) must be separated and
analyzed separately. R_J, also known as Gaussian jitter, is not
bounded and the peak-to-peak will continue to get larger as the
sample size increases. Alternatively, peak-to-peak value of D_J is
bounded and can easily be observed and predicted. Therefore, the
peak to peak jitter for the random component must be added to the
deterministic component. This is called total jitter (T_J).
Total Jitter (peak-to-peak) = [RMS Multiplier * Random Jitter
(R_J)] + Deterministic Jitter (D_J)
The total jitter equation is not specific to one type of jitter
classification. It can be used to calculate BER on various types of
RMS jitter. It is important that the user understands their jitter
requirement to ensure they are calculating the correct BER for their
jitter requirement.
NOTE: Use R_J and D_J values for AC Characteristics Tables 7B
through 7G to calculate T_J.
REVISION D 1/27/15
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