Essential principles of jitter part 2 the components of jitter
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Transcript of Essential principles of jitter part 2 the components of jitter
WEBINAR: Essential Principles of Jitter Part II Components of Jitter Thank you for joining us. We will begin at 2pm ET. NOTE: This presentation includes Q&A. We will be taking questions during the presentation with answers at the end using the questions section of your control panel.
LeCroy founded in 1964 by Walter LeCroy Origins are high speed digitizers for particle physics
research Teledyne LeCroy corporate headquarters is located in
Chestnut Ridge, NY Teledyne LeCroy has the most advanced technology
and widest line of Real-Time digital oscilloscopes (from 40 MHz to 100 GHz)
Long History of Innovation in Digital Oscilloscopes Teledyne LeCroy became the world leader in
protocol analysis with the purchase of CATC and Catalyst, and creating a protocol analyzer division based in Santa Clara, CA.
In August 2012, LeCroy became Teledyne LeCroy through an acquisition by Teledyne Technologies
Teledyne LeCroy Overview
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NEW: blog.teledynelecroy.com
Look here for information related to all your oscilloscope questions. Find basic tips on how to use an oscilloscope to more fundamental measurement concepts and application specific details such as: serial data, probing and power measurement. Available to you 24/7
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About the Presenters
Dr. Eric Bogatin • Signal Integrity Evangelist with the Teledyne LeCroy Front Range
Signal Integrity Lab • Adjunct Professor, University of Colorado, Boulder, ECEE • Soon to be: Dean, Teledyne LeCroy Signal Integrity Academy Email: [email protected] www.beTheSignal.com
Dr. Alan Blankman Signal Integrity Product Marketing Manager, Teledyne LeCroy • B.A. Northwestern University • PhD University of Pennsylvania • MBA New York University, Stern School of Business • Has been with Teledyne LeCroy for over 16 years Email: [email protected]
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Essential Principles of Jitter part 2 Dr. Alan Blankman Product Manager, High Speed Serial Data Products, Teledyne LeCroy and Dr. Eric Bogatin, Dean, Teledyne LeCroy Signal Integrity Academy, Teledyne LeCroy
Check out the Teledyne LeCroy Signal Integrity Academy at www.beTheSignal.com
Where to get a copy of the slides: www.beTheSignal.com
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Essential Principles of Jitter, or Jitter 101
1 Introduction to Jitter: The Time Interval Error: TIE
2 Jitter Synthesis: The Jitter Components
3 Jitter Analysis Extrapolation and Decomposition
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Jitter part 1: The Time Interval Error (TIE)
The actual edge arrival times – the expected edge arrival times, for each edge
Expected arrival times from CDR circuitry
Plotted over time: the TIE track Apply the power of statistics to
analyze the TIE track
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Jitter part 2: The Jitter Components
The power of statistical analysis
The five fundamental types of jitter: ISI, DCD, Periodic, Random, Other
Their statistical “signature”
The jitter “tree”
Synthesizing examples based on their root cause
Check out Alan’s new app note: “Understanding Jitter Calculations, why Dj can be less than DDj (or Pj)”
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How Can We Characterize Jitter?
What figures of merit do we use to characterize the TIE Track (jitter) waveform?
Look at a histogram distribution of the jitter over some time period What terms characterize the waveform?
Average Peak to peak (over some interval) Spectral density RMS, standard deviation (only has meaning if Gaussian) Best figures of merit to use depend on the features of the TIE Track
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Explore Jitter Analysis of Many NRZ Data Signals: look for patterns
Take an NRZ data pattern
Recover clock and calculate TIE Track
Plot a histogram of jitter over some time interval
Plot the spectral density of jitter over some time interval
Tpk-pk
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Best Figure of Merit Depends on the “Signature” of the Jitter
Peak-Peak is not a useful figure of merit for Gaussian (random) Jitter Random jitter is unbounded
Peak-Peak grows as we increase
the measured time interval
Expected pk-pk
Typically, the more samples, the farther the outliers…but it’s statistical
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Inter Symbol Interference (ISI): information from one bit leaks into others
200 psec UI
(described by S-parameter matrix)
ISI
“echoes of bits past”
One root cause of ISI jitter: reflection noise
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Another root cause of ISI jitter: frequency dependent loss rise time degradation vertical noise and horizontal jitter
SBR for extreme bit patterns, 11111010000000
00000010000000
5 Gbps, RT = 50 psec
Switching threshold time for the “1” bit is different when previous bits were all 0 or all 1
The more rise time degradation, the more deterministic jitter
20 inch interconnect:
40 inch interconnect:
No interconnect
And every bit pattern combination between Teledyne LeCroy Signal Integrity Acadamy 14
Jitter from Inter Symbol Interference (ISI) Signature: Jitter of an edge depends on the bit history
TIE Track repeats for a repeating bit pattern (e.g., PRBS7)
Features of jitter from ISI Discrete peaks corresponding to specific, finite bit patterns Bounded, pk to pk is a good FoM Broadens a little with increasing repeat bit pattern Complex spiky histogram pattern characterizes ISI jitter Tpk-pk= DDj
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Duty Cycle Distortion (DCD)
Caused by: Variation in crossing level and/or
shift in signal’s offset If rising, falling edge is symmetric about level, no DCD
Signature: two states in TIE Track and histogram Measures difference in bit width for 0 and 1 bits Bounded Figure of Merit: center to center of average of each
distribution
0 1 1 0
DCD = ∆T
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Periodic Jitter Caused by:
Coupling from other periodic signals in system, Noise on the power rails, Instability in a feedback loop
Signature: bowl-shape histogram, pks in spectrum
Bounded Contributed by ALL the frequency components of periodic jitter Characterized by the peak to peak jitter from all periodic sources
TIE track Pk-Pk periodic = Pj
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Random Jitter: root cause- “death by a thousand cuts”
2
2
1 tPDF(t) exp22
= − σπσ
Probability of an edge arriving a time t from the mean is a Gaussian distribution
Random jitter can have large excursions… just at low probability
Typically, the more samples, the farther the outliers…but it’s statistical
Peak to peak
Random jitter pk-pk grows with sample size
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Gaussian Statistics in 4 minutes
2
2
1 tPDF(t) exp22
= − σπσ
n
n
PDF(t)dt+ σ
− σ
= ∫n
n n
1 PDF(t)dt 2 x PDF(t)dt+ σ ∞
− σ + σ
= − =∫ ∫
Confidence interval measured in units of σ
outliers
Two regions: (the fraction in each region)
• Confidence interval defined as between +/-n σ: fraction of events occurring within the confidence interval =
• Outliers (outside the confidence interval): fraction of events occurring as outlier =
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What is the Connection between Outlier Fraction and Confidence Interval Width?
0
2
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12
14
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18
1.E-
16
1.E-
15
1.E-
14
1.E-
13
1.E-
12
1.E-
11
1.E-
10
1.E-
09
1.E-
08
1.E-
07
1.E-
06
1.E-
05
1.E-
04
1E
03
Alph
a (#
of s
igm
a)
Outlier Fraction
confidence interval width = α x σ
Confidence interval measured in units of σ
outliers
n
n
1 PDF(t)dt fraction of bits outside confidence int erval+ σ
− σ
− =∫
For an outlier fraction of 10-12, need α = 14.069 Rule #9: what do we expect? Teledyne LeCroy Signal Integrity Acadamy 20
So What?
δT
δT
UI
If strobe point is located δT from beginning of UI or end of UI, any edge with arrival time > δT will be an error (the outliers) For a given strobe location, the confidence interval is (2 x δT) and the fraction of outliers is the BER For a target BER of 10-12 , confidence interval is = α x σ = 14.069 x σ The σ characterizes the Gaussian distribution of jitter
wash on, wash off Teledyne LeCroy Signal Integrity Acadamy 21
Four Kinds of Jitter: They don’t always play well together
Periodic Jitter Intersymbol Interference
Duty Cycle Distortion Random Jitter
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The Fifth Type of Jitter: “Other”
Other: catch all grab bag Bounded in extent (not Gaussian) Uncorrelated to the data… Not Gaussian, not periodic… OBUJ
Other Bounded Uncorrelated Jitter Crosstalk / interference, switching noise, cavity noise
Interference translates into jitter Potentially broadband; spectral noise floor rises:
w/XTALK
Teledyne LeCroy Signal Integrity Acadamy 23
Classification of Jitter Types: Our Five Friends
Total Jitter – “Tj”
Intersymbol interference
“ISI”
Duty Cycle Distortion
“DCD”
Bounded Deterministic (not random)
“Dj”
Correlated Jitter Data Dependent Jitter
“DDj”
Periodic “Pj”
Unbounded, Random
“Rj”
Bounded, uncorrelated Jitter
“BUJ”
Other, bounded, uncorrelated with the data,
jitter “OBUJ”
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Alan Blankman Product Manager, High Speed Serial Data Products,
Teledyne LeCroy
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ISI
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DCD
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Periodic
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Random
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Multiple
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Four General Patterns from Different Causes of Jitter (5th is “other”)
Periodic Jitter Intersymbol Interference
Duty Cycle Distortion Random Jitter
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Essential Principles of Jitter, or Jitter 101
1 Introduction to Jitter: The Time Interval Error: TIE
2 Jitter Synthesis: The Jitter Components
3 Jitter Analysis Extrapolation and Decomposition
Teledyne LeCroy Signal Integrity Acadamy 32
For More Information
www.BeTheSignal.com
The Signal Integrity Academy
Online video training
Published by Prentice Hall, 2009
Check out Alan’s new app note: “Understanding Jitter Calculations, why Dj
can be less than DDj” Visit www.TeledyneLeCroy.com
Teledyne LeCroy Signal Integrity Acadamy 33
Q&A
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