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7/30/2019 Fast Characterization of PAs MWJ Webcast AAA
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Andy Howard
Senior Applications Engineer
Agilent EEsof
April 5, 2012Copyright 2012 Agilent Technologies
Welcome
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Fast Characterization ofPower Amplifier
Performance with
Modulated Signals
Efficient simulations withswept-power, modulated
signals
Agilent EEsof EDA
Andy Howard
Applications Engineer
April 5, 2012
April 5, 2012Copyright 2012 Agilent Technologies
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Power amplifier design and characterization has
become more complex
Characterizing amplifier performance with sinusoids is nolonger sufficient
Need to know ACLR, EVM, output power, etc.
Need to know performances versus power and at specific
output powers
How should design parameters be adjusted to improveperformance?
Need to know statistical distributions of performances
April 5, 20123
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Two Solutions
1) Simulate nonlinearity using 1-tone HB power sweep.Apply modulated signal to nonlinearity in post-processing.Interpolate to get data at specific output power.Repeat for each Monte Carlo trial or swept parameter value.
2) Use Ptolemy cosimulation and Automatic VerificationModeling.Interpolate to get data at specific output power.Repeat for each Monte Carlo trial or swept parameter value.
April 5, 20124
Solution 1: somewhat faster, but less accurate.Solution 2: more accurate and more information.
Copyright 2012 Agilent Technologies
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Two Solutions
1) Simulate nonlinearity using 1-tone HB power sweep.Apply modulated signal to nonlinearity in post-processing.
2) Use Ptolemy cosimulation and Automatic VerificationModeling.
April 5, 20125
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Weve offered this technique for a while, so whats
new?
Parameter sweep or Monte Carlo analysis now allowed See correlations between statistical variables and results
Data now available at user-specified output power(s) noneed to re-simulate or run an optimization
April 5, 20126
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To carry out this technique, what do you need?
Modulated signal or baseband I and Q data Main, adjacent, and alternate, channel frequency limits for
ACPR calculation
An example from which you copy the setup
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Many modulated signals could be used
(only have to create file once)
April 5, 20128
From a simplified Ptolemy example
Could use baseband I and Q data
Could use data from Signal Studio
Could use same signal with which you test real amplifier
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Run swept power HB simulation of amplifier
April 5, 20129
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Apply modulated signal to simulated amplifier s
nonlinearity
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Input trajectory
Ideal and distortedoutput trajectories
Amplifier nonlinearity
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ACPR, EVM, output power computed via equations
April 5, 201211
Ideal and distortedoutput trajectories ACPR is computed
fromOutputspectrum
EVM is computed from deltaat each time point
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Display swept-power (from scaling input signal
amplitude) and interpolated results
Interpolation gives data at specified output power
April 5, 201212
Fast plots update instantly
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Speed up calculation by specifying subset of
modulated time sequence
April 5, 201213
Using..EDGE_Sig[0::500]
Using..EDGE_Sig[0::5000]
Using ..EDGE_Sig- All time points included
Trade accuracy for calculation speed.
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Shorter sequence gives very similar results as
longer one
April 5, 201214
501 vs 5001time points ~8 seconds vs.~42 seconds
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Run Monte Carlo to see statistical variation
April 5, 201215
1072 seconds requiredDataset: 866 kbytes
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With shorter sequence, only sl ight changes
April 5, 201216
217 seconds requiredDataset: 751 kbytes
These data are only slightly different.
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New specified output power; histograms and data
update instantly no need to re-simulate
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Higher output power -> higher distortion, as expected.
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We now know the statistical variation.
Which statistical variables matter?
April 5, 201218
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Scatter plots show correlations - ACPR
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ACPR improveswith increasing
drain bias
ACPR improveswith increasing
TL width
Little correlation with
dielectric constant
Little correlationwith gate bias
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Scatter plots show correlations - EVM
April 5, 201220
EVM improveswith increasing
drain bias
EVM improveswith increasing
TL width
No correlationwith dielectricconstant
Little correlationwith gate bias
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Could design parameters be changed to attain
better performance?
April 5, 201221Copyright 2012 Agilent Technologies
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Sweeping a parameter to seek better performance
April 5, 201222
Variables definedin subcircuit canalso be swept
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Performance varies with transmission line length
April 5, 201223Copyright 2012 Agilent Technologies
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Sweeping one parameter at a time is inefficient
April 5, 201224
Use Monte Carlo to investigate multiple design parameterssimultaneously
Design variables allowed to vary uniformly over large range.All values within range are equally likely.
Similar to running a multi-dimensional parameter sweep
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Big variation in performance
April 5, 201225
Minimum ACPRswhile delivering26 dBm
Correspondingvariable values(lengths andwidths in mils)
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Which design variables affect Pout_dBm?
April 5, 201226
Betterperformance
Betterperformance
Betterperformance
Want 26 dBm Pout, but not all sets of
parameter values enable this
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Which design variables affect ACPR?
April 5, 201227
Betterperformance
Better performance
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Using this technique effectively
Use as many design variables as you want. Simulation timeonly determined by number of Monte Carlo trials.
Correlations indicate which variables matter
Best parameter values update as you change specified output
power
Iterate (re-run Monte Carlo) after adjusting parameter valueranges based on best set of parameter values
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Two Solutions
1) Simulate nonlinearity from 1-tone HB power sweep.Apply modulated signal to nonlinearity.
2) Use Ptolemy cosimulation and Automatic VerificationModeling.
April 5, 201229
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Weve offered this technique for years, so whats
new?
Power sweeps now run much more efficiently
See correlations between statistical variables and results
Data now available at user-specified output power(s) noneed to re-simulate or run optimizations
April 5, 201230
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Using Ptolemy cosimulation
April 5, 201231
Power amplifier subcircuitEDGEsource
EVM measurementACLR measurement
DC powerconsumptionmeasurement
Output powermeasurementInput power
sweep
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Power amplifier subcircuit
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Time step must be set should match source time step
Variables copied fromEDGE source.
Co-simulationrequiresEnvelopecontroller
Stop time setting is ignored
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Use Fast Cosimulation (Automatic Verification
Modeling)
April 5, 201233
Creates and simulates behavioral model-- but only if something in the circuit changes Simulates orders of magnitude faster than full transistor-level model
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Simulation results
April 5, 201234
Specify desired output power. Data is interpolatedto find values corresponding to this power level.
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Run Monte Carlo to see statistical variation
April 5, 201235
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Swept parameter results same transmission l ine
swept
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Comparing simulation results
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Results are similar, but not Identical.Differences increase at highest output
Powers.
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Comparing the methods
April 5, 201238
Ptolemy cosimulation advantages:- Specification-compliant measurements- Can include receive-side filtering, if required- Power-added efficiency (PAE) is computed
Swept-power harmonic balance simulation advantages:- Faster (but less accurate) for short time sequences- Can be used with any source
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Conclusions
April 5, 201239
ADS enables fast characterization of amplifier performance Powerful post-processing capabilities Understand statistical variation of your design Understand which variables matter
Copyright 2012 Agilent Technologies
E l h il bl h
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Examples shown are available here:
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http://edocs.soco.agilent.com/display/eesofkc/Computing+Swept+Input+Power+ACPR
http://edocs.soco.agilent.com/display/eesofkc/Swept+Power+ACPR%2C+EVM%2C+and+PAE+from+Ptolemy+Co-simulation
(Agilent EEsof Knowledge Center login required)
Copyright 2012 Agilent Technologies
Y I it d
http://edocs.soco.agilent.com/display/eesofkc/Computing+Swept+Input+Power+ACPRhttp://edocs.soco.agilent.com/display/eesofkc/Swept+Power+ACPR,+EVM,+and+PAE+from+Ptolemy+Co-simulationhttp://edocs.soco.agilent.com/display/eesofkc/Swept+Power+ACPR,+EVM,+and+PAE+from+Ptolemy+Co-simulationhttp://edocs.soco.agilent.com/display/eesofkc/Swept+Power+ACPR,+EVM,+and+PAE+from+Ptolemy+Co-simulationhttp://edocs.soco.agilent.com/display/eesofkc/Swept+Power+ACPR,+EVM,+and+PAE+from+Ptolemy+Co-simulationhttp://edocs.soco.agilent.com/display/eesofkc/Swept+Power+ACPR,+EVM,+and+PAE+from+Ptolemy+Co-simulationhttp://edocs.soco.agilent.com/display/eesofkc/Swept+Power+ACPR,+EVM,+and+PAE+from+Ptolemy+Co-simulationhttp://edocs.soco.agilent.com/display/eesofkc/Swept+Power+ACPR,+EVM,+and+PAE+from+Ptolemy+Co-simulationhttp://edocs.soco.agilent.com/display/eesofkc/Computing+Swept+Input+Power+ACPR7/30/2019 Fast Characterization of PAs MWJ Webcast AAA
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Hsieh-Hung Hsieh (PhTechnical Manager / R
Design Program
TSMC
You are Invited:
You can find more webcasts
www.agilent.com/find/eesof-innovations-in-edawww.agilent.com/find/eesof-webcasts-recorded
George Estep
RFIC Application
Development Engine
Agilent EEsof
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