fast characterization of pas mwj webcast aaa

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



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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

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.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.



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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

April 5, 20127



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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

April 5, 201210

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

April 5, 201217

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

April 5, 201219

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?



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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



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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

April 5, 201228



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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

April 5, 201232

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

April 5, 201237

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


E l h il bl h


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Examples shown are available here:

April 5, 201240

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)


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+ACPR


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Hsieh-Hung Hsieh (PhTechnical Manager / R

Design Program

TSMC

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RFIC Application

Development Engine

Agilent EEsof
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fast characterization of pas mwj webcast aaa

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