Monte Carlo Simulation in Statistical Design Kit

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Monte Carlo Simulationin Statistical Design Kit
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Overview
Monte Carlo simulation in statistical design kit
1. Monte Carlo Simulation 2. Practical
demonstration in Cadence 3. Simulation and
Measurement
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Monte Carlo Simulation
Monte Carlo simulation in statistical design kit
... allows the random variation of - process
parameters - mismatch parameters - process
mismatch parameters
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Monte Carlo process simulation
Monte Carlo simulation in statistical design kit
Wafer production will always show some variation
of techno- logical parameters The MC process
simulation is the adequate tool to give an early
estimation how it will affect the circuits
function.
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Monte Carlo process simulation
Monte Carlo simulation in statistical design kit
... dw_rpyhl_skew rcs_rpyhl_skew rsh_rpyhl_s
kew a_wc_skew_nsic a_be0_skew_nsic r_nsu_skew_nsic
r_nbl_skew_nsic r_ncx_skew_nsic r_nci_skew_nsic r
_wb_skew_nsic r_jbei_skew_nsic r_nbei_skew_nsic
...
For each simulation run a new random set of
process parameters is generated and is valid for
all active and passive components in the circuit
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Monte Carlo mismatch simulation
Monte Carlo simulation in statistical design kit
Even optimum layout cannot completely avoid
mismatch between components. The MC mismatch
analysis gives insight in the effect of these
slight variations.
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Monte Carlo mismatch simulation
Monte Carlo simulation in statistical design kit
For each device an individual mismatch random
variable is generated and is valid only for a
single run. The mismatch property can be set
globally or for selected devices only.
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Monte Carlo process mismatch simulation
Monte Carlo simulation in statistical design kit
In addition to the global random process
parameter set each device gets an individual
mismatch random variable. This combined
simulation will give an estimation of a real
wafer fabrication
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Monte Carlo Tool Demonstration
Monte Carlo simulation in statistical design kit
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Testbench
Monte Carlo simulation in statistical design kit
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Operational Amplifier V1
Monte Carlo simulation in statistical design kit
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Opamp V1 Mismatch and Process Variation
Monte Carlo simulation in statistical design kit
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Sweep of Process Parameter Model Setup
Monte Carlo simulation in statistical design kit
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Sweep of Process Parameter Model Setup
Monte Carlo simulation in statistical design kit
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Variation of Process Parameter with Corner Tool
Monte Carlo simulation in statistical design kit
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Variation of Process Parameter with Corner Tool
Monte Carlo simulation in statistical design kit
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Sweep of Process Parameter
Monte Carlo simulation in statistical design kit
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Opamp V1 Mismatch and Process Variation
Monte Carlo simulation in statistical design kit
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Circuit optimisation
Monte Carlo simulation in statistical design kit
Step 1 Add base current compensation
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Circuit optimisation Step 1
Monte Carlo simulation in statistical design kit
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Circuit optimisation
Monte Carlo simulation in statistical design kit
Step 2 Add buffer stage
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Monte Carlo simulation in statistical design kit
Circuit optimisation Step 2
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Circuit optimisation
Monte Carlo simulation in statistical design kit
Step 3 Adjust bias current and add
cascode stage
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Circuit optimisation Step 3
Monte Carlo simulation in statistical design kit
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Improvement in DC-Offset
Monte Carlo simulation in statistical design kit
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Overview
Monte Carlo simulation in statistical design kit
DC-Offset N 1000
simulation runs
Simulation
MM Proc MMProc before
optimisation 3.82 22.77 24.94mV
after optimisation 1.16 0.09
1.16mV
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Identify critical components and process
parameters
Monte Carlo simulation in statistical design kit
- Run sensitivity analysis - MC Simulation with
individual mismatch enable - Perform
correlation check after process simulation in
Monte Carlo Tool - sweep of single process
parameters
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Rules of thumb for Design
Monte Carlo simulation in statistical design kit
Wide spread at Mismatch Simulation -gt Increase
area factor of critical components Wide spread
at Process Simulation -gt Check circuit
topology e.g. - add base current compensation
- add cascode or buffer stage
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Simulation and Measurement
Monte Carlo simulation in statistical design kit
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Circuit Topology
Monte Carlo simulation in statistical design kit
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First approach toDC-Offset compensationwith
dummy stage
Monte Carlo simulation in statistical design kit
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Results from first Silicon
Monte Carlo simulation in statistical design kit
First silicon of a test circuit did show a wide
spreading of DC offsets especially in high gain
mode. The yield was unacceptable low DC
offset voltages Specification /- 20mV
First silicon 40mV (1-sigma)
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Typical DC Offset Distribution (Wafer probing)
Monte Carlo simulation in statistical design kit
1-Sigma 38.7mV
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Resimulation Mismatch Process Variation
Monte Carlo simulation in statistical design kit
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Redesign
Monte Carlo simulation in statistical design kit
Evaluation of the circuit without statistical
models is possible - but takes a lot of
time. Monte Carlo Analysis with new statistical
design kit provides a fast insight in the
circuits behaviour at mismatch and process
variation. The conformity of measurement and
simulation is rather good
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Circuit improvements
Monte Carlo simulation in statistical design kit
- enlarge area factor at critical elements -
add base current compensation - decrease current
of differential amplifier to limit influence of
beta variation - limit influence of early effect
by cascode stages and dummy amps - revise the
complete channel topology and gain chain (omit
dummy OP stage)
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Redesignwithout dummy stagebut OP design
improved
Monte Carlo simulation in statistical design kit
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New Design Mismatch Process Variation
Monte Carlo simulation in statistical design kit
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Overview
Monte Carlo simulation in statistical design kit
DC Offset _at_ Opamp output (300 simulation
runs)
Simulation Measurement MM
Proc MMProc Wafer First Design
13.6 32.9 32.9mV
38.7mV New Design 6.3 0.8
5.9mV ?
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More Information
Monte Carlo simulation in statistical design kit
1 Kraus, W. PCM- and Physics-Based
Statistical BJT Modeling Using HICUM and
TRADICA, 6th HICUM Workshop, 2006 2 Schröter,
M., Wittkopf, H., Kraus, W. Statistical
modeling of high-frequency bipolar transistors,
Proc. BCTM, pp 54 - 61, 2005