Multi-Dimensional Parameter Sweeps in ADS (14)
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In this section, we will learn about Multi-Dimensional Parameter Sweeps ADS, which can help us explore the impact of different parameter combinations on circuit performance.
So far, we have been performing simple S-parameter simulations. However, there are cases where we need to run sweeps on variables to examine the performance of a circuit.
First, we copy the TestBench we used previously and name the copy “TestBench_MyFilter_ParameterSweep”:
Open the copied schematic and delete unnecessary components, leaving only the S-parameter simulation controller and NETLIST INCLUDE.
First, we create a variable named “myL” to scan the inductance. To be close to reality, we set the Variable Value to 41 (no need to add units), and then click
We enter the sub-design and modify the L1 and C1 values to the variables we just defined (note the units):
Here we only put in two variables. In actual design, we can add or delete variables as needed.
The S-parameter simulation controller we placed previously uses frequency (freq) as the X-axis by default. Since our sweep variables this time are the values of capacitance and inductance, we need to select “Simulation-S_Param” in the Library Palettes and then select it
Then double-click
Then we select the “Simulations” tab and connect it to the existing simulator. We have previously created an S-parameter simulation called “SP1”, so we fill in “SP1” and click “Apply”.
Then click
Then we can see that the simulation results we get are a cluster of curves, each corresponding to a different inductance value:
Because we also defined the variable myC, we can create a nested loop to sweep. In this case, we duplicate a PARAMETER SWEEP and change “SweepVar” to “myC”. To create a nested loop, we need to connect them. We change “SiminstanceName[1]” of Sweep2 to “Sweep1”. We set the range of myC to 5-50:
Double-click the two PARAMETER SWEEPs, and we can see that the number of steps is 19, so we need to perform 19*19=361 simulations in total. Click
All data combinations are presented in the plot.
Next article: ADS Tutorial (XV) Multi-Dimensional Data Processing in ADS