Uploaded by AgilentEEsof on 18.02.2010

Transcript:

Hello and welcome to another presentation and demo on design for manufacturing in ADS,

but this one is going to be on sensitivity analysis.

This slide represents the DFM design process for MMIC, and you can see once you start your

design, start your nominal design here, usually designers, the next step they optimize their

design. What I’m showing here, once you have the setup, the circuit setup to be optimized,

you can automatically access the sensitivity analysis tool. It takes a few seconds to get

a fast response or a fast analysis on the sensitivity of the components in your design.

So let’s see how sensitivity analysis works in ADS.

Basically in ADS sensitivity analysis what it does, it takes one component at a time

in your design. For example, here if we have a capacitor C1 what sensitivity analysis does

is it increases the capacitor C1 to C1 prime. And C1 prime is one times E-6 larger than

C1. So it increases the component by a very, very small factor, which is one times E-6,

one times 10 to the -6 of the nominal value, and by doing this it will look for the response,

what is the gain? What is the return loss? What is the noise figure, whatever you’re

looking for.

So it looks for the response at the nominal value and it also looks at the response of

the circuit at the new value, which is one times ten to the minus six of the nominal

value. And you can see the difference in the response, we represent it with delta R, and

the difference in the component value, which is delta C here. So basically the sensitivity

is calculated to be delta R divided by delta C, and this is the amount of change you get

in the response relative to that little amount, one times ten to the minus six factor, of

the component value. Okay?

So I just want to mention here that sensitivity analysis is local. It’s localized. That

means it is taken at one component at a time regardless of the interaction of the other

components. We just take resistor R, do the sensitivity analysis only on that resistor,

then we do capacitor, then we do the other components. But not all together varying,

so it’s localized, okay, to kind of give you a quick analysis on the sensitivity of

that part.

I want to mention, in the previous video, we have other videos and presentations on

yield sensitivity histograms, all the parts vary at the same time and it gives you much

more meaningful results on the sensitivity of that component relative to everything moving

at the same time. But sensitivity analysis again is localized, it’s done on one component

at a time. But it’s really quick, in a few seconds you can access that, you can simulate

it. In like a few seconds you get an idea of how sensitive these components are. But

I do recommend to use the yield sensitivity histograms and the design of experiments to

make a full understanding of the behavior of your design for manufacturing.

So here’s an example of a run in ADS. Notice here I have the input matching network capacitor

C1, I have the interstage matching network capacitor C8 and C4, and I have the output

matching network capacitor C6 and C7, and I’m looking here at the S22 spec. Notice

that C1 input matching network and C8 interstage matching network has no effect, no sensitivity

to the output return loss. But as we move closer to the output matching network we find

out C4, which is close to the output matching network, it’s in the interstage matching

network, has a little effect sensitivity to the S22. But the biggest sensitivity is coming

from the capacitor in the output matching network, which makes sense.

So C6 is the red X component here, or the sensitive part, and C7, which might be a big

huge bypass capacitor, had no effect because it’s a big capacitor just for bypassing

purposes. So this is how you can tell, you list the components on the X-axis and you

list the measure you’re looking at on the Y-axis, and just visually you can see clearly

what component is more sensitive than another.

One thing I want to mention in ADS when you do sensitivity analysis you can access two

types of analysis, two types of results. We have the absolute sensitivity and we have

the normalized sensitivity, but they both give you a different meaning to the sensitivity.

And I do have a document written specifically to explain the difference between absolute

sensitivity and normalized sensitivity, please feel free to access that by asking for it

from the Agilent representative. But let me illustrate to you in the next slide normalized

sensitivity calculation is more meaningful to designers.

I’m a designer and always, 99% of the time I always access the normalized sensitive analysis.

I recommend that you use it because basically what it does (skip in tape) the results have

more meanings to you. It gives you the percent change in the response versus a 1% change

in the component value. It’s all normalized, you have many components for every 1% change

in that component value you can see the percent change in the response; in the gain, in the

noise figure, in the power output. So this is normalized, it’s very easy to compare

which component is sensitive more than another component.

In the absolute sensitivity calculations what ADS calculates or gives you, it gives the

change in the response, like the change in the gain for example, versus one unit change

in the component value. If you have a 10-ohm resistor, for one unit change, for 11 ohm,

from 10 to 11 ohms what is the gain change? But be careful when you compare apples with

apples here, when you compare the units. This is why I recommend the normalized sensitivity

calculation, it’s all normalized to percent change in the component value so you can really

compare, you can compare the analysis, sensitivity analysis relative to all components equally

because they're all changed by the same factor, percent.

So let me now show you a demo using ADS. Okay, so let’s go to ADS (skip in tape) the same

LNA, the KU band LNA design I used in the other demos, the design of experiments and

the yield sensitivity histogram demo. By the way, this project is available in ADS examples

directory under microwave circuits, it is the KU band LNA DFM circuit. So you can access

it and simulate it yourself.

But again this is the input matching network and this is the interstage or the FET structure,

here is the resistor lines in the FET. And here’s the output matching network, the

output port, the DC port which takes the voltage supply, DC port. So as I said before, designers

usually go through the nominal design followed by optimization. So notice here –

but this one is going to be on sensitivity analysis.

This slide represents the DFM design process for MMIC, and you can see once you start your

design, start your nominal design here, usually designers, the next step they optimize their

design. What I’m showing here, once you have the setup, the circuit setup to be optimized,

you can automatically access the sensitivity analysis tool. It takes a few seconds to get

a fast response or a fast analysis on the sensitivity of the components in your design.

So let’s see how sensitivity analysis works in ADS.

Basically in ADS sensitivity analysis what it does, it takes one component at a time

in your design. For example, here if we have a capacitor C1 what sensitivity analysis does

is it increases the capacitor C1 to C1 prime. And C1 prime is one times E-6 larger than

C1. So it increases the component by a very, very small factor, which is one times E-6,

one times 10 to the -6 of the nominal value, and by doing this it will look for the response,

what is the gain? What is the return loss? What is the noise figure, whatever you’re

looking for.

So it looks for the response at the nominal value and it also looks at the response of

the circuit at the new value, which is one times ten to the minus six of the nominal

value. And you can see the difference in the response, we represent it with delta R, and

the difference in the component value, which is delta C here. So basically the sensitivity

is calculated to be delta R divided by delta C, and this is the amount of change you get

in the response relative to that little amount, one times ten to the minus six factor, of

the component value. Okay?

So I just want to mention here that sensitivity analysis is local. It’s localized. That

means it is taken at one component at a time regardless of the interaction of the other

components. We just take resistor R, do the sensitivity analysis only on that resistor,

then we do capacitor, then we do the other components. But not all together varying,

so it’s localized, okay, to kind of give you a quick analysis on the sensitivity of

that part.

I want to mention, in the previous video, we have other videos and presentations on

yield sensitivity histograms, all the parts vary at the same time and it gives you much

more meaningful results on the sensitivity of that component relative to everything moving

at the same time. But sensitivity analysis again is localized, it’s done on one component

at a time. But it’s really quick, in a few seconds you can access that, you can simulate

it. In like a few seconds you get an idea of how sensitive these components are. But

I do recommend to use the yield sensitivity histograms and the design of experiments to

make a full understanding of the behavior of your design for manufacturing.

So here’s an example of a run in ADS. Notice here I have the input matching network capacitor

C1, I have the interstage matching network capacitor C8 and C4, and I have the output

matching network capacitor C6 and C7, and I’m looking here at the S22 spec. Notice

that C1 input matching network and C8 interstage matching network has no effect, no sensitivity

to the output return loss. But as we move closer to the output matching network we find

out C4, which is close to the output matching network, it’s in the interstage matching

network, has a little effect sensitivity to the S22. But the biggest sensitivity is coming

from the capacitor in the output matching network, which makes sense.

So C6 is the red X component here, or the sensitive part, and C7, which might be a big

huge bypass capacitor, had no effect because it’s a big capacitor just for bypassing

purposes. So this is how you can tell, you list the components on the X-axis and you

list the measure you’re looking at on the Y-axis, and just visually you can see clearly

what component is more sensitive than another.

One thing I want to mention in ADS when you do sensitivity analysis you can access two

types of analysis, two types of results. We have the absolute sensitivity and we have

the normalized sensitivity, but they both give you a different meaning to the sensitivity.

And I do have a document written specifically to explain the difference between absolute

sensitivity and normalized sensitivity, please feel free to access that by asking for it

from the Agilent representative. But let me illustrate to you in the next slide normalized

sensitivity calculation is more meaningful to designers.

I’m a designer and always, 99% of the time I always access the normalized sensitive analysis.

I recommend that you use it because basically what it does (skip in tape) the results have

more meanings to you. It gives you the percent change in the response versus a 1% change

in the component value. It’s all normalized, you have many components for every 1% change

in that component value you can see the percent change in the response; in the gain, in the

noise figure, in the power output. So this is normalized, it’s very easy to compare

which component is sensitive more than another component.

In the absolute sensitivity calculations what ADS calculates or gives you, it gives the

change in the response, like the change in the gain for example, versus one unit change

in the component value. If you have a 10-ohm resistor, for one unit change, for 11 ohm,

from 10 to 11 ohms what is the gain change? But be careful when you compare apples with

apples here, when you compare the units. This is why I recommend the normalized sensitivity

calculation, it’s all normalized to percent change in the component value so you can really

compare, you can compare the analysis, sensitivity analysis relative to all components equally

because they're all changed by the same factor, percent.

So let me now show you a demo using ADS. Okay, so let’s go to ADS (skip in tape) the same

LNA, the KU band LNA design I used in the other demos, the design of experiments and

the yield sensitivity histogram demo. By the way, this project is available in ADS examples

directory under microwave circuits, it is the KU band LNA DFM circuit. So you can access

it and simulate it yourself.

But again this is the input matching network and this is the interstage or the FET structure,

here is the resistor lines in the FET. And here’s the output matching network, the

output port, the DC port which takes the voltage supply, DC port. So as I said before, designers

usually go through the nominal design followed by optimization. So notice here –