Measurement using the N1010A FlexDCA software along with Option SIM which is the InfiniiSim
DCA waveform transformation software. The setup that we've got is a 10 gig signal PRBS 7
that is getting split into two through a splitter. One side of the splitter is connected
to channel 1, and that's what we're looking at right now. So it's a pretty open eye. And
the other side of that splitter is going through the same length of cable as that being used
on channel 1, but we are going through a four inch fixture which is made of FR4 material.
So it's a printed circuit board. I'm going to turn that on as well so we can see the
two signals laid on top of one another. And you can certainly see that channel 1, which
is in the yellow, is definitely, you know, better fidelity. It has faster rise time and
a more open eye-opening. If we, if we make a quick rise time measurement on channel 1,
and we'll go ahead and do the same thing on channel 2, you can see that channel 1 is about
20 picoseconds faster than channel 2. So you can definitely see that the fixture, the
FR4 is degrading the 10 gig signal. We're going to go into jitter mode and do an analysis
of jitter, a real deep dive on the components of jitter that are on channel 1. So you can
see that our source is channel 1. Jitter mode automatically detects the data rate and the
pattern length of the incoming signal. And it does a very fast and accurate analysis
of that signal. And it breaks the jitter down into its constituent components. We're going
to look at RJ and deterministic jitter. So RJ is the random jitter components of the
signal, and the DJ is the deterministic jitter component. And you can see the lower level
components of DJ. But we're just going to focus at the top level for the sake of this analysis,
this demonstration. So the RJ is just under 800 femtoseconds at about 780 femtoseconds
in this example. And the DJ is about 8 picoseconds. And using the dual Dirac model, we
are estimating total jitter at 10-12. And we're getting about 18.5 picoseconds. So
remember those numbers. We're going to go ahead and switch to channel 2. So this is
the signal, the 10 gig signal that is now passed through the FR4 section. And so we
would expect that the RJ is going to be the same or very similar because we're just going
through a passive device. And we would also expect that the bulk of the, the change is
as a result of increased data dependent jitter which part of the deterministic jitter, the
DJ bucket. So we'll let it complete its analysis. And you can see that it is very easy and very
fast to do this very complex measurement. And again, our random jitter, our RJ is just
under 800 femtoseconds at about 790. But our deterministic jitter is gone from 8.5 picoseconds
up to about 18.5 picoseconds. So it's increased by 10 picoseconds which is,
again, what we would expect because we're going through this lossy FR4 fixture. And
our TJ has increased from 18.5 to about 28.5 which is what, again, what we would expect.
So what we want to do is de-embed or remove the effects of that fixture. So we're going
to go into waveform signal processing and select the simulation tab. And we're going
to just do a basic insertion loss removal. Now this software does allow you to do more
complex de-embedding by taking into account source and load impedance. But we're going
to call up this block, this remove S2P block. I'm going to browse on my PC. And I'm
going to locate this S2P file called ET5580. That's the name of the fixture that I'm de-embedding.
And it's a discontinuity trace. And I'm going to turn on the output. So I'm going to drag
from the right-hand side the output. And remember, the input is on channel 2. So I'm dragging
channel 2 from the left onto my, my model. And so now I have on my input, I've got channel
2. Model is removing the S2P or the insertion loss of my discontinuity trace. And my output
is going to be on F1. Going to do an auto scale. And now you can see that my source
is F1 which is that de-embedded signal. Again, it auto detects the data rate and the pattern
length. And it separates jitter into its constituent components. Over on the right-hand side, you
can see that I'm actually doing an analysis in the amplitude domain as well. So it's possible
to look at timing impairments and as well as amplitude impairments. And my RJ, back
over on the left, is again just under 800 femtoseconds at about 760, 770 femtoseconds.
And my DJ is back at 8.5 picoseconds which is where it was for the channel 1 original
measurement. And my TJ is back at about 18.5 picoseconds. So I have effectively removed
that fixture, that FR4 fixture by using the de-embedding capability, or the de-convolution
in this case of InfiniiSim DCA. So let's summarize what we’ve seen in this short demo. The
total jitter on the 10 gig signal was estimated to be about 18.5 picoseconds. The same signal
was passed through an FR4 fixture. As expected, the fixture increased the DJ significantly.
The resultant TJ increased by about 10 picoseconds to around 28.5 picoseconds. The more
accurate your model, the more accurate a fixture can be de-embedded from a measurement.
In this case, the de-embedded channel 2 measurement correlates extremely well with channel 1.
Hopefully this has demonstrated that it's very easy and accurate to de-embed a signal
using InfiniiSim DCA.