Time Domain vs. Frequency Domain, What’s the Difference? – What the RF (S01E02)
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Time Domain vs. Frequency Domain, What’s the Difference? – What the RF (S01E02)


Today we will be discussing frequency
domain versus time domain. My name is- What’s up everyone? The name
is Nick Ben and I’m an engineer here at Keysight and welcome to this episode of
What the RF! In the last episode we discussed what a spectrum analyzer or signal analyzer
is and the various measurements you can make with it. Today we’ll go into more
detail about the difference between the frequency and time domain.
Alright, so previously we had briefly mentioned the time domain and frequency
domain but what exactly is the difference? And what about the frequency domain
tells us more about our signal? Lucky for us I have this set up here where I’m
sending the same signal into the oscilloscope and the signal analyzer. The
oscilloscope and signal analyzer are tools to visualize electrical signals in
the time and frequency domain respectively. As you may remember, an
oscilloscope displays signals with respect to time versus amplitude- or in
the time domain. Here we’re outputting a 10 MHz signal from the oscilloscope’s
waveform generator to channel one of the oscilloscope, and visually this is how it
appears on the oscilloscope, as a sinusoidal waveform with a period of
about 100 ns. Now if we were to adjust the output from the waveform generator
to a 20 MHz signal, then this is how it would look on the oscilloscope. Once again,
as a sinusoidal waveform with a period of about 50 ns. Basically the
higher the frequency, the more waves we see in the same span on our oscilloscope.
Now in my last video I got a question from one of you asking what the
advantage of a signal analyzer is if you’re already own an oscilloscope with
built-in FFT. Well I’m glad you asked! Signal analyzers have lower noise floors
this means they are much more sensitive to frequency components and are better
at showing you low-level signals. Signal analyzers also have better spurious free
dynamic range, or SFDR, than oscilloscopes. Alright so now we have
this signal analyzer and as you may remember signal analyzers display
signals with respect to frequency versus amplitude, or the frequency domain.
If we were to output the same 10 MHz signal from the waveform
generator that we had seen earlier on the oscilloscope to the analyzer, this is
how it would appear visually- just a single peak at 10 MHz. And if we
were to adjust the output of the waveform generator to be a 20 MHz signal,
then it would be a peak that appears at 20 MHz. So yeah, in the time domain
signals appear as sinusoidal waves and in the frequency domain they appear as a
distinct impulses. Ok well now this begs the question of “why the heck do we care
to use a signal analyzer?” Is it just to show a wave as a line or something? Well,
in a perfect world we would see the sinusoidal waveform like the ones we saw
on our oscilloscope at frequencies of 10 MHz and 20 MHz. Unfortunately
we don’t live in a perfect world. When dealing with various devices, it’s often
you see a not-so-perfect sine wave with many ripples, like this one that I’ve now
set up by feeding two sine waves from the waveform generator into the
oscilloscope. You can say that a real world signal can be represented as a sum
of different sinusoidal signals, rather different frequencies. Now let’s say
you’re designing a product and your product can only operate in a specified
bandwidth and it can’t be emitting in other bandwidths. Then you must determine
at what other frequencies do the other signals exist that are corrupting the
signal you want from your device. And that’s where our signal analyzers come
in they help separate and display this combination of different sinusoidal
signals into their distinct frequency components. So that if you’re expecting
your device to operate at let’s say 10 MHz you can see all the other
frequencies that are messing with your device- for example this 20 MHz
signal. And once that’s figured out you can use a band pass filter to tune out
those extra annoying signals you weren’t expecting. Alright that’s it for this
episode. Thank you so-

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