Agilent Spectrum Analysis Basics - Agilent Technologies

Let’s first test the two previous extreme cases.
As NF PRE + G PRE – NF SA becomes less than –10 dB, we find that system noise
figure asymptotically approaches NF SA – G PRE . As the value becomes greater
than +15 dB, system noise figure asymptotically approaches NF PRE less 2.5
dB. Next, let’s try two numerical examples. Above, we determined that the
noise figure of our analyzer is 24 dB. What would the system noise figure be
if we add an Agilent 8447D, a preamplifier with a noise figure of about 8 dB
and a gain of 26 dB? First, NF PRE + G PRE – NF SA is +10 dB. From the graph
of Figure 5-5 we find a system noise figure of about NF PRE – 1.8 dB, or about
8 – 1.8 = 6.2 dB. The graph accounts for the 2.5 dB factor. On the other
hand, if the gain of the preamplifier is just 10 dB, then NF PRE + G PRE – N FSA
is –6 dB. This time the graph indicates a system noise figure of
NF SA – G PRE + 0.6 dB, or 24 – 10 + 0.6 = 14.6 dB 7 . (We did not introduce
the 2.5 dB factor previously when we determined the noise figure of the
analyzer alone because we read the measured noise directly from the display.
The displayed noise included the 2.5 dB factor.)
Many modern spectrum analyzers have optional built-in preamplifiers
available. Compared to external preamplifiers, built-in preamplifiers simplify
measurement setups and eliminate the need for additional cabling. Measuring
signal amplitude is much more convenient with a built-in preamplifier,
because the preamplifier/spectrum analyzer combination is calibrated as a
system, and amplitude values displayed on screen are already corrected for
proper readout. With an external preamplifier, you must correct the spectrum
analyzer reading with a reference level offset equal to the preamp gain. Most
modern spectrum analyzers allow you to enter the gain value of the external
preamplifier from the front panel. The analyzer then applies this gain offset
to the displayed reference level value, so that you can directly view corrected
measurements on the display.
Noise as a signal
So far, we have focused on the noise generated within the measurement
system (analyzer or analyzer/preamplifier). We described how the measurement
system’s displayed average noise level limits the overall sensitivity. However,
random noise is sometimes the signal that we want to measure. Because of
the nature of noise, the superheterodyne spectrum analyzer indicates a value
that is lower than the actual value of the noise. Let’s see why this is so and
how we can correct for it.
By random noise, we mean a signal whose instantaneous amplitude has
a Gaussian distribution versus time, as shown in Figure 5-6. For example,
thermal or Johnson noise has this characteristic. Such a signal has no discrete
spectral components, so we cannot select some particular component and
measure it to get an indication of signal strength. In fact, we must define
what we mean by signal strength. If we sample the signal at an arbitrary
instant, we could theoretically get any amplitude value. We need some
measure that expresses the noise level averaged over time. Power, which
is of course proportionate to rms voltage, satisfies that requirement.
7. For more details on noise figure, see Agilent
Application Note 57-1, Fundamentals of RF and
Microwave Noise Figure Measurements, literature
number 5952-8255E.
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