
91
Software Defined Radio
oscillator carriers at 0 and -90 degrees and then combines the result, as
shown in Fig 7.5. This makes for a very elegant modulation system that
can handle a huge range of operat-
ing modes at any carrier frequency.
When it comes to reception
with SDR systems, IQ data is the
vital ingredient, as monitoring the
change in IQ values over time will
reveal the modulating message,
regardless of whether it’s a form of
AM, FM, PM or a combination of all
three, thus providing a simple multi-
mode demodulator.
Fast Fourier Transforms
Another important process in the development of SDR and digital signal
processing in general, has been the use of Fast Fourier Transforms (FFT)
to analyse sampled data streams from the ADC. One of the great
operational benefits of practical SDRs is the presentation of band
segments in spectrum analyser style. This enables the operator to
quickly locate active stations within a band and to use the click of the
mouse to tune to that station. Converting the sampled data stream into
a spectrum analyser format is handled by the FFT, so let’s take a quick,
non-mathematical look at how this works.
The FFT is an ingenious mathematical algorithm that can examine
a stream of sampled data from an ADC and separate the stream into its
component frequencies. It does this by dividing a section of the sam-
pled data into a number of bins (containers) each of which contains a
narrow band of frequencies – see Fig 7.6. It then measures the energy in
each bin and it is this data that’s used to feed the spectrum display or
drive other facilities. The size of each bin is dependent on the sample
rate of the digital signal and the number of bins used by the FFT. When
using FFT to analyse an audio signal we might typically have a sample
rate of, say, 44kHz – so that it can accurately capture frequencies as
Fig 7.5: Transmit
up-converter for
baseband IQ
data.
Fig 7.6:
Illustration of
using FFTs to
convert data
samples to FFT
frequency bins.
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