Field Guide · term

Also known as: Nyquist theorem, sampling theorem

The Nyquist–Shannon sampling theorem states that to represent a signal without loss you must sample at least twice its bandwidth.1 For IQ sampling, the practical takeaway is that usable bandwidth ≈ sample rate.

too few samples → a false (aliased) low-frequency wave
Nyquist: sample at least twice the bandwidth, or fast signals fold back as false low-frequency aliases.

How it works

Sample too slowly for the bandwidth and information does not merely vanish — it corrupts the data through aliasing, folding out-of-band energy to false frequencies.

Relevance to SDR

It is named for Harry Nyquist and Claude Shannon, and it sets the floor on the sample rate needed to capture a given channel.

Sources

  1. Nyquist–Shannon sampling theorem — Wikipedia, on the minimum sampling rate for lossless representation. ↩

See also

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