11 | | There are many usage scenarios where these expanded buffer lengths are useful. One such usage scenario is monitoring channel activity. With over 3 seconds of received waveform at a full 40MHz of bandwidth, we can see both a large extent of channel activity at very fine timescales. One popular visualization of frequency content across time is known as a [http://en.wikipedia.org/wiki/Spectrogram spectrogram]. In this example, we will use this technique to visualize activity in the 2.4 GHz band. |
| 11 | There are many usage scenarios where these expanded buffer lengths are useful. One such usage scenario is monitoring channel activity. With over 3 seconds of received waveform at a full 40 MHz of bandwidth, we can see a large extent of channel activity at very fine timescales (25 ns samples). One popular visualization of frequency content across time is known as a [http://en.wikipedia.org/wiki/Spectrogram spectrogram]. In this example, we will use this technique to visualize activity in the 2.4 GHz band. |
| 12 | |
| 13 | MATLAB offers a sophisticated [http://www.mathworks.com/help/signal/ref/spectrogram.html spectrogram tool] as part of the Signal Processing Toolbox. Our simple implementation of a spectrogram in this example does not offer the same advanced features like windowing or FFT overlap. Instead, our implementation works by simply plotting the output of {{{M}}} sequential FFTs of {{{N}}} samples each. |