Live demo: playback of a real 256-subcarrier CSI heatmap

2026-10-11 · 2 min read

This playback uses a real capture (GL-MT6000 / MT7986, 5 GHz HE80, 256 subcarriers, 60 s), downsampled in the browser (348 frames x 64 subcarriers) so it plays smoothly. The raw data and capture method are published ^{[1] [2]}.

How to read it

Amplitude view (default)

• Time on the horizontal axis, subcarriers on the vertical; brighter means a larger amplitude for that subcarrier;
• a person walking produces vertical bright/dark bands (multipath disturbed); an empty still room flattens out;
• colours are normalised per subcarrier, so absolute values are not comparable across environments.

Doppler / time-frequency view

• the same data run through a short-time Fourier transform: vertical axis is Doppler 0 → Nyquist, brighter means more energy at that frequency;
• the Doppler colours are relative energy: a per-frequency stationary background is removed, then the result is percentile-normalised, so the view highlights energy that changes over time, not absolute power;
• motion energy concentrates at low frequencies (slow body sway, respiration-driven channel fluctuation), and idle stretches go dark overall;
• important limitation: this capture's CSI measurement rate is only about 5.8 measurements/s, so the observable Doppler range is only 0–2.87 Hz (Nyquist = rate / 2). That is enough for respiration and slow motion, but it is not a walking-Doppler spectrum — seeing walking-speed Doppler needs a much higher measurement rate or dedicated radar.

The green curve below is shown in both views: it is the motion metric (mean absolute change between consecutive measurements), a cheap "is anything moving?" signal.

Where this data comes from

Reproduce it yourself: router CSI guide · Python pipeline