The Fast Fourier Transform (FFT) is a computationally efficient algorithm for converting time-domain or spatial-domain signals into their frequency-domain representations, decomposing a signal into its constituent frequency components. In WiFi/CSI sensing, FFT is applied to raw CSI amplitude and phase data to extract frequency-domain features that capture periodic motion patterns — such as the rhythmic movements characteristic of gestures or the subtle environmental disturbances caused by occupants — which are difficult to discern in the time domain. Key variants relevant to this field include the Short-Time Fourier Transform (STFT), which applies FFT over sliding temporal windows to capture time-varying spectral content, and the Inverse FFT (IFFT), which is used in channel reconstruction or noise filtering pipelines to transform processed frequency-domain data back into the time or spatial domain.
Source Papers
- A Survey on Green Wireless Sensing: Energy-Efficient Sensing via WiFi CSI and Lightweight Learning ↗ — A Survey on Green Wireless Sensing: Energy-Efficient Sensing
- An Overview on IEEE 802.11bf: WLAN Sensing ↗ — An Overview on IEEE 802.11bf: WLAN Sensing
- Deep Learning-Enhanced Human Sensing with Channel State Information: A Survey ↗ — Deep Learning-Enhanced Human Sensing with Channel State Info
- Device-Free Passive Identity Identification via WiFi Signals ↗ — Device-Free Passive Identity Identification via WiFi Signals
- Device-Free Wireless Sensing for Gesture Recognition Based on Complementary CSI Amplitude and Phase ↗ — Device-Free Wireless Sensing for Gesture Recognition Based o
- Device-free occupancy detection and crowd counting in smart buildings with WiFi-enabled IoT ↗ — Device-free occupancy detection and crowd counting in smart
- FreeCount: Device-Free Crowd Counting with Commodity WiFi ↗ — FreeCount: Device-Free Crowd Counting with Commodity WiFi
- Human Activity Recognition via Wi-Fi and Inertial Sensors With Machine Learning ↗ — Human Activity Recognition via Wi-Fi and Inertial Sensors Wi
- MMCOUNT: Stationary Crowd Counting System Based on Commodity Millimeter-Wave Radar ↗ — MMCOUNT: Stationary Crowd Counting System Based on Commodity
- OPERAnet, a multimodal activity recognition dataset acquired from radio frequency and vision-based sensors ↗ — OPERAnet, a multimodal activity recognition dataset acquired
- Passive WiFi Radar for Human Sensing Using a Stand-Alone Access Point ↗ — Passive WiFi Radar for Human Sensing Using a Stand-Alone Acc
- Time matters: Empirical insights into the limits and challenges of temporal generalization in CSI-based Wi-Fi sensing ↗ — Time matters: Empirical insights into the limits and challen
- Towards Environment Independent Device Free Human Activity Recognition ↗ — Towards Environment Independent Device Free Human Activity R
- WiFi Sensing with Channel State Information ↗ — WiFi Sensing with Channel State Information