OFDM channel estimation is the process of measuring and characterizing the frequency-selective wireless channel across the individual subcarriers of an Orthogonal Frequency Division Multiplexing (OFDM) transmission, typically by comparing received pilot or preamble signals against known reference sequences to extract per-subcarrier amplitude and phase information, collectively known as Channel State Information (CSI). This process is fundamental to Wi-Fi sensing research because the resulting CSI captures fine-grained multipath propagation effects that reflect how the physical environment — including the presence, position, and motion of people or objects — shapes the wireless signal, enabling passive, infrastructure-light sensing without dedicated hardware. Key variants differ in how and where estimation is performed: some approaches leverage standard 802.11 preamble-based estimation as implemented in commercial chipsets (as exploited by tools like the nexmon CSI Extractor), while others involve custom firmware modifications, software-defined radio pipelines, or post-processing corrections to recover CSI with higher fidelity, fewer hardware artifacts, or greater reproducibility across platforms and experimental conditions.

Source Papers

  • A survey on CSI-based Wi-Fi sensing datasets and models with a focus on reproducibility — A survey on CSI-based Wi-Fi sensing datasets and models with
  • Enabling ISAC on Low-Cost Devices via Spatial-Channel Estimation With a Single-RF Chain — Enabling ISAC on Low-Cost Devices via Spatial-Channel Estima
  • Free Your CSI — Free Your CSI
  • NeRF2: Neural Radio-Frequency Radiance Fields — NeRF2: Neural Radio-Frequency Radiance Fields
  • OPERAnet, a multimodal activity recognition dataset acquired from radio frequency and vision-based sensors — OPERAnet, a multimodal activity recognition dataset acquired
  • Radio Radiance Field: The New Frontier of Spatial Wireless Channel Representation — Radio Radiance Field: The New Frontier of Spatial Wireless C
  • Tool release — Tool release
  • Wi-CaL: WiFi Sensing and Machine Learning Based Device-Free Crowd Counting and Localization — Wi-CaL: WiFi Sensing and Machine Learning Based Device-Free