LiveSense: A Real-Time Wi-Fi Sensing Platform for Range-Doppler on COTS Laptop

2026-03-06

AI Summary

This work proposes a high-precision, real-time sensing system leveraging commercial off-the-shelf (COTS) Wi-Fi 6E/7 laptop NICs (e.g., Intel AX211/BE201) to achieve centimeter-level ranging and Doppler estimation without disrupting normal communication. By efficiently extracting channel state information (CSI), performing time-phase alignment, applying self-interference cancellation, and executing Range-Doppler processing, the system simultaneously estimates target distance, radial velocity, and micro-motions—such as respiration and gestures—at a rate of at least 40 Hz within a 160 MHz bandwidth. To the best of our knowledge, this is the first demonstration of integrated communication and sensing on COTS Wi-Fi hardware, with real-time visualization of sensing results provided through a Python/Qt graphical user interface.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Computer Vision: Motion & Tracking
• Application Domains: Internet of Things, Sensor Networks & Smart Cities

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Security and Privacy: Large-scale security measurements
• Responsible Web: Measurement, analysis, and circumvention of Web censorship

Abstract

We present LiveSense - a cross-platform that transforms a commercial off-the-shelf (COTS) Wi-Fi Network Interface Card (NIC) on a laptop into a centimeter-level Range-Doppler sensor while preserving simultaneous communication capability. The laptops are equipped with COTS Intel AX211 (Wi-Fi 6E) or Intel BE201 (Wi-Fi 7) NICs. LiveSense can (i) Extract fully-synchronized channel state information (CSI) at>= 40 Hz, (ii) Perform time-phase alignment and self-interference cancellation on-device, and (iii) Provide a real-time stream of range, Doppler, subcarrier magnitude/phase and annotated video frames to a Python/Qt Graphical User Interface (GUI). The demo will showcase the ability to detect (i) Distance and radial velocity of attendees within a few meters of the device, (ii) Micro-motion (respiration), and (iii) Hand-gesture ranging. To the best of our knowledge, this is the first-ever demo to obtain accurate range information of targets from commercial Wi-Fi, despite the limited 160 MHz bandwidth.

Problem

• Wi-Fi sensing
• Range-Doppler
• COTS
• real-time
• channel state information

Innovation

• Wi-Fi sensing
• Range-Doppler estimation
• Channel State Information (CSI)
• COTS Wi-Fi NIC
• Real-time sensing