WiFi-Based People Counting Using Beam-Steerable Antennas: A Test-bed Study

2026-06-15

AI Summary

This study addresses the challenge of high-accuracy, non-intrusive indoor occupancy counting by proposing a novel approach that integrates Wi-Fi 7 with beam-steerable antennas. Leveraging the fine-grained channel state information (CSI) extracted from 160/320 MHz wideband OFDM signals, the method combines MIMO antenna arrays and beamforming techniques to precisely estimate the channel impulse response and resolve multipath characteristics, thereby detecting changes in the number of occupants. This work is the first to synergize beam-steerable antennas with Wi-Fi 7, enabling robust multi-person counting in real-world environments and revealing the distinctiveness of individual-induced wireless signal perturbations. Experimental results demonstrate that the system significantly enhances counting accuracy and stability under complex indoor conditions.

Abstract

Ubiquitous perception through RF signals is a pivotal opportunity for future technology: it enables personalized services such as smart living, remote healthcare, automated logistics or interaction through free-space gestures. The ubiquity of Wi-Fi and cellular networks presents a promising platform for the development of innovative sensing tools. Future standards will also introduce dedicated sensing features which, for example, will allow routers to work as frequency modulated continuous wave radios targeting radar applications. Most of the current chip designs support ad-hoc firmware for CSI extraction with MIMO arrangements of the transmitter (TX) and receiver (RX) antennas and OFDM subcarriers. The CSI describes the phase shift and amplitude attenuation of multiple propagation paths on each subcarrier. The latest IEEE 802.11be standard (Wi-Fi 7) offers a wider subcarrier bandwidth of 160MHz (up to 320MHz), providing at least 120 usable pilot subcarriers for CSI or CIR estimation. Additionally, Wi-Fi signals have been recently exploited to track daily human movements and behaviors, while Wi-Fi signal variations have been shown to differ between different people and can consequently be used for their re-identification.

Problem

• WiFi-based sensing
• people counting
• channel state information
• ubiquitous perception
• human re-identification

Innovation

• beam-steerable antennas
• Wi-Fi sensing
• channel state information (CSI)
• people counting
• IEEE 802.11be