Riccardo Bersan

2papers

2 Papers

2.3NIApr 27, 2022
Wireless LAN sensing with smart antennas

Marco Santoboni, Riccardo Bersan, Stefano Savazzi et al.

The paper targets the problem of human motion detection using Wireless Local Area Network devices (WiFi) equipped with pattern reconfigurable antennas. Motion sensing is obtained by monitoring the body-induced alterations of the ambient WiFi signals originated from smart antennas supporting the beam-steering technology, thus allowing to channelize the antenna radiation pattern to pre-defined spots of interest. We first discuss signal and Channel State Information (CSI) processing and sanitization. Next, we describe the motion detection algorithm based on Angle-of-Arrival (AoA) monitoring. Proposed algorithms are validated experimentally inside a large size smart home environment.

2.0SPJun 15
WiFi-Based People Counting Using Beam-Steerable Antennas: A Test-bed Study

Riccardo Bersan, Anay Ajit Deshpande, Sanaz Kianoush et al.

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.