Rethinking RSSI for WiFi Sensing

TL;DR

This paper introduces WiRSSI, a WiFi sensing framework that uses RSSI signals for passive human tracking and gesture recognition, challenging the notion that RSSI is too coarse for fine-grained sensing.

Contribution

WiRSSI demonstrates how RSSI can be exploited for motion sensing and localization by extracting Doppler, AoA, and delay cues without relying on detailed CSI data.

Findings

Achieves median localization errors below 1 meter in various trajectories.

Enables meaningful gesture recognition using RSSI features.

Shows RSSI can support practical sensing when CSI is unavailable or privacy-sensitive.

Abstract

The Received Signal Strength Indicator (RSSI) is ubiquitously available on commodity WiFi devices but is commonly regarded as too coarse for fine-grained sensing. This paper revisits its sensing potential and presents WiRSSI, a bistatic WiFi sensing framework that enables RSSI-only passive human tracking and motion sensing. WiRSSI employs a transmitter and a receiver equipped with a three-antenna array (1Tx-3Rx), and is readily extensible to Multiple-Input Multiple-Output (MIMO) deployments. We first show how Channel State Information (CSI) power implicitly preserves phase-related motion modulation and how this relationship carries over to RSSI, indicating that RSSI can retain exploitable Doppler, Angle-of-Arrival (AoA), and delay cues. WiRSSI extracts Doppler-AoA features via a lightweight 2D Fast Fourier Transform (FFT) pipeline and infers bistatic delay from amplitude-only information in the absence of subcarrier-level phase. The estimated AoA and delay are then mapped to Cartesian coordinates and denoised to recover motion trajectories. Experiments in practical environments show that WiRSSI achieves median XY localization errors of 0.905 m, 0.784 m, and 0.785 m for elliptical, linear, and rectangular trajectories, respectively, compared with 0.574 m, 0.599 m, and 0.514 m from a representative CSI-based method. We further demonstrate RSSI-only gesture recognition on the Widar3.0 dataset, where WiRSSI features provide meaningful discriminative performance. These results suggest that, despite lacking subcarrier-level information compared with CSI, RSSI can support practical WiFi sensing as a complementary and hardware-friendly option when CSI is restricted, unreliable, or privacy-sensitive.