Distance Estimation for BLE-based Contact Tracing -- A Measurement Study

TL;DR

This study evaluates Bluetooth Low Energy's (BLE) accuracy for contact tracing through a measurement study, revealing its limitations and potential in detecting close contacts despite inherent inaccuracies.

Contribution

The paper provides a comprehensive measurement analysis of BLE-based distance estimation, comparing models and UWB benchmarks to understand its practical effectiveness for contact tracing.

Findings

BLE distance estimation is not highly accurate but can detect contacts below 2.5 m.

Logarithmic model yields a higher true positive rate (0.65) than linear (0.54).

Multi-path propagation improves indoor detection accuracy.

Abstract

Mobile contact tracing apps are -- in principle -- a perfect aid to condemn the human-to-human spread of an infectious disease such as COVID-19 due to the wide use of smartphones worldwide. Yet, the unknown accuracy of contact estimation by wireless technologies hinders the broader use. We address this challenge by conducting a measurement study with a custom testbed to show the capabilities and limitations of Bluetooth Low Energy (BLE) in different scenarios. Distance estimation is based on interpreting the signal pathloss with a basic linear and a logarithmic model. Further, we compare our results with accurate ultra-wideband (UWB) distance measurements. While the results indicate that distance estimation by BLE is not accurate enough, a contact detector can detect contacts below 2.5 m with a true positive rate of 0.65 for the logarithmic and of 0.54 for the linear model. Further, the measurements reveal that multi-path signal propagation reduces the effect of body shielding and thus increases detection accuracy in indoor scenarios.