BLE-Based Contact Tracing: Characterization of Distance Estimation Errors and Mitigation Options

Contact tracing is an accepted means to keep track of human infection chains during epidemics. Contact tracing smartphone apps such as deployed during the recent COVID-19 pandemic are widely based on distance estimation by privacy-preserving use of Bluetooth Low Energy (BLE). Yet, the BLE received signal strength indicator used for distance estimation is too weakly correlated with the distance in real scenarios. Major impacting factors are varying body shielding and signal propagation characteristics of the environment. We present a method that adjusts the common BLE pathloss model with a context factor, which can be experimentally derived based on phone carry position and environment detection. Experiments with a smartphone testbed show that the distance estimation error can be reduced to about 1 m for four major carry positions in short-distance indoor and outdoor settings. This result is an encouraging first step towards reliable privacy-preserving contact tracing.