BLE channel model analysis for SARS-COV2 location and tracking applications

Mutual proximity and exposure time can provide critical information to assess the risk of propagation of highly contagious viruses such as SARS- CoV2. To this extent, Bluetooth Low Energy (BLE) represents the best candidate in the low range communication technologies to estimate the proximity distance between smartphones by means of ranging algorithm based on Received Signal Strength Indicator (RSSI) measurements. Although promising, the high variability of the radio propagation channel for ISM-band technologies suggests that a deep analysis of BLE is needed in order to isolate the different propagation factors. In this paper we show, through extensive measurements, the fluctuation of BLE channel in various environments and provide a ray tracing model to fully capture the BLE channel behavior. Results show how unpredictable BLE measurements become at increasing distances and under different positioning configurations, leading to misleading detections for contact tracing apps. A possible solution could be to introduce the use of mathematical models to capture core aspects of population mobility in order to estimate realistic exposure information.