Abstract
This paper presents a measurement-based analysis of the Received Signal Strength (RSS) of Bluetooth Low Energy (BLE) signals, under Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) scenarios, performed in tandem at two universities in Tampere, Finland, and Bucharest, Romania. We adopted the same hardware and methodology for measurements in both places, and paid particular attention to the impact of RSS on various environmental factors, such as LOS and NLOS scenarios and interference in 2.4 GHz band. In addition, we considered the receiver orientation and the different frequencies of BLE advertising channels. We show that snapshot RSS measurements typically have high variability, not easily explainable by classical path-loss models. A snapshot recording is defined here as one continuous recording at fixed device locations in a static setup. Our observations also show that aggregated RSS data (i.e., considering several snapshot measurements together) is more informative from a statistical point of view and more in agreement with current theoretical path-loss models than snapshot measurements. However, in BLE applications such as contact tracing and proximity detection, the receivers typically have access only to snapshot measurements (e.g., taken over a short duration of 10–20 minutes or less), so the accuracy of contact-tracing and proximity detection can be highly affected by RSS instabilities. In addition to presenting the measurement-based BLE RSS analysis in a comprehensive and well-documented format, our paper also emphasizes open challenges when BLE RSS is used for contact tracing, ranging, and positioning applications.
Highlights
AND MOTIVATIONProximity-based application have become increasingly popular in recent years
received signal strength (RSS) measurements from any wireless signal (BLE, Wi-Fi, cellular, etc.) are known to fluctuate due to the presence and movement of people in the signal’s path [10], the presence of multipath [11], the switches between carrier frequencies of sub-channels used in the transmitted signal [11], the antenna polarization [12], the orientation of the transmitter (TX) and receiver (RX) [13], [14], and the chipset model [15]
This paper offers a comprehensive analysis of Bluetooth Low-Energy (BLE) RSS instabilities, fluctuations, and challenges in BLE-based proximity detection and contact tracing
Summary
Proximity-based application have become increasingly popular in recent years. Estimating the distance between two devices can be used to find lost objects, to share files between nearby devices, to enable smart homes to react to owners’ location, or to fight against a pandemic. Offering an extensive measurement-based analysis of BLE RSS fluctuations and showing that current singleslope path-loss models from the literature do not capture these effects. Analyzing the effect of BLE advertising channels on RSS fluctuations and showing that the aggregated RSS from all BLE advertising channels has significantly higher fluctuations than on individual BLE channels This is an important challenge in current BLE-based proximity apps, where channel information is usually not available;. Based on our state-of-the-art review (Section II), we believe that these high BLE RSS fluctuations have not yet been reported and documented to their full extent in the current literature and that there are still several challenges to be overcome when dealing with snapshot BLE RSS measurements, as those used in contact-tracing and proximity detection applications. This paper documents BLE RSS fluctuations and raises several research questions about the applicability of classical path-loss models in the LOS and NLOS propagation of BLE signals
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