Empirical Analysis of LoRaWAN Adaptive Data Rate for Mobile Internet of Things Applications

Abstract

Built on top of the Long Range (LoRa) physical layer, the LoRa Wide-Area Network (LoRaWAN) protocol has recently emerged as one of the most promising Low-Power Wide-Area Network (LPWAN) technologies, for several Internet of Things (IoT) applications. LoRaWAN introduces the Adaptive Data Rate (ADR) mechanism, aiming to deliver a fair compromise between network performance and system reliability. ADR performs adaptive tuning of communication parameters, e.g., the Spreading Factor (SF), which is used to modulate the transmitted signals. Although the performance of ADR has been explored in conjunction with stationary End-Devices (EDs), little is known about its suitability for mobile IoT applications. In this paper, we investigate the performance of ADR in diverse mobility scenarios by leveraging a large amount of LoRaWAN experimental traces, collected in the urban area of Antwerp, Belgium. Using a data-driven statistical approach, we show that, whilst ADR enhances network reliability and coverage in low mobility settings, its beneficial effects decrease as mobility increases, hence calling for possible improvement and optimization.