Abstract:
Long-Range Wide Area Network (LoRaWAN) is a fast-growing communication system for
Low Power Wide Area Networks (LPWAN) in the Internet of Things (IoTs) deployments. LoRaWAN
is built to optimize LPWANs for battery lifetime, capacity, range, and cost. LoRaWAN employs
an Adaptive Data Rate (ADR) scheme that dynamically optimizes data rate, airtime, and energy
consumption. The major challenge in LoRaWAN is that the LoRa specification does not state how
the network server must command end nodes pertaining rate adaptation. As a result, numerous
ADR schemes have been proposed to cater for the many applications of IoT technology, the quality of
service requirements, di erent metrics, and radio frequency (RF) conditions. This o ers a challenge
for the reliability and suitability of these schemes. This paper presents a comprehensive review
of the research on ADR algorithms for LoRaWAN technology. First, we provide an overview of
LoRaWAN network performance that has been explored and documented in the literature and then
focus on recent solutions for ADR as an optimization approach to improve throughput, energy
e ciency and scalability. We then distinguish the approaches used, highlight their strengths and
drawbacks, and provide a comparison of these approaches. Finally, we identify some research gaps
and future directions.
