Abstract:
Long RangeWide Area Network (LoRaWAN) technology is rapidly expanding as a technology
with long distance connectivity, low power consumption, low data rates and a large number
of end devices (EDs) that connect to the Internet of Things (IoT) network. Due to the heterogeneity
of several applications with varying Quality of Service (QoS) requirements, energy is expended as
the EDs communicate with applications. The LoRaWAN Adaptive Data Rate (ADR) manages the
resource allocation to optimize energy efficiency. The performance of the ADR algorithm gradually
deteriorates in dense networks and efforts have been made in various studies to improve the algorithm’s
performance. In this paper, we propose a fuzzy-logic based adaptive data rate (FL-ADR)
scheme for energy efficient LoRaWAN communication. The scheme is implemented on the network
server (NS), which receives sensor data from the EDs via the gateway (GW) node and computes
network parameters (such as the spreading factor and transmission power) to optimize the energy
consumption of the EDs in the network. The performance of the algorithm is evaluated in ns-3 using
a multi-gateway LoRa network with EDs sending data packets at various intervals. Our simulation
results are analyzed and compared to the traditional ADR and the ns-3 ADR. The proposed FL-ADR
outperforms the traditional ADR algorithm and the ns-3 ADR minimizing the interference rate and
energy consumption.
