Abstract
A Long-Range Wide Area Network (LoRaWAN) is one of the most efficient technologies and is widely adopted for the Internet of Things (IoT) applications. The IoT consists of massive End Devices (EDs) deployed over large geographical areas, forming a large environment. LoRaWAN uses an Adaptive Data Rate (ADR), targeting static EDs. However, the ADR is affected when the channel conditions between ED and Gateway (GW) are unstable due to shadowing, fading, and mobility. Such a condition causes massive packet loss, which increases the convergence time of the ADR. Therefore, we address the convergence time issue and propose a novel ADR at the network side to lower packet losses. The proposed ADR is evaluated through extensive simulation. The results show an enhanced convergence time compared to the state-of-the-art ADR method by reducing the packet losses and retransmission under dynamic mobile LoRaWAN network.
Highlights
Low Power Wide Area Networks (LPWANs) are one of the widely adopted technologies for the Internet of Things (IoT)
The underlying Adaptive Data Rate (ADR) of Long-Range Wide Area Network (LoRaWAN) is suggested for the static End Devices (EDs) [6] and performs inefficiently when the EDs are mobile due to the variation in the signal strength caused by the ED movement, resulting in low Packet Delivery Ratio (PDR) and convergence time issues
The simulation results showed that the proposed ADR is efficient at reducing convergence time and energy consumption
Summary
Low Power Wide Area Networks (LPWANs) are one of the widely adopted technologies for the Internet of Things (IoT) They offer long-range and multi-year battery life with low cost solutions. The underlying ADR of LoRaWAN is suggested for the static EDs [6] and performs inefficiently when the EDs are mobile due to the variation in the signal strength caused by the ED movement, resulting in low Packet Delivery Ratio (PDR) and convergence time issues. This situation occurs when EDs try to retransmit a lost packet, leading to massive interference.
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