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Improving the Convergence Period of Adaptive Data Rate in a Long Range Wide Area Network for the Internet of Things Devices

doi: 10.3390/en14185614
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.
- Abbottabad University of Science and Technology Pakistan
- Qurtuba University of Science and Information Technology Pakistan
- King Saud University Saudi Arabia
- Gachon University Korea (Republic of)
- Gachon University Korea (Republic of)
Technology, adaptive data rate, energy consumption, T, Internet of Things, interference, adaptive data rate; convergence time; energy consumption; Internet of Things; interference; LoRaWAN; mobility; retransmissions; resource allocation, convergence time, LoRaWAN
Technology, adaptive data rate, energy consumption, T, Internet of Things, interference, adaptive data rate; convergence time; energy consumption; Internet of Things; interference; LoRaWAN; mobility; retransmissions; resource allocation, convergence time, LoRaWAN
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