Abstract

Long-Range Wide-Area Network (LoRaWAN) technology offers efficient connectivity for numerous end devices over a wide coverage area in the Internet of Things (IoT) network, enabling the exchange of data over the Internet between even the most minor Internet-connected devices and systems. One of LoRaWAN’s hallmark features is the Adaptive Data Rate (ADR) algorithm. ADR is a resource allocation function which dynamically adjusts the network’s data rate, airtime, and energy dissipation to optimise its performance. The allocation of spreading factors plays a critical function in defining the throughput of the end device and its robustness to interference. However, in practical deployments, LoRaWAN networks experience considerable interference, severely affecting the packet delivery ratio, energy utilisation, and general network performance. To address this, we present a novel ADR framework, SSFIR-ADR, which utilises randomised spreading factor allocation to minimise energy consumption and packet collisions while maintaining optimal network performance. We implement a LoRa network composed of a single gateway that connects loads of end nodes to a network server. In terms of energy use, packet delivery rate, and interference rate (IR), our simulation implementation does better than LoRaWAN’s legacy ADR scheme for a range of application data intervals.

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