An Improved Spread Factor Assignment Method for Large-Scale LoRaWAN Deployments in IoT

摘要

Long-range communication is a major requirement for large-scale IoT deployments and LoRaWAN is one of the widely adopted low-power wide area network solutions used for IoT connectivity. Although LoRaWAN advantages from simplicity and flexibility in deployment and operation, it suffers from collisions that limit the scalability of the network because of its random access nature and large time-bandwidth product. In this paper, we model a network in which nodes select the spread factor parameter and start transmitting in an ALOHA based manner. We have shown that when the number of nodes transmitting periodically increases, collision becomes a serious challenge in the network which limits the scalability of the technology. We then propose a metaheuristic method for the selection of spread factors in the network to address this problem. The results show that using the proposed method, packet drop rate can be improved by 42% in low-density networks and up to 8% in the worst case for a scenario with thousands of nodes.