EARN: Enhanced ADR With Coding Rate Adaptation in LoRaWAN

As low-power wide-area (LPWA) networks emerge as a cost-effective choice of technologies for city-wide Internet-of-Things (IoT) applications, LoRaWAN, one of the most promising unlicensed band techniques, has received much attention from academia. LoRaWAN presents a set of tunable transmission parameters, along with an adaptive data rate (ADR) mechanism, to promote the best performance under the variable link state. But the performance of ADR, whose design neglects the complex correlation between such parameters, is yet to be practical in terms of both efficiency and scalability. In this article, we derive theoretical performance models of class A unconfirmed-mode LoRaWAN, focusing on the impact of coding rate (CR), a parameter that has not been explored in prior researches. Then, we present EARN, an enhanced greedy ADR mechanism with CR adaptation, to optimize the tradeoff between delivery ratio and energy consumption. In EARN design, we leverage the capture effect to increase the survival rate of colliding signals and introduce a concept of adaptive SNR margin to endure noisy link states. We validate our models and the feasibility of the CR adaptation with an empirical study, and large-scale simulations reveal that our method outperforms the conventional schemes.