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LoRaWAN (Long Range Wide Area Network) is emerging as an attractive networkinfrastructure for ultra low power Internet of Things devices. Even if thetechnology itself is quite mature and specified, the currently deployedwireless resource allocation strategies are still coarse and based on roughheuristics. This paper proposes an innovative "sequential waterfilling"strategy for assigning Spreading Factors (SF) to End-Devices (ED). Our designrelies on three complementary approaches: i) equalize the Time-on-Air of thepackets transmitted by the system's EDs in each spreading factor's group; ii)balance the spreading factors across multiple access gateways, and iii) keepinto account the channel capture, which our experimental results show to bevery substantial in LoRa. While retaining an extremely simple and scalableimplementation, this strategy yields a significant improvement (up to 38%) inthe network capacity over the legacy Adaptive Data Rate (ADR), and appears tobe extremely robust to different operating/load conditions and network topologyconfigurations.

Capture Aware Sequential Waterfilling for LoraWAN Adaptive Data Rate