PolarTracker: Attitude-Aware Channel Access for Floating Low Power Wide Area Networks

Low Power Wide Area Networks (LPWAN) such as Long Range (LoRa) show great potential in emerging aquatic IoT applications. However, our deployment experience shows that the floating LPWAN suffers significant performance degradation, compared to the static terrestrial deployments. Our measurement results reveal the reason behind this is the polarization and directivity of the antenna. The dynamic attitude of a floating node incurs varying signal strength losses, which is ignored by the attitude-oblivious link model adopted in most of the existing methods. When accessing the channel at a misaligned attitude, packet errors can happen. In this paper, we propose an attitude-aware link model that explicitly quantifies the impact of node attitude on link quality. Based on the new model, we propose
PolarTracker
, a novel channel access method for floating LPWAN.
PolarTracker
tracks the node attitude alignment state and schedules the transmissions into the aligned periods with better link quality. To support concurrent access of multiple LoRa nodes, an attitude-based slotted-ALOHA protocol is proposed to reduce collision. We implement a prototype of
PolarTracker
on commercial LoRa platforms and extensively evaluate its performance in various real-world environments. The experimental results show that
PolarTracker
can efficiently improve the packet reception ratio by 50.6%, compared with ALOHA in LoRaWAN.