An Energy-Efficient LoRa Multi-Hop Protocol through Preamble Sampling for Remote Sensing

Internet of Things technologies open up new applications for remote monitoring of forests, fields, etc. These networks require autonomous operation: combining ultra-long-range connectivity with low energy consumption. While typical low-power wide-area networks offer long-range characteristics, they fall short in providing coverage for environmental tracking in ultra-remote areas spanning hundreds of square kilometers. This paper presents a multi-hop protocol to extend the sensor's range, whilst still enabling low-power operation: maximizing sleep time by employing prolonged preamble sampling, and minimizing the transmit energy per actual payload bit through forwarded data aggregation. Real-life experiments, as well as large-scale simulations, prove the capabilities of the proposed multi-hop network protocol. By employing prolonged preamble sampling a node's lifespan can be increased to up to 4 years when transmitting packages every 6 h, a significant improvement compared to only 2 days when continuously listening for incoming packages. By aggregating forwarded data, a node is able to further reduce its energy consumption by up to 61%. The reliability of the network is proven: 90% of nodes achieve a packet delivery ratio of at least 70%. The employed hardware platform, network protocol stack and simulation framework for optimization are released in open access.

Automated summary

Internet of Things technologies enable remote monitoring of natural areas, and this paper presents a multi-hop protocol that extends the sensor's range and enables low-power operation. The protocol achieves this by employing prolonged preamble sampling to maximize sleep time and forwarded data aggregation to minimize transmit energy. Real-life experiments and simulations prove the effectiveness of the protocol in increasing node lifespan and reducing energy consumption.