AeroEcho: Towards Agricultural Low-power Wide-area Backscatter with Aerial Excitation Source
Yidong Ren, Gen Li, Yimeng Liu, Younsuk Dong, Zhichao Cao
Abstract
The Internet of Things (IoT) plays a pivotal role in advancing smart agriculture. Leveraging LoRa backscatter technology greatly enhances energy efficiency in agricultural IoT. However, cost and scalability issues prevent reliable coverage of extensive agricultural areas. In this paper, we introduce AeroE-cho, a novel system that integrates aerial excitation sources and backscatter tags to address these challenges and enable efficient agricultural IoT. Firstly, we co-design the excitation source and tag with a customized packet format to enable decoding for multiple tags. Secondly, we propose excitation cells to achieve optimal throughput and symbol error rate. Finally, we devise two aerial routing strategies to optimize system energy efficiency and coverage reliability for arbitrary agricultural sensor deployments. AeroEcho is realized using customized low-cost hardware, signal processing via software-defined radio on TV white space spectrum, and evaluated in real-world scenarios. Results demonstrate that AeroEcho enables concurrent trans-mission of 71 tags with less than 1 % bit error rate using the same non-linear chirp in a single channel, achieving a lOx higher transmission concurrency compared to existing methods. Furthermore, AeroEcho enhances the overall throughput of current backscatter transmission by 5.84 x and individual tag data rate by 12 x compared to state-of-the-art approaches.
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