EMU: Increasing the Performance and Applicability of LoRa through Chirp Emulation, Snipping, and Multiplexing

This paper presents EMU, a framework that enables the emulation, snipping, and multiplexing of LoRa chirps on commercial IoT devices equipped with low-power sub-GHz transceivers, including those supporting LoRa itself. Chirp snipping consists in artificially removing a sequence of chips and in putting the radio in low-power mode, which allows to reduce energy consumption while still commu-nicating reliably. Chirp multiplexing exploits the gaps introduced by chirp snipping to transmit portions of another chirp on a sep-arate channel, which allows to concurrently transmit two LoRa packets and to increase the throughput. We build EMU as a modu-lar framework and implement support for off-the-shelf LoRa and non-LoRa transceivers. We then evaluate its performance by com-paring the reliability, efficiency, and receiver sensitivity achieved by EMU with that of traditional LoRa for different physical layer settings. We finally showcase EMU's ability to send packets over two channels simultaneously, thereby improving the uplink throughput of LoRaWan, and demonstrate that even non-LoRa transceivers employing EMU can communicate to a LoRaWan gateway, enabling new use cases and expanding the applicability of LoRa technology.