Multiprotocol backscatter for personal IoT sensors

Abstract

We present multiscatter, a novel backscatter design that can simultaneously work with multiple excitation signals for personal IoT sensors. Specifically, we show for the first time that the backscatter tag can identify various excitation signals in an ultra-low-power way, including WiFi, Bluetooth, and ZigBee. Further, we employ a new modulation approach, overlay modulation, that can leverage those excitation signals to convey tag data on top of productive data, which makes decoding both data possible with only a single personal radio. Since 2.4 GHz signals and personal radios are everywhere, multiscatter is readily deployable in our everyday IoT applications. We prototype multiscatter using an FPGA and various commodity radios. Extensive experiments show that for mixed 802.11b&n, Bluetooth and ZigBee signals, the average identification accuracy of four protocols is more than 93%. The maximal aggregate throughput of both productive and tag data is 278.4 kbps with a single Bluetooth radio, and the maximal backscatter ranges are 28 m, 22 m, and 20 m for WiFi, Bluetooth, and ZigBee, respectively. We also demonstrate that it can leverage excitation diversity to provide uninterrupted communication and greater throughput gains, whereas the single-protocol tag being idle when target carriers are not available.