[2022] Content-Agnostic Backscatter from Thin Air

Abstract

We present CAB, a content-agnostic backscatter system that can demodulate both tag and ambient data from ambient backscattered WiFi alone. In contrast to prior ambient backscatter systems that use ambient data (content) as tag-data carriers, we focus on zero-subcarriers, which are invariant and independent for any ambient OFDM WiFi. The idea of using zero-subcarriers to convey tag data is simple and elegant. Not only does it for the first time remove the dependency of tag-data demodulation on ambient data, but it also significantly improves the practicality of ambient backscatter.

We prototype CAB using off-the-shelf FPGAs and SDRs. Extensive experiments show CAB is universal as it can work with multi-band, multi-stream, and multi-user ambient traffic, including WiFi 3/4/5/6. CAB is also high-performing since it can deliver 340.9 Mbps aggregate throughput, reaching 97% Shannon capacity. Since CAB is general, we extend it to leverage ambient LTE traffic as excitations, and the achieved tag-data BER is below 0.002%. As the first content-agnostic backscatter that delivers near Shannon-capacity throughput, we believe CAB takes a curial step forward on ubiquitous battery-free IoTs.

Authors:

Yifan Yang, Longzhi Yuan, Jia Zhao and Wei Gong

Publication:

ACM MobiSys 2022        (CCF-B)            [Link]  [PDF]  [Video]

Keywords:

Backscatter, OFDM, Internet of Things