Exploiting Residual Channel for Implicit Wi-Fi Backscatter Networks

Taekyung Kim, Wonjun Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)


The emerging deployment of IoT devices increasingly requires more energy-and-cost-efficient wireless links between devices. Nowadays backscatter networks, one of the most feasible technology to meet the requirement in IoT spaces, have evolved for better usability and wider coverage. The most likely consequence of the evolution is Wi-Fi backscatter networks that harmonize with widely deployed commercial devices. However recent Wi-Fi backscatter techniques are stuck in front of several hurdles. The backscatter techniques along with 802.11b devices impair the spectral efficiency of wireless channels and break backward compatibility. Meanwhile, the backscatter techniques along with the other types of 802.11 devices support only per-packet backscatter resulting poor performance. To tackle all these problems, we propose a flicker detector that achieves per-symbol in-band backscatter by exploiting residual channel of Wi-Fi packets. Our approach shows robust performance without any modification on the hardware and any side effect on wireless channels. Extensive experiments on a software-defined radio testbed demonstrate that our approach overcomes the hurdles of existing Wi-Fi backscatter networks.

Original languageEnglish
Title of host publicationINFOCOM 2018 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Electronic)9781538641286
Publication statusPublished - 2018 Oct 8
Event2018 IEEE Conference on Computer Communications, INFOCOM 2018 - Honolulu, United States
Duration: 2018 Apr 152018 Apr 19

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Other2018 IEEE Conference on Computer Communications, INFOCOM 2018
Country/TerritoryUnited States


  • Backscatter
  • Internet of Things
  • Wi-Fi

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering


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