Channel Independent Wi-Fi Backscatter Networks

Taekyung Kim, Wonjun Lee

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

7 Citations (Scopus)

Abstract

Wi-Fi backscatter is an emerging technique that enables ultra-low power wireless communications thanks to the simplicity of a backscatter tag. This simplicity drastically reduces communication power. However, this simplicity also removes channel selectivity of the backscatter tag. In this regard, we introduce two issues, violation of the wireless regulations and the waste of resources, in Wi-Fi backscatter networks. To solve these problems, we introduce channel independent packet detection and error vector demodulation. We first design a backscatter receiver accepting Wi-Fi frames on the listening channel as well as adjacent channels, because the backscatter tag responds to all incoming signals regardless of their frequencies. We then investigate how the error vectors of each subcarrier are changed in Wi-Fi backscatter systems. Based on the analysis, we propose a method that translates the error vectors into a backscatter frame. We implement and evaluate our design with commodity 802.11n access points as carrier sources, a software-defined radio as a receiver, and a 2.4 GHz backscatter tag. The results show that channel independent Wi-Fi backscatter is always better than channel dependent approaches.

Original languageEnglish
Title of host publicationINFOCOM 2019 - IEEE Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages262-270
Number of pages9
ISBN (Electronic)9781728105154
DOIs
Publication statusPublished - 2019 Apr
Event2019 IEEE Conference on Computer Communications, INFOCOM 2019 - Paris, France
Duration: 2019 Apr 292019 May 2

Publication series

NameProceedings - IEEE INFOCOM
Volume2019-April
ISSN (Print)0743-166X

Conference

Conference2019 IEEE Conference on Computer Communications, INFOCOM 2019
Country/TerritoryFrance
CityParis
Period19/4/2919/5/2

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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