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Fast and fine-grained counting and identification via constructive interference in WSNs

  • Dingming Wu
  • , Chao Dong
  • , Shaojie Tang
  • , Haipeng Dai
  • , Guihai Chen
  • Nanjing University
  • PLA University of Science and Technology
  • Shanghai Jiao Tong University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

Counting and identifying neighboring active nodes are two fundamental operations in wireless sensor networks (WSNs). In this paper, we propose two mechanisms, Power based Counting (Poc) and Power based Identification (Poid), which achieve fast and accurate counting and identification by allowing neighbors to respond simultaneously to a poller. A key observation that motivates our design is that the power of a superposed signal increases with the number of component signals under the condition of constructive interference (CI). However, due to the phase offsets and various hardware limitations (e.g., ADC saturation), the increased superposed power exhibits dynamic and diminishing returns as the number of component signals increases. This uncertainty of phase offsets and diminishing returns property of the superposed power pose serious challenges to the design of both Poc and Poid. To overcome these challenges, we design delay compensation methods to reduce the phase offset of each component signal, and propose a novel probabilistic estimation technique in cooperation with CI. We implement Poc and Poid on a testbed of 1 USRP and 50 TelosB nodes, the experimental results show that the accuracy of Poc is above 97.9%, and the accuracy of Poid is above 96.5% for most cases. In addition to their high accuracy, our methods demonstrate significant advantages over the state-of-the-art solutions in terms of substantially lower energy consumption and estimation delay.

Original languageEnglish
Title of host publicationIPSN 2014 - Proceedings of the 13th International Symposium on Information Processing in Sensor Networks (Part of CPS Week)
PublisherIEEE Computer Society
Pages191-202
Number of pages12
ISBN (Print)9781479931460
DOIs
StatePublished - 2014
Event13th IEEE/ACM International Conference on Information Processing in Sensor Networks, IPSN 2014 - Berlin, Germany
Duration: Apr 15 2014Apr 17 2014

Publication series

NameIPSN 2014 - Proceedings of the 13th International Symposium on Information Processing in Sensor Networks (Part of CPS Week)

Conference

Conference13th IEEE/ACM International Conference on Information Processing in Sensor Networks, IPSN 2014
Country/TerritoryGermany
CityBerlin
Period04/15/1404/17/14

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