PLACE: Physical layer cardinality estimation for large-scale RFID systems

Yuxiao Hou, Jiajue Ou, Yuanqing Zheng, Mo Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

22 Citations (Scopus)


Estimating the number of RFID tags is a fundamental operation in RFID systems and has recently attracted wide attentions. Despite the subtleties in their designs, previous methods estimate the tag cardinality from the slot measurements, which distinguish idle and busy slots and based on that derive the cardinality following some probability models. In order to fundamentally improve the counting efficiency, in this paper we introduce PLACE, a physical layer based cardinality estimator. We show that it is possible to extract more information and infer integer states from the same slots in RFID communications. We propose a joint estimator that optimally combines multiple sub-estimators, each of which independently counts the number of tags with different inferred PHY states. Extensive experiments based on the GNURadio/USRP platform and the large-scale simulations demonstrate that PLACE achieves approximately 3∼4× performance improvement over state-of-the-art cardinality estimation approaches.
Original languageEnglish
Title of host publication2015 IEEE Conference on Computer Communications, IEEE INFOCOM 2015
Number of pages9
ISBN (Electronic)9781479983810
Publication statusPublished - 21 Aug 2015
Event34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015 - Hong Kong, Hong Kong
Duration: 26 Apr 20151 May 2015


Conference34th IEEE Annual Conference on Computer Communications and Networks, IEEE INFOCOM 2015
Country/TerritoryHong Kong
CityHong Kong

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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