PLACE: Physical Layer Cardinality Estimation for Large-Scale RFID Systems

Yuxiao Hou, Jiajue Ou, Yuanqing Zheng, Mo Li

Research output: Journal article publicationJournal articleAcademic researchpeer-review

14 Citations (Scopus)

Abstract

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
Article number7298458
Pages (from-to)2702-2714
Number of pages13
JournalIEEE/ACM Transactions on Networking
Volume24
Issue number5
DOIs
Publication statusPublished - 1 Oct 2016

Keywords

  • cardinality estimation
  • physical layer
  • RFID

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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