Tag size profiling in multiple reader RFID systems

Shigeng Zhang, Xuan Liu, Jianxin Wang, Jiannong Cao

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

15 Citations (Scopus)


In this paper, we study the tag size profiling (TSP) problem in RFID systems with multiple readers, which is to estimate the number of tags in every subregion in the system covered by different set of readers. The TSF problem is vitally important to reader scheduling and many other related operations in large scale multi-reader RFID systems. To our knowledge, however, it is not well solved in previous researches. We propose a novel approach to the TSF problem. The key idea is to treat the size of subregions as variables and construct a linear system in these variables to solve them. We theoretically prove that for any multi-reader RFID system, a linear system that can be used to uniquely solve the variables corresponding to the subregion sizes can always be constructed. We then propose a time-efficient algorithm that uses two heuristics to quickly find enough linearly independent equations to construct the linear system. Extensive simulation results show that the proposed approach achieves very high accuracy. When the estimation results of individual readers contain 5% errors, our approach achieves median estimation error of smaller than 0.02 and 90-percentile estimation error of smaller than 0.04 in large systems containing more than one hundred readers.
Original languageEnglish
Title of host publicationINFOCOM 2017 - IEEE Conference on Computer Communications
ISBN (Electronic)9781509053360
Publication statusPublished - 2 Oct 2017
Event2017 IEEE Conference on Computer Communications, INFOCOM 2017 - Atlanta, United States
Duration: 1 May 20174 May 2017


Conference2017 IEEE Conference on Computer Communications, INFOCOM 2017
Country/TerritoryUnited States


  • Multiple Readers
  • Radio Frequency Identification
  • Reader Scheduling
  • RFID Estimation

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering


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