Fast RFID counting under unreliable radio channels

  • Authors:
  • Wai-Kit Sze;Wing-Cheong Lau;On-Ching Yue

  • Affiliations:
  • Department of Information Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong;Department of Information Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong;Department of Information Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

  • Venue:
  • ICC'09 Proceedings of the 2009 IEEE international conference on Communications
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

A fast RFID counting algorithm with performance guarantee can be used as a fundamental building block for other more sophisticated RFID query protocols and operations. Recently, Kodialam et. al. propose various low-latency RFID counting schemes with accuracy guarantees [1], [2] based on a probabilistic counting approach which does not require explicit identification of individual tags. However, the proposed schemes all assume a perfect communication channel between the reader and the tags which is unlikely to be true in practice. On the contrary, as demonstrated by recent empirical measurement studies, the radio communications between an RFID reader and a set of seemingly "in-range" tags are rather non-deterministic and can even be unreliable at times due to varying radio conditions. In this paper, we extend the algorithms in [2] by taking into account the effects of radio channel unreliability. By modeling the spatial distribution of tags and the corresponding channel fading effects, we analyze the new requirements on the algorithm parameters used in [2] (e.g. number of reader polling cycles, frame-size and persistent probability) in order to achieve a desired level of estimation accuracy. Another key observation is that, unlike the perfect channel case where one can indefinitely reduce the estimation error by increasing the number of reader polling cycles, with an unreliable radio channel, there is a lower-bound on the estimation error due to the inherent variation in the spatial distribution of the tags and the radio channel conditions. Towards this end, we have derived an expression for this lower-bound. We also demonstrate the efficacy of our analytical results and their corresponding guarantees in estimation accuracy via an simulation study.