Adaptive splitting protocols for RFID tag collision arbitration
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Fast and reliable estimation schemes in RFID systems
Proceedings of the 12th annual international conference on Mobile computing and networking
Cardinality Estimation for Large-scale RFID Systems
PERCOM '08 Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications
Dynamic tag estimation for optimizing tree slotted aloha in RFID networks
Proceedings of the 11th international symposium on Modeling, analysis and simulation of wireless and mobile systems
Randomized multi-channel interrogation algorithm for large-scale RFID systems
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Randomized multi-channel interrogation algorithm for large-scale RFID systems
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
IEEE Transactions on Wireless Communications
Every bit counts: fast and scalable RFID estimation
Proceedings of the 18th annual international conference on Mobile computing and networking
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In this paper, we study the anonymous cardinality estimation problem in radio frequency identification (RFID) systems. To preserve privacy and anonymity, each tag only transmits a portion of its ID to the reader when it is being queried. To achieve complete system coverage and increase the accuracy of measurement, multiple readers with overlapping interrogation zones are deployed. The cardinality estimation problem is to estimate the total number of tags (or the tag population) in an RFID system. We first propose an exclusive estimator to estimate the number of tags that are exclusively located in the interrogation zone of a selected reader. We then present a multiple-reader tag estimation (MRTE) algorithm that can accurately estimate the tag population using the measurement from different readers and the exclusive estimator. The accuracy of our proposed algorithm and the approximation are validated via simulations. We compare our proposed MRTE algorithm with the enhanced zero-based (EZB) and maximum a posteriori tag estimation (MPTE) algorithms. Although the mean of the estimation error for all three algorithms approaches zero under certain circumstances, the variance of the estimation error for MRTE algorithm increases linearly with the number of readers while it increases exponentially for EZB and MPTE algorithms.