Tag Cardinality Estimation Using Expectation-Maximization in ALOHA-Based RFID Systems With Capture Effect and Detection Error

Tag cardinality estimation is one of the most crucial issues in radio frequency identification technology. The issue, however, usually faces with challenges in wireless fading environments due to the presence of the so-called capture effect (CE) and detection error (DE). The aim of this letter is to provide an efficient and accurate estimation method to cope with the CE and DE using expectation-maximization algorithm and the standard Aloha-based protocol. We show that the proposed method gives more accurate estimates than a conventional one. Thanks to this fact, the Aloha frame size used for the tag identification process can also be optimally selected so that the identification efficiency can be improved. Computer simulations are presented to confirm the merit of the proposed method.

[1]  Yang Wang,et al.  Capture-aware Bayesian RFID tag estimate for large-scale identification , 2018, IEEE/CAA Journal of Automatica Sinica.

[2]  Wen-Tzu Chen,et al.  An Accurate Tag Estimate Method for Improving the Performance of an RFID Anticollision Algorithm Based on Dynamic Frame Length ALOHA , 2009, IEEE Transactions on Automation Science and Engineering.

[3]  G. McLachlan,et al.  The EM algorithm and extensions , 1996 .

[4]  Yunhao Liu,et al.  Toward More Rigorous and Practical Cardinality Estimation for Large-Scale RFID Systems , 2017, IEEE/ACM Transactions on Networking.

[5]  Jörg Robert,et al.  A Closed-Form Solution for ALOHA Frame Length Optimizing Multiple Collision Recovery Coefficients’ Reading Efficiency , 2018, IEEE Systems Journal.

[6]  Yunhao Liu,et al.  Cardinality Estimation for Large-Scale RFID Systems , 2011, IEEE Trans. Parallel Distributed Syst..

[7]  Hideaki Sakai,et al.  Maximum Likelihood Approach for RFID Tag Cardinality Estimation under Capture Effect and Detection Errors , 2013, IEICE Trans. Commun..

[8]  Albert Heuberger,et al.  A Time and Capture Probability Aware Closed Form Frame Slotted ALOHA Frame Length Optimization , 2015, IEEE Communications Letters.

[9]  Van-Dinh Nguyen,et al.  Modified tree-based identification protocols for solving hidden-tag problem in RFID systems over fading channels , 2017, IET Commun..

[10]  Bo Li,et al.  Efficient Anti-Collision Algorithm Utilizing the Capture Effect for ISO 18000-6C RFID Protocol , 2011, IEEE Communications Letters.

[11]  Rabab Kreidieh Ward,et al.  Probabilistic Analysis and Correction of Chen's Tag Estimate Method , 2011, IEEE Transactions on Automation Science and Engineering.