A Group-Based Binary Splitting Algorithm for UHF RFID Anti-Collision Systems
- 1 February 2020
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Communications
- Vol. 68 (2), 998-1012
- https://doi.org/10.1109/TCOMM.2019.2952126
Abstract
Identification efficiency is a key performance metrics to evaluate the ultra high frequency (UHF) based radio frequency identification (RFID) systems. In order to solve the tag collision problem and improve the identification rate in large scale networks, we propose a collision arbitration strategy termed as group-based binary splitting algorithm (GBSA), which is an integration of an efficient tag cardinality estimation method, an optimal grouping strategy and a modified binary splitting. In GBSA, tags are properly divided into multiple subsets according to the tag cardinality estimation and the optimal grouping strategy. In case that multiple tags fall into a same time slot and form a subset, the modified binary splitting strategy will be applied while the rest tags are waiting in the queue and will be identified in the following slots. To evaluate its performance, we first derive the closed-form expression of system throughput for GBSA. Through the theoretical analysis, the optimal grouping factor is further determined. Extensive simulation results supplemented by prototyping tests indicate that the system throughput of our proposed algorithm can reach as much as 0.4835, outperforming the existing anti-collision algorithms for UHF RFID systems.Keywords
Funding Information
- National Natural Science Foundation of China (61802196)
- Natural Science Foundation of Jiangsu Province (BK20180791)
- Natural Science Foundation of Jiangsu Higher Education Institutions of China (17KJB510036)
- Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology
- China Meteorological Administration
- Engineering Research Center of Digital Forensics, Ministry of Education
- National Science Foundation (CNS-1837146)
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