A Study of Anti-collision Multi-tag Identification Algorithms for Passive RFID Systems

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The major advantages of radio frequency identification (RFID) technology over barcodes are that the RFID-tagged objects do not require to be in line-of-sight with the reader for their identification and multiple objects can be read simultaneously. But when multiple objects are read simultaneously there is always a problem of collision which reduces the efficiency of the system. This thesis presents a comprehensive study of the dynamic framed slotted ALOHA (DFSA)-based anti-collision multi-tag identification algorithms for passive RFID system. Performance of various DFSA algorithms is compared through extensive simulation results. In addition, a number of simple performance improvement techniques have also … continued below

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Kamineni, Neelima May 2010.

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  • Kamineni, Neelima

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The major advantages of radio frequency identification (RFID) technology over barcodes are that the RFID-tagged objects do not require to be in line-of-sight with the reader for their identification and multiple objects can be read simultaneously. But when multiple objects are read simultaneously there is always a problem of collision which reduces the efficiency of the system. This thesis presents a comprehensive study of the dynamic framed slotted ALOHA (DFSA)-based anti-collision multi-tag identification algorithms for passive RFID system. Performance of various DFSA algorithms is compared through extensive simulation results. In addition, a number of simple performance improvement techniques have also been investigated in this thesis, including improved estimation techniques for the number of tags in each read cycle and a low-complexity heuristic stopping criterion that can be easily implemented in the practical system.

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  • May 2010

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  • Sept. 10, 2010, 1:20 a.m.

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  • Jan. 15, 2014, 2:03 p.m.

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Kamineni, Neelima. A Study of Anti-collision Multi-tag Identification Algorithms for Passive RFID Systems, thesis, May 2010; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc28439/: accessed May 26, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; .

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