Carnegie Mellon University
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Grouping of RFID Tags via Strongly Selective Families

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journal contribution
posted on 2013-05-01, 00:00 authored by Yi-Sheng Su, Jiun-Ren Lin, Ozan Tonguz

This letter proposes a novel scheme for grouping of radio-frequency identification (RFID) tags, based on strongly selective families (SSFs). Grouping of RFID tags allows verifying the integrity of groups of objects without external systems such as databases or verifiers, and can be extended to identify missing objects. The existing scheme is based on Gallager's low-density parity-check (LDPC) codes and, as such, it cannot easily achieve designated decoding guarantees due to its pseudo-random nature. Motivated by the strongly selective property of SSFs, this study proposes grouping of RFID tags via SSFs, such that designated decoding guarantees are more easily achieved. Simulation and theoretical results are presented, demonstrating that the proposed scheme can greatly improve the performance of the existing one.


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