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A Novel and Efficient Blocking Scheme for Multiple Tag Identifications in a Large Scale RFID System
Chuan-Gang Liu, Yu-Min Huo, I-Hsien Liu, Heng-Hua Liu, Chu-Fen Li and Jung-Shian Li

Over the past years, RFID is exploited and deployed widely in IoT. However, the performance of RFID is critically dependent on the use of effective anti-collision schemes. Hence, many anti-collision schemes are developed for various RFID collision cases. Among the various collision prevention schemes, a promising collision prevention scheme, Pair Resolution Blocking (PRB), can complete two tag identifications in one cycle, which not only solves collision issue but also achieves high efficiency in tag identification process. In conventional RFID systems, PRB is very efficient and crucial. Unfortunately, in a large scale RFID system, PRB seems unable to tackle the massive tag identification jobs in a short time. Hence, in this paper, we investigate the flaws of PRB and firstly propose an algorithm designated as Multiple Identification Blocking Algorithm-Paired Staying tags (MIBA-PS), to improve the bit error rate of the PRB algorithm. The second anti-collision blockingbased algorithm designated as Multiple Identification Blocking Algorithm-Numerous Staying tags (MIBA-NS) is then proposed for improving the efficiency of the RFID tag identification process by identifying multiple tags within a single time frame. Both proposed algorithms employ the collided signal caused by multiple tags to recognize the tags in one cycle. Furthermore, in order to reduce tags’ bit error rate in the wireless channel, the staying tags exploit newly-generated bit string to inform the reader instead of tag ID in the tag identification process. Analytical results and performance evaluation confirm that our proposed anti-collision algorithms have lower error probability, shorter identification delay and lower waiting time than existing famous anticollision schemes while identifying multiple tags in a large scale RFID system.

Keywords: RFID, anti-collision, multiple tag identification

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