An Efficient Slot-Segment Adjustment Strategy for Unknown Populations in RFID Systems

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• 作者：Litian Duan ; Zizhong John Wang ; Qiuyong Zhao
• 关键词：RFID ; EPCglobal Class ; 1 Gen ; 2 ; Anti ; collision ; Segment ; Dynamical adjustment
• 刊名：International Journal of Wireless Information Networks
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：24
• 期：1
• 页码：42-49
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Electrical Engineering;
• 出版者：Springer US
• ISSN：1572-8129
• 卷排序：24

文摘

In a passive radio frequency identification (RFID) System, tags collision is caused by multiple tags communicating with the reader simultaneously, which dramatically influences the system efficiency. Therefore, researching on anti-collision algorithms to reduce the collisions and increasing the system efficiency becomes a hotspot. In this paper, we focus on the passive RFID tags and first propose a dynamical frame slotted ALOHA-based estimation method to predict the unknown population of tags. Based on this, an adjustment strategy is proposed to dynamically modify the frame size as the population of tags changes. In this adjustment strategy, a segment fashion is proposed to instead the slot-by-slot fashion; the former one could efficiently increase the reading speed and ensure the system throughput. As a result, the proposed algorithm could reach to the throughput of 35% in average with a stable estimation accuracy of 80%. The simulation shows that our algorithm also outperforms the other algorithms in the identification speed (tags/s).