Capture-Aware Estimation for Large-Scale RFID Tags Identification
Capture-Aware Estimation for Large-Scale RFID Tags Identification
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DOI：
10.1109/lsp.2015.2396911
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发表时间：
2015-01
影响因子：
3.9
通讯作者：
Yang Wang;Haifeng Wu;Yu Zeng
中科院分区：
文献类型：
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作者：
Yang Wang;Haifeng Wu;Yu Zeng
对于具有捕获效应的动态帧长Aloha RFID系统，如何估计无源RFID标签的数量和捕获效应发生的概率是非常重要的。该估计将涉及设置最佳帧长度，这使得标签识别实现更高的效率。在大规模标签识别环境下，标签的数量可能远大于初始帧长度。在这种情况下，现有的估计并不适用。在这封信中，我们提出了一种新的估计方法的大规模标签识别。所提出的方法可以调整初始帧长度匹配的标签的数量，从帧中的前几个时隙。所提出的方法的优点是即使标签的数量大得多时也能更好地工作。仿真结果表明，该方法在大规模标签识别下具有较低的估计误差。在此基础上，通过对所提方法的估计结果设定最佳帧长，可以获得更高的识别效率。
How to estimate the number of passive radio frequency identification (RFID) tags and the occurrence probability of capture effect is very important for a dynamic frame length Aloha RFID system with capture effect. The estimation would relate to setting an optimal frame length, which makes tag identification achieve higher efficiency. Under large-scale tags identification environment, the number of tags may be much greater than an initial frame length. In this scenario, existing estimates do not work well. In this letter, we propose a novel estimation method for the large-scale tags identification. The proposed method could adjust the initial frame length matched to the number of tags from only the first several slots in the frame. The advantage of the proposed method is to work better even when the number of tags is much greater. Numerical results show that, the proposed method has lower estimation errors under the large-scale tag identification. After setting an optimal frame length from the estimated results of the proposed method, furthermore, we could obtain higher identification efficiency.