Tag Cardinality Estimation Using Expectation-Maximization in ALOHA-Based RFID Systems With Capture Effect and Detection Error
Tag Cardinality Estimation Using Expectation-Maximization in ALOHA-Based RFID Systems With Capture Effect and Detection Error
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DOI：
10.1109/lwc.2018.2890650
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发表时间：
2019-04
影响因子：
6.3
通讯作者：
Chuyen T. Nguyen;Van-Dinh Nguyen;A. Pham
中科院分区：
文献类型：
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作者：
Chuyen T. Nguyen;Van-Dinh Nguyen;A. Pham
标签基数估计是射频识别技术中最关键的问题之一。然而，在无线衰落环境中，由于所谓的捕获效应(CE)和检测误差(DE)的存在，这个问题通常会面临挑战。这封信的目的是使用期望最大化算法和标准的ALOHA协议来提供一种高效而准确的估计方法来应对CE和DE。结果表明，与传统方法相比，该方法给出了更准确的估计。由于这一事实，还可以优化选择用于标签识别处理的ALOHA帧大小，从而可以提高识别效率。计算机仿真结果证实了该方法的有效性。
Tag cardinality estimation is one of the most crucial issues in radio frequency identification technology. The issue, however, usually faces with challenges in wireless fading environments due to the presence of the so-called capture effect (CE) and detection error (DE). The aim of this letter is to provide an efficient and accurate estimation method to cope with the CE and DE using expectation-maximization algorithm and the standard Aloha-based protocol. We show that the proposed method gives more accurate estimates than a conventional one. Thanks to this fact, the Aloha frame size used for the tag identification process can also be optimally selected so that the identification efficiency can be improved. Computer simulations are presented to confirm the merit of the proposed method.