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物理层超高频射频识别标签信号分离中的信道估计 被引量:4

Channel Estimation for Recovery of UHF RFID Tag Collision on Physical Layer
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摘要 在被动式的超高频(UHF)射频识别(RFID)系统中,当多个标签选择同一个时隙向阅读器发送信息,标签间冲突就会产生,该冲突通常只在介质访问控制(MAC)层上解决。其实,若冲突信号在物理层上被分离,识别效率将能得到很大的提高。在物理层冲突信号分离中,信道估计是一项关键技术,因为好的信道估计有助于准确地恢复冲突信号。传统的信道估计方法在两个标签冲突的情况下具有较好的估计性能,但当冲突标签数超过2时,却会产生较高的误差。该文针对物理层的UHF RFID信号分离问题,提出一种新的信道估计方法。该方法利用已知的前缀信号,采用最小二乘方法对信道进行估计。从实验结果看,当标签冲突数超过2时,该文提出的信道估计方法的误差要小于传统的估计方法,而且估计的信道得到的分离效率也高于传统方法。 In a passive Ultra-High Frequency(UHF) Radio Frequency IDentification(RFID) system, when multiple tags choose a same time slot to send information to a reader, tag collision will occur. Generally, the collision is resolved only on a Medium Access Control(MAC) layer. In fact, the collision could be separated on a physical layer, and the efficiency of system identification could be advanced. In the physical layer separation, channel estimation is one of key techniques because good estimation could help to correctly recover the collided signals. Conventional channel estimates work well under the environment of two collided tags. When the number of collided tags is beyond two, however, the conventional channel estimates have more estimation errors. In this paper, a novel channel estimate method is proposed for the passive UHF RFID signal separation on physical layer. The proposed method uses the information of preambles which is a-priori known for a reader and applies a Least-Square(LS) criterion to estimate the channel parameters. From numerical results, the estimation errors of the proposed method are lower than the conventional methods under the number of collided tags is more than two. And, the separation efficiency of the proposed methods is also higher.
出处 《电子与信息学报》 EI CSCD 北大核心 2016年第1期119-126,共8页 Journal of Electronics & Information Technology
基金 国家自然科学基金(61262091) 云南省第十七批中青年学术和技术带头人资助项目(2014HB019) 云南省教育厅科学基金重点项目(2014Z093) 云南民族大学研究生创新基金项目(2015YJCXY254)~~
关键词 射频识别 标签冲突 信号分离 信道估计 最小二乘 Radio Frequency IDentification(RFID) Tag collision Signal separation Channel estimation Least Square(LS)
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参考文献19

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