基于碰撞信号恢复的RFID多标签防碰撞算法研究

发布时间：2018-04-23 01:27

本文选题：射频识别 + 防碰撞算法　；参考：《复旦大学》2014年硕士论文

【摘要】：射频识别(RFID)技术是一种基于射频通信的非接触式的自动识别技术,利用射频信号作为载体传递信息和能量,实现与被检测物体之间的信息交互。由于RFID技术具有通信距离远,识别速度快,安全性好等特点,在供应链管理、零售、身份验证、防伪认证、智能安防等领域有广泛应用。物联网相关应用的快速发展对RFID技术的识别速度提出了更高的要求。在很多应用场合,当读写器识别范围内的多个标签同时返回信号时,读写器无法识别到其中的任何一个标签,这时就会发生多标签碰撞。多标签防碰撞算法用于解决这种问题。目前广泛采用的动态帧时隙Aloha算法将碰撞时隙(两个或者更多标签同时响应的时隙)当成无效时隙。可以证明,即使在最优帧长的条件下,系统吞吐率存在理论极限,对算法的优化只能使系统吞吐率无限接近理论极限。通过硬件辅助的方法将碰撞时隙转化为成功时隙是一种提高防碰撞算法性能的可行的方案。本文对现有的多标签防碰撞算法进行了研究,分析了碰撞信号恢复的方法,提出了基于碰撞恢复的多种防碰撞算法优化方法,包括碰撞信号恢复、标签个数检测、帧长优化等；建立了基于MATLAB的仿真平台并对影响算法性能的因素做了分析与讨论；提出了基于碰撞信号恢复的防碰撞算法硬件实现的系统架构,并对碰撞恢复电路做了硬件实现。上述方法可以有效地提高系统多标签识别的吞吐率并突破理论极限。仿真结果表明,采用本文设计的碰撞信号恢复算法,在信噪比为30dB的条件下,当时隙内存在两个标签时,识别到两个标签的概率为51%,识别到一个标签的概率为44%。识别1000个标签时,系统吞吐率可以由0.37提高至0.69。采用本文提出的帧长优化算法,将衰减因子设为0.5,可以使系统吞吐率进一步提高至0.85。采用本文设计的标签个数检测方法,可以检测时隙内存在的标签个数,为碰撞信号恢复提供依据,其检测的平均准确率可以达到90%。本文对碰撞信号模块做了硬件实现,在SMIC 0.13μm工艺的条件下,其面积为0.17mm2,相比于一个不包含碰撞恢复的数字系统面积增加了10%。
[Abstract]:Radio frequency identification (RFID) technology is a non-contact automatic identification technology based on radio frequency communication. Radio frequency signal is used as carrier to transfer information and energy to realize the information interaction with the detected object. Because of its long communication distance, high recognition speed and good security, RFID technology has been widely used in supply chain management, retail, authentication, authentication, intelligent security and other fields. The rapid development of Internet of things (IoT) applications requires higher recognition speed of RFID technology. In many applications, when multiple tags in the range of reader recognition return signals at the same time, the reader can not recognize any of the tags, so there will be multiple tag collisions. Multi-label anti-collision algorithm is used to solve this problem. The dynamic frame slot Aloha algorithm, which is widely used at present, regards the collision slot (the time slot that two or more tags respond at the same time) as invalid slot. It can be proved that even under the optimal frame length condition, the system throughput has a theoretical limit, and the optimization of the algorithm can only make the system throughput infinitely close to the theoretical limit. It is a feasible scheme to improve the performance of anti-collision algorithm by converting collision time slot into successful time slot by hardware aided method. In this paper, the existing multi-label anti-collision algorithms are studied, the methods of collision signal recovery are analyzed, and several anti-collision algorithms based on collision recovery are proposed, including collision signal recovery, tag number detection, frame length optimization and so on. The simulation platform based on MATLAB is established, and the factors affecting the performance of the algorithm are analyzed and discussed, and the hardware architecture of anti-collision algorithm based on collision signal recovery is proposed, and the hardware implementation of collision recovery circuit is also given. The above method can effectively improve the throughput and break the theoretical limit of multi-label recognition. The simulation results show that when the SNR is 30dB, when there are two tags in the gap, the probability of identifying two tags is 51 and the probability of identifying one tag is 44. The system throughput can be increased from 0. 37 to 0. 69 when 1000 tags are identified. Using the frame length optimization algorithm proposed in this paper, the attenuation factor is set to 0.5, and the throughput of the system can be further increased to 0.85. By using the method designed in this paper, the number of tags in the time slot can be detected, which can provide the basis for the recovery of collision signal. The average accuracy of the detection can reach 90%. The hardware implementation of the collision signal module is presented in this paper. Under the condition of SMIC 0.13 渭 m process, the area of the collision signal module is 0.17mm ~ 2, which is 10 times larger than that of a digital system without collision recovery.
【学位授予单位】：复旦大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP391.44

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