Abstract:

Tag collision in Radio Frequency Identification (RFID) system increases the time overhead and energy consumption, reduces the speed of recognition. With the increasing number of tags, the collision is more obvious, thus the system performance decreases sharply. In order to solve the problem of collision among multiple tags in RFID system, an optimized anti-collision algorithm for RFID system based on tag grouping was proposed by analyzing frame slotted ALOHA algorithm. The tags of this algorithm were divided into several groups through the Cyclic Redundancy Check (CRC) code which tags carry, then it recorded tag group number and identified each group according to the grouping sequence, therefore the number of tags which simultaneously responded to the reader's order would be reduced. For the problem of timeslot selective confliction in the identification process, the chaotic system was used to generate uniformly distributed pseudorandom numbers, and it was conducive to select timeslots randomly for the tags within identification state, which made the timeslots selection more uniform in a frame and finally reached the purpose of reducing frequency of tag collision. In the comparative experiments with traditional algorithm, the optimization algorithm needed less orders when the number of tags to be identified was equal, and the order number and tag number showed an approximate linear relationship. The tag identification speed improvement of the optimization algorithm was stable at 50% when the number of tags to be identified was less than 256, and the speed improvement increased to 80% when the number of tags to be identified was more than 256. Theoretical analysis and simulation results indicate that the optimization algorithm has faster tag identification speed, and its performance is more obvious with the increasing of the tags.

摘要：

标签冲突增加了射频识别(RFID)系统的时间开销和能量损耗，降低了识别速度，随着标签数量的不断增加，冲突更加明显，系统性能急剧下降。为了解决RFID系统中的多标签防碰撞问题，在分析帧时隙ALOHA算法的基础上提出一种基于标签分组的帧时隙ALOHA优化算法。该算法首先通过标签自身携带的循环冗余校验(CRC) 码将标签分组，记录标签组的组号，按照组号的顺序依次识别，从而减少同时响应阅读器命令的标签数量；针对识别过程中的时隙选择冲突问题，可以通过混沌系统产生均匀分布的伪随机数，对进入识别状态的标签随机选择时隙号，使标签在一帧内选择的时隙分布更加均匀，从而减少标签碰撞的次数。与传统算法的对比实验中：当待识别标签数量相等时，优化算法识别完标签所需命令数更少，且所用命令数与标签数目呈近似线性关系；当待识别的标签数量小于256时，优化算法的标签识别速度提高率稳定在50%；当待识别的标签数量大于256时，优化算法能使标签识别速度提高率达80%。理论分析与实验结果表明，优化算法识别标签的速度更快，且随着标签数量的增加，其优势更明显。