基于ALOHA分区的多周期防碰撞搜索算法

在射频识别系统中，标签用于传递信息，在阅读器有效作用范围内，多个标签同时响应从而发生碰撞的情况不可避免，标签发生碰撞会降低系统的识别效率。为了提高系统的标签识别效率，本文在已有防碰撞算法的基础上提出一种基于ALOHA分区的多周期防碰撞搜索算法。该算法首先根据待识别标签数目划分相应时隙帧长，然后在发生碰撞的时隙内利用多周期防碰撞搜索算法识别标签，能够有效降低碰撞发生概率，提高标签识别效率。该算法可应用到数量庞大的标签识别系统中，对这类系统具有一定优势。理论分析与实验结果表明：该算法能够有效减少算法时隙数，提高系统的标签识别效率。

A Multi-period Anti-collision Tree Search Algorithm Based on ALOHA Partition

In the RFID system, tags are used to transmit information. Within the effective function range of the reader, multiple tags respond at the same time and thus collision is inevitable. The collision of tags will reduce the recognition efficiency of the system. In order to improve the efficiency of label recognition, this paper proposes a multi-cycle anti-collision search algorithm based on ALOHA partition and the existing anti-collision algorithms. Firstly, the frame length of the corresponding time slot is divided according to the number of tags to be recognized. Then, the multi-cycle anti-collision search algorithm is used to identify the tags in the time slot where the collision occurs, which can effectively reduce the probability of collision and improve the efficiency of tag recognition. This algorithm can be applied to a large number of label recognition systems, and has certain advantages over these systems. Theoretical analysis and experimental results show that the algorithm can effectively reduce the number of algorithmic time slots and improve the efficiency of label recognition.