为提高射频识别(RFID)系统的识别效率,研究了系统的标签防碰撞问题。考虑到对标签进行多分支处理能够有效地提高RFID系统标签识别效率,而传统的多分支防碰撞算法都是在标签估计的基础上对标签进行最优分组,标签估计产生的时延和误差都会影响整体的识别效率,提出了一种基于二进制树的自适应多分支(AMB)防碰撞算法。该算法根据二进制树结构特点,利用识别的标签数目对树结构中右节点标签进行估计并进行分组识别,经过多次调整的自适应多分支防碰撞算法,可以规避一次标签估计所引入的估计误差,从而提高系统的识别效率。仿真结果表明自适应多分支算法可以大大提高标签识别效率,在标签数量较大时系统效率可达43%左右。同时该算法实现简单,只需在阅读器中增加若干计数器,不需要改变任何空中接口,很容易与现有协议兼容。
To improve the identification efficiency of radio frequency identification (RFID) systems, the anti-collision problem of the systems was studied. Considering that dividing tags into multiple branches can efficiently improve the tags identification efficiency in RFID systems, while the conventional anti-collision algorithms based on multiple branch usually choose the optimal branches based on the tag number estimation, and the estimation delay and error can affect the identification efficiency, an adaptive multiple branche (AMB) algorithm for anti-collision based on binary tree was proposed. The alglorithm uses the number of the identified tags to estimate the tags in the right node of a binary tree in the same level according to the characters of binary tree and chooses the optimal branches, then executes this repeatedly, the system identification efficiency can be improved by avoiding the estimation error caused by only once tag number estimation. The simulation result shows that the AMB algorithm can improve the system identification efficiency, which reaches 43% when in large tag number quantity. Meanwhile, the algorithm is compatible with the existing protocols by only adding several counters in the reader and without changing any air interface orotocol.