基于树形框架的随机分组反碰撞算法

现存反碰撞算法不能有效处理中小规模标签识别问题。为此，提出一种基于树形框架的随机分组反碰撞算法。在树形算法的基础上，改进标签分组方法，采用标签随机选择的方法对标签进行分组，由此形成标签识别树。实验结果表明，该算法相对帧时隙ALOHA算法，识别吞吐率上升约10%，相对树形算法实现更简单。

Anti-collision Algorithm with Random Grouping Based on Tree Framework

The existing anti-collision algorithm can not deal with the problem of small and medium size labels identification.In order to solve this problem,this paper proposes an anti-collision algorithm with random grouping based on tree framework.The algorithm which is based on tree algorithm improves the tags grouping method.It uses the label random selection method to group the tags,and establishes the tags identification tree.Experimental results show that compared with the frame slotted ALOHA algorithm,the throughput of this algorithm increases by 10%,and the implementation is simpler than algorithms based on tree.