基于分组动态帧时隙的射频识别防碰撞算法

Reducing tag collision in radio frequency identification systems by using a grouped dynamic frame slotted ALOHA algorithm

提出了动态调整帧长度原则和标签分组方法,在此基础上结合二者设计了一种新型的分组动态帧时隙防碰撞算法,首先对未识别的标签进行数量估计,如果标签数量超过临界值,则对标签进行分组,通过动态调整识别帧长适应每组标签数量进行高效识别.仿真结果表明:系统吞吐率稳定在34.6%—36.8%之间,识别过程所需要的时隙数也保持了线性增加,在待识别标签数量大于2000的情况下,与传统的防碰撞算法相比,时隙效率提高了30%以上,极大优化了系统的吞吐率,节约系统资源.

In a radio frequency identification system, designing a tag anti-collision algorithm with good performance is the key to improving the system throughput. In this paper, we propose a principle of dynamic frame size regulation and a method of tag grouping, and design a novel algorithm called grouped dynamic framed slotted ALOHA （GDFSA） through combining the above, which first estimates the number of unread tags and divides them into groups, then uses dynamic frame slotted ALOHA in each group. The simulation results show that the proposed algorithm can stabilize the throughput rate between 34.6%–36.8% and the time slots increase linearly in the identification procedure. When the tag number is beyond 2000 compared with conventional algorithms, the proposed algorithm can enhance the slot efficiency by 30%, and optimize the throughput rate obviously and save the system resource.