可并行识别的分组动态帧时隙ALOHA标签防碰撞算法

该文针对现有动态帧时隙ALOHA标签防碰撞算法的系统吞吐率低、算法效率低等问题，提出一种可并行识别的分组动态帧时隙ALOHA(PIGDFSA)标签防碰撞算法。该文以实验为基础，探索了待识别标签数、标签分组数、帧长对系统吞吐率与标签碰撞率的影响，研究了提升系统吞吐率与降低标签碰撞率的策略与方法。结合射频识别(RFID)的多天线系统，引入FastICA技术，从而实现碰撞时隙重新定义，并以此为基础，利用未识别标签数目自适应确定分组数与帧长。仿真结果表明：PIGDFSA算法在标签数达到2000时，算法吞吐率仍能稳定在92%以上，与FSA-256, GDFSA, BSDBG等算法相比具有更高的算法吞吐率，更少的空隙时隙，更高的算法效率。

Grouped Dynamic Frame Slotted ALOHA Tag Anti-collision Algorithm Based on Parallelizable Identification

In order to solve the problem of low throughput rate and efficiency of the current dynamic frame slot ALOHA collision algorithms, a grouped dynamic frame slotted ALOHA tag anti-collision algorithm based on Parallelizable identification (PIGDFSA) is proposed. Based on the experiments, the method and strategy of increasing the system throughput rate and lowering the tag collision rate are presented by exploring effects of the number of the tags and its groups, the frame length on the system throughout and tag collision rate. Combining the multi-antenna of the RFID system and FastICA technology, the collision slot can be redefined, and the number of the unrecognized tags can be used to set the number of groups and frame length adaptively. The simulation results show that the PIGDFSA algorithm can stabilize the throughput rate more than 92% when the number of tags reaches 2000, and it has higher throughput rate, lesser idle slot and higher algorithm efficiency compared with the FSA-256, GDFSA, and BSDBG algorithm.