基于马尔科夫链的帧时隙ALOHA防碰撞算法仿真与研究

Simulation and Research on Frame Slotted ALOHA Anti-collision Algorithm Based on Markov Chain Model

为了研究帧时隙ALOHA防碰撞算法性能,应用马尔科夫链模型对该算法标签识别过程进行数学分析,得到成功识别出的标签数量的状态转移概率矩阵.用蒙特卡罗统计方法模拟这一过程,对马尔科夫链模型求解,得到了标签数量、时隙数和成功识别率之间的关系曲线.

In order to study the performance of the frame slotted ALOHA anti-collision algorithm,by use of the Markov Model,a mathematical analysis was done to the tag identification process of this algorithm and a state transition probability matrix is thus obtained for the successful identification of the number of tags.By using the Monte-Carlo method to simulate this process,the solution of the Markov Chain Model was worked out and the relationship curve between the number of tags, the number of slots and the rate of successful recognition was obtained.