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

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.