Bayesian estimation in dynamic framed slotted ALOHA algorithm for RFID system

摘要

This paper develops a novel dynamic framed slotted ALOHA (DFSA) algorithm based on Bayesian estimation to improve the throughput of the radio frequency identification (RFID) system. At first, four types of anti-collision algorithms for tag identification are analyzed. Then, the proposed DFSA based on Bayesian estimation is deduced and introduced. Compared with the conventional DFSA algorithms, this algorithm takes advantage of the evidence in previous frames as the a priori information of the current frame which can end up with more precise estimation of tag number and rational frame length adjustment. Finally, the common simulation tool from Matlab is used to demonstrate the effectiveness of the proposed new algorithm for the average throughput improvements of the RFID system.