Framed slotted ALOHA with grouping tactic and binary selection for anti-collision in RFID systems

In radio frequency identification (RFID) systems, tag collision arbitration is a significant issue for fast tag identification. This article proposes a novel tag anti-collision algorithm called framed slotted ALOHA with grouping tactic and binary selection (GB-FSA). The novelty of GB-FSA algorithm is that the reader uses binary tree algorithm to identify the tags according to the collided slot counters information. Furthermore, to save slots, tags are randomly divided into several groups based on the number of collided binary bits in the identification codes (IDs) of tags, and then only the number of the first group of tags is estimated. Performance analysis and simulation results show that the GB-FSA algorithm improves the identification efficiency by 9.9%–16.3% compared to other ALOHA-based tag anti-collision algorithms when the number of tags is 1 000.