An enhanced tag estimation method applied to tag anti-collision algorithm in RFID systems

In RFID systems, if two or more tags response a reader simultaneously, communication conflict or data interference (i.e. reader collision and/or tag collision) will occur. As a result, the reader cannot receive information of these tags correctly. In order to solve this type of tag collision problem, many tag anti-collision algorithms have been proposed, such as a series of Aloha-based algorithms and their varieties. As one of representatives of Aloha-based algorithms family, Dynamic Frame Slotted Aloha Algorithm (DFSA) is capable of changing the number of slots in a single frame dynamically according to the collision situation in the previous frame. When the number of slots in a frame equals the number of unidentified tags, the RFID system will win the best throughput. In this case, tag collision problem is focused on tag estimation. Because that the traditional Tag Estimation Method (TEM) ignores such information as number of empty slots and slots filled with only one tag, this paper proposes an enhanced tag estimation method (ETEM) to improve estimation accuracy. The simulation results indicate that the proposed ETEM algorithm performs better in both identification time and estimation error than the traditional TEM.