The Study Of RFID Tag Anti-collision Algorithms

Radio frequency identification technology (RFID) is an automatic data collection andnon-contact technology by the transmission medium of space electromagnetic waves. Bywireless radio frequency signals, systems achieve to identify data information automatly andcommunicating in two ways. Due to the high reliability, automatic and fast identification speed,strong real-time, far identifiable distance of RFID technology, are widely used in themanagement, supply, logistic, locate, track and other fields，it’s one of the ten importanttechnology of the21st century.In RFID systems, Tag anti-collision problem is one of the key technologies that need to beresolved. In the identification range of the reader, if multiple tags transmit ID informationsimultaneously to the reader, the information which shares the wireless channel will collide, sothe reader can not identify tag ID successfully. Collision will reduce the efficiency of tagidentification, and the efficiency and speed of tag identification determines the speed andefficiency of the entire RFID system.This paper introduces the development status, prospect and basic principles of RFIDtechnology firstly, and then elaborates the two types of RFID tag anti-collision algorithm:tree-based algorithm and ALOHA-based algorithm. Introduce the principle and performance ofthese two types of algorithm, simulate and compare the performance of the algorithm. Lastly,paper based on the group principle, proposes two new RFID tag anti-collision algorithms-improved intelligent separated tag anti-collision algorithm (IISA) and grouping dynamic frameslot ALOHA collision tracking algorithm (GDCA). IISA algorithm is using an existing algorithmand the principle of collision tracking, reducing the number of collision slots and the trafficeffectly. GDCA algorithm is combining the tags estimating dynamically, grouping and usingbased tree algorithm to identify tags in collision slot, reducing the total number of slots, andimproving the system throughput. The performance simulation of these algorithms shows thatthey accelerate the speed of the tag identification, and improve the efficiency of the systemidentification.