Research Of Anti-Collision Algorithm Based On ALOHA For RFID System

Radio Frequency Identification is a non-contact automatic identification technology, its principle is to use a radio frequency signal through electromagnetic coupling space (alternating magnetic or electromagnetic field) and achieve the purpose of identification with the information transmitted by radio frequency. Compared to other automatic identification techno logy(bar code technology, optical recognition, biometrics, etc),RFID technology have the advantages of high accuracy, strong ability to adapt to the environment, non-visual range reader, long service time,which is widely used in industrial automation, transportation management, animal and vehicle identification, access control system, library management. RFID technology is one of the four core technologies of Internet of Things, with the rapid development of the Internet of Things, has a very broad application prospects in the future.With the rapid development of RFID technology, the reader need to identification a large number of tags in a short time accurately. In the RFID system, tags collision will happen when multiple tags simultaneously communicate with the reader, tag anti-collision algorithm is to solve this problem. The design of tag anti-collision algorithm is the focal point research of RFID technology in order to reducing recognition time and improve of RFID system throughput in conditions of the control tag cost and complexity of the algorithm. This paper studies the RFID anti-collision algorithm based on ALOHA and improves it.Paper firstly introduces the composition and the working principle of radio frequency identification system. Secondly, it focuses on radio frequency identification system anti-collision algorithm. Thirdly, it analyzes tag anti-collision algorithm based on ALOHA and analyze the performance of typical ALOHA algorithm in detail and compares them. It draws conclusions that the two most critical factors affected the performance of the RFID system: first, estimation of tags; second, frame length adjustment. Finally, based on in-depth analysis of dynamic frame slotted ALOHA algorithm, paper optimize tags estimation algorithm and frame length adjustment:in tag estimation algorithm, take the idea of recursion, multiplied by a factor and the number of tags, the number of slots by the successful collision, the collision slot number and frame size, and obtain the relationship expectations of collision time slots and factor, in order to reduce the error rate; In DFSA algorithm, when the frame size equals to the number of un-identified tags, frame length adjustment is frequent and has more collision time slots, in order to solve this problem, it put forward Linear-regression-based dynamic framed slotted ALOHA algorithm, In the condition of holding more than35%of the throughput of the system, obtained relationship between the frame length and the number of tags by linear fit, describes the basic principles of the improved algorithm and simulates the improved algorithm,analysis of the throughput performance of the system. The simulation results show that the improved algorithm to achieve simply, and reduces the number of tag collision slots and reduces the times of frame length adjustment and the more tags the better performance and reduce the system delay time effectively.