Dynamic framed binary tree (DFBT)-based RFID anticollision method

Abstract

The invention provides a dynamic framed binary tree (DFBT)-based RFID anticollision method, and combines ideas of two types of existing label anticollision algorithms. A Vogt algorithm is adopted to estimate the number of to-be-identified labels in advance, a dynamic frame slotted ALOHA algorithm is selected to identify the labels, unidentified labels are extracted and subjected to collision position determination, and collision label splitting is carried out by combining the collision position condition and a binary tree algorithm. A simulation result shows that with a DFBT algorithm, identification time is shortened, the total number of required time slots is reduced and the identification efficiency is raised; when the label number reaches to around 1000, the system identification efficiency can still be maintained at around 64%; the identification efficiency of the DFBT algorithm is improved by 210% and 30% compared with that of the dynamic frame slotted ALOHA algorithm and that of a backward binary search tree algorithm respectively; and the method provided by the invention is featured by high stability and low cost and has a good application prospect in the current field of Internet of Things.

Description

technical field [0001] The invention belongs to the multi-label reading technology in the technical field of radio frequency identification, and relates to a method for solving the multi-label collision problem in the RFID system. Background technique [0002] Radio Frequency Identification (RFID) technology, as one of the core technologies of the Internet of Things, is being widely used in various fields with the rapid development of the Internet of Things. Radio frequency identification technology is a non-contact automatic data collection technology that uses space electromagnetic waves as the transmission medium. Its basic principle is to use electromagnetic propagation and radio frequency signals to realize automatic identification of objects to be identified. Compared with traditional identification technology, it can complete information input and processing without contact, non-optical visibility, and non-manual intervention. It has the advantages of convenient opera...

AI Technical Summary

Problems solved by technology

Although this type of algorithm can achieve a 100% tag reading rate, when the number of tags is large, that is, when the number of tags is large, the frequency of collisions will increase greatly, and each collision can only generate two branches, and the recognition time will decrease. increase sharply, the search efficiency will decrease

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