Multi-label anti-collision method based on grouping mechanism and jumping dynamic binary recognition

Abstract

The invention discloses a multi-label anti-collision method based on a grouping mechanism and jumping dynamic binary recognition used in an RFID system. The method comprises a label estimation phase and a label recognition phase, wherein in the label estimation phase, labels are grouped randomly, a first group of labels are recognized by adopting the jumping dynamic binary algorithm, and then the estimation of the quantity of unrecognized labels are completed according to the characteristics that the quantity of each group of labels are in accordance with even distribution; in the label recognition phase, a second grouping quantity, i.e. the optimal grouping conducted on the rest groups of labels is determined; in the recognition process, jumping dynamic binary algorithm is adopted to recognize collision labels, so as to recognize all the labels. The invention combines the advantages of binary tree algorithm and Aloha algorithm, thus greatly reducing the quantity of collision labels in the early and later phases of recognition. The invention has simple structure, rapid recognition speed, low complexity and label power consumption, thus being applicable to RFID system.

Description

technical field [0001] The invention belongs to the interdisciplinary field of electronics, computer and communication technologies, and relates to a technology for the Internet of Things, in particular to a multi-tag anti-collision method based on grouping mechanism and jump dynamic binary identification used in RFID systems. Background technique [0002] RFID is an automatic identification technology, which uses radio frequency to conduct non-contact two-way data communication to identify targets. A typical RFID system generally consists of RFID tags, readers, and computer systems. The RFID tag generally stores coded data in an agreed format, which is used to uniquely identify the object to which the tag is attached. Compared with traditional identification methods, RFID technology can complete information input and processing without direct contact, without optical visualization, and without manual intervention, and the operation is convenient and fast. It can be widely...

AI Technical Summary

Problems solved by technology

These two types of algorithms have their own advantages and disadvantages: the complexity of the Aloha algorithm and the requirements for labels are low, but there is an unstable working range, and it may lead to the "label starvation problem", that is, some specific labels may be in a very long It cannot be recognized within a short period of time; the recognition rate of the binary tree algorithm can reach 100%, that is, there is no "label starvation problem", but the algorithm is more complicated and the recognition time is longer

When the number of tags is large, the recognition efficiency of traditional anti-collision algorithms is usually low

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