Group-n-fork tracking tree-type rfid anti-collision algorithm

Abstract

The invention relates to a grouping N-fork tracking tree type RFID anti-collision algorithm (CBGN), which can effectively solve the transmission time delay caused by multiple access of tags to a shared wireless channel in an RFID system. First, the maximum likelihood algorithm (MLE) is used to estimate the number of tags in the application scenario. Secondly, the tag sets in the application environment are grouped according to tag IDs, which effectively reduces the depth of the query tree and avoids the problem of high initial collision probability of the tree algorithm. The CBGN algorithm distributes the tag sets on multiple subtrees (each group corresponds to a subtree). Finally, the identification of sub-trees uses N-fork division to construct N-fork trees, and N-fork division further reduces the depth of subtrees to reduce the collision probability. Therefore, the CBGN algorithm adopts the strategy of combining grouping and N-fork segmentation to greatly eliminate idle time slots, reduce the collision probability of label sets, and improve the overall recognition efficiency of the system. The invention provides the optimal grouping coefficients under different fork conditions so that the recognition efficiency of the CBGN algorithm can be optimized.

Description

technical field [0001] The invention relates to a grouping N-fork tracking tree type RFID anti-collision algorithm, which belongs to the field of RFID radio frequency identification under the framework of the Internet of Things. Background technique [0002] In the Internet of Things architecture, radio frequency identification technology (RFID) is the key supporting technology of the Internet of Things. RFID uses radio frequency signals to achieve non-contact information interaction to achieve the purpose of object identification. RFID technology and wireless sensor networks, Internet, computer technology The combination can realize the tracking, positioning and identification of objects, and then realize the integration of management systems and information sharing, so as to endow everything with intelligence, thus forming the Internet of Things that interconnects everything. Among them, RFID technology has the excellent characteristics of reading tags in batches, so it ca...

AI Technical Summary

Problems solved by technology

[0004] Recently, the CT algorithm was proposed, which uses the characteristics of Manchester encoding (ME) to locate the collision bit for label recognition, thereby avoiding the influence of idle time slots in the QT algorithm, so that the algorithm throughput can reach 50%, and obtain The optimal throughput rate of the current tree algorithm, however, when h is low, the tag collision probability is high, that is, there is a problem that the initial query collision probability is high

At the same time, the collision segmentation only performs binary tree segmentation, resulting in a deep query tree. The above two reasons lead to a high collision probability of the CT algorithm and a large number of collision slots.

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