An anti‐collision algorithm based on balanced incomplete block design in RFID systems

Abstract

An important challenge in radio frequency identification (RFID) systems is the collision concern. When an interrogator send a request, it has several tags to answer to in its transmission range, and a tag collision has occurred. The interrogator must be able to recognize tags as rapidly as possible. A collision problem is a powerconsuming occurrence that diminishes the operation of RFID structure. This article proposes a tag anti-collision power-clustering RFID algorithm for all tag identification. The tags are boundaries into the several power level clusters based on distances of the reader. Specifically, in the proposed algorithm, tags and readers use of balanced incomplete blocks design (BIBD) to reach a fast identification. In a BIBD matrix, any two columns intersect exactly in one component that makes it possible for easy transmission of any two tags via the tag's identification in their read cycles. The aim of this article is to propose a joint organization that while decreases power consumption increases the working lifetime of RFID structure. The reader can get each tag ID by distinguishing each unit of BIBD symbols, one by one. The use of proposed algorithm brings about a great improvement in the power consumption and identification time. K E Y W O R D S algorithm, collision, power consumption, RFID

Design of Distance Teaching System for Interior Design Course Based on Internet of Things and Education Platform

“…The gateway needs to save all the spread spectrum codes and the corresponding relationship with the terminal node. After receiving the data, it uses the spread spectrum code to separate the corresponding data [14].…”

Computer Algorithm Design and Linearity Analysis of Its Data Structures

“…The complexity of algorithms includes the time complexity and space complexity, the time complexity refers to the algorithms need to spend more time in the process of arithmetic, and the space complexity refers to the size of the storage space that the algorithm needs to occupy [3], [4]. In terms of operational efficiency, it is mainly constrained by the resources of both workload and space, and the complexity of the algorithm leads to the difficulty of the operational work, so it is necessary to reduce the complexity of the algorithm.…”