中国邮电高校学报(英文) ›› 2009, Vol. 16 ›› Issue (4): 47-52.doi: 10.1016/S1005-8885(08)60247-2

• Networks • 上一篇    下一篇

Framed slotted ALOHA with grouping tactic and binary selection for anti-collision in RFID systems

王亚奇,蒋国平,王静   

  1. Center for Control and Intelligence Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
  • 收稿日期:2008-08-04 修回日期:1900-01-01 出版日期:2009-08-31
  • 通讯作者: 王亚奇

Framed slotted ALOHA with grouping tactic and binary selection for anti-collision in RFID systems

WANG Ya-qi , JIANG Guo-ping, WANG Jing   

  1. Center for Control and Intelligence Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
  • Received:2008-08-04 Revised:1900-01-01 Online:2009-08-31
  • Contact: WANG Ya-qi

摘要:

In radio frequency identification (RFID) systems, tag collision arbitration is a significant issue for fast tag identification. This article proposes a novel tag anti-collision algorithm called framed slotted ALOHA with grouping tactic and binary selection (GB-FSA). The novelty of GB-FSA algorithm is that the reader uses binary tree algorithm to identify the tags according to the collided slot counters information. Furthermore, to save slots, tags are randomly divided into several groups based on the number of collided binary bits in the identification codes (IDs) of tags, and then only the number of the first group of tags is estimated. Performance analysis and simulation results show that the GB-FSA algorithm improves the identification efficiency by 9.9%–16.3% compared to other ALOHA-based tag anti-collision algorithms when the number of tags is 1 000.

关键词:

RFID,;anti-collision,;binary;tree,;identification;efficiency;

Abstract:

In radio frequency identification (RFID) systems, tag collision arbitration is a significant issue for fast tag identification. This article proposes a novel tag anti-collision algorithm called framed slotted ALOHA with grouping tactic and binary selection (GB-FSA). The novelty of GB-FSA algorithm is that the reader uses binary tree algorithm to identify the tags according to the collided slot counters information. Furthermore, to save slots, tags are randomly divided into several groups based on the number of collided binary bits in the identification codes (IDs) of tags, and then only the number of the first group of tags is estimated. Performance analysis and simulation results show that the GB-FSA algorithm improves the identification efficiency by 9.9%–16.3% compared to other ALOHA-based tag anti-collision algorithms when the number of tags is 1 000.

Key words:

RFID;anti-collision;binary tree;identification efficiency