Applying Cubic Spline Method to Estimate the Number of RFID Tags in Error-Prone Communication Channels

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2 Citations (Scopus)

Abstract

Radio frequency identification systems aid in fast identification of tagged objects simultaneously, by means of radio signals. However, when radio frequency signals are emitted simultaneously, there is a probability of collision occurrence because of which the identification process may fail, and thereby resulting in a waste of resources. Therefore, several anti-collision algorithms have been proposed to reduce the probability of collision occurrence. In almost all the existing anti-collision algorithms, a prior knowledge of the number of tags has a significant effect on the efficiency of the algorithms. However, since the exact number of tags is unavailable, it is essential to develop an accurate tag estimation method to reduce the collision probability. In this paper, the authors present a novel tag estimation method, which estimates the number of tags by means of the captured number of idle slots, by applying the cubic spline technique. Besides presenting highly accurate estimation results, this method also demonstrates compatibility with error-prone communication channels. Cubic spline method estimates the number of tags accurately, with <1 % error rate. Based on the results, it is observed that more accurate estimation results from the proposed method provides greater channel efficiency and lowers the average identification time.

Original languageEnglish
Pages (from-to)361-382
Number of pages22
JournalWireless Personal Communications
Volume83
Issue number1
DOIs
Publication statusPublished - 10 Jul 2015

Fingerprint

Radio frequency identification (RFID)
Splines
Identification (control systems)

Keywords

  • Anti-collision algorithms
  • Cubic spline interpolation
  • Estimation methods
  • Framed slotted ALOHA
  • RFID systems
  • Tag identification

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications

Cite this

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title = "Applying Cubic Spline Method to Estimate the Number of RFID Tags in Error-Prone Communication Channels",
abstract = "Radio frequency identification systems aid in fast identification of tagged objects simultaneously, by means of radio signals. However, when radio frequency signals are emitted simultaneously, there is a probability of collision occurrence because of which the identification process may fail, and thereby resulting in a waste of resources. Therefore, several anti-collision algorithms have been proposed to reduce the probability of collision occurrence. In almost all the existing anti-collision algorithms, a prior knowledge of the number of tags has a significant effect on the efficiency of the algorithms. However, since the exact number of tags is unavailable, it is essential to develop an accurate tag estimation method to reduce the collision probability. In this paper, the authors present a novel tag estimation method, which estimates the number of tags by means of the captured number of idle slots, by applying the cubic spline technique. Besides presenting highly accurate estimation results, this method also demonstrates compatibility with error-prone communication channels. Cubic spline method estimates the number of tags accurately, with <1 {\%} error rate. Based on the results, it is observed that more accurate estimation results from the proposed method provides greater channel efficiency and lowers the average identification time.",
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AB - Radio frequency identification systems aid in fast identification of tagged objects simultaneously, by means of radio signals. However, when radio frequency signals are emitted simultaneously, there is a probability of collision occurrence because of which the identification process may fail, and thereby resulting in a waste of resources. Therefore, several anti-collision algorithms have been proposed to reduce the probability of collision occurrence. In almost all the existing anti-collision algorithms, a prior knowledge of the number of tags has a significant effect on the efficiency of the algorithms. However, since the exact number of tags is unavailable, it is essential to develop an accurate tag estimation method to reduce the collision probability. In this paper, the authors present a novel tag estimation method, which estimates the number of tags by means of the captured number of idle slots, by applying the cubic spline technique. Besides presenting highly accurate estimation results, this method also demonstrates compatibility with error-prone communication channels. Cubic spline method estimates the number of tags accurately, with <1 % error rate. Based on the results, it is observed that more accurate estimation results from the proposed method provides greater channel efficiency and lowers the average identification time.

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