NDLI: Novel RFID method for faster convergence of tag estimation on dynamic frame size ALOHA algorithms

Content Provider	IET Digital Library
Author	Ferreira, Hillner P. A. Assis, Francisco M. Serres, Alexandre R.
Abstract	This paper introduces a novel RFID method for accelerating the tag estimation performance in dynamic framed slotted ALOHA (DFSA) algorithms. Assuming a critical scenario where the number of tags in the interrogation zone is much greater than the initial frame size, the proposed Double-Approximation (DA) method uses, besides the backlog estimation to adjust the size of first frames, a second approximation that successively reduces the tags available to transmit until achieving a faster convergence to the first frame sizes. Once the convergence threshold is achieved, a more accurate tag estimation can be calculated and all temporarily disabled tags become able to transmit again. Simulation results show that all DFSA algorithms implemented with the DA method outperforms the traditional DFSA in terms of throughput and reduction of simultaneous tag signals.
Starting Page	1218
Ending Page	1224
Page Count	7
ISSN	17518628
Volume Number	13
e-ISSN	17518636
Issue Number	Issue 9, Jun (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/13/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2018.5506
Journal	IET Communications
Publisher Date	2019-02-22
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Access Protocols Accurate Tag Estimation Backlog Estimation Combinatorial Mathematics Convergence Threshold Critical Scenario DA Method DFSA Algorithm Double-approximation Method Dynamic Frame Size ALOHA Dynamic Framed Slotted ALOHA Algorithm Faster Convergence Frame Sizes Frames Initial Frame Size Interrogation Zone Novel RFID Method Other Radio Link Protocol Radiofrequency Identification RFID System Simultaneous Tag Signal Tag Estimation Performance Telecommunication Control Temporarily Disabled Tags Traditional DFSA Wireless Channel
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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