By Topic

Efficient Estimation and Collision-Group-Based Anticollision Algorithms for Dynamic Frame-Slotted ALOHA in RFID Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chun-Fu Lin ; Dept. of Inf. Manage., Nat. Taiwan Univ., Taipei, Taiwan ; Lin, F.Y.-S.

There are two challenges for the frame-slotted ALOHA algorithms in radio-frequency identification (RFID). The first challenge is estimating unknown tag-set size accurately; the second challenge is improving the efficiency of the arbitration process so that it uses less time slots to read all tags. This study proposes estimation algorithm based on the Poisson distribution theory and identifies the overestimation phenomenon in full collision. Our novel anticollision algorithm alternates two distinct reading cycles for dividing and solving tags in collision groups. This makes it more efficient for a reader to identify all tags within a small number of time slots.

Published in:

Automation Science and Engineering, IEEE Transactions on  (Volume:7 ,  Issue: 4 )