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Retrospective Maximum Likelihood Decision Rule for Tag Cognizance in RFID Networks  

Kim, Joon-Mo (Dankook University)
Park, Jin-Kyung (Dankook University)
Ha, Jun (Dankook University)
Seo, Hee-Won (Dankook University)
Choi, Cheon-Won (Dankook University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea TC / v.48, no.2, 2011 , pp. 21-28 More about this Journal
Abstract
We consider an RFID network configured as a star in which tags stationarily move into and out of the vicinity of the reader. To cognize the neighboring tags in the RFID network, we propose a scheme based on dynamic framed and slotted ALOHA which determines the number of slots belonging to a frame in a dynamic fashion. The tag cognizance scheme distinctively employs a rule for estimating the expected number of neighboring tags, identified as R-retrospective maximum likelihood rule, where the observations attained in the R previous frames are used in maximizing the likelihood of expected number of tags. Simulation result shows that a slight increase in depth of retrospect is able to significantly improve the cognizance performance.
Keywords
RFID; tag cognizance; ALOHA; maximum likelihood rule; cognizance rate;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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