DocumentCode
263475
Title
A Unified Approach for Fast and Accurate Cardinality Estimation in RFID Systems
Author
Wenchao Jiang ; Yanmin Zhu
Author_Institution
Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ., Shanghai, China
fYear
2014
fDate
28-30 Oct. 2014
Firstpage
407
Lastpage
415
Abstract
Radio Frequency IDentification (RFID) systems have rich applications in daily life. A crucial problem in RFID systems is to estimate the cardinality of RFID tags. Most exiting probabilistic RFID cardinality estimation algorithms utilize a certain pattern hidden in the response vector formed by the tag responses to make estimators. In this paper, we argue that finding the patterns is actually not necessary! In this paper, we present a novel approach to RFID cardinality estimation by making the full use of the whole response vector. We characterize the critical relationship between the number of RFID tags and the specific distribution of the bits in the response vector. In this paper, we consider two kinds of responses, i.e., empty / non-empty responses and empty / singleton / collision responses. To cater for RFID systems with a very large number of tags, we also generalize our estimation approach to handle geometrically distributed response vectors. Both rigid theoretical analysis and extensive simulations have been conducted and the conclusive results demonstrate that our approach is more accurate than existing state-of-the-art RFID estimation approaches.
Keywords
estimation theory; radiofrequency identification; RFID cardinality estimation algorithms; RFID systems; RFID tags; geometrically distributed response vectors; radio frequency identification systems; Conferences; Mobile communication; Sensor systems; RFID; cardinality; estimation; geometric distribution; maximum likelihood;
fLanguage
English
Publisher
ieee
Conference_Titel
Mobile Ad Hoc and Sensor Systems (MASS), 2014 IEEE 11th International Conference on
Conference_Location
Philadelphia, PA
Print_ISBN
978-1-4799-6035-4
Type
conf
DOI
10.1109/MASS.2014.34
Filename
7035710
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