Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/65967
Title: Efficient physical-layer unknown tag identification in large-scale RFID systems
Authors: Zhu, F
Xiao, B
Liu, J
Chen, LJ
Keywords: Physical layer
RFID system
Time efficiency
Unknown tag identification
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on communications, 2017, v. 65, no. 1, 7736075, p. 283-295 How to cite?
Journal: IEEE transactions on communications 
Abstract: Radio frequency identification (RFID) is an automatic identification technology that brings a revolutionary change to quickly identify tagged objects from the collected tag IDs. Considering the misplaced and newly added tags, fast identifying such unknown tags is of paramount importance, especially in large-scale RFID systems. Existing solutions can either identify all unknown tags with low time-efficiency, or identify most unknown tags quickly by sacrificing the identification accuracy. Unlike existing work, this paper proposes a protocol that utilizes physical layer (PHY) information to identify the intact unknown tag set with high efficiency. We exploit the physical signals in collision slots to separate unknown tags from known tags, a new technique to speed up the ID collection. Such new technique was verified in an RFID prototype system using the USRP-based reader and WISP tags. We also evaluated our protocol to show the efficiency of leveraging PHY signals to successfully get all unknown tag IDs without wasted known tag ID transmission. Simulation results show that our protocols outperform prior unknown tag identification protocols. For example, given 1000 unknown tags and 10 000 known tags, our best protocol has 56.8% less time to the state-of-the-art protocol when collecting all unknown tag IDs.
URI: http://hdl.handle.net/10397/65967
ISSN: 0090-6778
EISSN: 1558-0857
DOI: 10.1109/TCOMM.2016.2625252
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

15
Last Week
0
Last month
Checked on Sep 25, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.