Tag Identification and Estimation in RFID Systems

PhD Qualifying Examination


Title: "Tag Identification and Estimation in RFID Systems"

by

Mr. Haoxiang Liu


Abstract:


Radio Frequency Identification (RFID) technology is increasingly used in object 
tracking, inventory control, supply management etc. A typical RFID system 
consists of multiple readers and tags, where each tag is assigned a unique ID 
and attached to an object. An RFID reader can remotely collect +tag IDs for tag 
identification. There are two major fundamental problems in RFID systems, 
namely how to efficiently identify the tag IDs and how to rapidly count the 
number of tags especially in a large scale RFID system. The standard MAC-layer 
tag identification protocol is based on framed slotted ALOHA (FSA), which is 
inefficient in essence. FSA can achieve a maximum identification efficiency of 
1/e = 36.8%. Specifically, a maximum of 36.8% of tags can be identified in one 
round of identification. To improve the identification efficiency of FSA, a 
number of approaches are proposed, either using MAC layer or physical layer 
techniques. Counting the number of tags can be trivially accomplished by 
identifying each of the tags. This approach, however, takes too long time 
especially in large scale RFID systems. Rather than count precisely, we can 
derive an estimation of tag set cardinality using much quicker methods. The 
majority of tag cardinality estimation schemes adopt statistical methods and 
usually several rounds of estimation are required to approximate the fixed 
precision.

In this survey, we will review a series of tag identification and cardinality 
estimation methods primarily in single-reader-multi-tag scenario.The 
identification and estimation efficiency of different protocols will also be 
presented.


Date:			Wednesday, 9 January 2013

Time:                   4:00pm - 6:00pm

Venue:                  Room 3501
                         lifts 25/26

Committee Members:	Dr. Yunhao Liu (Supervisor)
                         Dr. Ke Yi (Supervisor)
 			Prof. James Kwok (Chairperson)
 			Dr. Lei Chen


**** ALL are Welcome ****