Paper Info
Title
A New GA-Based Resource Allocation Scheme for a Reader-to-Reader Interference Problem in RFID Systems
Abstract
In radio frequency identification (RFID) system, the reader-to-reader interference leads to reader collision that disturbs readers in tag recognition. The existing reader anti-collision techniques based on TDM or FDM are inefficient solutions to the reader collision problem since they do not consider jointly the distance between the interfering readers and the frequencies, and time slots that readers use. In this paper, we formulate a TDM/FDM-based reader-to-reader interference model to analyze the effects of the above factors and an optimization problem to maximize the RFID system performance. We then propose a novel resource allocation technique based on genetic algorithm (RA-GA) to solve the optimization problem. The RA-GA includes a unique encoding scheme and fitness function to obtain an optimal resource allocation for the RFID system effectively. Simulation results show that the RA-GA is superior to the resource allocation based on random method.
Year
DOI
Venue
2010
10.1109/ICC.2010.5502751
ICC
Keywords
Field
DocType
unique encoding scheme,fitness function,random method,radiofrequency interference,time division multiplexing,reader collision,fdm,resource allocation,optimal resource allocation,tag recognition,optimization problem,codes,radiofrequency identification,rfid systems,genetic algorithm,tdm,genetic algorithms,reader-to-reader interference problem,frequency division multiplexing,ga-based resource allocation scheme,reader anticollision techniques,optimization,encoding,radio frequency identification,frequency,time frequency analysis,backscatter,resource management,interference,system performance
Resource management,Telecommunications,Computer science,Computer network,Fitness function,Resource allocation,Collision problem,Optimization problem,Computer engineering,Radio-frequency identification,Genetic algorithm,Encoding (memory)
Conference
ISSN
ISBN
Citations 
1550-3607
978-1-4244-6402-9
19
PageRank 
References 
Authors
0.88
3
2
Name
Order
Citations
PageRank
Hyun-Sik Seo1342.75
Chaewoo Lee233127.28