Title :
RFID reader anti-collision using chaos neural network based on annealing strategy
Author :
Tian, Jinghe ; Fan, Yushun ; Zhu, Yunlong ; Hu, KunYuan
Abstract :
In a dense reader environment, RFID system performance will be limited by the reader collision so much that all the readers can not operate normally. In order to eliminate reader collisions in RFID system, this paper presents a RFID anti-collision algorithm-chaos neural network based on annealing strategy (RAC-ACNN). By the algorithm, any two readers that potentially collide with each other will be assigned two different time slots in which readers are permitted to operate. The algorithm possesses the capability of ergodic random search due to chaos mechanism, and it can control the departure of chaos state by annealing strategy. The simulation result shows that ACNN has high speed and success rate of convergence, which tests that the algorithm proposed in this paper is a reliable and efficient algorithm for RFID reader anti-collision.
Keywords :
chaos; neural nets; radiofrequency identification; search problems; simulated annealing; RFID reader anticollision; RFID system performance; annealing strategy; chaos neural network; ergodic random search; reader environment; Annealing; Automation; Chaos; Chaotic communication; Frequency; Interference; Network servers; Neural networks; Radiofrequency identification; Time division multiple access; Chaos neural network; RFID reader anti-collision; annealing;
Conference_Titel :
Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4244-2113-8
Electronic_ISBN :
978-1-4244-2114-5
DOI :
10.1109/WCICA.2008.4594560