DocumentCode :
3770377
Title :
Multilayer Feed-forward Neural Network learning based Dynamic Chinese restaurant model for dynamic spectrum access in cognitive radio networks
Author :
Jianlan Liu;Xiao jun Jing;Songlin Sun;Xiaohan Wang;Dongmei Cheng;Hai Huang
Author_Institution :
Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Minstry of Education, Beijing University of Posts and Telecommunications, China
fYear :
2015
Firstpage :
173
Lastpage :
176
Abstract :
As an effective approach to improve spectrum efficiency, cognitive radio network make it possible for secondary users (SU) to share the spectrum with primary users (PU), on the condition that the primary users have preemptive priority. In this paper, we applied the Dynamic Chinese restaurant game, which ideally modeled the spectrum sensing and access in cognitive network. We propose the use of Multilayer Feed-forward Neural Networks (MFNN) as an effective method for users to learn the network state, which can be regarded as how a customer learn the table state in the restaurant. Moreover, in order to select an optimal table for a secondary user, subsequent secondary users´ sequential decisions are considered. The effectiveness and efficiency of the proposed scheme is verified in the simulation.
Keywords :
"Cognitive radio","Neurons","Games","Sensors","Neural networks","Information and communication technology","Nonhomogeneous media"
Publisher :
ieee
Conference_Titel :
Communications and Information Technologies (ISCIT), 2015 15th International Symposium on
Type :
conf
DOI :
10.1109/ISCIT.2015.7458335
Filename :
7458335
Link To Document :
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