Paper Info
Title
Optimal channel-sensing policy based on Fuzzy Q-Learning process over cognitive radio systems
Abstract
In a cognitive radio (CR) network, the channel sensing scheme to detect the appearance of a primary user (PU) directly affects the performances of both CR and PU. However, in practical systems, the CR is prone to sensing errors due to inefficient sensing scheme. This may lead to interfering with primary user and low system performance. In this paper, we present a learning based scheme for channel sensing in CR network. Specifically, we formulate the channel sensing problem as a partially observable Markov decision process (POMDP), where the most likely channel state is derived by a learning process called Fuzzy Q-Learning (FQL). The optimal policy is derived by solving the problem. The simulation results show the effectiveness and efficiency of our proposed scheme.
Year
DOI
Venue
2013
10.1109/ICC.2013.6654941
Communications
Keywords
Field
DocType
Markov processes,cognitive radio,fuzzy set theory,learning (artificial intelligence),telecommunication computing,wireless channels,CR network,FQL,POMDP,PU,channel sensing scheme,cognitive radio systems,fuzzy Q-Learning process,optimal channel sensing policy,partially observable Markov decision process,primary user,sensing errors,Cognitive Radio (CR),Fuzzy Q-Learning (FQL),Reinforcement learning (RL),channel sensing,partially observable Markov decision process (POMDP)
Markov process,Fuzzy q learning,Partially observable Markov decision process,Computer science,Fuzzy logic,Communication channel,Fuzzy set,Artificial intelligence,Telecommunication computing,Cognitive radio
Conference
ISSN
Citations 
PageRank 
1550-3607
6
0.44
References 
Authors
9
2
Name
Order
Citations
PageRank
Fereidoun H. Panahi1225.12
Tomoaki Ohtsuki2182.34