Optimal channel-sensing scheme for cognitive radio systems based on fuzzy Q-learning

Fereidoun H. Panahi, Tomoaki Ohtsuki

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


In a cognitive radio (CR) network, the channel sensing scheme used to detect the existence 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 the inefficiency of the sensing scheme. This may yield primary user interference and low system performance. In this paper, we present a learning-based scheme for channel sensing in CR networks. Specifically, we formulate the channel sensing problem as a partially observableMarkov 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. Simulation results show the effectiveness and efficiency of our proposed scheme.

Original languageEnglish
Pages (from-to)283-294
Number of pages12
JournalIEICE Transactions on Communications
Issue number2
Publication statusPublished - 2014 Jan 1


  • Baum-Welch Algorithm (BWA)
  • Cognitive radio (CR)
  • Fuzzy Q-Learning (FQL)
  • Partially observable Markov decision process (POMDP)

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering


Dive into the research topics of 'Optimal channel-sensing scheme for cognitive radio systems based on fuzzy Q-learning'. Together they form a unique fingerprint.

Cite this