Bayesian Sequential Learning for Railway Cognitive Radio

  • Cheng Wang Soochow University
  • Yiming Wang Soochow University
  • Cheng Wu Soochow University
Keywords: railway, cognitive radio, MAC protocol, naive Bayesian method, spectrum management

Abstract

Applying cognitive radio in the railway communication systems is a cutting-edge research area. The rapid motion of the train makes the spectrum access of the railway wireless environment instable. To address the issue, first we formulate the spectrum management of railway cognitive radio as a distributed sequential decision problem. Then, based on the available environmental information, we propose a multi-cognitive-base-station cascade collaboration algorithm by using naive Bayesian learning and agent theory. Finally, our experiment results reveal that the model can improve the performance of spectrum access. This cognitive-base-station multi-agent system scheme comprehensively solves the problem of low efficiency in the dynamic access of the railway cognitive radio. The article is also a typical case of artificial intelligence applied in the field of the smart city.

Author Biographies

Cheng Wang, Soochow University

CHENG WANG was born in Xuzhou , Jiangsu
Privince, China in 1995.
He received the B.S. and M.S. degrees in communication engineering from the Soochow University in 2017.
His research interests include dynamic multiagent systems, intelligent human-computer interaction and Big Data technology and applications.

Yiming Wang, Soochow University

WANG YIMING received the M.Sc. degree in
computer engineering from Soochow University,
and the Ph.D. degree from Nanjing University of
Posts and Communications.
Currently, she is a Full Professor at the School
of Urban Rail Transportation, Soochow University, China. Her research interests include wireless communications, cognitive wireless sensor network, and intelligent transportation technology
and applications.
She authored or co-authored over 60 publications in Wireless Personal Communications, Chinese Journal of Electronics and IEEE GlobalSIP
Conference etc. She was also involved in several projects in which these techniques are being applied in the fields of communication, robotics and computer vision. She is also an active reviewer for Wireless Communications and Mobile Computing, and System and Signal Processing etc.

Cheng Wu, Soochow University
CHENG WU received the M.Sc. degree in computer engineering from Concordia University in Canada, in 2005, and the Ph.D. degree from Northeastern University, USA, in 2010.
Currently, he is an Associate Professor at the
School of Urban Rail Transportation, Soochow
University, China. His research interests include
neural and fuzzy systems, dynamic multi-agent
systems, intelligent human-computer interaction
and Big Data technology and applications.
He authored or co-authored over 20 publications in International Journal of Intelligent and Fuzzy System, International Conference on Autonomous
Agents and Multi-agent Systems etc. He was also involved in several projects in which these techniques are being applied in the fields of communication, robotics and computer vision.

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Published
2019-03-26
How to Cite
1.
Wang C, Wang Y, Wu C. Bayesian Sequential Learning for Railway Cognitive Radio. Promet - Traffic & Transportation [Internet]. 26Mar.2019 [cited 22Apr.2019];31(2):141-9. Available from: http://traffic.fpz.hr/index.php/PROMTT/article/view/2934
Section
Articles