NDLI: Self-Learning Repeated Game Framework for Distributed Primary-Prioritized Dynamic Spectrum Access

Content Provider	IEEE Xplore Digital Library
Author	Wang, B. Zhu, J. Liu, K.J.R.
Copyright Year	2007
Description	Author affiliation: Department of Electrical and Computer Engineering and Institute for Systems Research, University of Maryland, College Park, MD, USA (Wang, B.; Zhu, J.; Liu, K.J.R.)
Abstract	Dynamic spectrum access has become a promising approach to fully utilize the scarce spectrum resources. In a dynamically changing spectrum environment, it is very important to design a distributed access scheme that can coordinate different users' access adapt to spectrum dynamics with only local information. In this paper, we propose a self-learning repeated game framework for distributed primary-prioritized dynamic spectrum access through modeling the interactions between secondary users as a noncooperative game. With the proposed framework, the inefficiency due to users' selfish behavior can be highly improved, and the secondary users can distributively obtain their optimal access probabilities with only local observations. The simulation results show that the proposed framework can achieve comparable performances with those of the centralized primary-prioritized dynamic spectrum aess sheme.
Starting Page	1
Ending Page	8
File Size	5117378
Page Count	8
File Format	PDF
ISBN	142441315X
e-ISBN	1424413168
DOI	10.1109/SDRN.2007.4348967
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-06-18
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wireless networks Communication industry Access protocols FCC Interference Probability Nash equilibrium Educational institutions Cognitive radio Game theory
Content Type	Text
Resource Type	Article

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