NDLI: Decision-Theoretic Distributed Channel Selection for Opportunistic Spectrum Access: Strategies, Challenges and Solutions

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Decision-Theoretic Distributed Channel Selection for Opportunistic Spectrum Access: Strategies, Challenges and Solutions

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Decision-Theoretic Distributed Channel Selection for Opportunistic Spectrum Access: Strategies, Challenges and Solutions

Content Provider	IEEE Xplore Digital Library
Author	Yuhua Xu Anpalagan, A. Qihui Wu Liang Shen Zhan Gao Jinglong Wang
Copyright Year	1998
Abstract	Opportunistic spectrum access (OSA) has been regarded as the most promising approach to solve the paradox between spectrum scarcity and waste. Intelligent decision making is key to OSA and differentiates it from previous wireless technologies. In this article, a survey of decision-theoretic solutions for channel selection and access strategies for OSA system is presented. We analyze the challenges facing OSA systems globally, which mainly include interactions among multiple users, dynamic spectrum opportunity, tradeoff between sequential sensing cost and expected reward, and tradeoff between exploitation and exploration in the absence of prior statistical information. We provide comprehensive review and comparison of each kind of existing decision-theoretic solution, i.e., game models, Markovian decision process, optimal stopping problem and multi-armed bandit problem. We analyze their strengths and limitations and outline further research for both technical contents and methodologies. In particular, these solutions are critically analyzed in terms of information, cost and convergence speed, which are key concerns for practical implementation. Moreover, it is noted that each kind of existing decision-theoretic solution mainly addresses one aspect of the challenges, which implies that two or more kinds of decision-theoretic solutions should be incorporated to address more challenges simultaneously.
Starting Page	1689
Ending Page	1713
Page Count	25
File Size	881563
File Format	PDF
ISSN	1553877X
Volume Number	15
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cognitive radio Spread spectrum management Channel estimation Markov processes Decision making Opportunistic software systems development Game theory multi-armed bandit problem Opportunistic spectrum access cognitive radio distributed channel selection game theory Markovian decision process optimal stopping problem
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Optimality of myopic sensing in multi-channel opportunistic access.

Optimality of myopic sensing in multi-channel opportunistic access (2008)

Myopic policy for opportunistic access in cognitive radio networks by exploiting primary user feedbacks

Dynamic spectrum access with non-stationary Multi-Armed Bandit

Decentralized Blind Spectrum Selection in Cognitive Radio Networks Considering Handoff Cost

QoS-Based Blind Spectrum Selection with Multi-armed Bandit Problem in Cognitive Radio Networks

Optimal channel stopping rule under constrained conditions for CRNs

Two-Stage Decision Making Policy Using Bayesian Multi-armed Bandit Algorithm for Opportunistic Spectrum Access

1Learning and Decision Making with Negative Externality for Opportunistic Spectrum Access

Decision-Theoretic Distributed Channel Selection for Opportunistic Spectrum Access: Strategies, Challenges and Solutions

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