A Two-Dimensional Multiarmed Bandit Approach to Secondary Users with Network Coding in Cognitive Radio Networks
2015 ◽
Vol 2015
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pp. 1-10
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We study how to utilize network coding to improve the throughput of secondary users (SUs) in cognitive radio networks (CRNs) when the channel quality is unavailable at SUs. We use a two-dimensional multiarmed bandit (MAB) approach to solve the problem of SUs with network coding under unknown channel quality in CRNs. We analytically prove the asymptotical-throughput optimality of the proposed two-dimensional MAB algorithm. Simulation results show that our proposed algorithm achieves comparable throughput performance, compared to both the theoretical upper bound and the scheme assuming known channel quality information.
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2014 ◽
Vol 46
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pp. 166-181
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2009 ◽
Vol 53
(8)
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pp. 1158-1170
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2017 ◽
Vol 30
(18)
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pp. e3371
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2017 ◽
Vol 13
(3)
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pp. 1449-1466
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