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Kim, Hyoil
Wireless & Mobile Networking Lab (WMNL)
Research Interests
  • Wireless networks, cognitive radio, WLAN, LTE, mobile cloud, 5G

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Optimal online sensing sequence in multichannel cognitive radio networks

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dc.contributor.author Kim, Hyoil ko
dc.contributor.author Shin, Kang G. ko
dc.date.available 2014-04-10T02:17:35Z -
dc.date.created 2013-07-04 ko
dc.date.issued 2013-07 ko
dc.identifier.citation IEEE TRANSACTIONS ON MOBILE COMPUTING, v.12, no.7, pp.1349 - 1362 ko
dc.identifier.issn 1536-1233 ko
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/3658 -
dc.description.abstract We address the problem of rapidly discovering spectrum opportunities for seamless service provisioning in cognitive radio networks (CRNs). In particular, we focus on multichannel communications via channel-bonding with heterogeneous channel characteristics of ON/OFF patterns, sensing time, and channel capacity. Using dynamic programming (DP), we derive an optimal online sensing sequence incurring a minimal opportunity-discovery delay, and propose a suboptimal sequence that presents a near-optimal performance while incurring significantly less computational overhead than the DP algorithm. To facilitate fast opportunity discovery, we also propose a channel-management strategy that maintains a list of backup channels to be used at building the optimal sequence. A hybrid of maximum likelihood (ML) and Bayesian inference is introduced as well for flexible estimation of ON/OFF channel-usage patterns, which selectively chooses the better between the two according to the frequency of sensing and ON/OFF durations. The performance of the proposed schemes, in terms of the opportunity-discovery delay, is evaluated via in-depth simulation, and for the scenarios we considered, the proposed suboptimal sequence achieves a near-optimal performance with only an average of 0.5 percent difference from the optimal delay, and outperforms the previously proposed probabilistic scheme by up to 50.1 percent. In addition, the backup channel update scheme outperforms the no-update case by up to 49.9 percent. ko
dc.description.statementofresponsibility close -
dc.language 영어 ko
dc.publisher IEEE COMPUTER SOC ko
dc.title Optimal online sensing sequence in multichannel cognitive radio networks ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-84878145505 ko
dc.identifier.wosid 000319411600008 ko
dc.type.rims ART ko
dc.description.wostc 2 *
dc.description.scopustc 1 *
dc.date.tcdate 2015-02-28 *
dc.date.scptcdate 2014-08-27 *
dc.identifier.doi 10.1109/TMC.2012.108 ko
dc.identifier.url http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84878145505 ko
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