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Author

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

Cited 2 times inthomson ciCited 1 times inthomson ci
Title
Optimal online sensing sequence in multichannel cognitive radio networks
Author
Kim, HyoilShin, Kang G.
Keywords
Backup channels; Bayesian estimations; candidate channels; sensing sequence; Spectrum sensing
Issue Date
201307
Publisher
IEEE COMPUTER SOC
Citation
IEEE TRANSACTIONS ON MOBILE COMPUTING, v.12, no.7, pp.1349 - 1362
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.
URI
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DOI
http://dx.doi.org/10.1109/TMC.2012.108
ISSN
1536-1233
Appears in Collections:
ECE_Journal Papers

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