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Open AccessArticle

Data-Throughput Enhancement Using Data Mining-Informed Cognitive Radio

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Department of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
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Department of Aerospace Engineering, The Pennsylvania State University, University Park, PA 16802, USA
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School of Engineering Design, Technology, and Professional Programs, The Pennsylvania State University, University Park, PA 16802, USA
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Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA 16802, USA
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Department of Industrial and Manufacturing Engineering, The Pennsylvania State University, University Park, PA 16802, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Sanqing Hu, Lian Zhao and Nazanin Rahnavard
Electronics 2015, 4(2), 221-238; https://doi.org/10.3390/electronics4020221
Received: 23 November 2014 / Revised: 14 March 2015 / Accepted: 16 March 2015 / Published: 26 March 2015
(This article belongs to the Special Issue Cognitive Radio: Use the Spectrum in a More Efficient Way)
We propose the data mining-informed cognitive radio, which uses non-traditional data sources and data-mining techniques for decision making and improving the performance of a wireless network. To date, the application of information other than wireless channel data in cognitive radios has not been significantly studied. We use a novel dataset (Twitter traffic) as an indicator of network load in a wireless channel. Using this dataset, we present and test a series of predictive algorithms that show an improvement in wireless channel utilization over traditional collision-detection algorithms. Our results demonstrate the viability of using these novel datasets to inform and create more efficient cognitive radio networks. View Full-Text
Keywords: cognitive radio network; big data applications; data mining; wireless communication; data mining-informed cognitive radio cognitive radio network; big data applications; data mining; wireless communication; data mining-informed cognitive radio
MDPI and ACS Style

Kotobi, K.; Mainwaring, P.B.; Tucker, C.S.; Bilén, S.G. Data-Throughput Enhancement Using Data Mining-Informed Cognitive Radio. Electronics 2015, 4, 221-238.

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