Electronics | |
Data-Throughput Enhancement Using Data Mining-Informed Cognitive Radio | |
Khashayar Kotobi1  Philip B. Mainwaring4  Conrad S. Tucker2  Sven G. Bilén1  Sanqing Hu3  Lian Zhao3  | |
[1] Department of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802, |
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关键词: cognitive radio network; big data applications; data mining; wireless communication; data mining-informed cognitive radio; | |
DOI : 10.3390/electronics4020221 | |
来源: mdpi | |
【 摘 要 】
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.
【 授权许可】
CC BY
© 2015 by the authors; licensee MDPI, Basel, Switzerland
【 预 览 】
Files | Size | Format | View |
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RO202003190014966ZK.pdf | 2002KB | download |