Data-Throughput Enhancement Using Data Mining-Informed Cognitive Radio
AbstractWe 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
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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.
Kotobi K, Mainwaring PB, Tucker CS, Bilén SG. Data-Throughput Enhancement Using Data Mining-Informed Cognitive Radio. Electronics. 2015; 4(2):221-238.Chicago/Turabian Style
Kotobi, Khashayar; Mainwaring, Philip B.; Tucker, Conrad S.; Bilén, Sven G. 2015. "Data-Throughput Enhancement Using Data Mining-Informed Cognitive Radio." Electronics 4, no. 2: 221-238.