| 研究実績の概要 |
Based on our research results in 2017, we studied crowdsourced radio environment map construction problem by using machine learning techniques, and online crowdsourcing incentive mechanism for radio environment map by taking into consideration the dynamically arrived users. Specifically, we proposed two machine learning based approaches to select the measurement, i.e., one decision tree based approach and one neural network based approach. For the second problem, we propose a novel online incentive mechanism for sensing augmented spectrum database. Simulation results demonstrate that the proposed mechanism could save noticeable expenditure.
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| 今後の研究の推進方策 |
In the following year, we will extend the problems to sophisticated and practical ones (i.e., machine learning based zone refinement and resource reward incentive mechanism). Meanwhile, we will perform the experiments on real radio environment map construction by using spectrum analyzer.
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