2018 Fiscal Year Research-status Report
Sensing Augmented Database-Driven Spectrum Sharing Framework
Project/Area Number |
17K12670
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Research Institution | Ibaraki University |
Principal Investigator |
王 瀟岩 茨城大学, 理工学研究科(工学野), 助教 (10725667)
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Project Period (FY) |
2017-04-01 – 2020-03-31
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Keywords | spectrum sharing / incentive mechanism |
Outline of Annual Research Achievements |
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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Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
We consider that the research progresses smoothly. We have published 1 journal paper, 2 internal conference papers and multiple domestic conference papers in the past year under this funding. The 2 research problems considered in the application form are all well addressed.
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Strategy for Future Research Activity |
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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