Presentation | 2018-01-19 Machine Learning-based Primary Exclusive Region Update for Spectrum Sharing Aogu Yamada, Takayuki Nishio, Masahiro Morikura, Koji Yamamoto, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In spectrum sharing, secondary users (SUs) utilize a licensed frequency band under a condition to avoid interference with a primary user (PU), such as a primary exclusive region (PER), wherein the SUs are prohibited to transmit. However, when SUs outside the PER interfere with the PU due to long term variation of propagation paths, the PER needs to be updated. In this paper, we propose a framework for updating the PER adaptively with supervised learning, when interference occurs. This frameworks employs training data sets, which are transmission logs of SUs with supervised labels whether or not PU detects interference from SUs. However, dominance of the non-interference labels compared to the interference labels degrades learning performance. To overcome imbalance of the supervised labels, we designed a novel sampling schemes considering propagation characteristics. Simulation results show the proposed framework continues to reduce interference probability and achieves smaller PER with fewer iterations compared to the conventional frameworks. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Machine learning / Spectrum sharing / Cognitive radio / Supervised learning / Imbalanced data |
Paper # | MoNA2017-52 |
Date of Issue | 2018-01-11 (MoNA) |
Conference Information | |
Committee | MoNA |
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Conference Date | 2018/1/18(2days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Campus Plaza Kyoto |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | Mobile Network, Application of Machine Learning, Mobile Data, etc. |
Chair | Ryoichi Shinkuma(Kyoto Univ.) |
Vice Chair | Shigeaki Tagashira(Kansai Univ.) / Gen Kitagata(Tohoku Univ.) |
Secretary | Shigeaki Tagashira(Kyushu Univ.) / Gen Kitagata(NTT) |
Assistant | Takayuki Nishio(Kyoto Univ.) / Takato Saito(NTT) |
Paper Information | |
Registration To | Technical Committee on Mobile Network and Applications |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Machine Learning-based Primary Exclusive Region Update for Spectrum Sharing |
Sub Title (in English) | |
Keyword(1) | Machine learning |
Keyword(2) | Spectrum sharing |
Keyword(3) | Cognitive radio |
Keyword(4) | Supervised learning |
Keyword(5) | Imbalanced data |
1st Author's Name | Aogu Yamada |
1st Author's Affiliation | Kyoto University(Kyoto Univ.) |
2nd Author's Name | Takayuki Nishio |
2nd Author's Affiliation | Kyoto University(Kyoto Univ.) |
3rd Author's Name | Masahiro Morikura |
3rd Author's Affiliation | Kyoto University(Kyoto Univ.) |
4th Author's Name | Koji Yamamoto |
4th Author's Affiliation | Kyoto University(Kyoto Univ.) |
Date | 2018-01-19 |
Paper # | MoNA2017-52 |
Volume (vol) | vol.117 |
Number (no) | MoNA-390 |
Page | pp.pp.63-68(MoNA), |
#Pages | 6 |
Date of Issue | 2018-01-11 (MoNA) |