| Presentation | 2020-11-18 A Study on Forecasting of Available Spectrum Resources for Sharing using Envelope Extraction and Machine Learning Tatsuya Nagao, Takahiro Hayashi, Yoshiaki Amano, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In recent years, the demand for spectrum resources has been increasing, which has raised expectations for dynamic spectrum access (DSA). DSA is a technique for allowing secondary systems to use the same spectrum band at locations and times when the primary system is not used. DSA is a technique for improving the spectrum utilization efficiency while avoiding interference between systems, by allowing secondary systems to use the same spectrum at locations and times when the primary system is not in use. Especially in the millimeter-wave band, which is expected to be used more in the future, it is greatly affected by the surrounding environment, such as the number of people and vehicles. As a result, the coverage of radio waves varies depending on environmental changes. By considering those variations, it is possible to detect additional spectrum resources that will be newly available to the secondary system. In this paper, we propose a method for predicting the received power of a primary system that varies due to environmental changes and detecting the future available spectrum resources by machine learning, and show the results of the simulation evaluation. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Dynamic Spectrum Access / Machine Learning / Time-series analysis |
| Paper # | SR2020-22 |
| Date of Issue | 2020-11-11 (SR) |
| Conference Information | |
| Committee | SR |
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| Conference Date | 2020/11/18(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Software Radio, Cognitive Radio, Spectrum Sharing, etc. |
| Chair | Masayuki Ariyoshi(NEC) |
| Vice Chair | Suguru Kameda(Tohoku Univ.) / Osamu Takyu(Shinshu Univ.) / Kentaro Ishidu(NICT) |
| Secretary | Suguru Kameda(ATR) / Osamu Takyu(Univ. of Electro-Comm.) / Kentaro Ishidu(Mie Univ.) |
| Assistant | Mai Ohta(Fukuoka Univ.) / Teppei Oyama(Fujitsu Lab.) / Kentaro Kobayashi(Nagoya Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Smart Radio |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study on Forecasting of Available Spectrum Resources for Sharing using Envelope Extraction and Machine Learning |
| Sub Title (in English) | |
| Keyword(1) | Dynamic Spectrum Access |
| Keyword(2) | Machine Learning |
| Keyword(3) | Time-series analysis |
| 1st Author's Name | Tatsuya Nagao |
| 1st Author's Affiliation | KDDI Research, Inc.(KDDI Research) |
| 2nd Author's Name | Takahiro Hayashi |
| 2nd Author's Affiliation | KDDI Research, Inc.(KDDI Research) |
| 3rd Author's Name | Yoshiaki Amano |
| 3rd Author's Affiliation | KDDI Research, Inc.(KDDI Research) |
| Date | 2020-11-18 |
| Paper # | SR2020-22 |
| Volume (vol) | vol.120 |
| Number (no) | SR-238 |
| Page | pp.pp.1-4(SR), |
| #Pages | 4 |
| Date of Issue | 2020-11-11 (SR) |