| Presentation | 2022-07-13 Compensation method for transmission weight matrix of SVD-MIMO using machine learning Kiminobu Makino, Takayuki Nakagawa, Naohiko Iai, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This paper proposes a compensation method for the actual transmission weight matrix of singular value decomposition (SVD)-multiple-input multiple-output (MIMO) systems using machine learning. Though the transmission weight matrix is an important factor for SVD-MIMO, the matrix is deteriorated by a lot of factors for the actual transmission. This paper defines deterioration compensation as a regression problem that solves the parameters of the ideal transmission weight matrix from the matrix deteriorated. This paper proposes a solution method using support vector regression as a simple machine learning method, a creation method for learning data, and simple channel metrics. The compensation performance of the conditions selected by simple channel metrics is evaluated by computer simulation. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | SVD-MIMO / Machine learning / Regression problem / SVR / Wireless links |
| Paper # | RCS2022-73 |
| Date of Issue | 2022-07-06 (RCS) |
| Conference Information | |
| Committee | NS / SR / RCS / SeMI / RCC |
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| Conference Date | 2022/7/13(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | The Kanazawa Theatre + Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Distributed Wireless Network, M2M (Machine-to-Machine)，D2D (Device-to-Device)，IoT（Internet of Things）, etc |
| Chair | Tetsuya Oishi(NTT) / Suguru Kameda(Hiroshima Univ.) / Kenichi Higuchi(Tokyo Univ. of Science) / Koji Yamamoto(Kyoto Univ.) / Shunichi Azuma(Nagoya Univ.) |
| Vice Chair | Takumi Miyoshi(Shibaura Insti of Tech.) / Osamu Takyu(Shinshu Univ.) / Kentaro Ishidu(NICT) / Kazuto Yano(ATR) / Tomoya Tandai(Toshiba) / Fumihide Kojima(NICT) / Osamu Muta(Kyushu Univ.) / Kazuya Monden(Hitachi) / Yasunori Owada(NICT) / Shunsuke Saruwatari(Osaka Univ.) / Shunichi Azuma(Hokkaido Univ.) / Koji Ishii(Kagawa Univ.) |
| Secretary | Takumi Miyoshi(NTT) / Osamu Takyu(Kogakuin Univ.) / Kentaro Ishidu(Mie Univ.) / Kazuto Yano(Tokai Univ.) / Tomoya Tandai(NTT) / Fumihide Kojima(Panasonic) / Osamu Muta(Univ. of Electro-Comm) / Kazuya Monden(Sharp) / Yasunori Owada(NTT DOCOMO) / Shunsuke Saruwatari(Tokyo Univ. of Agri. and Tech.) / Shunichi Azuma(Osaka Univ.) / Koji Ishii(CRIEPI) |
| Assistant | Kotaro Mihara(NTT) / Taichi Ohtsuji(NEC) / WANG Xiaoyan(Ibaraki Univ.) / Akemi Tanaka(MathWorks) / Katsuya Suto(Univ. of Electro-Comm) / Manabu Sakai(Mitsubishi Electric) / Masashi Iwabuchi(NTT) / Tatsuki Okuyama(NTT DOCOMO) / Issei Kanno(KDDI Research) / Yuyuan Chang(Tokyo Inst. of Tech) / Yuki Matsuda(NAIST) / Akihito Taya(Aoyama Gakuin Univ.) / Takeshi Hirai(Osaka Univ.) / SHAN LIN(NICT) / Ryosuke Adachi(Yamaguchi Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Network Systems / Technical Committee on Smart Radio / Technical Committee on Radio Communication Systems / Technical Committee on Sensor Network and Mobile Intelligence / Technical Committee on Reliable Communication and Control |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Compensation method for transmission weight matrix of SVD-MIMO using machine learning |
| Sub Title (in English) | |
| Keyword(1) | SVD-MIMO |
| Keyword(2) | Machine learning |
| Keyword(3) | Regression problem |
| Keyword(4) | SVR |
| Keyword(5) | Wireless links |
| 1st Author's Name | Kiminobu Makino |
| 1st Author's Affiliation | Japan Broadcasting Corporation(NHK) |
| 2nd Author's Name | Takayuki Nakagawa |
| 2nd Author's Affiliation | Japan Broadcasting Corporation(NHK) |
| 3rd Author's Name | Naohiko Iai |
| 3rd Author's Affiliation | Japan Broadcasting Corporation(NHK) |
| Date | 2022-07-13 |
| Paper # | RCS2022-73 |
| Volume (vol) | vol.122 |
| Number (no) | RCS-106 |
| Page | pp.pp.26-31(RCS), |
| #Pages | 6 |
| Date of Issue | 2022-07-06 (RCS) |