| Presentation | 2023-03-01 DNN-based Multi-class Classification for CDL Channels Liu Jingyu, Mondher Bouazizi, Tomoaki Ohtsuki, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Transfer learning-based methods for Channel State Information (CSI) feedback can achieve a good CSI reconstruction matrix with small amounts of computation time and cost. However, such methods need to select a proper source channel model each time. In this paper, we use a one-step algorithm and a two-step algorithm to classify the downlink Clustered Delay Line (CDL) channels into one of 5 channel models with the help of a selected set of features. Through simulation, we show that the overall classification accuracy for 5 CDL channel models using the one-step algorithm is 80.73%. The overall classification accuracy using the two-stepalgorithm is 78.3%. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | 5GClassificationMIMOCDLdeep-neural netwroksource model |
| Paper # | RCS2022-253 |
| Date of Issue | 2023-02-22 (RCS) |
| Conference Information | |
| Committee | RCS / SR / SRW |
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| Conference Date | 2023/3/1(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Tokyo Institute of Technology, and Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Mobile Communication Workshop |
| Chair | Kenichi Higuchi(Tokyo Univ. of Science) / Suguru Kameda(Hiroshima Univ.) / Hanako Noda(Anritsu) |
| Vice Chair | Tomoya Tandai(Toshiba) / Fumihide Kojima(NICT) / Osamu Muta(Kyushu Univ.) / Osamu Takyu(Shinshu Univ.) / Kentaro Ishidu(NICT) / Kazuto Yano(ATR) / Keiichi Mizutani(Kyoto Univ.) / Kentaro Saito(Tokyo Denki Univ.) / Hirokazu Sawada(NICT) |
| Secretary | Tomoya Tandai(Panasonic) / Fumihide Kojima(Univ. of Electro-Comm) / Osamu Muta(Sharp) / Osamu Takyu(Mie Univ.) / Kentaro Ishidu(Tokai Univ.) / Kazuto Yano(NTT) / Keiichi Mizutani(KUT) / Kentaro Saito(NIigata Univ.) / Hirokazu Sawada |
| Assistant | Manabu Sakai(Mitsubishi Electric) / Masashi Iwabuchi(NTT) / Issei Kanno(KDDI Research) / Yuyuan Chang(Tokyo Inst. of Tech) / Kazuki Maruta(Tokyo Univ. of Science) / Mai Ohta(NEC) / WANG Xiaoyan(Ibaraki Univ.) / Akemi Tanaka(MathWorks) / Katsuya Suto(Univ. of Electro-Comm) / Maki Arai(Nihon Univ.) / Yuichi Masuda(Univ. of Tokyo) |
| Paper Information | |
| Registration To | Technical Committee on Radio Communication Systems / Technical Committee on Smart Radio / Technical Committee on Short Range Wireless Communications |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | DNN-based Multi-class Classification for CDL Channels |
| Sub Title (in English) | |
| Keyword(1) | 5GClassificationMIMOCDLdeep-neural netwroksource model |
| 1st Author's Name | Liu Jingyu |
| 1st Author's Affiliation | Keio University(Keio Unvi.) |
| 2nd Author's Name | Mondher Bouazizi |
| 2nd Author's Affiliation | Keio University(Keio Unvi.) |
| 3rd Author's Name | Tomoaki Ohtsuki |
| 3rd Author's Affiliation | Keio University(Keio Unvi.) |
| Date | 2023-03-01 |
| Paper # | RCS2022-253 |
| Volume (vol) | vol.122 |
| Number (no) | RCS-399 |
| Page | pp.pp.36-41(RCS), |
| #Pages | 6 |
| Date of Issue | 2023-02-22 (RCS) |