| Presentation | 2018-03-01 CSI Overhead Reduction for Massive MIMO using Multi-Dimensional Scaling Extended in Time-Domain and AR Model Rei Nagashima, Tomoaki Ohtsuki, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Massive MIMO (multiple-input multiple-output) is one of the technologies that has been focused in 5G (5th generation mobile communications). However, there exists an issue such as the increase of the amount of feedback of channel state information (CSI) from the receiving terminal to the base station (BS), due to the enormous number of antennas. For the purpose of solving this issue, there exists the method to compress CSI to a lower dimension matrix by multi-dimensional scaling (MDS). However, this conventional method needs to hold a lot of CSIs at the receiving terminal and predict CSIs considering the delays using them, thus the loads applied to each receiving terminal is large. Besides, the number of dimensions when mapping CSI in the multi-dimensional space depends on the number of receiving antennas. However, because the number of antennas that can be deployed at the receiving terminal is limited, the number of antennas that can be assigned when compressing is limited. In this report, we propose the method that feeds back the CSI after extending in time-domain and compressing and compensates the mismatches of the time change by prediction based on auto regressive (AR) model. In our proposed method, the choices of the eigenvalues that can be adopted are increased by extending the size of the channel matrix, and the all CSI prediction process using AR model is performed at the BS. By computer simulation, we show that our proposed method achieves the higher system capacity compared to the conventional CSI compression method using MDS due to the improvement of the accuracy of CSI compression and restoration. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Massive MIMO / Overhead Reduction / Multi-Dimensional Scaling / AR Model / Dimensions Reduction / 5G |
| Paper # | RCS2017-349 |
| Date of Issue | 2018-02-21 (RCS) |
| Conference Information | |
| Committee | RCS / SR / SRW |
|---|---|
| Conference Date | 2018/2/28(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | YRP |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Mobile Communication Workshop |
| Chair | Hidekazu Murata(Kyoto Univ.) / Kenta Umebayashi(Tokyo Univ. of Agric. and Tech.) / Tadao Nakagawa(Tottori Univ.) |
| Vice Chair | Yukitoshi Sanada(Keio Univ.) / Eisuke Fukuda(Fujitsu Labs.) / Satoshi Suyama(NTT DoCoMo) / Masayuki Ariyoshi(NEC) / Suguru Kameda(Tohoku Univ.) / Satoshi Denno(Okayama Univ.) / Makoto Hamaminato(Fujitsu labs.) |
| Secretary | Yukitoshi Sanada(Toshiba) / Eisuke Fukuda(Hokkaido Univ.) / Satoshi Suyama(NICT) / Masayuki Ariyoshi(ATR) / Suguru Kameda(NICT) / Satoshi Denno(Kyoto Univ.) / Makoto Hamaminato |
| Assistant | Tetsuya Yamamoto(Panasonic) / Koichi Ishihara(NTT) / Kazushi Muraoka(NEC) / Shinsuke Ibi(Osaka Univ.) / Hiroshi Nishimoto(Mitsubishi Electric) / Mamiko Inamori(Tokai Univ.) / Hiroyuki Shiba(NTT) / Gia Khanh Tran(Tokyo Inst. of Tech.) / Syusuke Narieda(NIT, Akashi College) / Kentaro Saito(Tokyo Inst. of Tech.) / Hiromasa Yamauchi(Fujitsu labs.) |
| Paper Information | |
| Registration To | Technical Committee on Radio Communication Systems / Technical Committee on Smart Radio / Technical Committee on Short Range Wireless Communications |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | CSI Overhead Reduction for Massive MIMO using Multi-Dimensional Scaling Extended in Time-Domain and AR Model |
| Sub Title (in English) | |
| Keyword(1) | Massive MIMO |
| Keyword(2) | Overhead Reduction |
| Keyword(3) | Multi-Dimensional Scaling |
| Keyword(4) | AR Model |
| Keyword(5) | Dimensions Reduction |
| Keyword(6) | 5G |
| 1st Author's Name | Rei Nagashima |
| 1st Author's Affiliation | Keio University(Keio Univ.) |
| 2nd Author's Name | Tomoaki Ohtsuki |
| 2nd Author's Affiliation | Keio University(Keio Univ.) |
| Date | 2018-03-01 |
| Paper # | RCS2017-349 |
| Volume (vol) | vol.117 |
| Number (no) | RCS-456 |
| Page | pp.pp.185-190(RCS), |
| #Pages | 6 |
| Date of Issue | 2018-02-21 (RCS) |