| Presentation | 2021-03-05 Deep Learning-based Channel Estimation to Mitigate Channel Aging in Massive MIMO with Pilot Contamination Hiroki Hirose, Tomoaki Ohtsuki, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In a massive multiple-input multiple-output (MIMO) system based on time division duplex (TDD), the channel state information (CSI) between the base station (BS) and the user terminal (UT) is required. Due to Doppler shift, the fluctuations of the channel between the BS and the UT causes differences of the channel between the channel estimation and channel utilization, which is an issue called channel aging. In this report, we propose a data-aided channel estimation method based on deep learning to mitigate the effect of channel aging in a massive MIMO system with pilot contamination. After signal detection using the estimated channel obtained from the received signal in the pilot part, the detected symbol is regarded as a pilot and the channel for each time slot is estimated from the received signal in the data part. Through computer simulations, we show that the proposed method improves the channel estimation accuracy compared with the deep learning-based channel estimation with received pilot signal and the interpolation method. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Channel aging / Channel estimation / Convolutional neural network / Massive MIMO / Pilot contamination |
| Paper # | RCS2020-254 |
| Date of Issue | 2021-02-24 (RCS) |
| Conference Information | |
| Committee | RCS / SR / SRW |
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| Conference Date | 2021/3/3(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Mobile Communication Workshop |
| Chair | Eiji Okamoto(Nagoya Inst. of Tech.) / Masayuki Ariyoshi(NEC) / Satoshi Denno(Okayama Univ.) |
| Vice Chair | Fumiaki Maehara(Waseda Univ.) / Toshihiko Nishimura(Hokkaido Univ.) / Tomoya Tandai(Toshiba) / Suguru Kameda(Tohoku Univ.) / Osamu Takyu(Shinshu Univ.) / Kentaro Ishidu(NICT) / Keiichi Mizutani(Kyoto Univ.) / Kentaro Saito(Tokyo Inst. of Tech.) / Hanako Noda(Anritsu) |
| Secretary | Fumiaki Maehara(Kyushu Univ.) / Toshihiko Nishimura(NEC) / Tomoya Tandai(ATR) / Suguru Kameda(Univ. of Electro-Comm.) / Osamu Takyu(Mie Univ.) / Kentaro Ishidu(NTT) / Keiichi Mizutani(NIigata Univ.) / Kentaro Saito / Hanako Noda |
| Assistant | Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Manabu Sakai(Mitsubishi Electric) / Masashi Iwabuchi(NTT) / Tatsuki Okuyama(NTT DOCOMO) / Mai Ohta(Fukuoka Univ.) / Teppei Oyama(Fujitsu Lab.) / Kentaro Kobayashi(Nagoya Univ.) / Masaaki Fuse(Anritsu) / Akihito Noda(Nanzan Univ.) |
| 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 | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Deep Learning-based Channel Estimation to Mitigate Channel Aging in Massive MIMO with Pilot Contamination |
| Sub Title (in English) | |
| Keyword(1) | Channel aging |
| Keyword(2) | Channel estimation |
| Keyword(3) | Convolutional neural network |
| Keyword(4) | Massive MIMO |
| Keyword(5) | Pilot contamination |
| 1st Author's Name | Hiroki Hirose |
| 1st Author's Affiliation | Keio University(Keio Univ.) |
| 2nd Author's Name | Tomoaki Ohtsuki |
| 2nd Author's Affiliation | Keio University(Keio Univ.) |
| Date | 2021-03-05 |
| Paper # | RCS2020-254 |
| Volume (vol) | vol.120 |
| Number (no) | RCS-404 |
| Page | pp.pp.234-239(RCS), |
| #Pages | 6 |
| Date of Issue | 2021-02-24 (RCS) |