| Presentation | 2021-06-23 A basic study on signal detection using learned approximate message passing Mari Miyoshi, Wakaba Tsujimoto, Toshihiko Nishimura, Takeo Ohgane, Yasutaka Ogawa, Junichiro Hagiwara, Takanori Sato, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Approximate message passing (AMP) is applicable to massive MIMO signal detection and achieves a high detection performance with low computational complexity. However, when two conditions required by AMP, i.e., the large system limit and a property that each entry of the channel matrix follows an independent and identically distributed complex Gaussian distribution, are not satisfied, the detection performance is severely degraded. It has been found that the degradation is relaxed by introducing a constant multiplier to the observation rate which is the ratio of the numbers of received to transmitted signals. The optimal value of the multiplier depends on the numbers of transmit and receive antennas, signal-to-noise ratio, and other conditions. In this paper, we replace two terms including the observation rate with independent parameters and optimize them by deep unfolding as a learned AMP. Simulation results show that the degradation is highly reduced by the optimized network and that the network is applicable to various channel conditions. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | MIMO / approximate message passing / deep learning / deep unfolding / spatial correlation |
| Paper # | RCS2021-31 |
| Date of Issue | 2021-06-16 (RCS) |
| Conference Information | |
| Committee | RCS |
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| Conference Date | 2021/6/23(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | First Presentation in IEICE Technical Committee, Resource Control, Scheduling, Wireless Communications, etc. |
| Chair | Eiji Okamoto(Nagoya Inst. of Tech.) |
| Vice Chair | Fumihide Kojima(NICT) / Toshihiko Nishimura(Hokkaido Univ.) / Tomoya Tandai(Toshiba) |
| Secretary | Fumihide Kojima(Panasonic) / Toshihiko Nishimura(NEC) / Tomoya Tandai |
| Assistant | Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Manabu Sakai(Mitsubishi Electric) / Masashi Iwabuchi(NTT) / Tatsuki Okuyama(NTT DOCOMO) |
| Paper Information | |
| Registration To | Technical Committee on Radio Communication Systems |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A basic study on signal detection using learned approximate message passing |
| Sub Title (in English) | |
| Keyword(1) | MIMO |
| Keyword(2) | approximate message passing |
| Keyword(3) | deep learning |
| Keyword(4) | deep unfolding |
| Keyword(5) | spatial correlation |
| 1st Author's Name | Mari Miyoshi |
| 1st Author's Affiliation | Hokkaido University(Hokkaido Univ.) |
| 2nd Author's Name | Wakaba Tsujimoto |
| 2nd Author's Affiliation | Hokkaido University(Hokkaido Univ.) |
| 3rd Author's Name | Toshihiko Nishimura |
| 3rd Author's Affiliation | Hokkaido University(Hokkaido Univ.) |
| 4th Author's Name | Takeo Ohgane |
| 4th Author's Affiliation | Hokkaido University(Hokkaido Univ.) |
| 5th Author's Name | Yasutaka Ogawa |
| 5th Author's Affiliation | Hokkaido University(Hokkaido Univ.) |
| 6th Author's Name | Junichiro Hagiwara |
| 6th Author's Affiliation | Hokkaido University(Hokkaido Univ.) |
| 7th Author's Name | Takanori Sato |
| 7th Author's Affiliation | Hokkaido University(Hokkaido Univ.) |
| Date | 2021-06-23 |
| Paper # | RCS2021-31 |
| Volume (vol) | vol.121 |
| Number (no) | RCS-72 |
| Page | pp.pp.13-18(RCS), |
| #Pages | 6 |
| Date of Issue | 2021-06-16 (RCS) |