| 電子情報通信学会 研究会発表申込システム 講演論文 詳細 |
技報閲覧サービス [ログイン] 技報アーカイブ |
| トップに戻る | 前のページに戻る | [Japanese] / [English] |
| 講演抄録／キーワード | ||
| 講演名 | 2019-10-24 16:55 ［招待講演］Deep Learning for Physical-Layer 5G Wireless Techniques ○Guan Gui（NJUPT）  RCS2019-191 |
|
| 抄録 | （和） | The new demands for high-reliability and ultra-high capacity wireless communication have led to extensive research into 5G communications. However, the current communication systems, which were designed on the basis of conventional communication theories, significantly restrict further performance improvements and lead to severe limitations. Recently, the emerging deep learning techniques have been recognized as a promising tool for handling the complicated communication systems, and their potential for optimizing wireless communications has been demonstrated. In this article, we first review the development of deep learning solutions for 5G communication, and then propose efficient schemes for deep learning-based 5G scenarios. Specifically, the key ideas for several important deep learning-based communication methods are presented along with the research opportunities and challenges. In particular, novel communication frameworks of non-orthogonal multiple access (NOMA), massive multiple-input multiple-output (MIMO), and millimeter wave (mmWave) are investigated, and their superior performances are demonstrated. We vision that the appealing deep learning-based wireless physical layer frameworks will bring a new direction in communication theories and that this work will move us forward along this road. |
| （英） | The new demands for high-reliability and ultra-high capacity wireless communication have led to extensive research into 5G communications. However, the current communication systems, which were designed on the basis of conventional communication theories, significantly restrict further performance improvements and lead to severe limitations. Recently, the emerging deep learning techniques have been recognized as a promising tool for handling the complicated communication systems, and their potential for optimizing wireless communications has been demonstrated. In this article, we first review the development of deep learning solutions for 5G communication, and then propose efficient schemes for deep learning-based 5G scenarios. Specifically, the key ideas for several important deep learning-based communication methods are presented along with the research opportunities and challenges. In particular, novel communication frameworks of non-orthogonal multiple access (NOMA), massive multiple-input multiple-output (MIMO), and millimeter wave (mmWave) are investigated, and their superior performances are demonstrated. We vision that the appealing deep learning-based wireless physical layer frameworks will bring a new direction in communication theories and that this work will move us forward along this road. | |
| キーワード | （和） | Deep learning / 5G communications / non-orthogonal multiple access / massive MIMO / millimeter wave / / / |
| （英） | Deep learning / 5G communications / non-orthogonal multiple access / massive MIMO / millimeter wave / / / | |
| 文献情報 | 信学技報, vol. 119, no. 244, RCS2019-191, pp. 71-76, 2019年10月. | |
| 資料番号 | RCS2019-191 | |
| 発行日 | 2019-10-17 (RCS) | |
| ISSN | Online edition: ISSN 2432-6380 | |
| 著作権に ついて |
技術研究報告に掲載された論文の著作権は電子情報通信学会に帰属します．(許諾番号：10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| PDFダウンロード | RCS2019-191 |
|
| 研究会情報 | |
| 研究会 | RCS |
| 開催期間 | 2019-10-24 - 2019-10-25 |
| 開催地（和） | 横須賀リサーチパーク (YRP) |
| 開催地（英） | Yokosuka Research Park |
| テーマ（和） | 無線通信方式，無線通信システム，標準化，将来システムおよび一般 |
| テーマ（英） | Wireless Communication Schemes, Wireless Communication Systems, Wireless Standards, Future Wireless Systems, etc. |
| 講演論文情報の詳細 | |
| 申込み研究会 | RCS |
| 会議コード | 2019-10-RCS |
| 本文の言語 | 英語 |
| タイトル（和） | |
| サブタイトル（和） | |
| タイトル（英） | Deep Learning for Physical-Layer 5G Wireless Techniques |
| サブタイトル（英） | |
| キーワード(1)（和/英） | Deep learning / Deep learning |
| キーワード(2)（和/英） | 5G communications / 5G communications |
| キーワード(3)（和/英） | non-orthogonal multiple access / non-orthogonal multiple access |
| キーワード(4)（和/英） | massive MIMO / massive MIMO |
| キーワード(5)（和/英） | millimeter wave / millimeter wave |
| キーワード(6)（和/英） | / |
| キーワード(7)（和/英） | / |
| キーワード(8)（和/英） | / |
| 第1著者 氏名（和/英/ヨミ） | Guan Gui / Guan Gui / |
| 第1著者 所属（和/英） | Nanjing University of Posts and Telecommunications (略称： NJUPT) Nanjing University of Posts and Telecommunications (略称： NJUPT) |
| 講演者 | 第1著者 |
| 発表日時 | 2019-10-24 16:55:00 |
| 発表時間 | 50分 |
| 申込先研究会 | RCS |
| 資料番号 | RCS2019-191 |
| 巻番号（vol） | vol.119 |
| 号番号（no） | no.244 |
| ページ範囲 | pp.71-76 |
| ページ数 | 6 |
| 発行日 | 2019-10-17 (RCS) |
[研究会発表申込システムのトップページに戻る]