Presentation 2020-03-04
A Lazy Learning Based Cancellation Approach for Full-Duplex Wireless Communication Systems
Ou Zhao, Wei-Shun Liao, Keren Li, Takeshi Matsumura, Fumihide Kojima, Hiroshi Harada,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) To further improve spectral efficiency for current wireless communication systems, we propose a new lazy learning-based cancellation approach to suppress self-interference (SI) sent from a base station itself and enable in-band full-duplex (IBFD) transmissions in cellular networks. Compared to the existing IBFD systems that used the traditional approaches, our proposal consists of two phases: an offline phase for database generation and an online phase for data transmission. In the offline phase, output before 0/1 decision is previously measured without desired signal input and is recorded to a database with self-defined feature vector as label. In the online phase, for the same system architecture with desired signal input, suitable result is searched from the generated database with the help of learning method and the usage of feature vector, then the result is assigned as a value of SI cancellation. Computer simulation results indicated that the proposed cancellation approaches can considerably suppress SI and thus enable the IBFD transmissions in the the considered systems.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Full-duplex / Lazy learning / Machine learning / Self-interference cancellation / Digital cancellation
Paper # RCS2019-337
Date of Issue 2020-02-26 (RCS)

Conference Information
Committee RCS / SR / SRW
Conference Date 2020/3/4(3days)
Place (in Japanese) (See Japanese page)
Place (in English) Tokyo Institute of Technology
Topics (in Japanese) (See Japanese page)
Topics (in English) Mobile Communication Workshop
Chair Tomoaki Otsuki(Keio Univ.) / Masayuki Ariyoshi(NEC) / Satoshi Denno(Okayama Univ.)
Vice Chair Satoshi Suyama(NTT DoCoMo) / Fumiaki Maehara(Waseda Univ.) / Toshihiko Nishimura(Hokkaido Univ.) / Suguru Kameda(Tohoku Univ.) / Osamu Takyu(Shinshu Univ.) / Kentaro Ishidu(NICT) / Keiichi Mizutani(Kyoto Univ.)
Secretary Satoshi Suyama(NTT) / Fumiaki Maehara(Kyushu Univ.) / Toshihiko Nishimura(ATR) / Suguru Kameda(Univ. of Electro-Comm.) / Osamu Takyu(Mie Univ.) / Kentaro Ishidu(Tokyo Inst. of Tech.) / Keiichi Mizutani(Anritsu)
Assistant Kazushi Muraoka(NEC) / Shinsuke Ibi(Doshisha Univ.) / Koichi Adachi(Univ. of Electro-Comm.) / Osamu Nakamura(Sharp) / Manabu Sakai(Mitsubishi Electric) / Mai Ohta(Fukuoka Univ.) / Teppei Oyama(Fujitsu Lab.) / Kentaro Kobayashi(Nagoya Univ.) / Masaaki Fuse(Anritsu) / Tomoki Murakami(NTT)

Paper Information
Registration To Technical Committee on Radio Communication Systems / Technical Committee on Smart Radio / Technical Committee on Short Range Wireless Communications
Language ENG-JTITLE
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Lazy Learning Based Cancellation Approach for Full-Duplex Wireless Communication Systems
Sub Title (in English)
Keyword(1) Full-duplex
Keyword(2) Lazy learning
Keyword(3) Machine learning
Keyword(4) Self-interference cancellation
Keyword(5) Digital cancellation
1st Author's Name Ou Zhao
1st Author's Affiliation National Institute of Information and Communications Technology(NICT)
2nd Author's Name Wei-Shun Liao
2nd Author's Affiliation National Institute of Information and Communications Technology(NICT)
3rd Author's Name Keren Li
3rd Author's Affiliation National Institute of Information and Communications Technology(NICT)
4th Author's Name Takeshi Matsumura
4th Author's Affiliation National Institute of Information and Communications Technology(NICT)
5th Author's Name Fumihide Kojima
5th Author's Affiliation National Institute of Information and Communications Technology(NICT)
6th Author's Name Hiroshi Harada
6th Author's Affiliation National Institute of Information and Communications Technology(NICT)
Date 2020-03-04
Paper # RCS2019-337
Volume (vol) vol.119
Number (no) RCS-448
Page pp.pp.93-98(RCS),
#Pages 6
Date of Issue 2020-02-26 (RCS)