Presentation 2022-07-15
Research on OFDM Receivers Using Deep Learning
You Yong, Chenggao Han,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Orthogonal Frequency-Division Multiplexing (OFDM) is widely used in wideband wireless communication systems due to its features such as high frequency efficiency, but it is vulnerable to Doppler shift. Therefore, in this paper, a receiver is designed using deep learning for an OFDM system in a doubly selective fading channel. Simulations confirm that the receiver achieves better performance than receivers using conventional LS (Least Square) and LMMSE (Linear Minimum Mean Square Error) channel estimation.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) OFDM / Deep Learning
Paper # CS2022-30
Date of Issue 2022-07-07 (CS)

Conference Information
Committee CS
Conference Date 2022/7/14(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Yakushima Environmental and Cultural Village Center
Topics (in Japanese) (See Japanese page)
Topics (in English) Next Generation Networks, Access Networks, Broadband Access, Power Line Communications, Wireless Communication Systems, Coding Systems, etc.
Chair Daisuke Umehara(Kyoto Inst. of Tech.)
Vice Chair Seiji Kozaki(Mitsubishi Electric)
Secretary Seiji Kozaki(Chiba Inst. of Tech.)
Assistant Hikaru Kawasaki(NICT) / Yuta Ida(Yamaguchi Univ.)

Paper Information
Registration To Technical Committee on Communication Systems
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Research on OFDM Receivers Using Deep Learning
Sub Title (in English)
Keyword(1) OFDM
Keyword(2) Deep Learning
1st Author's Name You Yong
1st Author's Affiliation The University of Electro-Communications(UEC)
2nd Author's Name Chenggao Han
2nd Author's Affiliation The University of Electro-Communications(UEC)
Date 2022-07-15
Paper # CS2022-30
Volume (vol) vol.122
Number (no) CS-110
Page pp.pp.74-77(CS),
#Pages 4
Date of Issue 2022-07-07 (CS)