Presentation | 2022-07-15 Research on OFDM Receivers Using Deep Learning You Yong, Chenggao Han, |
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PDF Download Page | PDF download Page Link |
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 |
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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 |
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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) |