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  • 标题:Deep neural network for orthogonal frequency division multiplexing systems without cyclic prefix transmission
  • 本地全文:下载
  • 作者:Viet-Hung Nguyen ; Minh-Tuan Nguyen ; Yong-Hwa Kim
  • 期刊名称:MATEC Web of Conferences
  • 电子版ISSN:2261-236X
  • 出版年度:2018
  • 卷号:189
  • DOI:10.1051/matecconf/201818904016
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Orthogonal frequency division multiplexing (OFDM) is widely used in wired or wireless transmission systems. In the structure of OFDM, a cycle prefix (CP) has been exploited to avoid the effects of inter-symbol interference (ISI) and inter-carrier interference (ICI). This paper proposes a new approach to transmit the signals without CP transmission. Using the deep neural network, the proposed OFDM system transmits data without the CP. Simulation results show that the proposed scheme can estimate the CP at the receiver and overcome the effect of ISI.
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