Deep Learning Based Single Carrier Communications Over Time-Varying Underwater Acoustic Channel

Deep Learning Based Single Carrier Communications Over Time-Varying Underwater Acoustic Channel

In recent years, deep learning (DL) techniques have shown great potential in wireless communications. Unlike DL-based receivers for time-invariant or slow time-varying channels, we propose a new DL-based receiver for single carrier communication in time-varying underwater acoustic (UWA) channels. Wi...

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Bibliographic Details
Main Authors: Youwen Zhang, Junxuan Li, Yuriy V. Zakharov, Jianghui Li, Yingsong Li, Chuan Lin, Xiang Li
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Channel equalization
deep learning
deep neural network
DFE
machine learning
single carrier communication
Online Access:https://ieeexplore.ieee.org/document/8672093/

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