Underwater Acoustic Orthogonal Frequency-Division Multiplexing Communication Using Deep Neural Network-Based Receiver: River Trial Results

In this article, a deep neural network (DNN)-based underwater acoustic (UA) communication receiver is proposed. Conventional orthogonal frequency-division multiplexing (OFDM) receivers perform channel estimation using linear interpolation. However, due to the significant delay spread in multipath UA...

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Hlavní autoři:	Sabna Thenginthody Hassan, Peng Chen, Yue Rong, Kit Yan Chan
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	MDPI AG 2024-09-01
Edice:	Sensors
Témata:	underwater acoustic communication orthogonal frequency-division multiplexing long short-term memory deep neural network convolutional neural network Doppler shift
On-line přístup:	https://www.mdpi.com/1424-8220/24/18/5995
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