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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Principais autores:	Sabna Thenginthody Hassan, Peng Chen, Yue Rong, Kit Yan Chan
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	MDPI AG 2024-09-01
סדרה:	Sensors
נושאים:	underwater acoustic communication orthogonal frequency-division multiplexing long short-term memory deep neural network convolutional neural network Doppler shift
גישה מקוונת:	https://www.mdpi.com/1424-8220/24/18/5995
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