Deep Learning-Based Cyclic Shift Keying Spread Spectrum Underwater Acoustic Communication

A deep learning-based cyclic shift keying spread spectrum (CSK-SS) underwater acoustic (UWA) communication system is proposed for improving the performance of the conventional system in low signal-to-noise ratio and multipath effects. The proposed deep learning-based system involves the long- and sh...

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Autores principales:	Yufei Liu, Feng Zhou, Gang Qiao, Yunjiang Zhao, Guang Yang, Xinyu Liu, Yinheng Lu
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	cyclic shift keying spread spectrum low signal-to-noise ratio multipath effects neural network model long- and short-term memory Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
Acceso en línea:	https://doaj.org/article/c96b736ec43c41df9a58407429dbf879
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Deep Learning-Based Cyclic Shift Keying Spread Spectrum Underwater Acoustic Communication

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