Efficiency Enhancement for Underwater Adaptive Modulation and Coding Systems: Via Sparse Principal Component Analysis

In this letter, to explore key channel state information (CSI) as a more efficient switching metric in the task of underwater adaptive modulation and coding (AMC), a sparse principal component analysis (SPCA) based approach is proposed from the perspective of statistical analysis plus machine learni...

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Vydané v:	IEEE communications letters Ročník 24; číslo 8; s. 1808 - 1811
Hlavní autori:	Huang, Lihuan, Zhang, Qunfei, Zhang, Lifan, Shi, Juan, Zhang, Lingling
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.08.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	adaptive modulation and coding (AMC) Adaptive systems Channel estimation Coding Feature extraction Loading Machine learning Measurement Modulation Principal component analysis Principal components analysis sparse principal component analysis (SPCA) Statistical analysis Switches Switching Underwater Underwater acoustic communication (UAC)
ISSN:	1089-7798, 1558-2558
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