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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Bibliographic Details
Published in:	IEEE communications letters Vol. 24; no. 8; pp. 1808 - 1811
Main Authors:	Huang, Lihuan, Zhang, Qunfei, Zhang, Lifan, Shi, Juan, Zhang, Lingling
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.08.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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
Online Access:	Get full text
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