Machine Learning based Dolphin Whistle Tranceiver for Bio-inspired Underwater Covert Communication

被引：0

作者：

Ahn, Jongmin ^{[1
]}

Lee, Hojun ^{[1
]}

Kim, Yongcheol ^{[1
]}

Chung, Jaehak ^{[1
]}

Lee, SanKug ^{[2
]}

机构：

[1] Inha Univ, Elect Engn, Incheon, South Korea

[2] Agcy Def Dev, Jinhea, South Korea

来源：

OCEANS 2019 MTS/IEEE SEATTLE | 2019年

关键词：

bio-inspired; pattern recognize; dolphin whistle; covert underwater communication;

D O I：

暂无

中图分类号：

U6 [水路运输]; P75 [海洋工程];

学科分类号：

0814 ; 081505 ; 0824 ; 082401 ;

摘要：

This paper proposes an underwater covert communication method using variety dolphin whistle patterns. The proposed method classifies dolphin whistles into G groups, and binary information is allocated to every consecutive different dolphin whistle. Received dolphin whistles are decoded by the random forest method and the transient probability of consecutive dolphin whistles. Computer simulation demonstrates that the BER performance of the proposed method is better than that of random forest method.

引用

页数：4

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