Neural Network Approach for Underwater Acoustic Communication in the Shallow Water

被引:0
作者
Park, K. C. [1 ]
Yoon, J. R. [1 ]
机构
[1] Pukyong Natl Univ, Dept Informat & Commun Engn, Busan, South Korea
来源
PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INDUSTRIAL ENGINEERING (AIIE 2015) | 2015年 / 123卷
关键词
underwater acoustic communication; shallow water; QPSK system; neural network; inter-symbol interference;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The transmitted acoustic signals are severely influenced by boundaries like as sea surface and bottom in the shallow water. Very large reflection signals from boundaries cause inter-symbol interference effect, the performance of the communication are degraded. Usually, to compensate the reflected signals under this kind of acoustic channel, is adopting the channel estimation based equalizers. In this study, we express neural network approaches for image data transmission in the shallow water. A simple neural network is adopted for the decision from output data. The QPSK system is used for the underwater acoustic communication simulations and experiments.
引用
收藏
页码:200 / 202
页数:3
相关论文
共 50 条
[31]   Research on the construction and application of polar codes for shallow water acoustic communication [J].
Xing L. ;
Li Z. ;
Huang Y. .
Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University, 2024, 51 (02) :116-125
[32]   Automatic modulation identification for underwater acoustic signals based on the space-time neural network [J].
Lyu, Yaohui ;
Cheng, Xiao ;
Wang, Yan .
FRONTIERS IN MARINE SCIENCE, 2024, 11
[33]   On the Possibility of using Vertical Receiving Arrays for Underwater Acoustic Communication on the Arctic Shelf [J].
Volkov, M. V. ;
Grigoriev, V. A. ;
Lunkov, A. A. ;
Petnikov, V. G. .
ACOUSTICAL PHYSICS, 2019, 65 (03) :269-278
[34]   Underwater Acoustic Communications: Long-Term Test of Turbo Equalization in Shallow Water [J].
Otnes, Roald ;
Eggen, Trym Haakon .
IEEE JOURNAL OF OCEANIC ENGINEERING, 2008, 33 (03) :321-334
[35]   Underwater acoustic wireless multiuser communication [J].
Yin Jingwei ;
Wang Lei ;
Chen Kai .
2008 IFIP INTERNATIONAL CONFERENCE ON WIRELESS AND OPTICAL COMMUNICATIONS NETWORKS, 2008, :123-+
[36]   Spectral Efficient Neural Network-Based M-ary Chirp Spread Spectrum Receivers for Underwater Acoustic Communication [J].
Liu, Songzuo ;
Zuberi, Habib Hussain ;
Arfeen, Zuhair ;
Zhang, Xuanye ;
Bilal, Muhammad ;
Sun, Zongxin .
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2024, 49 (12) :16593-16609
[37]   Characterization of underwater acoustic communication channel [J].
Malarkodi, A. ;
Lathaa, G. ;
Srinivasanb, S. .
INDIAN JOURNAL OF GEO-MARINE SCIENCES, 2020, 49 (08) :1323-1329
[38]   Underwater acoustic target recognition using line enhancement and deep neural network [J].
Yu X. ;
Chi C. ;
Li S. ;
Li D. .
Shengxue Xuebao/Acta Acustica, 2024, 49 (04) :656-663
[39]   An MMSE Approach to Channel Shorting for Underwater Acoustic FH-FSK Communication [J].
Fan, Weiwei ;
Liu, Lu ;
Zhang, Youwen ;
Dong, Jigang ;
Sun, Dajun .
SENSORS, MECHATRONICS AND AUTOMATION, 2014, 511-512 :334-341
[40]   Experimental evaluation of norm constraint sparsity exploitation for shallow water acoustic communication [J].
Cao, Xiuling ;
Tong, Feng ;
Li, Bin ;
Zheng, Siyuan .
APPLIED ACOUSTICS, 2021, 180