Enhanced Adaptive Equalization for MIMO Underwater Acoustic Communications
Abstract
An enhanced normalized least mean squares (NLMS) adaptive equalization scheme is proposed for single-carrier underwater acoustic (UWA) communications. The enhancement is achieved via two techniques: the sparse adaptation (SA) technique and the data reuse (DR) technique. The SA technique speeds up the convergence and improves the performance of the adaptive equalization, by taking advantage of the inherent sparsity of the equalizer. It is implemented as the selective zero-attracting NLMS (SZA-NLMS) algorithm, developed by introducing a range of attraction for the existing zero-attracting NLMS (ZA-NLMS) algorithm. Compared with the ZA-NLMS, the SZA-NLMS incurs a lower complexity and achieves a better performance. The DR technique effectively prolongs the training length and significantly reduces the training overhead. Attributed to the DR technique, a high transmission efficiency is achieved even for a block transmission. The proposed adaptive equalization is verified by the real data collected in an at-sea multiple-input multiple-output (MIMO) underwater acoustic communication trial. The experimental results show it considerably outperforms the standard NLMS adaptive equalization, especially with a low DR number.
Recommended Citation
J. Tao et al., "Enhanced Adaptive Equalization for MIMO Underwater Acoustic Communications," Proceedings of OCEANS 2017 MTS/IEEE Anchorage (2017, Anchorage, AK), Institute of Electrical and Electronics Engineers (IEEE), Sep 2017.
Meeting Name
OCEANS '17 MTS/IEEE Anchorage (2017, Sep. 18-21, Anchorage, AK)
Department(s)
Electrical and Computer Engineering
Sponsor(s)
Key Laboratory of Underwater Acoustic Signal Processing, Southeast University, China
Key Laboratory of System Control and Information Processing, China
Fundamental Research Funds for the Central Universities
Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions
Keywords and Phrases
Anchorages (foundations); Carrier communication; Equalizers; MIMO systems; Adaptive equalization; Block transmissions; High transmission; Lower complexity; Normalized least mean square; Training overhead; Underwater acoustic communications; Zero-attracting; Underwater acoustics
International Standard Book Number (ISBN)
978-0-6929-4690-9
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Sep 2017
Comments
The work of Jun Tao was supported in part by the Open Project Program of the Key Laboratory of Underwater Acoustic Signal Processing of Ministry of Education, Southeast University, Nanjing, China, under Grant UASP1601, in part by the Foundation of Key Laboratory of System Control and Information Processing, Ministry of Education, P. R. China, under Grant Scip201610, in part by the Fundamental Research Funds for the Central Universities under Grant 2242016K30013, and in part by the Priority Academic Program Development (PAPD) of Jiangsu Higher Eduction Institutions under Grant 1104007112. The work of Liang An was supported in part by the Defense Industrial Technology Development Program under Grant B0720132001, and in part by the National Natural Science Foundation of China under Grant 11574048. The work was also supported in part by the Natural Science Foundation of Jiangsu Province under Grant BK20161428, and in part by the National Natural Science Foundation of China under Grant 11674057.