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Title: Accurate channel estimation and adaptive underwater acoustic communications based on Gaussian likelihood and constellation aggregation
Authors: Wang, Liang
Qiao, Peiyue
Liang, Junyan
Chen, Tong
Wang, Xinjie
Yang, Guang
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Source: Wang, L., Qiao, P., Liang, J., Chen, T., Wang, X. & Yang, G. (2022). Accurate channel estimation and adaptive underwater acoustic communications based on Gaussian likelihood and constellation aggregation. Sensors, 22(6), 2142-.
Journal: Sensors
Abstract: Achieving accurate channel estimation and adaptive communications with moving transceivers is challenging due to rapid changes in the underwater acoustic channels. We achieve an accurate channel estimation of fast time-varying underwater acoustic channels by using the superimposed training scheme with a powerful channel estimation algorithm and turbo equalization, where the training sequence and the symbol sequence are linearly superimposed. To realize this, we develop a 'global' channel estimation algorithm based on Gaussian likelihood, where the channel correlation between (among) the segments is fully exploited by using the product of the Gaussian probability-density functions of the segments, thereby realizing an ideal channel estimation of each segment. Moreover, the Gaussian-likelihood-based channel estimation is embedded in turbo equalization, where the information exchange between the equalizer and the decoder is carried out in an iterative manner to achieve an accurate channel estimation of each segment. In addition, an adaptive communication algorithm based on constellation aggregation is proposed to resist the severe fast time-varying multipath interference and environmental noise, where the encoding rate is automatically determined for reliable underwater acoustic communications according to the constellation aggregation degree of equalization results. Field experiments with moving transceivers (the communication distance was approximately 5.5 km) were carried out in the Yellow Sea in 2021, and the experimental results verify the effectiveness of the two proposed algorithms.
ISSN: 1424-8220
DOI: 10.3390/s22062142
Schools: School of Electrical and Electronic Engineering 
Rights: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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