Adaptive and efficient nonlinear channel equalization for underwater acoustic communication
Date
2017Source Title
Physical Communication
Print ISSN
1874-4907
Publisher
Elsevier B.V.
Volume
24
Pages
83 - 93
Language
English
Type
ArticleItem Usage Stats
151
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views
108
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downloads
Abstract
We investigate underwater acoustic (UWA) channel equalization and introduce hierarchical and adaptive nonlinear (piecewise linear) channel equalization algorithms that are highly efficient and provide significantly improved bit error rate (BER) performance. Due to the high complexity of conventional nonlinear equalizers and poor performance of linear ones, to equalize highly difficult underwater acoustic channels, we employ piecewise linear equalizers. However, in order to achieve the performance of the best piecewise linear model, we use a tree structure to hierarchically partition the space of the received signal. Furthermore, the equalization algorithm should be completely adaptive, since due to the highly non-stationary nature of the underwater medium, the optimal mean squared error (MSE) equalizer as well as the best piecewise linear equalizer changes in time. To this end, we introduce an adaptive piecewise linear equalization algorithm that not only adapts the linear equalizer at each region but also learns the complete hierarchical structure with a computational complexity only polynomial in the number of nodes of the tree. Furthermore, our algorithm is constructed to directly minimize the final squared error without introducing any ad-hoc parameters. We demonstrate the performance of our algorithms through highly realistic experiments performed on practical field data as well as accurately simulated underwater acoustic channels. © 2017 Elsevier B.V.
Keywords
Adaptive filterNonlinear channel equalization
Piecewise linear equalization
Self-organizing tree
Underwater acoustic communication
Adaptive filtering
Adaptive filters
Bit error rate
Equalizers
Errors
Forestry
Optical communication
Piecewise linear techniques
Trees (mathematics)
Bit error rate (BER) performance
Equalization algorithms
Nonlinear channel
Piecewise linear
Piecewise linear modeling
Self-organizing trees
Underwater acoustic channels
Underwater acoustic communications
Underwater acoustics
Permalink
http://hdl.handle.net/11693/37343Published Version (Please cite this version)
http://dx.doi.org/10.1016/j.phycom.2017.06.001Collections
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