Adaptive and efficient nonlinear channel equalization for underwater acoustic communication

Date
2017
Authors
Kari, D.
Vanli, N. D.
Kozat, S. S.
Advisor
Instructor
Source Title
Physical Communication
Print ISSN
1874-4907
Electronic ISSN
Publisher
Elsevier B.V.
Volume
24
Issue
Pages
83 - 93
Language
English
Type
Article
Journal Title
Journal ISSN
Volume Title
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.

Course
Other identifiers
Book Title
Keywords
Adaptive filter, Nonlinear 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
Citation
Published Version (Please cite this version)