Abstract
The problem of blind adaptive equalization of underwater single-input multiple-output (SIMO) acoustic channels was analyzed by using the linear prediction method. Minimum mean square error (MMSE) blind equalizers with arbitrary delay were described on a basis of channel identification. Two methods for calculating linear MMSE equalizers were proposed. One was based on full channel identification and realized using RLS adaptive algorithms, and the other was based on the zero-delay MMSE equalizer and realized using LMS and RLS adaptive algorithms, respectively. Performance of the three proposed algorithms and comparison with two existing zero-forcing (ZF) equalization algorithms were investigated by simulations utilizing two underwater acoustic channels. The results show that the proposed algorithms are robust enough to channel order mismatch. They have almost the same performance as the corresponding ZF algorithms under a high signal-to-noise (SNR) ratio and better performance under a low SNR.
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Foundation item: Supported by the National Natural Science Foundation of China under Grant No.60372086 and the Foundation for the Author of National Excellent Doctoral Dissertation of China under Grant No.200753.
Yinbing Zhang was born in 1983. He is a PhD candidate for underwater acoustic engineering. His research interests include underwater acoustic signal processing, communication signal processing and channel equalization.
Junwei Zhao was born in 1937. He is a professor of Northwestern Polytechnical University. His research interests include underwater acoustic signal processing, sonar technique, underwater acoustic communication, et al.
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Zhang, Y., Zhao, J., Guo, Y. et al. Blind adaptive MMSE equalization of underwater acoustic channels based on the linear prediction method. J. Marine. Sci. Appl. 10, 113–120 (2011). https://doi.org/10.1007/s11804-011-1050-9
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DOI: https://doi.org/10.1007/s11804-011-1050-9