Abstract
Underwater acoustic channel (UAC) is one of the most challengeable communication channels in the world, owing to its complex multi-path and absorption as well as variable ambient noise. Although adaptive equalization could effectively eliminate the inter-symbol interference (ISI) with the help of training sequences, the convergence rate of equalization in sparse UAC decreased remarkably. Besides, channel estimation algorithms could roughly figure out channel impulse response and other channel parameters through several specific mathematical criterion. In this paper, a typical channel estimation method, Least-Square (LS) algorithm is applied in adaptive equalization to obtain the initial tap weights of least-mean-square (LMS) algorithm. Simulation results show that the proposed method significantly enhances the convergence rate of the LMS algorithm.
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Acknowledgments
This work is supported in part by National Natural Science Foundation of China (No. 61401118, No. 61371100 and No. 61671184), Natural Science Foundation of Shandong Province (No. ZR2014FP016), the Foundation of Science and Technology on Communication Networks Key Laboratory, the Fundamental Research Funds for the Central Universities (No. HIT.NSRIF.2016100 and 201720) and the Scientific Research Foundation of Harbin Institute of Technology at Weihai (No. HIT(WH)201409 and No. HIT(WH)201410).
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Li, B., Zhao, Y., Yang, H., Liu, G., Peng, X. (2019). The Joint Channel Equalization and Estimation Algorithm for Underwater Acoustic Channel. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_38
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DOI: https://doi.org/10.1007/978-981-10-6571-2_38
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