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http://dx.doi.org/10.6109/jkiice.2014.18.9.2094

Optimizing of BCJR Equalization with BCJR Decoder in the Underwater Communication  

Kim, Tae-Hun (Department of Radio Communication Engineering, Korea Maritime and Ocean University)
Jung, Ji-Won (Department of Radio Communication Engineering, Korea Maritime and Ocean University)
Park, Tae-Doo (Hanwha Corporation Gumi Plant (Development Team3))
Lee, Dong-Won (Hanwha Corporation Gumi Plant (Development Team3))
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.18, no.9, 2014 , pp. 2094-2100 More about this Journal
Abstract
The performance of underwater acoustic communication system is sensitive to the inter-symbol interference due to delay spread develop of multipath signal propagation. Thus, it is necessary technique of equalizer and channel code to eliminate inter-symbol interference. In this paper, underwater acoustic communication system were analyzed by experiment using these techniques on the Kyeong-chun lake, Munkyeong City. Based on the results of experiment, we confirmed that the performance of the proposed iterative BCJR equalization method is improved by increasing the number of iterations.
Keywords
Underwater acoustic communication; Convolutional codes; BCJR equalization; BCJR decoding; DFE (Decision Feedback Equalizer);
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1 Daniel B. Kilfoyle and Arthur B. Baggeroer , "The state of art in underwater acoustic telemetry," IEEE J. Oceanic Eng., vol.25, no.1, pp.4-27, Jan. 2000.   DOI   ScienceOn
2 M. Stojanovic, J. Catipovic, and J. Proakis, "Phase coherent digital communications for underwater acoustic channels.", IEEE J. Ocean. Eng., vol. 19, no. 1, pp.100-111, Jan. 1994.   DOI   ScienceOn
3 L. Bahl, J. Cocke, F. Jelinek, and J. Raviv, "Optimal Decoding of Linear Codes for minimizing symbol error rate", IEEE Transactions on Information Theory, vol. IT-20(2), pp. 284-287, 1974.
4 K. Berberdis, T. Rontogiannis and S. Theodoridis, "Efficient block implementation of the LMS based DFE," Proceedings 13th Digital Signal Processing International Conference, Vol.1, pp. 143-146, July 1997.
5 J. Salz, "Optimum Mean-Square Decision Feedbac Equalization," BSTJ, 52, No. 8 (October 1973), p. 1341-73. 4
6 M. Tuchler, et al. "Turbo Equalization : Principles and New Results," IEEE Trans. Communications, Vol. 50, No. 5, pp. 754-767, 2002.   DOI   ScienceOn
7 R. Koetter, A. C. Singer, and M. Tuchler, "Turbo equalization," IEEE Signal Process. Mag., vol. 21, no. 1, pp. 67-80, Jan. 2004.   DOI   ScienceOn