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Optimum Turbo Equalization Method based on Layered Space Time Codes in Underwater Communications

MIMO 수중통신에서 최적의 터보 등화 기법

  • 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)
  • Received : 2014.02.21
  • Accepted : 2014.03.31
  • Published : 2014.05.31

Abstract

The performance of underwater acoustic(UWA) communication system is sensitive to the Inter-Symbol Interference(ISI) due to delay spread develop of multipath signal propagation. And due to limited frequency using acoustic wave, UWA is a low transmission rate. Thus, it is necessary technique of Space-time code, equalizer and channel code to improve transmission speed and eliminate ISI. In this paper, UWA communication system were analyzed by simulation using these techniques. In the result of simulation, the proposed Turbo Equalization method based on layered Space Time Codes has improved performance compared to conventional UWA communication.

수중에서의 음향 통신의 성능은 신호의 다중경로 전달과정에 의해 발생하는 지역 확산 현상으로 인하여 인접간섭의 영향을 받는다. 그리고 음파를 이용한 주파수의 제한으로 인하여 낮은 전송 속도로 통신을 한다. 따라서 전송속도의 향상과 함께 인접간섭을 제거하기 위하여 수중 통신에 적합한 시공간 부호화 기술과 등화기 기술, 채널 부호화 기술이 필요하다. 본 논문에서는 이러한 기술들을 시뮬레이션을 통하여 MIMO 수중 통신 시스템에서 최적의 터보 등화 기법을 이용한 복호구조를 제안한다. 각 모듈별 시뮬레이션을 통한 성능결과 본 논문에서 제안한 계층적 시공간 부호화 방식 기반의 터보 등화 기법을 이용하면 일반적인 수중 통신 보다 성능이 우수함을 알 수 있다.

Keywords

References

  1. G. Ungerboeck, "Channel coding with multi level/phase signals," IEEE Trans. on Information Theory, Vol. IT-28, No. 1, 1982.
  2. M. J. Gans, G. J. Foschini, "On limits of wireless communication in a fading environment when wsing multiple antennas," Wireless Personal Communication, Vol. 5, No. 3, pp. 311-335, 1998.
  3. R. S. Blum, X. Lin, "Improved space-time codes using serial concatenation", IEEE Communication Letter, Vol. 4, pp. 221-223, 2000. https://doi.org/10.1109/4234.852921
  4. C. Berrou, A. Glavieux, and P. Thitimajshima, "Near Shanon Limit Error-Correcting Coding and Decoding : Turbo-Codes", in Proc. ICC9, 1993.
  5. 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.
  6. M. Tuchler, et al. "Turbo Equalization : Principles and New Results," IEEE Trans. Communications, Vol. 50, No. 5, pp. 754-767, 2002. https://doi.org/10.1109/TCOMM.2002.1006557
  7. S. Alamouti, "A simple transmit diversity technique for wireless communications," IEEE J. Select. Areas Commun., vol. 16, pp. 1451-1458, Aug. 1998. https://doi.org/10.1109/49.730453
  8. Jung, Ji Won, and Ki Man Kim. "Optimizing of Iterative Turbo Equalizer for Underwater Sensor Communication." International Journal of Distributed Sensor Networks 2013, 2013.
  9. Q. H. Spencer, A. L. Swindlehurst, and M. Haardt, "Zero-forcing methods for downlink spatial multiplexing in multi-user MIMO channels," IEEE Transactions on Signal Processing, vol. 52, no. 2, February 2004.
  10. J. Salz, "Optimum Mean-Square Decision Feedbac Equalization," BSTJ, 52, No. 8 (October 1973), p. 1341-73. 4.
  11. 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.

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