Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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Euclidean Distance of Biased Error Probability for Communication in Non-Gaussian Noise

비-가우시안 잡음하의 통신을 위한 바이어스된 오차 분포의 유클리드 거리

  • Kim, Namyong (School of Electronic, Info. & Comm. Engineering, kangwon National University)
  • 김남용 (강원대학교 전자정보통신공학부)
  • Received : 2012.10.04
  • Accepted : 2013.03.07
  • Published : 2013.03.31
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Abstract

In this paper, the Euclidean distance between the probability density functions (PDFs) for biased errors and a Dirac-delta function located at zero on the error axis is proposed as a new performance criterion for adaptive systems in non-Gaussian noise environments. Also, based on the proposed performance criterion, a supervised adaptive algorithm is derived and applied to adaptive equalization in the shallow-water communication channel distorted by severe multipath fading, impulsive and DC-bias noise. The simulation results compared with the performance of the existing MEDE algorithm show that the proposed algorithm yields over 5 dB of MSE enhancement and the capability of relocating the mean of the error PDF to zero on the error axis.

비-가우시안 잡음 환경의 적응 시스템을 위해, 평행 이동한 오차 분포와 오차 0에 위치한 델타 함수 사이의 유클리드 거리를 새로운 성능기준으로 제안하였다. 또한, 이 성능 기준에 근거하여 적응 알고리듬을 개발하였고, 얕은 바다에서 구한 수중 통신 다경로 채널에 충격성 잡음과 직류 바이어스 잡음이 더해진 환경으로 등화 성능을 시뮬레이션한 결과, 제안한 알고리듬이 기존의 MEDE 알고리듬 보다 5 dB 이상 향상된 MSE 성능을 보이며 오차 분포의 중심 위치가 정확히 0에 위치하였다.

Keywords

References

  1. F. Traverso, G. Vernazza, A. Trucco, "Simulation of non-White and non-Gaussian underwater ambient noise", OCEANS-2012, Yeosu, pp.1-10, May 2012.
  2. E. Voudouri, L. Kurz, "A class of sequential adaptive detectors for underwater non-Gaussian noise environments", IEEE Journal of Oceanic Engineering, vol. 12, pp. 38 - 47, Jan 1987. DOI: http://dx.doi.org/10.1109/JOE.1987.1145247
  3. N. Kim, "Communication equalizer Algorithms with Decision feedback based on Error probability", Journal of The Korea Academia-Industrial cooperation Society, vol. 12, no. 5, pp. 2390-2395, May, 2011. https://doi.org/10.5762/KAIS.2011.12.5.2390
  4. S. Kassam, Signal Detection in Non-Gaussian Noise, Springer-Verlag, 1988. DOI: http://dx.doi.org/10.1007/978-1-4612-3834-8
  5. H. Sedarat, and K. Fishera, "Multicarrier communication in presence of biased-Gaussian noise sources", Signal Processing, vol. 88, pp. 1627-1635, July 2008. DOI: http://dx.doi.org/10.1016/j.sigpro.2007.11.025
  6. E. Parzen, "On the estimation of a probability density function and the mode," Ann.Math.Stat. vol. 33, p. 1065, 1962. DOI: http://dx.doi.org/10.1214/aoms/1177704472
  7. S. Kim, S. Kim, C. Youn, and Y. Lim, "Performance analysis of receiver for underwater acoustic communications using acquisition data in shallow water", Journal of Acoustical Society of Korea, vol. 29, no. 5, pp. 303-313, May 2010.