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

  • 제10권3호
  • /
  • Pages.542-546
  • /
  • 2009
  • /
  • 1975-4701(pISSN)
  • /
  • 2288-4688(eISSN)
한국산학기술학회 (The Korea Academia-Industrial cooperation Society)
권호 표지
DOI QR코드

DOI QR Code

셀룰라 이동 통신에서 NNAC를 이용한 협대역 간섭 신호 제어

A NNAC using narrowband interference signal control in cellular mobile communication systems

  • 조현섭 (청운대학교 디지털방송공학과)
  • Cho, Hyun-Seob (Dept. of Digital Broadcast Engineering, Chungwoon University)
  • 발행 : 2009.03.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 논문은 신경망을 이용한 간섭 신호 제어로써 합성 다층 퍼셉트론에 입각하여 셀룰라 이동통신에서의 수신된 신호들을 역전파 학습알고리즘을 이용하여 검파하는 것에 대하여 소개하였다. 그리고 컴퓨터 시뮬레이션 결과를 통하여 co-channel간섭과 협대역 간섭의 실제 음색에서 기존에 쓰여진 Rake수신기보다 더 낮은 비트 오차 확률을 가지는 NNAC(neural network adaptive correlator)에 대하여 분석 고찰하였다.

In this Paper, a back propagation neural network learning algorithm based on the complex multilayer perceptron is represented for controling and detecting interference of the received signals in cellular mobile communication system. We proposed neural network adaptive correlator which has fast convergence rate and good performance with combining back propagation neural network and the receiver of cellular. We analyzed and proved that NNAC has lower bit error probability than that of traditional RAKE receiver through results of computer simulation in the presence of the tone and narrow - band interference and the co-channel interference.

키워드

참고문헌

  1. W. C. Y. Lee, "Mobile Cellular Telecommunications", McGRAW-HILL CO., pp.1797-208, 1990.
  2. Israe Kom, "Differential Phase Shift Keying in Two-path Rayleigh Channel With Adjacent Channel Interference" IEEE Tran. Vol. 40. pp.461-471, 5월, 1991. https://doi.org/10.1109/25.289428
  3. R.C Dixon "Spread Spectrum System", wiley interscience, 1976.
  4. Sang-Dong Ra, Hyeon-Seob Cho, " A Study on Neur ai-fuzzy Pattern Matching Word Recognition" 'NNASP'93, 8월, 1993.
  5. J. Gevargiz, P. K. Das, and L. B. Milstein "Adaptive Narrow-Band Interference Rejection in a DS Spread-S pectrum Intercept Receiver Using Transform Domain Signal Processing Techniques" in IEEE Trans, Commun. Vol 37, pp 1359-1366, 12월, 1989. https://doi.org/10.1109/26.44207
  6. J. J. Hopfield and D. Tank, "Neural computation of decision in optimization problems," Biol. Cybern., Vol 52, pp. 141-152, 1985.
  7. J. Ramanujam and P. Sadayappan, "Optimization by neural networks," IEEE Conference on Neural Networks, San Diego, Vol, 2. pp, 325-332. 7월, 1988. https://doi.org/10.1109/ICNN.1988.23944
  8. A. J. Maren, C. T. Harston, and R. M. Pap, Handbook of neural computing application, Academic Press, pp. 107-250, 1990.