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A Performance Evaluation of Blind Equalization Algorithma for a Variable Step-Size MSAG-GMMA

가변 스텝 크기 MSAG-GMMA 적응 블라인드 등화 알고리즘의 성능 평가

  • 정영화 (남서울대학교 정보통신공학과)
  • Received : 2018.05.08
  • Accepted : 2018.06.08
  • Published : 2018.06.30

Abstract

This paper is concerned with the performance analysis of a modified stop-and-go generalized multi-modulus algorithm (MSAG-GMMA) adaptive blind equalization algorithm with variable step size. The proposed algorithm multiplies the fixed step size by the error signal of the decision-oriented algorithm in the equalization coefficient update equation, and changes the step size according to the error size. Also, the MSAG-GMMA having a fixed step size is operated so as to maintain a fast convergence speed from a certain threshold to a steady state by determining the error signal size of the decision-directed algorithm, and when the MSAG-GMMA to work To evaluate the performance of the proposed algorithm, we use the ensemble ISI, ensemble-averaged MSE, and equalized constellation obtained from the output of the equalizer as the performance index. Simulation results show that the proposed algorithm has faster convergence speeds than MMA, GMMA, and MSAG-GMMA and has a small residual error in steady state.

본 논문은 가변 스텝 크기를 가지는 MSAG-GMMA(modified Stop-and-Go generalized multi modulus algorithm) 적응 블라인드 등화 알고리즘의 성능 분석에 관한 것이다. 제안한 알고리즘은 등화 계수 갱신 식에서 고정 스텝 크기에 결정지향 알고리즘의 오차신호의 크기를 곱하여 오차크기에 따라서 스텝 크기가 변하도록 하였다. 또한 결정지향 알고리즘의 오차신호의 크기를 판단하여 어느 임계값 이상에서는 정상상태로의 빠른 수렴 속도를 유지하도록 스텝 크기가 고정인 값을 가지는 MSAG-GMMA가 동작하고, 미만일 때는 스텝 크기가 가변되는 MSAG-GMMA가 동작하도록 하였다. 제안한 알고리즘의 성능을 평가하기 위하여 성능 지수로 앙상블 ISI, 앙상블-평균 MSE, 그리고 등화기의 출력으로 얻어지는 등화 후 신호점도를 사용하였다. 모의실험을 통하여 제안한 알고리즘이 MMA, GMMA, 그리고 MSAG-GMMA보다 빠른 수렴 속도와 정상상태에서 작은 잔류 오차를 가짐을 확인하였다.

Keywords

Acknowledgement

Supported by : 남서울대학교

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