An Adaptive Blind Equalizer Using Gaussian Two-Cluster Model

Abstract

In this paper, blind equalization technique using Gaussian two-cluster model is proposed. The proposed approach, by modeling the received M-QAM signals as Gaussian distributed two-cluster, minimizes the computational complexity and enhances the reliability of the signal estimates. In addition, by using a nonlinear estimator with variable parameters to estimate the transmitted signal, and by selectively applying the reduced constellation and the original constellation when estimating the signals, the reliability of the signal estimation was further improved. As a result, the proposed approach has improved the performance while reducing the complexity of the equalizer. Through computer simulations for blind equalization of higher-order signals of 64-QAM, it was confirmed that the proposed method showed better performance than traditional approaches. . 아울 러 블라인드 등화는 눈모형을 열리게 하는 것에 중 점을 두기 때문에 눈모형이 열린 이후의 수렴 성능 은, 예를 들면 excess MSE(mean square error) 레