NOVEL ADAPTIVE EQUALIZERS FOR THE NONLINEAR CHANNEL USING THE KERNEL LEAST MEAN SQUARES ALGORITHM

  • Nguyễn Viết Minh

Abstract

The combination of the kernel trick and the least-mean-square (LMS)
algorithm provides an interesting sample by sample update for an adaptive
equalizer in reproducing Kernel Hilbert Spaces (RKHS), which is named here the
KLMS. This paper shows that in the finite training data case, the KLMS algorithm
is well-posed in RKHS without the addition of an extra regularization term to
penalize solution norms. In this paper, we propose an algorithm for Kernel
equalizers based on LMS algorithm with more simple computation, while the
convergence rate will be adjusted based on the algorithm's control step size. The
solution can be applied to the equalizers in OFDM satellite systems in order to
reduce output errors and capacity of computation.
điểm /   đánh giá
Published
2020-03-18
Section
RESEARCH AND DEVELOPMENT