关键词: 非线性信道均衡, 再生核希尔伯特空间, 核方法, 维纳模型, 仿射投影算法, 核仿射投影算法, 蒙特卡罗方法

Abstract: It is necessary to research nonlinear channel equalization to reduce Inter-Symbol-Interference（ISI） in the high-
rated wireless communication area. Adaptive equalization algorithm of nonlinear channel is studied in the Reproducing Kernel Hilbert Space（RKHS）. The structure of equalizer is proposed on nonlinear Wiener model and Kernel Affine Projection Algorithms（KAPA） is derived based on kernel method in RKHS and Affine Projection Algorithms（APA）. A simulation for the proposed adaptive algorithm is made by Monte Carlo method and comparisons are drawn between the algorithm and the others in the paper on convergence performance, bit error rate, traceability, computational complexity and so on. Simulation results show that the proposed algorithm can greatly reduce Bits Error Ratio（BER） without increasing computation complexity and is well suited for time-varying, nonlinear channel equalization.

Key words: nonlinear channel equalization, reproducing kernel Hilbert space, kernel method, Winner model, Affine Projection Algorithm（APA）, Kernel Affine Projection Algorithm（KAPA）, Monte Carlo method