An adaptive equalizer with significantly reduced number of operations

In adaptive equalization, the coefficients of a transversal filter are automatically adjusted according to a minimum mean-square error criterion. The convolution for the filter process and the cross-correlation in the coefficient-adjustment algorithm require a large number of arithmetic operations. This paper describes an equalizer for complex signals in which filtering and coefficient adjustment are performed in the frequency domain employing Winograd's Fourier transform algorithms. Compared to the time-domain implementation, the number of multiplications is reduced by typically a factor five without increasing the number of additions. A fast initialization algorithm will be presented. In contrast to earlier work, the convergence behavior will be shown for random data signals transmitted over realistic telephone channels.