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. Recent advances in the theory of computational complexity have yielded efficient methods which allow that processing load to be significantly reduced. This paper describes an equalizer for complex signs in which filtering and coefficient adjustment are performed in the frequency domain employing Winograd's Fourier transform algorithms. Compared to a conventional time-domain implementation, the number of multiplications is reduced by typically a factor four without increasing the number of additions . A fast initialization algorithm will be presented which overcomes the somewhat slower adjustment of the equalizer due to the blockwise processing of signal samples. The convergence behavior of the adaptive equalizer will be shown for random data signals transmitted over a realistic telephone channel.
By: D. Maiwald, H. P. Kaeser, F. Closs
Published in: RZ918 in 1978
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