Adaptive minimum bit-error rate equalization for binary signaling

We consider the design and adaptation of a linear equalizer with a finite n umber of coefficients in the contest of a classical linear intersymbol-inte rference channel with Gaussian noise and a memoryless decision device. If t he number of equalizer coefficients is sufficient, the popular minimum mean -squared-error (MMSE) linear equalizer closely approximates the optimal lin ear equalizer that directly minimizes bit-error rate (BER). However, when t he number of equalizer coefficients is insufficient to approximate the chan nel inverse, the minimum-BER equalizer ran outperform the MMSE equalizer by as much as 16 dB in certain cases. We propose a simple stochastic adaptive algorithm for realizing the minimum-BER equalizer. Compared to the least-m ean-square algorithm, the proposed algorithm can provide a substantial redu ction in BER with no increase in complexity.