Decision feedback equalizer design using support vector machines

Abstract

We consider the conventional decision feedback equalizer (DFE) that employs a linear combination of the channel observations and the past decisions. The design of this class of DFE is to construct a hyperplane that separates the different signal classes. It is well known that the popular minimum mean square error (MMSE) design is generally not the optimal minimum bit error rate (MBER) solution. We propose a strategy for designing the DFE based on support vector machines (SVM). The SVM design achieves asymptotically the MBER solution and is superior in performance to the usual MMSE solution. Unlike the exact MBER solution, this SVM solution can be computed much more efficiently.

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