Reduced Complexity Polynomial Expansion Approximation to MMSE-DFE

In this paper, we investigate polynomial expansion approximation to reduce matrix inversion complexity as encountered in the design of the minimum mean squared error decision feedback equalizer (MMSE-DFE). The scaling factor needed in this polynomial expansion is optimized for a fixed polynomial approximation order so that the received signal to interference plus noise ratio (SINR) is maximized. The BER performance of the reduced-complexity MMSE-DFE is comparable to that of the direct matrix inversion based MMSE-DFE and outperforms earlier approaches reported in the literature.