A modified EVA/DD algorithm for the equalization of non-constant modulus signals based on eigen analysis of cross-cumulants
Said E. El‐Khamy, S.E. Shaaban, Ahmed K. Sadek · 2003
This paper presents a modified approach for enhancing the performance of the eigenvector approach (EVA) based on the cross-cumulants criterion for blindly equalizing non-constant modulus signals. The EVA algorithm depends only on the known statistical properties of the data source. The modified approach presented in this paper takes into account the extra information about the known constellation alphabet of the data source through utilizing the decision directed (DD) algorithm. It is shown with simulation that this extra information will dramatically enhance the performance of the modified EVA/DD equalizer.