Balanced Information Potentials for PDF-Distance Algorithms with Constant Modulus Error

Blind equalization techniques have been widely used in wireless communication systems. In this paper, we propose to apply the balanced information potentials to the criterion of minimum Euclidian distance between two PDFs with constant modulus errors for adaptive blind equalizers. One of the two PDFs is constructed with constant modulus error samples and another does with Dirac delta functions. Two information potentials derived from the criterion are balanced in order to have better performance by putting a weighting factor to each information potentials. The proposed blind algorithm has shown in the MSE convergence performance that it can produce enhanced performance by over 3 dB of steady state MSE.