Convergence analysis of the stop-and-go blind equalization algorithm

Unlike traditional trained channel equalizers, not much work has been done to theoretically characterize the convergence properties of blind channel e qualizers due to their inherent nonlinearity, It is only recently that conv ergence properties of some well-known algorithms such as GSA and CMA have b een analytically derived. in this' paper, the convergence properties of the stop-and-go algorithm proposed by Picchi and Prati are analyzed. The deriv ed mean squared error and the coefficient trajectories are compared with si mulation results to verify the validity of the analytical results.