A New Blind Equalization Algorithm Based on Data Reusing

Soft Decision Adjusted Modulus Algorithm (SDAMA) is a new blind equalization algorithm with high performance which introduces soft decision to reduce misestimation while maintaining low residual error. However, the convergence rate is not fast when dealing the burst signals and time-varying channel signals. In addition, SDAMA not only fails to correct the phase deflections in the received signals but also generates additional errors. In this paper, we construct a new data reusing algorithm to further improve the convergence rate of the equalization algorithm, and combine decision directed (DD) scheme to correct the phase deflection.