NORMALIZED SLIDING WINDOW CONSTANT MODULUS AND DECISION-DIRECTED ALGORITHMS - A LINK BETWEEN BLIND EQUALIZATION AND CLASSICAL ADAPTIVE FILTERING

By minimizing a deterministic criterion of the constant modulus (CM) t ype or of the decision-directed (DD) type, we derive normalized stocha stic gradient algorithms for blind linear equalization (BE) of QAM sys tems, These algorithms allow us to formulate CM and DD separation prin ciples, which help obtain a whole family of CM or DD BE algorithms fro m classical adaptive filtering algorithms, We focus on the algorithms obtained by using the affine projection adaptive filtering algorithm ( APA), Their increased convergence speed and ability to escape from loc al minima of their cost function make these algorithms very promising for BE applications.