Variable Step-Size Least Mean Modulus Algorithm for robust filtering in digital QAM systems

This paper proposes Variable Step-Size Least Mean Modulus Algorithm (VSS-LMMA) for robust filtering in impulsive noise environments. The VSS-LMMA for use in adaptive filters in digital QAM systems is basically the LMMA combined with a new simple variable step-size control algorithm to improve the convergence speed of the LMMA while preserving its robustness against additive impulsive observation noise. Through analysis and experiment, we demonstrate effectiveness of the proposed VSS-LMMA in making adaptive filters fast convergent and highly robust in the presence of impulsive observation noise. Good agreement between simulated and theoretical convergence behavior in transient and steady state proves the validity of the analysis.