Variable step-size NLMS algorithms designed for echo cancellation
ABSTRACT A major issue in echo cancellation is to recover the near-end signal from the error signal of the adaptive filter. In this paper, we use this requirement in order to design a family of variable step-size normalized least-mean-square (VSS-NLMS) algorithms. The main parameter that is needed within these algorithms is the near-end signal power estimate. Several solutions for this problem are presented and evaluated in terms of different practical aspects (i.e., available parameters, complexity). Due to their specific characteristic, these VSS-NLMS algorithms are equipped with good robustness features against near-end signal variations (e.g., double-talk) and can be reliable candidates for real-world echo cancellation scenarios.
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ABSTRACT: The paper presents an acoustic echo cancellation application of three variable step-size Normalized Least Mean Square (NLMS) algorithms: the simple VSS-NLMS (SVSS-NLMS), the new non-parametric (NEW-NPVSS-NLMS) and the practical VSS-NLMS (PVSS-NLMS) algorithms. Simulations were performed in two scenarios: single-talk and double-talk. We will prove that the PVSS-NLMS algorithm can be used in a double-talk situation without using a double-talk detector (DTD). The capabilities and performances of the algorithms are analyzed in terms of convergence rate, tracking and robustness, but also from other practical point of view, such as available parameters.01/2011;