Conference Paper

Variable step-size NLMS algorithms designed for echo cancellation

Univ. Politeh. of Bucharest, Bucharest, Romania
DOI: 10.1109/ACSSC.2009.5469916 Conference: Signals, Systems and Computers, 2009 Conference Record of the Forty-Third Asilomar Conference on
Source: IEEE Xplore

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: Numerous variable step-size normalized least mean-square (VSS-NLMS) algorithms have been derived to solve the dilemma of fast convergence rate or low excess mean-square error in the past two decades. This paper proposes a new, easy to implement, nonparametric VSS-NLMS algorithm that employs the mean-square error and the estimated system noise power to control the step-size update. Theoretical analysis of its steady-state behavior shows that, when the input is zero-mean Gaussian distributed, the misadjustment depends only on a parameter $\beta$ controlling the update of step size. Simulation experiments show that the proposed algorithm performs very well. Furthermore, the theoretical steady-state behavior is in very good agreement with the experimental results.
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