Coefficients-Switched Normalized Least-Mean- Squares Adaption in Echo Canceler of Sparse-Echo-Path
The Normalized Least-Mean-Squares (NLMS) algorithm commonly used in echo cancelers suffers from a number of limitations due to the existing sparsity in the echo path. Although some sparsity-aware algorithms have been proposed, the high computational complexity greatly increases the their difficulty of implementation. To reduce the complexity and improve the performance in echo cancelers, we introduce a Coefficients-Switched (CS) processing into the NLMS algorithm and propose the CS-NLMS algorithm and the Mean-square-deviation (MSD) analysis to evaluate its effectiveness. Simulations of the MSD were performed with different system parameters. The performance of the proposed algorithm is verified by comparison with the simulation results of the previously proposed algorithms. The superiority of the proposed algorithm in terms of computational complexity is also discussed.
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Coefficients-Switched Normalized Least-Mean- Squares Adaption in Echo Canceler of Sparse-Echo-Path
Semantic Scholar · Engineering · 2023
Abstract
The Normalized Least-Mean-Squares (NLMS) algorithm commonly used in echo cancelers suffers from a number of limitations due to the existing sparsity in the echo path. Although some sparsity-aware algorithms have been proposed, the high computational complexity greatly increases the their difficulty of implementation. To reduce the complexity and improve the performance in echo cancelers, we introduce a Coefficients-Switched (CS) processing into the NLMS algorithm and propose the CS-NLMS algorithm and the Mean-square-deviation (MSD) analysis to evaluate its effectiveness. Simulations of the MSD were performed with different system parameters. The performance of the proposed algorithm is verified by comparison with the simulation results of the previously proposed algorithms. The superiority of the proposed algorithm in terms of computational complexity is also discussed.