A Data Reuse Fast NLMS Algorithm for Acoustic Echo Cancellation

This paper addresses the challenge of Acoustic Echo Cancellation (AEC) using adaptive filtering algorithms, introducing the Data-Reuse Fast Normalized Least Mean Square (DR-FNLMS) algorithm. This algorithm incorporates the Data-Reuse (DR) method into the fast NLMS framework, the DR-FNLMS algorithm ensures stability, while its tracking performance can be precisely tuned through the adjustment of the data-reuse parameter. Simulation-based performance evaluations demonstrate that the DR-FNLMS algorithm significantly outperforms the original FNLMS, particularly in terms of convergence rate and tracking capabilities, making it a robust and reliable choice for practical applications.