Acoustic Echo and Noise Canceller Using Shared-Error Normalized Least Mean Square Algorithm

We propose an acoustic echo and noise canceller (AENC) using a shared-error normalized least mean square (SENLMS) algorithm. The AENC consists of an acoustic echo canceller (AEC) and a noise suppressor (NS) to reduce the acoustic echo and background noise. One of the structures of the AENC is the AEC based on a frequency-domain block normalized least mean square (FBNLMS) algorithm and the NS based on a Wiener filter (WF). However, FBNLMS and WF are different from each other in terms of the optimization problem. Hence, it is difficult to optimize both the AEC and the NS at the same time. In this paper, the SENLMS algorithm is proposed and used for the AENC. The proposed AENC utilizes time-domain adaptive digital filters (ADFs) for both the AEC and the adaptive noise canceller (ANC), and two ADFs are optimized by the NLMS algorithm with the shared error. Simulation results show that the proposed AENC can improve the ability of acoustic echo reduction while maintaining the ability of noise reduction under the high and low signal-to-noise ratio conditions.