Distributed Combined Acoustic Echo Cancellation and Noise Reduction in Wireless Acoustic Sensor and Actuator Networks

Abstract

The paper presents distributed algorithms for combined acoustic echo cancellation (AEC) and noise reduction (NR) in a wireless acoustic sensor and actuator network (WASAN) where each node may have multiple microphones and multiple loudspeakers, and where the desired signal is a speech signal. A centralized integrated AEC and NR algorithm, i.e., multichannel Wiener filter (MWF), is used as starting point where echo signals are viewed as background noise signals and loudspeaker signals are used as additional input signals to the algorithm. By including prior knowledge (PK), namely that the loudspeaker signals do not contain any desired signal component, an alternative centralized cascade algorithm (PK-MWF) is obtained with an AEC stage first followed by an MWF-based NR stage. Distributed algorithms can then be obtained from the MWF and PK-MWF algorithm, i.e., the GEVD-DANSE and PK-GEVD-DANSE algorithm, respectively. In the former, each node performs a reduced dimensional integrated AEC and NR algorithm and broadcasts only 1 fused signal (instead of all its signals) to the other nodes. In the PK-GEVD-DANSE algorithm, each node performs a reduced dimensional cascade AEC and NR algorithm and broadcasts only 2 fused signals (instead of all its signals) to the other nodes. The distributed algorithms achieve the same performance as the corresponding centralized integrated (MWF) and cascade (PK-MWF) algorithm. It is observed, however, that the communication cost in the PK-GEVD-DANSE algorithm can be reduced, where each node then broadcasts only 1 fused signal (instead of 2 signals) to the other nodes, which finally results in an algorithm with a low communication cost as well as a low computational complexity in each node.

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