Distributed distortionless signal estimation in wireless acoustic sensor networks

Abstract

Wireless microphone networks or so-called wireless acoustic sensor networks (WASNs) consist of physically distributed microphone nodes that exchange data over wireless links. In this paper, we propose a novel distributed distortionless signal estimation algorithm for noise reduction in WASNs. The most important feature of the proposed algorithm is that the nodes broadcast only single-channel signals while still obtaining optimal estimation performance, even in a scenario with multiple desired sources or speakers (in existing distributed methods, this is achieved only in scenarios with a single desired source). The idea is to create a one-dimensional desired signal subspace by using the same reference microphone at all the nodes. Since the theory is based on a distortionless signal estimation technique, namely linearly constrained minimum variance (LCMV) beamforming, we will show that this reference microphone does not need to be transmitted over the wireless link. We provide simulations to demonstrate the performance of the algorithm.