Distributed Rate-Constrained LCMV Beamforming

Abstract: In this letter, we propose a decentralized framework for rate-distributed linearly constrained minimum variance (LCMV) beamforming in wireless acoustic sensor networks. To save the energy usage within the network, we propose to minimize the transmission cost and put a constraint on the noise reduction performance. Subsequently, we decentralize the obtained LCMV filter structure by exploiting an imposed block diagonal form of the noise correlation matrix. As a result, the beamformer weights are calculated in a decentralized fashion and each node can determine its quantization rate locally. Finally, numerical results validate the proposed method.

Related publications

1. Distributed Rate-Constrained LCMV Beamforming
   Jie Zhang; Andreas Koutrouvelis; Richard Heusdens; Richard C. Hendriks;
   IEEE Signal Processing Letters,
   Volume 26, Issue 5, pp. 675-697, May 2019. DOI: 10.1109/LSP.2019.2905161
   document