Distributed Rate-Constrained LCMV Beamforming

Zhang, J.; Koutrouvelis, A.; Heusdens, R.; Hendriks, R.C.

doi:10.1109/LSP.2019.2905161

Distributed Rate-Constrained LCMV Beamforming

Journal article (2019)

Authors

J. Zhang Signal Processing Systems -

A. Koutrouvelis Signal Processing Systems -

R. Heusdens Signal Processing Systems -

R.C. Hendriks Signal Processing Systems -

Research Group

Signal Processing Systems () (TU Delft)

DOI: https://doi.org/10.1109/LSP.2019.2905161

Noise reduction Distributed beamforming LCMV Energy usage Rate allocation Acoustic sensor networks

To reference this document use:

http://resolver.tudelft.nl/uuid:d9eef6d7-8dc5-49e0-ab51-a630b07ef323

More Info

expand_more

Published Date

2019

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Signal Processing Systems

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.

Files

53544644_Jie_SPL2019.pdf

(pdf | 0.216 Mb)

Unknown license