Distributed Rate-Constrained LCMV Beamforming

Journal Article (2019)
Author(s)

Jie Zhang (TU Delft - Signal Processing Systems)

Andreas I. Koutrouvelis (TU Delft - Signal Processing Systems)

Richard Heusdens (TU Delft - Signal Processing Systems)

Richard C. Hendriks (TU Delft - Signal Processing Systems)

Research Group
Signal Processing Systems
Copyright
© 2019 J. Zhang, A. Koutrouvelis, R. Heusdens, R.C. Hendriks
DOI related publication
https://doi.org/10.1109/LSP.2019.2905161
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 J. Zhang, A. Koutrouvelis, R. Heusdens, R.C. Hendriks
Research Group
Signal Processing Systems
Issue number
5
Volume number
26
Pages (from-to)
675-679
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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.

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