Distributed Rate-Constrained LCMV Beamforming

Jie Zhang*, Andreas I. Koutrouvelis, Richard Heusdens, Richard C. Hendriks

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)
86 Downloads (Pure)


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.

Original languageEnglish
Article number8667644
Pages (from-to)675-679
Number of pages5
JournalIEEE Signal Processing Letters
Issue number5
Publication statusPublished - 2019


  • acoustic sensor networks
  • distributed beamforming
  • energy usage
  • LCMV
  • noise reduction
  • Rate allocation


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