Distributed estimation of the inverse of the correlation matrix for privacy preserving beamforming
A privacy preserving distributed MVDR beamformer for WASNs is presented. Estimation of the inverse correlation matrix can be structured as consensus problems. Convergence error will accumulate across time using gossip-based estimation. Clique-based distributed processing can completely eliminate convergence error. The presented MVDR beamformer has identical performance as centralized MVDR.
distributed estimation correlation matrix gossip processing wireless acoustic sensor networks