Globally optimal decentralized spatial smoothing for wireless sensor networks with local interactions

S. Barbarossa, T. Battisti, A. Swami
2008 Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing  
In most sensor network applications, the vector containing the observations gathered by the sensors lies in a space of dimension equal to the number of nodes, typically because of observation noise, even though the useful signal belongs to a subspace of much smaller dimension. This motivates smoothing or rank reduction. We formulate a convex optimization problem, where we incorporate a fidelity constraint that prevents the final smoothed estimate from diverging too far from the observations.
more » ... he observations. This leads to a distributed algorithm in which nodes exchange updates only with neighboring nodes. We show that the widely studied consensus algorithm is indeed only a very specific case of our more general formulation. Finally, we study the convergence rate and propose some approaches to maximize it.
doi:10.1109/icassp.2008.4518097 dblp:conf/icassp/BarbarossaBS08 fatcat:ftresgpv45bohjqyrpmdvrx7ge