Cooperative Synchronization in Wireless Networks
Journal article, 2014

Synchronization is a key functionality in wireless networks, enabling a wide variety of services. We consider a Bayesian inference framework whereby network nodes can achieve phase and skew synchronization in a fully distributed way. In particular, under the assumption of Gaussian measurement noise, we derive two message passing methods (belief propagation and mean field), analyze their convergence behavior, and perform a qualitative and quantitative comparison with a number of competing algorithms. We also show that both methods can be applied in networks with and without master nodes. Our performance results are complemented by, and compared with, the relevant Bayesian Cramer-Rao bounds.

mean field

belief propagation

Bayesian Cramer-Rao bound

Network synchronization

distributed estimation


B. Etzlinger

Johannes Kepler University of Linz (JKU)

Henk Wymeersch

Chalmers, Signals and Systems, Communication, Antennas and Optical Networks

A. Springer

Johannes Kepler University of Linz (JKU)

IEEE Transactions on Signal Processing

1053-587X (ISSN) 1941-0476 (eISSN)

Vol. 62 11 2837-2849 6778066

Cooperative Situational Awareness for Wireless Networks (COOPNET)

European Commission (EC) (EC/FP7/258418), 2011-05-01 -- 2016-04-30.

Subject Categories

Signal Processing



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