# Cooperative Synchronization in Wireless Networks

arXiv: https://arxiv.org/abs/1304.8029 · HTML: https://mlsanity.com/paper/1304.8029/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Apr 2013.

## Built on by (most cited first, 1 of 1)

- [DNN-assisted Particle-based Bayesian Joint Synchronization and Localization](https://mlsanity.com/paper/2110.02771/) (2021)

## Abstract (arXiv)

Synchronization is a key functionality in wireless network, 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 Cram'er-Rao bounds.