# A Hybrid Bayesian Approach Towards Clock Offset and Skew Estimation in 5G Networks

arXiv: https://arxiv.org/abs/2004.09469 · HTML: https://mlsanity.com/paper/2004.09469/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Apr 2020.

## 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)

In this work, we propose a hybrid Bayesian approach towards clock offset and skew estimation, thereby synchronizing large scale networks. In particular, we demonstrate the advantage of Bayesian Recursive Filtering (BRF) in alleviating time-stamping errors for pairwise synchronization. Moreover, we indicate the benefit of Factor Graph (FG), along with Belief Propagation (BP) algorithm in achieving high precision end-to-end network synchronization. Finally, we reveal the merit of hybrid synchronization, where a large-scale network is divided into local synchronization domains, for each of which a suitable synchronization algorithm (BP- or BRF-based) is utilized. The simulation results show that, despite the simplifications in the hybrid approach, the Root Mean Square Errors (RMSEs) of clock offset and skew estimation remain below 5 ns and 0.3 ppm, respectively.