A Hybrid Bayesian Approach Towards Clock Offset and Skew Estimation in 5G Networks
Abstract
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.
Keywords
Cite
@article{arxiv.2004.09469,
title = {A Hybrid Bayesian Approach Towards Clock Offset and Skew Estimation in 5G Networks},
author = {Meysam Goodarzi and Darko Cvetkovski and Nebojsa Maletic and Jesus Gutierrez and Eckhard Grass},
journal= {arXiv preprint arXiv:2004.09469},
year = {2020}
}
Comments
arXiv admin note: text overlap with arXiv:2002.12660