# Bayesian Joint Synchronization and Localization Based on Asymmetric Time-stamp Exchange

arXiv: https://arxiv.org/abs/2008.08481 · HTML: https://mlsanity.com/paper/2008.08481/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Aug 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 study the joint synchronization and localization (sync&loc) of Mobile Nodes (MNs) in ultra dense networks. In particular, we deploy an asymmetric timestamp exchange mechanism between MNs and Access Nodes (ANs), that, traditionally, provides us with information about the MNs' clock offset and skew. However, information about the distance between an AN and a MN is also intrinsic to the propagation delay experienced by exchanged time-stamps. In addition, we utilize Angle of Arrival (AoA) estimation to determine the incoming direction of time-stamp exchange packets, which gives further information about the MNs' location. Finally, we employ Bayesian Recursive Filtering (BRF) to combine the aforementioned pieces of information and jointly estimate the position and clock parameters of MNs. The simulation results indicate that the Root Mean Square Errors (RMSEs) of position and clock offset estimation are kept below 1 meter and 1 ns, respectively.