Time-varying Clock Offset Estimation in Two-way Timing Message Exchange in Wireless Sensor Networks Using Factor Graphs

TL;DR

This paper introduces a Bayesian factor graph-based method for estimating time-varying clock offsets in wireless sensor networks, improving accuracy by modeling oscillator imperfections.

Contribution

It presents a novel Bayesian approach with a factor graph representation and max-product message passing for clock offset estimation.

Findings

Closed-form Bayesian inference expression derived

Effective modeling of oscillator imperfections

Enhanced accuracy in clock synchronization

Abstract

The problem of clock offset estimation in a two-way timing exchange regime is considered when the likelihood function of the observation time stamps is exponentially distributed. In order to capture the imperfections in node oscillators, which render a time-varying nature to the clock offset, a novel Bayesian approach to the clock offset estimation is proposed using a factor graph representation of the posterior density. Message passing using the max-product algorithm yields a closed form expression for the Bayesian inference problem.