Multi-Stage Structured Estimators for Information Freshness
Information Theory
2026-01-27 v1 Signal Processing
math.IT
Abstract
Most of the contemporary literature on information freshness solely focuses on the analysis of freshness for martingale estimators, which simply use the most recently received update as the current estimate. While martingale estimators are easier to analyze, they are far from optimal, especially in pull-based update systems, where maximum aposteriori probability (MAP) estimators are known to be optimal, but are analytically challenging. In this work, we introduce a new class of estimators called -MAP estimators, which enable us to model the MAP estimator as a piecewise constant function with finitely many stages, bringing us closer to a full characterization of the MAP estimators when modeling information freshness.
Cite
@article{arxiv.2601.18763,
title = {Multi-Stage Structured Estimators for Information Freshness},
author = {Sahan Liyanaarachchi and Sennur Ulukus and Nail Akar},
journal= {arXiv preprint arXiv:2601.18763},
year = {2026}
}