Age of Information with Hybrid-ARQ: A Unified Explicit Result

TL;DR

This paper provides a comprehensive analysis of Age of Information (AoI) for reactive and proactive HARQ techniques in 5G NR, deriving explicit formulas and optimizing code strategies to enhance information freshness in status update systems.

Contribution

It offers the first unified closed-form expressions for AoI of reactive and proactive HARQ, along with an optimization framework for age-minimizing codeblock assignment in finite block-length regimes.

Findings

Proactive HARQ improves AoI and system robustness.

Explicit AoI formulas for both HARQ types are derived.

Optimal codeblock strategies reduce AoI effectively.

Abstract

Delivering timely status updates in a timeliness-critical communication system is of paramount importance to assist accurate and efficient decision making. Therefore, the topic of analyzing Age of Information has aroused new research interest. This paper contributes to new results in this area by systematically analyzing the AoI of two types of Hybrid Automatic Repeat reQuest (HARQ) techniques that have been newly standardized in the Release-16 5G New Radio (NR) specifications, namely reactive HARQ and proactive HARQ. Under a code-based status update system with non-trivial coding delay, transmission delay, propagation delay, decoding delay, and feedback delay, we derive unified closed-form average AoI and average Peak AoI expressions for reactive HARQ and proactive HARQ, respectively. Based on the obtained explicit expressions, we formulate an AoI minimization problem to investigate the age-optimal codeblock assignment strategy in the finite block-length (FBL) regime. Through case studies and analytical results, we provide comparative insights between reactive HARQ and proactive HARQ from a perspective of freshness of information. The numerical results and optimization solutions show that proactive HARQ draws its strength from both age performance and system robustness, thus enabling the potential to provide new system advancement of a freshness-critical status update system.