Analysis and Optimization of Age of Information in Large-Scale Random Access Networks

Abstract

We consider a large-scale network where multiple nodes transmit time-sensitive information via a shared channel to a wireless base station using a Carrier-Sense Multiple Access (CSMA) protocol. In this network, packet transmissions from different nodes are interdependent, making it challenging to analyze and optimize information freshness, captured by the Age of Information (AoI) metric. In this paper, we develop a tractable analytical framework for analyzing and optimizing the AoI. By combining mean-field approximation with first return time and renewal reward analysis, the proposed approach provides a fast, tractable, and accurate AoI approximation that explicitly accounts for carrier sensing, enabling us to quickly find the network parameters that minimize AoI. Since the framework is built on a finite-state Markov representation of the CSMA protocol, it applies to a broad class of Random Access systems. As a concrete example, we study age-threshold CSMA protocols and derive closed-form or efficiently computable AoI approximations under different protocol settings. We validate the proposed AoI analysis via extensive simulations, demonstrating a tight agreement between analysis and simulation.