Status Updating via Integrated Sensing and Communication: Freshness Optimisation

Abstract

In this paper, we study how sensing and communication should be jointly coordinated in integrated sensing and communication (ISAC) systems to maintain timely situational awareness under reliability and resource constraints. We consider an ISAC-enabled base station that supports a remote source by dynamically choosing between sensing new state information and communicating previously acquired information, with the two operations semantically intertwined rather than serving separate targets and users. Both sensing and communication are unreliable and costly. The objective is to optimise a long-term cost that captures information freshness at the source, measured by the age of information (AoI), together with sensing and communication overheads. The resulting sequential decision problem is formulated as an infinite-horizon Markov decision process (MDP) with two-dimensional AoI states that capture information freshness at the source and at the base station. We prove that the optimal stationary policy admits a monotone threshold structure characterised by a nondecreasing switching curve in the AoI state space, and show that, as the base-station information becomes staler, the system increasingly favours sensing over communication. Our numerical analysis corroborates the theoretical findings.