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Information source sampling and update scheduling have been treatedseparately in the context of real-time status update for age of informationoptimization. In this paper, a unified sampling and scheduling($\mathcal{S}^2$) approach is proposed, focusing on decentralized updates inmultiaccess wireless networks. To gain some insights, we first analyze anexample consisting of two-state Markov sources, showing that when bothoptimized, the unified approach outperforms the separate approach significantlyin terms of status tracking error by capturing the key status variation. Wethen generalize to source nodes with random-walk state transitions whosescaling limit is Wiener processes, the closed-form Whittle's index witharbitrary status tracking error functions is obtained and indexabilityestablished. Furthermore, a mean-field approach is applied to solve for thedecentralized status update design explicitly. In addition to simulationresults which validate the optimality of the proposed $\mathcal{S}^2$ schemeand its advantage over the separate approach, a use case of dynamic channelstate information (CSI) update is investigated, with CSI generated by aray-tracing electromagnetic software.

A Unified Sampling and Scheduling Approach for Status Update in Multiaccess Wireless Networks