Exploring the Tradeoff between Age of Information and Synchronization over Broadcast Channels

We consider a scenario whereby the state of a common source is being updated at multiple distributed devices. We are particularly interested in the tradeoff that exists between the freshness of the updates at the distributed devices and the synchrony of the updates across them. In this paper, we explore this tradeoff in a wireless downlink setting whereby the transmit-ter can choose between unicast transmissions (with given success probabilities) to particular users and broadcast transmissions (with a smaller success probability) to all users. After discussing the Linear Programming (LP)-based optimal design and extreme choices of “always-unicasting” and “always-broadcasting” poli-cies, we note that the optimal design is not scalable and the extreme policies are inefficient. This motivates us to develop two classes of policies, namely a “mixed randomized policy” and a “feature-based learning policy”, which have desirable performance and computational-complexity characteristics. We perform extensive numerical studies to compare the performance of these designs over the benchmarks to reveal their gains.