Minimizing the Age of Synchronization in Power-Constrained Wireless Networks with Unreliable Time-Varying Channels

We study a network with a central controller collecting random updates from power-limited sensors. The time-varying channels between sensors and the central controller are modeled as ergodic Markov chains while packet-loss may happen due to decoding error. We measure the data freshness from the central controller by the metric Age of Synchronization (AoS), i.e., the average time elapsed since information about a sensor becomes desynchronized. To minimize the average AoS under all aforementioned bandwidth and power constraints, we first relax the hard bandwidth limit and decouple the multi-sensor problem into a single-sensor constrained Markov decision process (CMDP), which is then solved through linear programming (LP). We then propose an asymptotic optimal scheduling policy to solve the original hard-bandwidth-constrained problem. It is revealed that sensors are more likely to send updates under better channel states and higher AoS to save energy and avoid packet-loss.