  We study the multi-user scheduling problem for minimizing the Age of
Information (AoI) in cellular wireless networks under stationary and
non-stationary regimes. We derive fundamental lower bounds for the scheduling
problem and design efficient online policies with provable performance
guarantees. In the stationary setting, we consider the AoI optimization problem
for a set of mobile users travelling around multiple cells. In this setting, we
propose a scheduling policy and show that it is $2$-optimal. Next, we propose a
new adversarial channel model for studying the scheduling problem in
non-stationary environments. For $N$ users, we show that the competitive ratio
of any online scheduling policy in this setting is at least $\Omega(N)$. We
then propose an online policy and show that it achieves a competitive ratio of
$O(N^2)$. Finally, we introduce a relaxed adversarial model with channel state
estimations for the immediate future. We propose a heuristic model predictive
control policy that exploits this feature and compare its performance through
numerical simulations.
