  Beyond fifth generation wireless communication networks (B5G) are applied in
many use-cases, such as industrial control systems, smart public transport, and
power grids. Those applications require innovative techniques for timely
transmission and increased wireless network capacities. Hence, this paper
proposes optimizing the data freshness measured by the age of information (AoI)
in dense internet of things (IoT) sensor-actuator networks. Given different
priorities of data-streams, i.e., different sensitivities to outdated
information, mixed-criticality is introduced by analyzing different functions
of the age, i.e., we consider linear and exponential aging functions. An
intricate non-convex optimization problem managing the physical transmission
time and packet outage probability is derived. Such problem is tackled using
stochastic reformulations, successive convex approximations, and fractional
programming, resulting in an efficient iterative algorithm for AoI
optimization. Simulation results validate the proposed scheme's performance in
terms of AoI, mixed-criticality, and scalability. The proposed non-orthogonal
transmission is shown to outperform an orthogonal access scheme in various
deployment cases. Results emphasize the potential gains for dense B5G empowered
IoT networks in minimizing the AoI.
