  Wireless communications for status update are becoming increasingly
important, especially for machine-type control applications. Existing work has
been mainly focused on Age of Information (AoI) optimizations. In this paper, a
status-aware predictive wireless interface design, networking and
implementation are presented which aim to minimize the status recovery error of
a wireless networked system by leveraging online status model predictions. Two
critical issues of predictive status update are addressed: practicality and
usefulness. Link-level experiments on a Software-Defined-Radio (SDR) testbed
are conducted and test results show that the proposed design can significantly
reduce the number of wireless transmissions while maintaining a low status
recovery error. A Status-aware Multi-Agent Reinforcement learning neTworking
solution (SMART) is proposed to dynamically and autonomously control the
transmit decisions of devices in an ad hoc network based on their individual
statuses. System-level simulations of a multi dense platooning scenario are
carried out on a road traffic simulator. Results show that the proposed schemes
can greatly improve the platooning control performance in terms of the minimum
safe distance between successive vehicles, in comparison with the AoI-optimized
status-unaware and communication latency-optimized schemes---this demonstrates
the usefulness of our proposed status update schemes in a real-world
application.
