LAUSR

In the presence of global pandemics, the increasing demands of remote healthcare, online education, and automation systems have driven the development of the Tactile Internet (TI), which aims to support timely and reliable interactions among humans and machines. Since ultra-reliable low-latency communications (URLLC) have been considered in the fifth generation (5G) standards, the state-of-the-art 5G mobile networks are well aligned with the TI. Nevertheless, TI applications in different vertical industries have unique requirements on top of URLLC, such as global connectivity, high mobility, and low jitter. Since these issues have not been addressed in URLLC, 5G is not ready for the full vision of the TI. Motivated by this fact, we identify promising technologies to fulfill these requirements and summarize corresponding new research challenges in the sixth generation mobile networks. To handle these new challenges, we put forward an intelligent communication framework. Specifically, machine learning is applied in prediction and decision making, where the impacts of prediction errors on the reliability of the TI are considered. In this case study, we illustrate how to implement the framework in a typical TI application. Our results show that the proposed framework has the potential to achieve zero latency and can improve the trade-offs among latency, reliability, and resource utilization efficiency remarkably compared to existing benchmarks.