Deep Reinforcement Learning for Practical Phase-Shift Optimization in RIS-Aided MISO URLLC Systems
We study the joint active/passive beamforming and channel blocklength (CBL) allocation in a nonideal reconfigurable intelligent surface (RIS)-aided ultrareliable and low-latency communication […]
Deep Reinforcement Learning-Based Deterministic Routing and Scheduling for Mixed-Criticality Flows
Deterministic networking has recently drawn much attention by investigating deterministic flow scheduling. Combined with artificial intelligent (AI) technologies, it can be leveraged […]
Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfaces
The emerging technology of reconfigurable intelligent surfaces (RISs) is provisioned as an enabler of smart wireless environments offering a highly scalable low-cost […]