Joint Service Migration and Resource Allocation in Edge IoT System Based on Deep Reinforcement Learning
Multi-access Edge Computing (MEC) provides services for resource-sensitive and delay-sensitive Internet of Things (IoT) applications by extending the capabilities of cloud computing […]
Meta Reinforcement Learning for Resource Allocation in Aerial Active-RIS-Assisted Networks With Rate-Splitting Multiple Access
Mounting a reconfigurable intelligent surface (RIS) on an unmanned aerial vehicle (UAV) holds promise for improving traditional terrestrial network performance. Unlike conventional […]
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 […]