Latest Publications
Deep Reinforcement Learning for URLLC in 5G Mission-Critical Cloud Robotic Application
In this paper, we investigate the problem of robot swarm control in 5G mission-critical robotic applications, i.e., in an automated grid-based warehouse scenario. Such application requires both the kinematic energy consumption of the robots and the ultra-reliable and low latency […]
Deep Q-Learning for Joint Server Selection, Offloading, and Handover in Multi-access Edge Computing
In this paper, we propose a deep reinforcement learning (DRL) based approach to solving the problem of joint server selection, task offloading and handover in a multi-access edge computing (MEC) wireless network. The 5G networks tend to have a large […]
UAV Control for Wireless Service Provisioning in Critical Demand Areas: A Deep Reinforcement Learning Approach
In this paper, we investigate the problem of wireless service provisioning through a rotary-wing UAV which can serve as an aerial base station (BS) to communicate with multiple ground terminals (GTs) in a boost demand area. Our objective is to […]
Joint Server Selection, Cooperative Offloading and Handover in Multi-access Edge Computing Wireless Network: A Deep Reinforcement Learning Approach
In this paper, we consider a multi-user MEC wireless network in which multiple mobile devices can associate and perform computation offloading via wireless channels to MEC servers attached to the base stations. The decision whether the computation task is executed […]
