Reinforcement Learning Based Scheduling Algorithm for Optimizing Age of Information in Ultra Reliable Low Latency Networks
Age of Information (AoI) measures the freshness of the information at a remote location. AoI reflects the time that is elapsed since […]
Reinforcement Learning Based Vehicle-cell Association Algorithm for Highly Mobile Millimeter Wave Communication
Vehicle-to-everything (V2X) communication is a growing area of communication with a variety of use cases. This paper investigates the problem of vehicle-cell […]
Decentralized Deep Reinforcement Learning for Delay-Power Tradeoff in Vehicular Communications
This paper targets at the problem of radio resource management for expected long-term delay-power tradeoff in vehicular communications. At each decision epoch, […]
Network Slicing with Mobile Edge Computing for Micro-Operator Networks in Beyond 5G
We model the scenarios of network slicing allocation for the micro-operator (MO) network. The MO creates the slices “as a service” of […]
Learning to Entangle Radio Resources in Vehicular Communications
In this paper, we investigate non-cooperative radio resource management in a vehicle-to-vehicle communication network. The technical challenges lie in high-vehicle mobility and […]