Fog-RAN Enabled Multi-Connectivity and Multi-Cell Scheduling Framework for Ultra-Reliable Low Latency Communication
Ultra-Reliable Low Latency Communication (URLLC) is a newly introduced service class targeting emerging Internet-of-Things (IoT) application scenarios. This paper assumes an interference-limited […]
Joint Client Scheduling and Resource Allocation Under Channel Uncertainty in Federated Learning
The performance of federated learning (FL) over wireless networks depend on the reliability of the client-server connectivity and clients’ local computation capabilities. […]
Sleeping Multi-Armed Bandit Learning for Fast Uplink Grant Allocation in Machine Type Communications
Scheduling fast uplink grant transmissions for machine type communications (MTCs) is one of the main challenges of future wireless systems. In this […]
Contextual Bandit Learning for Machine Type Communications in the Null Space of Multi-Antenna Systems
Ensuring an effective coexistence of conventional broadband cellular users with machine type communications (MTCs) is challenging due to the interference from MTCs […]
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 […]
Scenario-Based Emergency Material Scheduling Using V2X Communications
Vehicle-to-everything (V2X) communications can be applied in emergency material scheduling due to their performance in collecting and transmitting disaster-related data in real […]