Resource Allocation for RIS-Enhanced OFDM-MIMO ISAC Systems
Integrated sensing and communications (ISAC) has emerged as a key enabler for 6G and beyond. However, ISAC systems face significant challenges, including […]
Multi-Timescale Resource Reservation and Allocation Through Meta Distribution for Network Operators to Enable eMBB and URLLC Coexistence
We study the problem of resource reservation and allocation (RRA), aiming to enable network operators (NOs) to effectively develop the coexistence of […]
Strategic Utilization of Cellular Operator Energy Storage for Smart Grid Frequency Regulation
The innovative use of cellular operator energy storage enhances power grid resilience and efficiency. Traditionally used to ensure uninterrupted operation of cellular […]
A Comprehensive Survey of Machine Learning Applied to Resource Allocation in Wireless Communications
Telecommunications play a pivotal role in shaping today’s interconnected world by fostering global development, supporting seamless information exchange across vast distances, and […]
Semantic Revolution from Communications to Orchestration for 6G: Challenges, Enablers, and Research Directions
In the context of emerging 6G services, the realization of everything-to-everything interactions involving a myriad of physical and digital entities presents a […]
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 […]
Double Deep Q-Learning-based Path Selection and Service Placement for Latency-Sensitive Beyond 5G Applications
Nowadays, as the need for capacity continues to grow, entirely novel services are emerging. A solid cloud-network integrated infrastructure is necessary to […]
Optimal Traffic Load Allocation for Aloha-Based IoT LEO Constellations
The deployment of satellite networks is key to providing global wireless connectivity for the Internet of Things (IoT). In this line, we […]
Traffic Prediction and Fast Uplink for Hidden Markov IoT Models
In this work we present a novel traffic prediction and fast uplink (FU) framework for IoT networks controlled by binary Markovian events. […]
Time-Triggered Federated Learning Over Wireless Networks
The newly emerging federated learning (FL) framework offers a new way to train machine learning models in a privacy-preserving manner. However traditional […]