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 […]
Network-Aided Intelligent Traffic Steering in 6G O-RAN: A Multi-Layer Optimization Framework
To enable an intelligent, programmable and multi-vendor radio access network (RAN) for 6G networks, considerable efforts have been made in standardization and […]
Cooperative Multi-Agent Learning for Navigation via Structured State Abstraction
Cooperative multi-agent reinforcement learning (MARL) for navigation enables agents to cooperate to achieve their navigation goals. Using emergent communication, agents learn a […]
Communication-Efficient and Federated Multi-Agent Reinforcement Learning
In this paper, we consider a distributed reinforcement learning setting where agents are communicating with a central entity in a shared environment […]
Millimeter Wave Communications With an Intelligent Reflector
In this paper a novel framework is proposed to optimize the downlink multi-user communication of a millimeter wave base station which is […]
V2V Cooperative Sensing using Reinforcement Learning with Action Branching
Cooperative perception plays a vital role in extending a vehicle’s sensing range beyond its line-of-sight. However, exchanging raw sensory data under limited […]
Deep Reinforcement Based Optimization of Function Splitting in Virtualized Radio Access Networks
Virtualized Radio Access Network (vRAN) is one of the key enablers of future wireless networks as it brings the agility to the […]
Collaborative Cross System AI
The emerging industrial verticals set new challenges for 5G and beyond systems. Indeed, the heterogeneity of the underlying technologies and the challenging […]
Learning-based trajectory optimization for 5G mmWave uplink UAVs
A Connectivity-constrained based path planning for unmanned aerial vehicles (UAVs) is proposed within the coverage area of a 5G NR Base Station […]
Link-Level Throughput Maximization Using Deep Reinforcement Learning
A multi-agent deep reinforcement learning framework is proposed to address link level throughput maximization by power allocation and modulation and coding scheme […]