In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …

Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important
role in realizing and optimizing 6G network applications. In this paper, we present a brief …

Network Slicing and Deep Reinforcement Learning (DRL) are vital enablers for achieving
5G and 6G networks. A 5G/6G network can comprise various network slices from unique or …

Network slicing is a key paradigm in 5G and is expected to be inherited in future 6G
networks for the concurrent provisioning of diverse quality of service (QoS). Unfortunately …

Along with the springing up of the semantics-empowered communication (SemCom)
research, it is now witnessing an unprecedentedly growing interest towards a wide range of …

Network slicing is a key technology to support the concurrent provisioning of heterogeneous
Quality of Service (QoS) in the 5th Generation (5G)-beyond and the 6th Generation (6G) …

We propose a mechanism for distributed resource management and interference mitigation
in wireless networks using multi-agent deep reinforcement learning (RL). We equip each …

Advances in communication technologies and artificial intelligence are accelerating the
paradigm of industrial Internet of Things (IIoT). With IIoT enabling continuous integration of …

Abstract The 5th Generation (5G) and beyond networks are expected to offer huge
throughputs, connect large number of devices, support low latency and large numbers of …

Network slicing aims to efficiently provision diversified services with distinct requirements
over the same physical infrastructure. Therein, in order to efficiently allocate resources …