Holistic network virtualization and pervasive network intelligence for 6G
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 …
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …
Device-to-device relaying: Optimization, performance perspectives, and open challenges towards 6G networks
A relaying can significantly improve performance of contemporary mobile networks in terms
of capacity and/or energy consumption. Nevertheless, an incorporation of conventional relay …
of capacity and/or energy consumption. Nevertheless, an incorporation of conventional relay …
Multi-agent reinforcement learning based resource management in MEC-and UAV-assisted vehicular networks
In this paper, we investigate multi-dimensional resource management for unmanned aerial
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
Resource allocation based on deep reinforcement learning in IoT edge computing
By leveraging mobile edge computing (MEC), a huge amount of data generated by Internet
of Things (IoT) devices can be processed and analyzed at the network edge. However, the …
of Things (IoT) devices can be processed and analyzed at the network edge. However, the …
AI-assisted network-slicing based next-generation wireless networks
The integration of communications with different scales, diverse radio access technologies,
and various network resources renders next-generation wireless networks (NGWNs) highly …
and various network resources renders next-generation wireless networks (NGWNs) highly …
SDN/NFV-empowered future IoV with enhanced communication, computing, and caching
Internet-of-Vehicles (IoV) connects vehicles, sensors, pedestrians, mobile devices, and the
Internet with advanced communication and networking technologies, which can enhance …
Internet with advanced communication and networking technologies, which can enhance …
Dynamic RAN slicing for service-oriented vehicular networks via constrained learning
In this paper, we investigate a radio access network (RAN) slicing problem for Internet of
vehicles (IoV) services with different quality of service (QoS) requirements, in which multiple …
vehicles (IoV) services with different quality of service (QoS) requirements, in which multiple …
Deep reinforcement learning based resource management for multi-access edge computing in vehicular networks
In this paper, we study joint allocation of the spectrum, computing, and storing resources in a
multi-access edge computing (MEC)-based vehicular network. To support different vehicular …
multi-access edge computing (MEC)-based vehicular network. To support different vehicular …
Dynamic SDN-based radio access network slicing with deep reinforcement learning for URLLC and eMBB services
A Filali, Z Mlika, S Cherkaoui… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Radio access network (RAN) slicing is a key technology that enables 5G network to support
heterogeneous requirements of generic services, namely ultra-reliable low-latency …
heterogeneous requirements of generic services, namely ultra-reliable low-latency …
UAV-assisted wireless energy and data transfer with deep reinforcement learning
As a typical scenario in future generation communication network applications, UAV-
assisted communication can perform autonomous data delivery for massive machine type …
assisted communication can perform autonomous data delivery for massive machine type …