Zero touch management: A survey of network automation solutions for 5G and 6G networks
Mobile networks are facing an unprecedented demand for high-speed connectivity
originating from novel mobile applications and services and, in general, from the adoption …
originating from novel mobile applications and services and, in general, from the adoption …
Deep reinforcement learning for resource management on network slicing: A survey
JA Hurtado Sánchez, K Casilimas… - Sensors, 2022 - mdpi.com
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 …
5G and 6G networks. A 5G/6G network can comprise various network slices from unique or …
Deep federated Q-learning-based network slicing for industrial IoT
Fifth generation and beyond networks are envisioned to support multi industrial Internet of
Things (IIoT) applications with a diverse quality-of-service (QoS) requirements. Network …
Things (IIoT) applications with a diverse quality-of-service (QoS) requirements. Network …
[HTML][HTML] Machine learning-based zero-touch network and service management: A survey
The exponential growth of mobile applications and services during the last years has
challenged the existing network infrastructures. Consequently, the arrival of multiple …
challenged the existing network infrastructures. Consequently, the arrival of multiple …
Energy-efficient UAV-enabled data collection via wireless charging: A reinforcement learning approach
In this article, we study the application of unmanned aerial vehicle (UAV) for data collection
with wireless charging, which is crucial for providing seamless coverage and improving …
with wireless charging, which is crucial for providing seamless coverage and improving …
[HTML][HTML] A survey of deep reinforcement learning application in 5G and beyond network slicing and virtualization
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 …
throughputs, connect large number of devices, support low latency and large numbers of …
QR-SDN: Towards reinforcement learning states, actions, and rewards for direct flow routing in software-defined networks
Flow routing can achieve fine-grained network performance optimizations by routing distinct
packet traffic flows over different network paths. While the centralized control of Software …
packet traffic flows over different network paths. While the centralized control of Software …
A survey on XAI for 5G and beyond security: Technical aspects, challenges and research directions
With the advent of 5G commercialization, the need for more reliable, faster, and intelligent
telecommunication systems is envisaged for the next generation beyond 5G (B5G) radio …
telecommunication systems is envisaged for the next generation beyond 5G (B5G) radio …
Slicing the core network and radio access network domains through intent-based networking for 5G networks
The fifth-generation mobile network presents a wide range of services which have different
requirements in terms of performance, bandwidth, reliability, and latency. The legacy …
requirements in terms of performance, bandwidth, reliability, and latency. The legacy …
Coordinated slicing and admission control using multi-agent deep reinforcement learning
5G Cloud Radio Access Networks (C-RANs) facilitate new forms of flexible resource
management as dynamic RAN function splitting and placement. Virtualized RAN functions …
management as dynamic RAN function splitting and placement. Virtualized RAN functions …