Zero touch management: A survey of network automation solutions for 5G and 6G networks

E Coronado, R Behravesh… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Mobile networks are facing an unprecedented demand for high-speed connectivity
originating from novel mobile applications and services and, in general, from the adoption …

[HTML][HTML] A survey on Zero touch network and Service Management (ZSM) for 5G and beyond networks

M Liyanage, QV Pham, K Dev, S Bhattacharya… - Journal of Network and …, 2022 - Elsevier
Faced with the rapid increase in smart Internet-of-Things (IoT) devices and the high demand
for new business-oriented services in the fifth-generation (5G) and beyond network, the …

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 …

On the specialization of fdrl agents for scalable and distributed 6g ran slicing orchestration

F Rezazadeh, L Zanzi, F Devoti… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Network slicing enables multiple virtual networks to be instantiated and customized to meet
heterogeneous use case requirements over 5G and beyond network deployments …

Toward greener 5G and beyond radio access networks—A survey

LMP Larsen, HL Christiansen, S Ruepp… - IEEE Open journal of …, 2023 - ieeexplore.ieee.org
Mobile network traffic is increasing and so is the energy consumption. The Radio Access
Network (RAN) part is responsible for the largest share of the mobile network energy …

Machine learning in network slicing—a survey

HP Phyu, D Naboulsi, R Stanica - IEEE Access, 2023 - ieeexplore.ieee.org
5G and beyond networks are expected to support a wide range of services, with highly
diverse requirements. Yet, the traditional “one-size-fits-all” network architecture lacks the …

RAN resource slicing in 5G using multi-agent correlated Q-learning

H Zhou, M Elsayed… - 2021 IEEE 32nd Annual …, 2021 - ieeexplore.ieee.org
5G is regarded as a revolutionary mobile network, which is expected to satisfy a vast number
of novel services, ranging from remote health care to smart cities. However, heterogeneous …

A novel intelligent nonlinear controller for dual active bridge converter with constant power loads

X Meng, Y Jia, Q Xu, C Ren, X Han… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The stability of dual active bridge converter (DAB) is threatened when feeding the constant
power loads (CPLs). This article proposes a deep reinforcement learning-based …

Deep reinforcement learning approaches to network slice scaling and placement: A survey

N Saha, M Zangooei, M Golkarifard… - IEEE Communications …, 2023 - ieeexplore.ieee.org
Network slicing in 5G and beyond networks allows the network to be customized for each
application or service by chaining together different virtualized network functions (VNFs) …

[图书][B] 6G Frontiers: Towards Future Wireless Systems

C De Alwis, QV Pham, M Liyanage - 2022 - books.google.com
6G Frontiers Enables readers to understand the exciting new technologies, architectural
directions, technical aspects, and applications of 6G, plus legal and standardization …