The applicability of reinforcement learning methods in the development of industry 4.0 applications

T Kegyes, Z Süle, J Abonyi - Complexity, 2021 - Wiley Online Library
Reinforcement learning (RL) methods can successfully solve complex optimization
problems. Our article gives a systematic overview of major types of RL methods, their …

Heterogeneous IoT/LTE ProSe virtual infrastructure for disaster situations

S Abdellatif, O Tibermacine, W Bechkit… - Journal of Network and …, 2023 - Elsevier
Natural disasters of any kind can have catastrophic consequences for properties,
infrastructure, and human lives. During large-scale calamities, two common problems are …

Resource allocation for joint energy and spectral efficiency in cloud radio access network based on deep reinforcement learning

A Iqbal, ML Tham, YC Chang - Transactions on Emerging …, 2022 - Wiley Online Library
The rapid increase of user data traffic demand has promoted the telecommunication sector
toward adopting a new generation, that is, fifth‐generation (5G). Cloud radio access network …

Internet of things for smart community solutions

D Singh, M Divan, M Singh - Sensors, 2022 - mdpi.com
The term IoT (Internet of Things) constitutes the quickly developing advanced gadgets with
highest computing power with in a constrained VLSI design space. It is called things on the …

Latency and energy efficient bio-inspired conic optimized and distributed Q learning for D2D communication in 5G

S Varadala, SE Roslin - IETE Journal of Research, 2023 - Taylor & Francis
The next-generation communication, ie fifth generation (5G), will be manifesting the
advertisers in near future. The Device to Device communication would be a proportion of 5G …

Development of deep reinforcement learning based resource allocation techniques in cloud radio access network

I Amjad - 2022 - eprints.utar.edu.my
Nextgeneration networks are envisioned to support management to maximize the user s'
dynamic and agile network quality of service (QoS). Cloud radio access network (CRAN) …