A survey on resource management for 6G heterogeneous networks: current research, future trends, and challenges

HF Alhashimi, MHDN Hindia, K Dimyati, EB Hanafi… - Electronics, 2023 - mdpi.com
The sixth generation (6G) mobile communication system is expected to meet the different
service needs of modern communication scenarios. Heterogeneous networks (HetNets) …

[HTML][HTML] A survey of applications of artificial intelligence and machine learning in future mobile networks-enabled systems

İ Yazici, I Shayea, J Din - … Science and Technology, an International Journal, 2023 - Elsevier
Different fields have been thriving with the advents in mobile communication systems in
recent years. These fields reap benefits of data collected by Internet of Things (IoT) in next …

Spatial–temporal graph neural network traffic prediction based load balancing with reinforcement learning in cellular networks

S Liu, M He, Z Wu, P Lu, W Gu - Information Fusion, 2024 - Elsevier
Balancing network traffic among base stations poses a primary challenge for mobile
operators because of the escalating demand for enhanced data speeds in large-scale 5G …

Dynamic load balancing techniques in the IoT: A review

D Kanellopoulos, VK Sharma - Symmetry, 2022 - mdpi.com
The Internet of things (IoT) extends the Internet space by allowing smart things to sense
and/or interact with the physical environment and communicate with other physical objects …

At the Dawn of Generative AI Era: A tutorial-cum-survey on new frontiers in 6G wireless intelligence

A Celik, AM Eltawil - IEEE Open Journal of the …, 2024 - ieeexplore.ieee.org
As we transition from the 5G epoch, a new horizon beckons with the advent of 6G, seeking a
profound fusion with novel communication paradigms and emerging technological trends …

Reducing idleness in financial cloud services via multi-objective evolutionary reinforcement learning based load balancer

P Yang, L Zhang, H Liu, G Li - Science China Information Sciences, 2024 - Springer
In recent years, various companies have started to shift their data services from traditional
data centers to the cloud. One of the major motivations is to save on operational costs with …

[HTML][HTML] Artificial intelligence linear regression model for mobility robustness optimization algorithm in 5G cellular networks

SA Saad, I Shayea, NMOS Ahmed - Alexandria Engineering Journal, 2024 - Elsevier
Ensuring reliable and stable communication links between User Equipment (UE) and
serving cellular networks during UE movement is one of the significant difficulties facing the …

A survey of handover management in mobile HetNets: current challenges and future directions

AU Rehman, MB Roslee, T Jun Jiat - Applied Sciences, 2023 - mdpi.com
With the rapid growth of data traffic and mobile devices, it is imperative to provide reliable
and stable services during mobility. Heterogeneous Networks (HetNets) and dense …

Advanced mobility robustness optimization models in future mobile networks based on machine learning solutions

W Tashan, I Shayea, S Aldirmaz-Çolak, OA Aziz… - IEEE …, 2022 - ieeexplore.ieee.org
Ultra-dense heterogeneous networks (HetNets) are deployment scenarios in the advent of
fifth generation (5G) and beyond network generations. A massive number of small base …

Machine Learning Empowered Emerging Wireless Networks in 6G: Recent Advancements, Challenges & Future Trends

HMF Noman, E Hanafi, KA Noordin, K Dimyati… - IEEE …, 2023 - ieeexplore.ieee.org
The upcoming 6G networks are sixth-sense next-generation communication networks with
an ever-increasing demand for enhanced end-to-end (E2E) connectivity towards a …