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 …
originating from novel mobile applications and services and, in general, from the adoption …
Enabling AI in future wireless networks: A data life cycle perspective
Recent years have seen rapid deployment of mobile computing and Internet of Things (IoT)
networks, which can be mostly attributed to the increasing communication and sensing …
networks, which can be mostly attributed to the increasing communication and sensing …
Machine learning meets communication networks: Current trends and future challenges
The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …
massively expanding number of connected devices and online services, require intelligent …
Target Tracking Area Selection and Handover Security in Cellular Networks: A Machine Learning Approach
VO Nyangaresi - Proceedings of Third International Conference on …, 2023 - Springer
Abstract The 3rd Generation Partnership Project (3GPP) has specified the 5G Authentication
and Key Agreement (5G AKA) protocol for handover authentication. However, this protocol is …
and Key Agreement (5G AKA) protocol for handover authentication. However, this protocol is …
Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?
The global decline of water quality in rivers and streams has resulted in a pressing need to
design new watershed management strategies. Water quality can be affected by multiple …
design new watershed management strategies. Water quality can be affected by multiple …
Spatial–temporal graph neural network traffic prediction based load balancing with reinforcement learning in cellular networks
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 …
operators because of the escalating demand for enhanced data speeds in large-scale 5G …
EM DeepRay: An expedient, generalizable, and realistic data-driven indoor propagation model
Efficient and realistic indoor radio propagation modeling tools are inextricably intertwined
with the design and operation of next-generation wireless networks. Machine-learning (ML) …
with the design and operation of next-generation wireless networks. Machine-learning (ML) …
Efficient extreme gradient boosting based algorithm for QoS optimization in inter-radio access technology handoffs
The deployment of many base stations within a small network coverage area can potentially
increase network capacities. However, this implies frequent handoffs as the users move …
increase network capacities. However, this implies frequent handoffs as the users move …
[HTML][HTML] Telemedicine and smart healthcare—the role of artificial intelligence, 5G, cloud services, and other enabling technologies
TA Suleiman, A Adinoyi - International Journal of Communications …, 2023 - scirp.org
This paper discusses telemedicine and the employment of advanced mobile technologies in
smart healthcare delivery. It covers the technological advances in connected smart …
smart healthcare delivery. It covers the technological advances in connected smart …
Blockchain-empowered data-driven networks: A survey and outlook
The paths leading to future networks are pointing towards a data-driven paradigm to better
cater to the explosive growth of mobile services as well as the increasing heterogeneity of …
cater to the explosive growth of mobile services as well as the increasing heterogeneity of …