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 …

Enabling AI in future wireless networks: A data life cycle perspective

DC Nguyen, P Cheng, M Ding… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
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 …

[PDF][PDF] A System for Analysing call drop dynamics in the telecom industry using Machine Learning and Feature Selection

D DASTAGIRAIAH - Journal of Theoretical and Applied Information …, 2024 - jatit.org
Quality of service in the telecom industry plays a vital role in the growth and economy of the
country. In India, several telecom operators provide services, and there is a regulatory …

Machine learning meets communication networks: Current trends and future challenges

I Ahmad, S Shahabuddin, H Malik, E Harjula… - IEEE …, 2020 - ieeexplore.ieee.org
The growing network density and unprecedented increase in network traffic, caused by the
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 …

Can machine learning accelerate process understanding and decision‐relevant predictions of river water quality?

C Varadharajan, AP Appling, B Arora… - Hydrological …, 2022 - Wiley Online Library
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 …

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 …

EM DeepRay: An expedient, generalizable, and realistic data-driven indoor propagation model

S Bakirtzis, J Chen, K Qiu, J Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Efficient and realistic indoor radio propagation modeling tools are inextricably intertwined
with the design and operation of next-generation wireless networks. Machine-learning (ML) …

Leveraging network data analytics function and machine learning for data collection, resource optimization, security and privacy in 6G networks

PK Gkonis, N Nomikos, P Trakadas, L Sarakis… - IEEE …, 2024 - ieeexplore.ieee.org
The full deployment of sixth-generation (6G) networks is inextricably connected with a
holistic network redesign able to deal with various emerging challenges, such as integration …

Efficient extreme gradient boosting based algorithm for QoS optimization in inter-radio access technology handoffs

MA Al Sibahee, J Ma, VO Nyangaresi… - … congress on human …, 2022 - ieeexplore.ieee.org
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 …