Towards energy-efficient wireless networking in the big data era: A survey

X Cao, L Liu, Y Cheng, X Shen - … Communications Surveys & …, 2017 - ieeexplore.ieee.org
With the proliferation of wireless devices, wireless networks in various forms have become
global information infrastructure and an important part of our daily life, which, at the same …

Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions

ME Morocho-Cayamcela, H Lee, W Lim - IEEE access, 2019 - ieeexplore.ieee.org
Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be
a key enabler and a leading infrastructure provider in the information and communication …

A survey on deep learning for ultra-reliable and low-latency communications challenges on 6G wireless systems

A Salh, L Audah, NSM Shah, A Alhammadi… - IEEE …, 2021 - ieeexplore.ieee.org
The sixth generation (6G) wireless communication network presents itself as a promising
technique that can be utilized to provide a fully data-driven network evaluating and …

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 …

Artificial intelligence in 5G technology: A survey

MEM Cayamcela, W Lim - 2018 International Conference on …, 2018 - ieeexplore.ieee.org
A fully operative and efficient 5G network cannot be complete without the inclusion of
artificial intelligence (AI) routines. Existing 4G networks with all-IP (Internet Protocol) …

A deep learning-based approach to power minimization in multi-carrier NOMA with SWIPT

J Luo, J Tang, DKC So, G Chen, K Cumanan… - IEEE …, 2019 - ieeexplore.ieee.org
Simultaneous wireless information and power transfer (SWIPT) and multi-carrier non-
orthogonal multiple access (MC-NOMA) are promising technologies for future fifth …

ML-based radio resource management in 5G and beyond networks: A survey

IA Bartsiokas, PK Gkonis, DI Kaklamani… - IEEE Access, 2022 - ieeexplore.ieee.org
In this survey, a comprehensive study is provided, regarding the use of machine learning
(ML) algorithms for effective resource management in fifth-generation and beyond (5G/B5G) …

Machine learning for performance prediction in mobile cellular networks

J Riihijarvi, P Mahonen - IEEE Computational Intelligence …, 2018 - ieeexplore.ieee.org
In this paper, we discuss the application of machine learning techniques for performance
prediction problems in wireless networks. These problems often involve using existing …

A comprehensive review on the use of AI in UAV communications: Enabling technologies, applications, and challenges

F Al-Turjman, H Zahmatkesh - Unmanned Aerial Vehicles in Smart Cities, 2020 - Springer
Artificial intelligence (AI) has a great capability to deal with big data and complexity as well
as speedy and high-accuracy processing. AI algorithms along with robotics can be used to …

Improved resource allocation scheme for optimizing the performance of cell-edge users in LTE-A system

R Gatti, Shivashankar - Journal of Ambient Intelligence and Humanized …, 2021 - Springer
Improved resource allocation scheme for optimizing the performance of cell edge users in
Long Term Evolution-Advanced (LTE-A) system is proposed in this paper. The proposed …