Thirty years of machine learning: The road to Pareto-optimal wireless networks

J Wang, C Jiang, H Zhang, Y Ren… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Future wireless networks have a substantial potential in terms of supporting a broad range of
complex compelling applications both in military and civilian fields, where the users are able …

Machine learning for resource management in cellular and IoT networks: Potentials, current solutions, and open challenges

F Hussain, SA Hassan, R Hussain… - … surveys & tutorials, 2020 - ieeexplore.ieee.org
Internet-of-Things (IoT) refers to a massively heterogeneous network formed through smart
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …

6G and beyond: The future of wireless communications systems

IF Akyildiz, A Kak, S Nie - IEEE access, 2020 - ieeexplore.ieee.org
6G and beyond will fulfill the requirements of a fully connected world and provide ubiquitous
wireless connectivity for all. Transformative solutions are expected to drive the surge for …

A survey of multi-access edge computing in 5G and beyond: Fundamentals, technology integration, and state-of-the-art

QV Pham, F Fang, VN Ha, MJ Piran, M Le, LB Le… - IEEE …, 2020 - ieeexplore.ieee.org
Driven by the emergence of new compute-intensive applications and the vision of the
Internet of Things (IoT), it is foreseen that the emerging 5G network will face an …

White paper on broadband connectivity in 6G

N Rajatheva, I Atzeni, E Bjornson, A Bourdoux… - arXiv preprint arXiv …, 2020 - arxiv.org
This white paper explores the road to implementing broadband connectivity in future 6G
wireless systems. Different categories of use cases are considered, from extreme capacity …

Model-driven deep learning for MIMO detection

H He, CK Wen, S Jin, GY Li - IEEE Transactions on Signal …, 2020 - ieeexplore.ieee.org
In this paper, we investigate the model-driven deep learning (DL) for MIMO detection. In
particular, the MIMO detector is specially designed by unfolding an iterative algorithm and …

[HTML][HTML] Cybersecurity challenges in vehicular communications

Z El-Rewini, K Sadatsharan, DF Selvaraj… - Vehicular …, 2020 - Elsevier
As modern vehicles are capable to connect to an external infrastructure and Vehicle-to-
Everything (V2X) communication technologies mature, the necessity to secure …

A gentle introduction to reinforcement learning and its application in different fields

M Naeem, STH Rizvi, A Coronato - IEEE access, 2020 - ieeexplore.ieee.org
Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has
become one of the most important and useful technology. It is a learning method where a …

Deep learning-based end-to-end wireless communication systems with conditional GANs as unknown channels

H Ye, L Liang, GY Li, BH Juang - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this article, we develop an end-to-end wireless communication system using deep neural
networks (DNNs), where DNNs are employed to perform several key functions, including …

6G white paper on machine learning in wireless communication networks

S Ali, W Saad, N Rajatheva, K Chang… - arXiv preprint arXiv …, 2020 - arxiv.org
The focus of this white paper is on machine learning (ML) in wireless communications. 6G
wireless communication networks will be the backbone of the digital transformation of …