Application of reinforcement learning and deep learning in multiple-input and multiple-output (MIMO) systems

M Naeem, G De Pietro, A Coronato - Sensors, 2021 - mdpi.com
The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …

Intelligent massive MIMO systems for beyond 5G networks: An overview and future trends

O Elijah, SKA Rahim, WK New, CY Leow… - IEEE …, 2022 - ieeexplore.ieee.org
Machine learning (ML) which is a subset of artificial intelligence is expected to unlock the
potential of challenging large-scale problems in conventional massive multiple-input …

From 5G to 6G technology: meets energy, internet-of-things and machine learning: a survey

MN Mahdi, AR Ahmad, QS Qassim, H Natiq… - Applied Sciences, 2021 - mdpi.com
Due to the rapid development of the fifth-generation (5G) applications, and increased
demand for even faster communication networks, we expected to witness the birth of a new …

ADAPTIVE6G: Adaptive resource management for network slicing architectures in current 5G and future 6G systems

A Thantharate, C Beard - Journal of Network and Systems Management, 2023 - Springer
Future intelligent wireless networks demand an adaptive learning approach towards a
shared learning model to allow collaboration between data generated by network elements …

The future of artificial intelligence in cybersecurity: A comprehensive survey

F Tao, MS Akhtar, Z Jiayuan - EAI Endorsed Transactions on …, 2021 - publications.eai.eu
AI in Cybersecurity Market scheme helps organizations in observance, detecting, reporting,
and countering cyber threats to keep up information confidentiality. The increasing …

A deep ensemble-based wireless receiver architecture for mitigating adversarial attacks in automatic modulation classification

R Sahay, CG Brinton, DJ Love - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Deep learning-based automatic modulation classification (AMC) models are susceptible to
adversarial attacks. Such attacks inject specifically crafted wireless interference into …

[HTML][HTML] Knowledge-defined networking: Applications, challenges and future work

S Ashtari, I Zhou, M Abolhasan, N Shariati, J Lipman… - Array, 2022 - Elsevier
Future 6G wireless communication systems are expected to feature intelligence and
automation. Knowledge-defined networking (KDN) is an evolutionary step toward …

Development of a data-driven mobile 5g testbed: Platform for experimental research

Y Wang, A Gorski, AP da Silva - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
The presented 5G testbed aims to prototype an end-to-end mobile data-driven platform for
experimental 5G and interdisciplinary research. The testbed design and implementation for …

Wild networks: Exposure of 5G network infrastructures to adversarial examples

G Apruzzese, R Vladimirov… - … on Network and …, 2022 - ieeexplore.ieee.org
Fifth Generation (5G) networks must support billions of heterogeneous devices while
guaranteeing optimal Quality of Service (QoS). Such requirements are impossible to meet …

Robust automatic modulation classification in the presence of adversarial attacks

R Sahay, DJ Love, CG Brinton - 2021 55th Annual Conference …, 2021 - ieeexplore.ieee.org
Automatic modulation classification (AMC) is used in intelligent receivers operating in
shared spectrum environments to classify the modulation constellation of radio frequency …