A literature survey on AI-aided beamforming and beam management for 5G and 6G systems

DS Brilhante, JC Manjarres, R Moreira… - Sensors, 2023 - mdpi.com
Modern wireless communication systems rely heavily on multiple antennas and their
corresponding signal processing to achieve optimal performance. As 5G and 6G networks …

Machine learning for wireless link quality estimation: A survey

G Cerar, H Yetgin, M Mohorčič… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Since the emergence of wireless communication networks, a plethora of research papers
focus their attention on the quality aspects of wireless links. The analysis of the rich body of …

Proactive received power prediction using machine learning and depth images for mmWave networks

T Nishio, H Okamoto, K Nakashima… - IEEE Journal on …, 2019 - ieeexplore.ieee.org
This study demonstrates the feasibility of proactive received power prediction by leveraging
spatiotemporal visual sensing information towards reliable millimeter-wave (mmWave) …

Handover management for mmWave networks with proactive performance prediction using camera images and deep reinforcement learning

Y Koda, K Nakashima, K Yamamoto… - IEEE Transactions …, 2019 - ieeexplore.ieee.org
For millimeter-wave networks, this paper presents a paradigm shift for leveraging time-
consecutive camera images in handover decision problems. While making handover …

Machine learning-based field data analysis and modeling for drone communications

L Shan, R Miura, T Kagawa, F Ono, HB Li… - IEEE Access, 2019 - ieeexplore.ieee.org
In recent years, unmanned aerial vehicle (UAV), also called a drone, is getting more and
more important in many emerging technology areas. For communication area, the drone …

Going beyond RF: A survey on how AI-enabled multimodal beamforming will shape the NextG standard

D Roy, B Salehi, S Banou, S Mohanti, G Reus-Muns… - Computer Networks, 2023 - Elsevier
Incorporating artificial intelligence and machine learning (AI/ML) methods within the 5G
wireless standard promises autonomous network behavior and ultra-low-latency …

Energy efficiency and throughput maximization using millimeter waves–microwaves HetNets

S Jamil, MU Rahman, J Tanveer, A Haider - Electronics, 2022 - mdpi.com
The deployment of millimeter waves can fulfil the stringent requirements of high bandwidth
and high energy efficiency in fifth generation (5G) networks. Still, millimeter waves …

Optimal handover policy for mmWave cellular networks: A multi-armed bandit approach

L Sun, J Hou, T Shu - 2019 IEEE Global Communications …, 2019 - ieeexplore.ieee.org
Millimeter wave (mmWave) is a promising technology in 5G communication due to its
abundant bandwidth re-source. However, its severe path attenuation and vulnerability to line …

An RSS-based classification of user equipment usage in indoor millimeter wave wireless networks using machine learning

L Zhang, Y Hua, SL Cotton, SK Yoo… - ieee …, 2020 - ieeexplore.ieee.org
The use of millimeter wave technologies offer a promising solution for dense small cell
networks, despite having to contend with challenging propagation characteristics. In …

A hybrid data manipulation approach for energy and latency-efficient vision-aided UDNs

M Al-Quraan, AR Khan, L Mohjazi… - … on Software Defined …, 2021 - ieeexplore.ieee.org
The combination of deep learning (DL) and computer vision (CV) is shaping the future of
wireless communications by supporting the operations of ultra-dense networks (UDNs) …