A review on machine learning and deep learning for various antenna design applications

MM Khan, S Hossain, P Mozumdar, S Akter… - Heliyon, 2022 - cell.com
The next generation of wireless communication networks will rely heavily on machine
learning and deep learning. In comparison to traditional ground-based systems, the …

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 …

[HTML][HTML] 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 …

Design and analysis of wideband in-band-full-duplex FR2-IAB networks

J Zhang, H Luo, N Garg, A Bishnu… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
This paper develops a 3GPP-inspired design for the in-band-full-duplex (IBFD) integrated
access and backhaul (IAB) networks in the frequency range 2 (FR2) band, which can …

Adversarial machine learning security problems for 6G: mmWave beam prediction use-case

E Catak, FO Catak, A Moldsvor - 2021 IEEE International Black …, 2021 - ieeexplore.ieee.org
6G is the next generation for the communication systems. In recent years, machine learning
algorithms have been applied widely in various fields such as health, transportation, and the …

Hand grip impact on 5G mmWave mobile devices

A Alammouri, J Mo, BL Ng, JC Zhang… - IEEE Access, 2019 - ieeexplore.ieee.org
This paper contributes a comprehensive study on the effect of the user hand grip on the
design of 5G millimeter-wave (mmWave) mobile handsets, specifically in terms of the …

Hand blockage impact on 5G mmWave beam management performance

F Fernandes, C Rom, J Harrebek, S Svendsen… - IEEE …, 2022 - ieeexplore.ieee.org
Modelling and managing user-induced rotation and blockage in handheld multi-antenna
panel devices are some of the pivotal challenges of future narrow beam millimeter wave …

Decentralized interference-aware codebook learning in millimeter wave MIMO systems

Y Zhang, A Alkhateeb - IEEE Transactions on Communications, 2024 - ieeexplore.ieee.org
Beam codebooks are integral components of future millimeter wave MIMO systems.
Therefore, it is critical to optimize these codebooks for efficient and reliable communications …

Beam management with orientation and RSRP using deep learning for beyond 5G systems

KN Nguyen, A Ali, J Mo, BL Ng, V Va… - 2022 IEEE …, 2022 - ieeexplore.ieee.org
Beam management (BM), ie, the process of finding and maintaining a suitable transmit and
receive beam pair, can be challenging, particularly in highly dynamic scenarios. Side …

Adaptive non-uniform hybrid beamforming for mmWave train-to-ground communications in high-speed railway scenarios

Y Liu, B Ai, Y Niu, Z Han, Z Zhong… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Higher frequency bands, especially millimeter wave (mmWave), are a key enabler for future
high-speed railway (HSR) wireless communication systems. Hybrid analog and digital …