Performance Evaluation of AI/ML Model to Enhance Beam Management in 5G-Advanced System

J Xu, I Nakamura, R Feng, L Liu… - … Conference on Mobile …, 2023 - ieeexplore.ieee.org
In fifth generation (5G) wireless communication systems, the millimeter wave (mmWave) is
identified as a significant frequency band, offering extensive spectrum resources. Despite its …

Recurrent Neural Network Based Beam Prediction for Millimeter-Wave 5G Systems

S Khunteta, AKR Chavva - 2021 IEEE Wireless …, 2021 - ieeexplore.ieee.org
5G millimeter-wave (mmWave) system provides ultra low latency and higher peak data rate
with a major drawback of higher path loss at mmWave spectrum. Multiple beams are formed …

AI-aided 3-D beamforming for millimeter wave communications

WC Kao, SQ Zhan, TS Lee - 2018 International Symposium on …, 2018 - ieeexplore.ieee.org
Millimeter wave (mmWave) communications are a mainstream technology of the fifth
generation (5G) systems. Beamforming plays an important role in mmWave communications …

Machine learning based time domain millimeter-wave beam prediction for 5G-advanced and beyond: design, analysis, and over-the-air experiments

Q Li, P Sisk, A Kannan, T Yoo, T Luo… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
Artificial intelligence (AI) or machine learning (ML) based beam prediction is currently
studied in the 3rd Generation Partnership Project (3GPP) fifth generation (5G)-Advanced …

Multi-modal fusion for millimeter-wave communication systems: A spatio-temporal enabled approach

Q Zhou, Y Lai, H Yu, R Zhang, X Jing, L Luo - Neurocomputing, 2023 - Elsevier
In millimeter-wave (mmWave) massive multi-input multi-output (MIMO) systems, beam
selection can enhance channel capacity and reduce error rate. However, existing beam …

MmWave beam prediction with situational awareness: A machine learning approach

Y Wang, M Narasimha… - 2018 IEEE 19th …, 2018 - ieeexplore.ieee.org
Millimeter-wave communication is a challenge in the highly mobile vehicular context.
Traditional beam training is inadequate in satisfying low overheads and latency. In this …

LiDAR aided future beam prediction in real-world millimeter wave V2I communications

S Jiang, G Charan, A Alkhateeb - IEEE Wireless …, 2022 - ieeexplore.ieee.org
This letter presents the first large-scale real-world evaluation for using LiDAR data to guide
the mmWave beam prediction task. A machine learning (ML) model that leverages LiDAR …

Deep learning-based predictive beam management for 5G mmWave systems

AÖ Kaya, H Viswanathan - 2021 IEEE Wireless …, 2021 - ieeexplore.ieee.org
Periodic measurement reporting based beam management is not sufficiently agile for 5G
New Radio (NR) and comes with significant overhead that scales with the number of beams …

Low-complexity beam training for tracking spatially consistent millimeter wave channels

F Alsaleem, J Thompson… - 2020 IEEE 31st Annual …, 2020 - ieeexplore.ieee.org
In fifth generation (5G) wireless systems, millimetre wave (mmWave) frequency bands will
be exploited to support high data demands. The exploitation of mmWave carrier frequencies …

Neural networks based beam codebooks: Learning mmWave massive MIMO beams that adapt to deployment and hardware

M Alrabeiah, Y Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Millimeter wave (mmWave) and massive MIMO systems are intrinsic components of 5G and
beyond. These systems rely on using beamforming codebooks for both initial access and …