An online context-aware machine learning algorithm for 5G mmWave vehicular communications

GH Sim, S Klos, A Asadi, A Klein… - IEEE/ACM Transactions …, 2018 - ieeexplore.ieee.org
Millimeter-Wave (mmWave) bands have become the de-facto candidate for 5G vehicle-to-
everything (V2X) since future vehicular systems demand Gbps links to acquire the …

FML: Fast machine learning for 5G mmWave vehicular communications

A Asadi, S Müller, GH Sim, A Klein… - IEEE INFOCOM 2018 …, 2018 - ieeexplore.ieee.org
Millimeter-Wave (mmWave) bands have become the de-facto candidate for 5G vehicle-to-
everything (V2X) since future vehicular systems demand Gbps links to acquire the …

Flash: Federated learning for automated selection of high-band mmwave sectors

B Salehi, J Gu, D Roy… - IEEE INFOCOM 2022 …, 2022 - ieeexplore.ieee.org
Fast sector-steering in the mmWave band for vehicular mobility scenarios remains an open
challenge. This is because standard-defined exhaustive search over predefined antenna …

Efficient beam alignment in millimeter wave systems using contextual bandits

M Hashemi, A Sabharwal, CE Koksal… - IEEE INFOCOM 2018 …, 2018 - ieeexplore.ieee.org
In this paper, we investigate the problem of beam alignment in millimeter wave (mmWave)
systems, and design an optimal algorithm to reduce the overhead. Specifically, due to …

Beam alignment and tracking for millimeter wave communications via bandit learning

J Zhang, Y Huang, Y Zhou, X You - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Millimeter wave (mmwave) communications have attracted increasing attention thanks to the
abundant spectrum resource. The short wave-length of mmwave signals facilitates exploiting …

Deep learning-based channel estimation and tracking for millimeter-wave vehicular communications

S Moon, H Kim, I Hwang - Journal of Communications and …, 2020 - ieeexplore.ieee.org
The application of millimeter-wave (mmWave) frequencies is a potential technology for
satisfying the continuously increasing need for handling data traffic in highly advanced …

Machine learning based mmWave channel tracking in vehicular scenario

Y Guo, Z Wang, M Li, Q Liu - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Millimeter wave (mmWave) communication has become a key enabling technology for 5G
and beyond networks because of its large bandwidth and high transmission rate. In a …

Transfer reinforcement learning for 5G new radio mmWave networks

M Elsayed, M Erol-Kantarci… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this paper, we aim at interference mitigation in 5G millimeter-Wave (mm-Wave)
communications by employing beamforming and Non-Orthogonal Multiple Access (NOMA) …

MAMBA: A multi-armed bandit framework for beam tracking in millimeter-wave systems

I Aykin, B Akgun, M Feng… - IEEE INFOCOM 2020-IEEE …, 2020 - ieeexplore.ieee.org
Millimeter-wave (mmW) spectrum is a major candidate to support the high data rates of 5G
systems. However, due to directionality of mmW communication systems, misalignments …

Machine learning enabling analog beam selection for concurrent transmissions in millimeter-wave V2V communications

Y Yang, Z Gao, Y Ma, B Cao… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
With the development of millimeter-wave (mmWave) technology and vehicle-to-vehicle
(V2V) communications, the mmWave vehicular ad hoc networks (VANETs) is envisioned to …