PARAMOUNT: Towards generalizable deeP leARning for mmwAve beaM selectiOn using sUb-6GHz chaNnel measuremenTs
Deep neural networks (DNNs) in the wireless communication domain have been shown to
be hardly generalizable to scenarios where the train and test datasets follow a different …
be hardly generalizable to scenarios where the train and test datasets follow a different …
Deep learning for mmWave beam and blockage prediction using sub-6 GHz channels
M Alrabeiah, A Alkhateeb - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Predicting the millimeter wave (mmWave) beams and blockages using sub-6 GHz channels
has the potential of enabling mobility and reliability in scalable mmWave systems. Prior work …
has the potential of enabling mobility and reliability in scalable mmWave systems. Prior work …
BsNet: A deep learning-based beam selection method for mmWave communications
CH Lin, WC Kao, SQ Zhan… - 2019 IEEE 90th Vehicular …, 2019 - ieeexplore.ieee.org
Millimeter wave (mmWave) techniques have attracted much attention in recent years owing
to features such as substantial bandwidth for communication, and it has applications in radar …
to features such as substantial bandwidth for communication, and it has applications in radar …
Deep learning-based mmWave beam selection for 5G NR/6G with sub-6 GHz channel information: Algorithms and prototype validation
In fifth-generation (5G) communications, millimeter wave (mmWave) is one of the key
technologies to increase the data rate. To overcome this technology's poor propagation …
technologies to increase the data rate. To overcome this technology's poor propagation …
Tune: Transfer learning in unseen environments for v2x mmwave beam selection
The use of non-RF data can potentially speed up millimeter wave-band sector-steering in
vehicular mobility scenarios by gaining contextual knowledge of the environment. While …
vehicular mobility scenarios by gaining contextual knowledge of the environment. While …
[HTML][HTML] Augmenting Beam Alignment for mmWave Communication Systems via Channel Attention
J Kim, J Kim - Electronics, 2023 - mdpi.com
The beamforming technique has attracted considerable attention in wireless communication
due to its various advantages such as interference reduction and improved wireless …
due to its various advantages such as interference reduction and improved wireless …
Deep regularized waveform learning for beam prediction with limited samples in non-cooperative mmWave systems
Millimeter wave (mmWave) systems need beam management to establish and maintain
reliable links. This complex and time-consuming process seriously affects communication …
reliable links. This complex and time-consuming process seriously affects communication …
Learning and data-driven beam selection for mmWave communications: An angle of arrival-based approach
C Antón-Haro, X Mestre - IEEE Access, 2019 - ieeexplore.ieee.org
This paper investigates how angle-of-arrival (AoA) information can be exploited by deep-
/machine-learning approaches to perform beam selection in the uplink of a mmWave …
/machine-learning approaches to perform beam selection in the uplink of a mmWave …
Learning site-specific probing beams for fast mmWave beam alignment
Beam alignment–the process of finding an optimal directional beam pair–is a challenging
procedure crucial to millimeter wave (mmWave) communication systems. We propose a …
procedure crucial to millimeter wave (mmWave) communication systems. We propose a …
Deep learning assisted beam prediction using out-of-band information
K Ma, P Zhao - 2020 IEEE 91st Vehicular Technology …, 2020 - ieeexplore.ieee.org
The low-frequency and mmWave links usually co-exist in the next generation wireless
terminals, where the low-frequency link is always on and the mmWave link becomes active …
terminals, where the low-frequency link is always on and the mmWave link becomes active …