Leveraging machine learning for millimeter wave beamforming in beyond 5G networks
Millimeter wave (mmWave) communication has attracted considerable attention as a key
technology for the next-generation wireless communications thanks to its exceptional …
technology for the next-generation wireless communications thanks to its exceptional …
Transport layer performance in 5G mmWave cellular
The millimeter wave (mmWave) bands are likely to play a significant role in next generation
cellular systems due to the possibility of very high throughput thanks to the availability of …
cellular systems due to the possibility of very high throughput thanks to the availability of …
Deep learning on multimodal sensor data at the wireless edge for vehicular network
Beam selection for millimeter-wave links in a vehicular scenario is a challenging problem, as
an exhaustive search among all candidate beam pairs cannot be assuredly completed …
an exhaustive search among all candidate beam pairs cannot be assuredly completed …
Machine learning enabling analog beam selection for concurrent transmissions in millimeter-wave V2V communications
With the development of millimeter-wave (mmWave) technology and vehicle-to-vehicle
(V2V) communications, the mmWave vehicular ad hoc networks (VANETs) is envisioned to …
(V2V) communications, the mmWave vehicular ad hoc networks (VANETs) is envisioned to …
End-to-end simulation of 5G mmWave networks
Due to its potential for multi-gigabit and low latency wireless links, millimeter wave
(mmWave) technology is expected to play a central role in 5th generation (5G) cellular …
(mmWave) technology is expected to play a central role in 5th generation (5G) cellular …
LIDAR and position-aided mmWave beam selection with non-local CNNs and curriculum training
Efficient millimeter wave (mmWave) beam selection in vehicle-to-infrastructure (V2I)
communication is a crucial yet challenging task due to the narrow mmWave beamwidth and …
communication is a crucial yet challenging task due to the narrow mmWave beamwidth and …
Machine learning for reliable mmwave systems: Blockage prediction and proactive handoff
A Alkhateeb, I Beltagy, S Alex - 2018 IEEE Global conference …, 2018 - ieeexplore.ieee.org
The sensitivity of millimeter wave (mmWave) signals to blockages is a fundamental
challenge for mobile mmWave communication systems. The sudden blockage of the line-of …
challenge for mobile mmWave communication systems. The sudden blockage of the line-of …
Where, when, and how mmWave is used in 5G and beyond
Wireless engineers and business planners commonly raise the question on where, when,
and how millimeter-wave (mmWave) will be used in 5G and beyond. Since the next …
and how millimeter-wave (mmWave) will be used in 5G and beyond. Since the next …
Generative adversarial estimation of channel covariance in vehicular millimeter wave systems
X Li, A Alkhateeb… - 2018 52nd Asilomar …, 2018 - ieeexplore.ieee.org
Enabling highly-mobile millimeter wave (mmWave) systems is challenging because of the
huge training overhead associated with acquiring the channel knowledge or designing the …
huge training overhead associated with acquiring the channel knowledge or designing the …
Self-supervised deep learning for mmWave beam steering exploiting sub-6 GHz channels
mmWave communication requires accurate and continuous beam steering to overcome the
severe propagation loss and user mobility. In this paper, we leverage a self-supervised deep …
severe propagation loss and user mobility. In this paper, we leverage a self-supervised deep …