6G for vehicle-to-everything (V2X) communications: Enabling technologies, challenges, and opportunities
We are on the cusp of a new era of connected autonomous vehicles with unprecedented
user experiences, tremendously improved road safety and air quality, highly diverse …
user experiences, tremendously improved road safety and air quality, highly diverse …
Machine learning at the network edge: A survey
Resource-constrained IoT devices, such as sensors and actuators, have become ubiquitous
in recent years. This has led to the generation of large quantities of data in real-time, which …
in recent years. This has led to the generation of large quantities of data in real-time, which …
Deep learning for safe autonomous driving: Current challenges and future directions
Advances in information and signal processing technologies have a significant impact on
autonomous driving (AD), improving driving safety while minimizing the efforts of human …
autonomous driving (AD), improving driving safety while minimizing the efforts of human …
Reliable federated learning for mobile networks
Federated learning, as a promising machine learning approach, has emerged to leverage a
distributed personalized dataset from a number of nodes, for example, mobile devices, to …
distributed personalized dataset from a number of nodes, for example, mobile devices, to …
Machine learning for resource management in cellular and IoT networks: Potentials, current solutions, and open challenges
Internet-of-Things (IoT) refers to a massively heterogeneous network formed through smart
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
Spectrum sharing in vehicular networks based on multi-agent reinforcement learning
This paper investigates the spectrum sharing problem in vehicular networks based on multi-
agent reinforcement learning, where multiple vehicle-to-vehicle (V2V) links reuse the …
agent reinforcement learning, where multiple vehicle-to-vehicle (V2V) links reuse the …
[HTML][HTML] Cybersecurity challenges in vehicular communications
Z El-Rewini, K Sadatsharan, DF Selvaraj… - Vehicular …, 2020 - Elsevier
As modern vehicles are capable to connect to an external infrastructure and Vehicle-to-
Everything (V2X) communication technologies mature, the necessity to secure …
Everything (V2X) communication technologies mature, the necessity to secure …
A survey of 5G technology evolution, standards, and infrastructure associated with vehicle-to-everything communications by internet of vehicles
CR Storck, F Duarte-Figueiredo - IEEE access, 2020 - ieeexplore.ieee.org
The very last wireless network technology, created to increase the speed and the
connections responsiveness, the Fifth-Generation Network (5G) can transmit a great volume …
connections responsiveness, the Fifth-Generation Network (5G) can transmit a great volume …
A survey of collaborative machine learning using 5G vehicular communications
SV Balkus, H Wang, BD Cornet… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
By enabling autonomous vehicles (AVs) to share data while driving, 5G vehicular
communications allow AVs to collaborate on solving common autonomous driving tasks …
communications allow AVs to collaborate on solving common autonomous driving tasks …
Deep reinforcement learning for autonomous internet of things: Model, applications and challenges
The Internet of Things (IoT) extends the Internet connectivity into billions of IoT devices
around the world, where the IoT devices collect and share information to reflect status of the …
around the world, where the IoT devices collect and share information to reflect status of the …