6G for vehicle-to-everything (V2X) communications: Enabling technologies, challenges, and opportunities

M Noor-A-Rahim, Z Liu, H Lee, MO Khyam… - Proceedings of the …, 2022 - ieeexplore.ieee.org
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 …

Applications of artificial intelligence and machine learning in smart cities

Z Ullah, F Al-Turjman, L Mostarda… - Computer Communications, 2020 - Elsevier
Smart cities are aimed to efficiently manage growing urbanization, energy consumption,
maintain a green environment, improve the economic and living standards of their citizens …

Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing

W Xu, Z Yang, DWK Ng, M Levorato… - IEEE journal of …, 2023 - ieeexplore.ieee.org
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …

Survey on 6G frontiers: Trends, applications, requirements, technologies and future research

C De Alwis, A Kalla, QV Pham, P Kumar… - IEEE Open Journal …, 2021 - ieeexplore.ieee.org
Emerging applications such as Internet of Everything, Holographic Telepresence,
collaborative robots, and space and deep-sea tourism are already highlighting the …

Multi-agent reinforcement learning based resource management in MEC-and UAV-assisted vehicular networks

H Peng, X Shen - IEEE Journal on Selected Areas in …, 2020 - ieeexplore.ieee.org
In this paper, we investigate multi-dimensional resource management for unmanned aerial
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …

A tutorial on ultrareliable and low-latency communications in 6G: Integrating domain knowledge into deep learning

C She, C Sun, Z Gu, Y Li, C Yang… - Proceedings of the …, 2021 - ieeexplore.ieee.org
As one of the key communication scenarios in the fifth-generation and also the sixth-
generation (6G) mobile communication networks, ultrareliable and low-latency …

Asynchronous deep reinforcement learning for collaborative task computing and on-demand resource allocation in vehicular edge computing

L Liu, J Feng, X Mu, Q Pei, D Lan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) is enjoying a surge in research interest due to the
remarkable potential to reduce response delay and alleviate bandwidth pressure. Facing the …

Resource allocation modes in C-V2X: from LTE-V2X to 5G-V2X

K Sehla, TMT Nguyen, G Pujolle… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
The paradigm of Internet of Vehicles (IoV) as an extension to the Internet of Things (IoT)
concept can assist the development of smart cities. IoV relies on vehicular communications …

Future intelligent and secure vehicular network toward 6G: Machine-learning approaches

F Tang, Y Kawamoto, N Kato, J Liu - Proceedings of the IEEE, 2019 - ieeexplore.ieee.org
As a powerful tool, the vehicular network has been built to connect human communication
and transportation around the world for many years to come. However, with the rapid growth …

Single and multi-agent deep reinforcement learning for AI-enabled wireless networks: A tutorial

A Feriani, E Hossain - IEEE Communications Surveys & …, 2021 - ieeexplore.ieee.org
Deep Reinforcement Learning (DRL) has recently witnessed significant advances that have
led to multiple successes in solving sequential decision-making problems in various …