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 …

Deep learning in mobile and wireless networking: A survey

C Zhang, P Patras, H Haddadi - IEEE Communications surveys …, 2019 - ieeexplore.ieee.org
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …

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 …

[PDF][PDF] 6G 移动通信网络: 愿景, 挑战与关键技术

赵亚军, 郁光辉, 徐汉青 - 中国科学: 信息科学, 2019 - arxiv.org
摘要随着5G 网络开启规模商业部署, 越来越多的研究机构及相关人员开始对下一代移动通信
系统进行研究. 本文将探讨十年后(2030 年~) 的6G 概念. 本文首先用四个关键词概括未来6G …

Deep learning for intelligent wireless networks: A comprehensive survey

Q Mao, F Hu, Q Hao - IEEE Communications Surveys & …, 2018 - ieeexplore.ieee.org
As a promising machine learning tool to handle the accurate pattern recognition from
complex raw data, deep learning (DL) is becoming a powerful method to add intelligence to …

Spectrum sharing in vehicular networks based on multi-agent reinforcement learning

L Liang, H Ye, GY Li - IEEE Journal on Selected Areas in …, 2019 - ieeexplore.ieee.org
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 …

Deep learning in the industrial internet of things: Potentials, challenges, and emerging applications

RA Khalil, N Saeed, M Masood, YM Fard… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Recent advances in the Internet of Things (IoT) are giving rise to a proliferation of
interconnected devices, allowing the use of various smart applications. The enormous …

[HTML][HTML] A review of optimization methods for computation offloading in edge computing networks

K Sadatdiynov, L Cui, L Zhang, JZ Huang… - Digital Communications …, 2023 - Elsevier
Handling the massive amount of data generated by Smart Mobile Devices (SMDs) is a
challenging computational problem. Edge Computing is an emerging computation paradigm …

Securing connected & autonomous vehicles: Challenges posed by adversarial machine learning and the way forward

A Qayyum, M Usama, J Qadir… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Connected and autonomous vehicles (CAVs) will form the backbone of future next-
generation intelligent transportation systems (ITS) providing travel comfort, road safety …

Toward intelligent vehicular networks: A machine learning framework

L Liang, H Ye, GY Li - IEEE Internet of Things Journal, 2018 - ieeexplore.ieee.org
As wireless networks evolve toward high mobility and providing better support for connected
vehicles, a number of new challenges arise due to the resulting high dynamics in vehicular …