AI models for green communications towards 6G

B Mao, F Tang, Y Kawamoto… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …

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 …

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 …

Comprehensive survey on machine learning in vehicular network: Technology, applications and challenges

F Tang, B Mao, N Kato, G Gui - IEEE Communications Surveys …, 2021 - ieeexplore.ieee.org
Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …

Deep learning for super-resolution channel estimation and DOA estimation based massive MIMO system

H Huang, J Yang, H Huang, Y Song… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
The recent concept of massive multiple-input multiple-output (MIMO) can significantly
improve the capacity of the communication network, and it has been regarded as a …

Deep-learning-based millimeter-wave massive MIMO for hybrid precoding

H Huang, Y Song, J Yang, G Gui… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) has been
regarded to be an emerging solution for the next generation of communications, in which …

Smart resource allocation for mobile edge computing: A deep reinforcement learning approach

J Wang, L Zhao, J Liu, N Kato - IEEE Transactions on emerging …, 2019 - ieeexplore.ieee.org
The development of mobile devices with improving communication and perceptual
capabilities has brought about a proliferation of numerous complex and computation …

Survey on machine learning for intelligent end-to-end communication toward 6G: From network access, routing to traffic control and streaming adaption

F Tang, B Mao, Y Kawamoto… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
The end-to-end quality of service (QoS) and quality of experience (QoE) guarantee is quite
important for network optimization. The current 5G and conceived 6G network in the future …

Flight delay prediction based on aviation big data and machine learning

G Gui, F Liu, J Sun, J Yang, Z Zhou… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Accurate flight delay prediction is fundamental to establish the more efficient airline
business. Recent studies have been focused on applying machine learning methods to …

Optimizing space-air-ground integrated networks by artificial intelligence

N Kato, ZM Fadlullah, F Tang, B Mao… - IEEE Wireless …, 2019 - ieeexplore.ieee.org
It is widely acknowledged that the development of traditional terrestrial communication
technologies cannot provide all users with fair and high quality services due to scarce …