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 …

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 …

Spectrum interference-based two-level data augmentation method in deep learning for automatic modulation classification

Q Zheng, P Zhao, Y Li, H Wang, Y Yang - Neural Computing and …, 2021 - Springer
Automatic modulation classification is an essential and challenging topic in the development
of cognitive radios, and it is the cornerstone of adaptive modulation and demodulation …

Intelligent edge computing based on machine learning for smart city

Z Lv, D Chen, R Lou, Q Wang - Future Generation Computer Systems, 2021 - Elsevier
To alleviate the huge computing pressure caused by the single mobile edge server
computing mode as the amount of data increases, in this research, we propose a method to …

A deep reinforcement learning-based dynamic traffic offloading in space-air-ground integrated networks (SAGIN)

F Tang, H Hofner, N Kato, K Kaneko… - IEEE Journal on …, 2021 - ieeexplore.ieee.org
Space-Air-Ground Integrated Networks (SAGIN) is considered as the key structure of the
next generation network. The space satellites and air nodes are the potential candidates to …

DRL-R: Deep reinforcement learning approach for intelligent routing in software-defined data-center networks

W Liu, J Cai, QC Chen, Y Wang - Journal of Network and Computer …, 2021 - Elsevier
Data-center networks (DCN) possess multiple new features: coexistence of elephant
flow/mice flow/coflow, and coexistence of multiple network resources (bandwidth, cache and …

Lightweight automatic modulation classification based on decentralized learning

X Fu, G Gui, Y Wang, T Ohtsuki… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Due to the implementation and performance limitations of centralized learning automatic
modulation classification (CentAMC) method, this paper proposes a decentralized learning …

MD-GAN-based UAV trajectory and power optimization for cognitive covert communications

Z Li, X Liao, J Shi, L Li, P Xiao - IEEE internet of things journal, 2021 - ieeexplore.ieee.org
This article investigates the covert performance of an unmanned aerial vehicle (UAV)
jammer-assisted cognitive radio (CR) network. In particular, the covert transmission of …

A perspective on 6G: Requirement, technology, enablers, challenges and future road map

PP Ray - Journal of Systems Architecture, 2021 - Elsevier
Mobile network operators are at the verge of distribution and allotment of existing mobile
communications with 5G. It is a high time that we should be focused on the forthcoming sixth …

Bringing fairness to actor-critic reinforcement learning for network utility optimization

J Chen, Y Wang, T Lan - IEEE INFOCOM 2021-IEEE …, 2021 - ieeexplore.ieee.org
Fairness is a crucial design objective in virtually all network optimization problems, where
limited system resources are shared by multiple agents. Recently, reinforcement learning …