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Fengxiao Tang
Fengxiao Tang
tohoku university, central south university
Verified email at it.is.tohoku.ac.jp
Title
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Cited by
Year
State-of-the-art deep learning: Evolving machine intelligence toward tomorrow’s intelligent network traffic control systems
ZM Fadlullah, F Tang, B Mao, N Kato, O Akashi, T Inoue, K Mizutani
IEEE Communications Surveys & Tutorials 19 (4), 2432-2455, 2017
9352017
6G: Opening new horizons for integration of comfort, security, and intelligence
G Gui, M Liu, F Tang, N Kato, F Adachi
IEEE Wireless Communications 27 (5), 126-132, 2020
6642020
Future intelligent and secure vehicular network toward 6G: Machine-learning approaches
F Tang, Y Kawamoto, N Kato, J Liu
Proceedings of the IEEE 108 (2), 292-307, 2019
5722019
The deep learning vision for heterogeneous network traffic control: Proposal, challenges, and future perspective
N Kato, ZM Fadlullah, B Mao, F Tang, O Akashi, T Inoue, K Mizutani
IEEE wireless communications 24 (3), 146-153, 2016
4582016
Ten challenges in advancing machine learning technologies toward 6G
N Kato, B Mao, F Tang, Y Kawamoto, J Liu
IEEE Wireless Communications 27 (3), 96-103, 2020
3882020
Optimizing space-air-ground integrated networks by artificial intelligence
N Kato, ZM Fadlullah, F Tang, B Mao, S Tani, A Okamura, J Liu
IEEE Wireless Communications 26 (4), 140-147, 2019
3842019
Routing or computing? The paradigm shift towards intelligent computer network packet transmission based on deep learning
B Mao, ZM Fadlullah, F Tang, N Kato, O Akashi, T Inoue, K Mizutani
IEEE Transactions on Computers 66 (11), 1946-1960, 2017
3782017
On removing routing protocol from future wireless networks: A real-time deep learning approach for intelligent traffic control
F Tang, B Mao, ZM Fadlullah, N Kato, O Akashi, T Inoue, K Mizutani
IEEE Wireless Communications 25 (1), 154-160, 2017
2862017
AC-POCA: Anticoordination game based partially overlapping channels assignment in combined UAV and D2D-based networks
F Tang, ZM Fadlullah, N Kato, F Ono, R Miura
IEEE Transactions on Vehicular Technology 67 (2), 1672-1683, 2017
2732017
An intelligent traffic load prediction-based adaptive channel assignment algorithm in SDN-IoT: A deep learning approach
F Tang, ZM Fadlullah, B Mao, N Kato
IEEE Internet of Things Journal 5 (6), 5141-5154, 2018
2722018
The Roadmap of Communication and Networking in 6G for the Metaverse
F Tang, X Chen, M Zhao, N Kato
IEEE Wireless Communications 30 (4), 72-81, 2022
2472022
AI models for green communications towards 6G
B Mao, F Tang, Y Kawamoto, N Kato
IEEE Communications Surveys & Tutorials 24 (1), 210-247, 2021
1802021
Comprehensive survey on machine learning in vehicular network: Technology, applications and challenges
F Tang, B Mao, N Kato, G Gui
IEEE Communications Surveys & Tutorials 23 (3), 2027-2057, 2021
1702021
Deep reinforcement learning for dynamic uplink/downlink resource allocation in high mobility 5G HetNet
F Tang, Y Zhou, N Kato
IEEE Journal on selected areas in communications 38 (12), 2773-2782, 2020
1622020
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, N Kato
IEEE Communications Surveys & Tutorials 23 (3), 1578-1598, 2021
1502021
Optimizing computation offloading in satellite-UAV-served 6G IoT: A deep learning approach
B Mao, F Tang, Y Kawamoto, N Kato
Ieee Network 35 (4), 102-108, 2021
1392021
On a novel deep-learning-based intelligent partially overlapping channel assignment in SDN-IoT
F Tang, B Mao, ZM Fadlullah, N Kato
IEEE Communications Magazine 56 (9), 80-86, 2018
1322018
A novel non-supervised deep-learning-based network traffic control method for software defined wireless networks
B Mao, F Tang, ZM Fadlullah, N Kato, O Akashi, T Inoue, K Mizutani
IEEE Wireless Communications 25 (4), 74-81, 2018
1292018
An intelligent route computation approach based on real-time deep learning strategy for software defined communication systems
B Mao, F Tang, ZM Fadlullah, N Kato
IEEE Transactions on Emerging Topics in Computing 9 (3), 1554-1565, 2019
1192019
A deep reinforcement learning-based dynamic traffic offloading in space-air-ground integrated networks (SAGIN)
F Tang, H Hofner, N Kato, K Kaneko, Y Yamashita, M Hangai
IEEE Journal on Selected Areas in Communications 40 (1), 276-289, 2021
982021
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