Koji Yamamoto
Koji Yamamoto
Graduate School of Informatics, Kyoto University
Verified email at - Homepage
Cited by
Cited by
Optimal transmission scheduling for a hybrid of full-and half-duplex relaying
K Yamamoto, K Haneda, H Murata, S Yoshida
IEEE Communications Letters 15 (3), 305-307, 2011
A comprehensive survey of potential game approaches to wireless networks
K Yamamoto
IEICE Transactions on Communications, 1804-1823, 2015
Hybrid-FL for wireless networks: Cooperative learning mechanism using non-IID data
N Yoshida, T Nishio, M Morikura, K Yamamoto, R Yonetani
ICC 2020-2020 IEEE International Conference on Communications (ICC), 1-7, 2020
Treatment of Alzheimer-type dementia with intravenous mecobalamin
T Ikeda, K Yamamoto, K Takahashi, Y Kaku, M Uchiyama, K Sugiyama, ...
Clinical therapeutics 14 (3), 426-437, 1992
IEEE 802.11 ah based M2M networks employing virtual grouping and power saving methods
K Ogawa, M Morikura, K Yamamoto, T Sugihara
IEICE Transactions on Communications 96 (12), 2976-2985, 2013
Distillation-based semi-supervised federated learning for communication-efficient collaborative training with non-iid private data
S Itahara, T Nishio, Y Koda, M Morikura, K Yamamoto
arXiv preprint arXiv:2008.06180, 2020
Proactive received power prediction using machine learning and depth images for mmWave networks
T Nishio, H Okamoto, K Nakashima, Y Koda, K Yamamoto, M Morikura, ...
IEEE Journal on Selected Areas in Communications 37 (11), 2413-2427, 2019
Tradeoff between area spectral efficiency and end-to-end throughput in rate-adaptive multihop radio networks
K Yamamoto, S Yoshida
IEICE transactions on communications 88 (9), 3532-3540, 2005
Impact of shadowing correlation on coverage of multihop cellular systems
K Yamamoto, A Kusuda, S Yoshida
2006 IEEE International Conference on Communications 10, 4538-4542, 2006
Deep reinforcement learning-based channel allocation for wireless lans with graph convolutional networks
K Nakashima, S Kamiya, K Ohtsu, K Yamamoto, T Nishio, M Morikura
IEEE Access 8, 31823-31834, 2020
Hybrid-fl: Cooperative learning mechanism using non-iid data in wireless networks
N Yoshida, T Nishio, M Morikura, K Yamamoto, R Yonetani
arXiv preprint arXiv:1905.07210, 2019
Reinforcement learning based predictive handover for pedestrian-aware mmWave networks
Y Koda, K Yamamoto, T Nishio, M Morikura
IEEE INFOCOM 2018-IEEE Conference on Computer Communications Workshops …, 2018
Handover management for mmwave networks with proactive performance prediction using camera images and deep reinforcement learning
Y Koda, K Nakashima, K Yamamoto, T Nishio, M Morikura
IEEE Transactions on Cognitive Communications and Networking 6 (2), 802-816, 2019
Machine-learning-based throughput estimation using images for mmWave communications
H Okamoto, T Nishio, M Morikura, K Yamamoto, D Murayama, K Nakahira
2017 IEEE 85th Vehicular Technology Conference (VTC Spring), 1-6, 2017
Performance comparison between channel-bonding and multi-channel CSMA
L Xu, K Yamamoto, S Yoshida
2007 IEEE Wireless Communications and Networking Conference, 406-410, 2007
Differentially private aircomp federated learning with power adaptation harnessing receiver noise
Y Koda, K Yamamoto, T Nishio, M Morikura
GLOBECOM 2020-2020 IEEE Global Communications Conference, 1-6, 2020
Proactive base station selection based on human blockage prediction using RGB-D cameras for mmWave communications
Y Oguma, R Arai, T Nishio, K Yamamoto, M Morikura
2015 IEEE Global Communications Conference (GLOBECOM), 1-6, 2015
Analysis and design specifications for full-duplex radio transceivers under RF oscillator phase noise with arbitrary spectral shape
V Syrjälä, K Yamamoto, M Valkama
IEEE Transactions on Vehicular Technology 65 (8), 6782-6788, 2015
Analysis of reverse link capacity enhancement for CDMA cellular systems using two-hop relaying
IEICE transactions on fundamentals of electronics, communications and …, 2004
Proactive handover based on human blockage prediction using RGB-D cameras for mmWave communications
Y Oguma, T Nishio, K Yamamoto, M Morikura
IEICE Transactions on Communications 99 (8), 1734-1744, 2016
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