A Channel Selection Algorithm Using Reinforcement Learning for Mobile Devices in Massive IoT System

被引:1
作者
Furukawa, Honami [1 ]
Li, Aohan [1 ]
Shoji, Yozo [2 ]
Watanabe, Yoshito [2 ]
Kim, Song-Ju [3 ]
Sato, Koya [1 ]
Andreopoulos, Yiannis [4 ]
Hasegawa, Mikio [1 ]
机构
[1] Tokyo Univ Sci, Dept Elect Engn, Tokyo, Japan
[2] Natl Inst Informat & Commun Technol, Social ICT Syst Lab, Tokyo, Japan
[3] Keio Univ, Grad Sch Media & Governance, Fujisawa, Kanagawa, Japan
[4] Univ Coll London UCL, Dept Elect & Elect Engn, London, England
来源
2021 IEEE 18TH ANNUAL CONSUMER COMMUNICATIONS & NETWORKING CONFERENCE (CCNC) | 2021年
关键词
D O I
10.1109/CCNC49032.2021.9369474
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
引用
收藏
页数:2
相关论文
共 4 条
[1]  
Hasegawa S., 2020, ICAIIC2020
[2]   Efficient decision-making by volume-conserving physical object [J].
Kim, Song-Ju ;
Aono, Masashi ;
Nameda, Etsushi .
NEW JOURNAL OF PHYSICS, 2015, 17
[3]   Amoeba-inspired algorithm for cognitive medium access [J].
Kima, Song-Ju ;
Aono, Masashi .
IEICE NONLINEAR THEORY AND ITS APPLICATIONS, 2014, 5 (02) :198-209
[4]   A Reinforcement-Learning-Based Distributed Resource Selection Algorithm for Massive IoT [J].
Ma, Jing ;
Hasegawa, So ;
Kim, Song-Ju ;
Hasegawa, Mikio .
APPLIED SCIENCES-BASEL, 2019, 9 (18)