Hirotaka Asano
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Hirotaka Asano has a total of 5 co-authors. Here are the top co-authors by number of shared publications:
- Maki Arai
College of Engineering, Shibaura Institute of Technology
2 shared publications - Mikio Hasegawa
Department of Electrical Engineering, Tokyo University of Science, Tokyo, Japan
2 shared publications - Haruto Ando
Department of Electrical Engineering, Tokyo University of Science
1 shared publication - Jin Nakazato
Tokyo University of Science, Tokyo, Japan
1 shared publication - Takatomo Mihana
Department of Information Physics and Computing, Graduate School of Information Science and Technology, The University of Tokyo
1 shared publication
Latest Publications
- 1 January 2026
- Published by Institute of Electronics, Information and Communications Engineers (IEICE) in Nonlinear Theory and Its Applications, IEICE
- Vol. 17 (3) , 1263-1273
Dynamic wireless resource allocation using ultra-high-speed decision making via laser networks
- 1 January 2026
- Published by Institute of Electronics, Information and Communications Engineers (IEICE) in Nonlinear Theory and Its Applications, IEICE
- Vol. 17 (3) , 1263-1273
Dynamic wireless resource allocation using ultra-high-speed decision making via laser networks
- Open Access
- 1 January 2025
- Published by Institute of Electronics, Information and Communications Engineers (IEICE) in Nonlinear Theory and Its Applications, IEICE
- Vol. 16 (3) , 495-505
Fast beam tracking in Massive MIMO by Laser Chaos Decision Maker
Massive MIMO (Multiple Input Multiple Output) requires appropriate beam management to prevent misalignment, which leads to significant array gain degradation. In this paper, we propose a method to apply Laser Chaos Decision Maker to beam alignment in order to achieve fast beam management, especially when the communication channel environment changes rapidly. In addition, we proposed a method to speed up the decision-making process by dividing a two-dimensional beam into two components for beam selection. Simulation results show that the proposed method provides higher average channel capacity than other beam selection methods in an environment where users move at high speed.
- 1 January 2025
- Published by Institute of Electronics, Information and Communications Engineers (IEICE) in Nonlinear Theory and Its Applications, IEICE
- Vol. 16 (3) , 495-505
Open AccessFast beam tracking in Massive MIMO by Laser Chaos Decision Maker
Massive MIMO (Multiple Input Multiple Output) requires appropriate beam management to prevent misalignment, which leads to significant array gain degradation. In this paper, we propose a method to apply Laser Chaos Decision Maker to beam alignment in order to achieve fast beam management, especially when the communication channel environment changes rapidly. In addition, we proposed a method to speed up the decision-making process by dividing a two-dimensional beam into two components for beam selection. Simulation results show that the proposed method provides higher average channel capacity than other beam selection methods in an environment where users move at high speed.