56 citations · 67 across the 9 of their papers we have counts for
9 papers
High-Speed Resource Allocation Algorithm Using a Coherent Ising Machine for NOMA Systems
Teppei Otsuka, Aohan Li, Hiroki Takesue +3
Non-orthogonal multiple access (NOMA) technique is important for achieving a high data rate in next-generation wireless communications. A key challenge to fully utilizing the effec…
Pairing optimization via statistics: Algebraic structure in pairing problems and its application to performance enhancement
Naoki Fujita, André Röhm, Takatomo Mihana +4
Fully pairing all elements of a set while attempting to maximize the total benefit is a combinatorically difficult problem. Such pairing problems naturally appear in various situat…
A Lightweight Transmission Parameter Selection Scheme Using Reinforcement Learning for LoRaWAN
Aohan Li, Ikumi Urabe, Minoru Fujisawa +4
The number of IoT devices is predicted to reach 125 billion by 2023. The growth of IoT devices will intensify the collisions between devices, degrading communication performance. S…
Theory of Acceleration of Decision Making by Correlated Time Sequences
Norihiro Okada, Tomoki Yamagami, Nicolas Chauvet +3
Photonic accelerators have been intensively studied to provide enhanced information processing capability to benefit from the unique attributes of physical processes. Recently, it…
Efficient Pairing in Unknown Environments: Minimal Observations and TSP-based Optimization
Naoki Fujita, Nicolas Chauvet, Andre Roehm +4
Generating paired sequences with maximal compatibility from a given set is one of the most important challenges in various applications, including information and communication tec…
Resource allocation method using tug-of-war-based synchronization
Song-Ju Kim, Hiroyuki Yasuda, Ryoma Kitagawa +1
We propose a simple channel-allocation method based on tug-of-war (TOW) dynamics, combined with the time scheduling based on nonlinear oscillator synchronization to efficiently use…
Arm order recognition in multi-armed bandit problem with laser chaos time series
Naoki Narisawa, Nicolas Chauvet, Mikio Hasegawa +1
By exploiting ultrafast and irregular time series generated by lasers with delayed feedback, we have previously demonstrated a scalable algorithm to solve multi-armed bandit (MAB)…
Dynamic channel selection in wireless communications via a multi-armed bandit algorithm using laser chaos time series
Shungo Takeuchi, Mikio Hasegawa, Kazutaka Kanno +3
Dynamic channel selection is among the most important wireless communication elements in dynamically changing electromagnetic environments wherein a user can experience improved co…
Scalable photonic reinforcement learning by time-division multiplexing of laser chaos
Makoto Naruse, Takatomo Mihana, Hirokazu Hori +4
Reinforcement learning involves decision making in dynamic and uncertain environments and constitutes a crucial element of artificial intelligence. In our previous work, we experim…