15 citations · 59 across the 14 of their papers we have counts for
11 papers · 1 filter
Millimeter Wave Communications on Overhead Messenger Wire: Deep Reinforcement Learning-Based Predictive Beam Tracking
Yusuke Koda, Masao Shinzaki, Koji Yamamoto +5
This paper discusses the feasibility of beam tracking against dynamics in millimeter wave (mmWave) nodes placed on overhead messenger wires, including wind-forced perturbations and…
MAB-based Client Selection for Federated Learning with Uncertain Resources in Mobile Networks
Naoya Yoshida, Takayuki Nishio, Masahiro Morikura +1
This paper proposes a client selection method for federated learning (FL) when the computation and communication resource of clients cannot be estimated; the method trains a machin…
Online Trainable Wireless Link Quality Prediction System using Camera Imagery
Sohei Itahara, Takayuki Nishio, Masahiro Morikura +1
Machine-learning-based prediction of future wireless link quality is an emerging technique that can potentially improve the reliability of wireless communications, especially at hi…
Distillation-Based Semi-Supervised Federated Learning for Communication-Efficient Collaborative Training with Non-IID Private Data
Sohei Itahara, Takayuki Nishio, Yusuke Koda +2
This study develops a federated learning (FL) framework overcoming largely incremental communication costs due to model sizes in typical frameworks without compromising model perfo…
Distributed Heteromodal Split Learning for Vision Aided mmWave Received Power Prediction
Yusuke Koda, Jihong Park, Mehdi Bennis +3
The goal of this work is the accurate prediction of millimeter-wave received power leveraging both radio frequency (RF) signals and heterogeneous visual data from multiple distribu…
Transfer Learning-Based Received Power Prediction with Ray-tracing Simulation and Small Amount of Measurement Data
Masahiro Iwasaki, Takayuki Nishio, Masahiro Morikura +1
This paper proposes a method to predict received power in urban area deterministically, which can learn a prediction model from small amount of measurement data by a simulation-aid…