This paper proposes a decentralized FL scheme for IoE devices connected ...
This paper discusses the opportunity of bringing the concept of zero-sho...
This paper discusses the feasibility of beam tracking against dynamics i...
This paper proposes a client selection method for federated learning (FL...
Machine-learning-based prediction of future wireless link quality is an
...
This study develops a federated learning (FL) framework overcoming large...
The goal of this work is the accurate prediction of millimeter-wave rece...
This paper proposes a method to predict received power in urban area
det...
Federated learning (FL) enables a neural network (NN) to be trained usin...
Over-the-air computation (AirComp)-based federated learning (FL) enables...
This paper proposes a robust adversarial reinforcement learning (RARL)-b...
This paper proposes a radio channel selection algorithm based on a conte...
The goal of this study is to improve the accuracy of millimeter wave rec...
Focusing on the received power prediction of millimeter-wave (mmWave)
ra...
For reliable millimeter-wave (mmWave) networks, this paper proposes
coop...
A decentralized learning mechanism, Federated Learning (FL), has attract...
Last year, IEEE 802.11 Extremely High Throughput Study Group (EHT Study
...
For mmWave networks, this paper proposes an image-to-decision proactive
...
Sharing perceptual data with other vehicles enhances the traffic safety ...
In millimeter wave (mmWave) vehicular communications, multi-hop relay
di...
This paper discusses a machine-learning (ML)-based future received signa...
This paper provides the signal-to-interference-plus-noise ratio (SINR)
c...