activity
20202024
most citedMachine Learning-Based mmWave MIMO Beam Tracking in V2I Scenarios: Algorithms and Datasets

8 citations · 14 across the 4 of their papers we have counts for

collaborators
Showing eess.SPShow all

5 papers · 1 filter

eess.SP2025

DL-Based Beam Management for mmWave Vehicular Networks Exploring Temporal Correlation

Ailton Oliveira, Amir Khatibi, Daniel Suzuki +3

Millimeter wave communications are essential for modern wireless networks. It supports high data rates but suffers from severe path loss, which requires precise beam alignment to m…

eess.SP20248 cited

Machine Learning-Based mmWave MIMO Beam Tracking in V2I Scenarios: Algorithms and Datasets

Ailton Oliveira, Daniel Suzuki, Sávio Bastos +2

This work investigates the use of machine learning applied to the beam tracking problem in 5G networks and beyond. The goal is to decrease the overhead associated to MIMO millimete…

eess.SP20226 cited

Simulation of machine learning-based 6G systems in virtual worlds

Ailton Oliveira, Felipe Bastos, Isabela Trindade +5

Digital representations of the real world are being used in many applications, such as augmented reality. 6G systems will not only support use cases that rely on virtual worlds but…

eess.SP2021

Generating MIMO Channels For 6G Virtual Worlds Using Ray-tracing Simulations

Aldebaro Klautau, Ailton de Oliveira, Isabela Pamplona Trindade +1

Some 6G use cases include augmented reality and high-fidelity holograms, with this information flowing through the network. Hence, it is expected that 6G systems can feed machine l…

eess.SP2020

Ray-Tracing 5G Channels from Scenarios with Mobility Control of Vehicles and Pedestrians

Ailton Oliveira, Marcus Dias, Isabela Trindade +1

Millimeter waves is one of 5G networks strategies to achieve high bit rates. Measurement campaigns with these signals are difficult and require expensive equipment. In order to gen…