activity
20182021
most citedLIDAR Data for Deep Learning-Based mmWave Beam-Selection

180 citations · 191 across the 12 of their papers we have counts for

collaborators

13 papers

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.SP2021

5G MIMO Data for Machine Learning: Application to Beam-Selection using Deep Learning

Aldebaro Klautau, Pedro Batista, Nuria Gonzalez-Prelcic +2

The increasing complexity of configuring cellular networks suggests that machine learning (ML) can effectively improve 5G technologies. Deep learning has proven successful in ML ta…

cs.NI2021★ 7 cited

System Intelligence for UAV-Based Mission Critical with Challenging 5G/B5G Connectivity

Cristiano Bonato Both, João Borges, Luan Gonçalves +4

Unmanned aerial vehicles (UAVs) and communication systems are fundamental elements in Mission Critical services, such as search and rescue. In this article, we introduce an archite…

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…

eess.SP2020★ 1 cited

Testbed for Connected Artificial Intelligence using Unmanned Aerial Vehicles and Convolutional Pose Machines

Diego Dantas, Carnot Braun, Kaio Forte +5

Unmanned Aerial Vehicles (UAVs) became very popular in a vast number of applications in recent years, especially drones with computer vision functions enabled by on-board cameras a…

eess.SP2020★ 2 cited

Virtualized C-RAN Orchestration with Docker, Kubernetes and OpenAirInterface

Camila Novaes, Cleverson Nahum, Igor Trindade +3

Virtualization is a key feature in Cloud Radio Access Network (C-RAN). It can help to save costs since it allows the use of virtualized base stations instead of physically deployme…

eess.SP2020

Downlink Fronthaul Compression in Frequency Domain using OpenAirInterface

Cleverson Nahum, Leonardo Ramalho, Joary Fortuna +4

This paper presents a compression scheme developed for the transport of downlink radio signals in packet fronthaul of centralized-radio access networks (C-RAN). The technique is ta…

eess.SP2019★ 1 cited

C-RAN Virtualization with OpenAirInterface

Igor Trindade, Cleverson Nahum, Camila Novaes +3

C-RAN virtualization is a research topic with great interest since it allows to share baseband processing resources.Therefore, in this work, we report the implementation of a virtu…

eess.SP2019

Evaluation of Simplified Methodology for Obtaining mmWave MIMO Channels from Ray-Tracing Simulations

Isabela Trindade, Brenda Vilas Boas, Aldebaro Klautau

The use of higher frequencies and MIMO is important in many 5G use cases. However, the available channel models for millimeter waves (mmWaves) currently demand investigation and th…

eess.SP2019

Development and Evaluation of Least Square Satellite Tracking in Real Antenna Control System

Thiago Sarmento, Andrey Nakamura, Itelo Filho +4

This work describes the implementation of a satellite tracking technique in a real antenna control system. The technique uses least squares estimation to search for the best antenn…

eess.SP2019

Tenant-Aware Slice Admission Control using Neural Networks-Based Policy Agent

Pedro Batista, Shah Nawaz Khan, Peter Öhlén +1

5G networks will provide the platform for deploying large number of tenant-associated management, control and end-user applications having different resource requirements at the in…

eess.SP2019★ 180 cited

LIDAR Data for Deep Learning-Based mmWave Beam-Selection

Aldebaro Klautau, Nuria González-Prelcic, Robert W. Heath

Millimeter wave communication systems can leverage information from sensors to reduce the overhead associated with link configuration. LIDAR (light detection and ranging) is one se…

eess.AS2018

Frequency Tracking: LMS and RLS Applied to Speech Formant Estimation (2000)

Aldebaro Klautau

Introduction Several speech processing algorithms assume the signal is stationary during short intervals (approximately 20 to 30 ms). This assumption is valid for several applicati…