F
Felipe A. P. de Figueiredo
Researcher at Inatel
Publications - 67
Citations - 514
Felipe A. P. de Figueiredo is an academic researcher from Inatel. The author has contributed to research in topics: MIMO & Computer science. The author has an hindex of 10, co-authored 56 publications receiving 298 citations. Previous affiliations of Felipe A. P. de Figueiredo include State University of Campinas & Samsung.
Papers
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Journal ArticleDOI
Bit Error Probability for Large Intelligent Surfaces Under Double-Nakagami Fading Channels
Ricardo Coelho Ferreira,Michelle S. P. Facina,Felipe A. P. de Figueiredo,Gustavo Fraidenraich,Eduardo Rodrigues de Lima +4 more
TL;DR: This work presents an accurate approximation and upper bounds for the bit error rate of the probability distribution function of the channel fading between a base station, an array of intelligent reflecting elements, known as large intelligent surfaces (LIS), and a single-antenna user.
Journal ArticleDOI
Channel Estimation for Massive MIMO TDD Systems Assuming Pilot Contamination and Frequency Selective Fading
TL;DR: This paper presents a simple and practical channel estimator for multipath multi-cell massive MIMO time division duplex systems with pilot contamination, which poses significant challenges to channel estimation.
Journal ArticleDOI
Channel estimation for massive MIMO TDD systems assuming pilot contamination and flat fading
TL;DR: A simple and practical channel estimator for multi-cell MU massive MIMO time division duplex (TDD) systems with pilot contamination in flat Rayleigh fading channels, which performs asymptotically as well as the minimum mean square error (MMSE) estimator with respect to the number of antennas.
Journal ArticleDOI
Large Intelligent Surfaces With Discrete Set of Phase-Shifts Communicating Through Double-Rayleigh Fading Channels
Felipe A. P. de Figueiredo,Michelle S. P. Facina,Ricardo Coelho Ferreira,Yun Ai,Rukhsana Ruby,Quoc-Viet Pham,Gustavo Fraidenraich +6 more
TL;DR: In this article, the performance of a single-input single-output (SISO) system in which an LIS acts as a controllable scatterer is evaluated.
Journal ArticleDOI
Deep Learning-Based Spectrum Prediction Collision Avoidance for Hybrid Wireless Environments
Ruben Mennes,Maxim Claeys,Felipe A. P. de Figueiredo,Irfan Jabandzic,Ingrid Moerman,Steven Latre +5 more
TL;DR: Spectrum Prediction Collision Avoidance (SPCA) is presented, an algorithm that can predict the behavior of other surrounding networks, by using supervised deep learning; and adapt its behavior to increase the overall throughput of both its own Multiple Frequencies Time Division Multiple Access network as well as that of the other neighboring networks.