8 citations · 22 across the 13 of their papers we have counts for
13 papers
VR-VFL: Joint Rate and Client Selection for Vehicular Federated Learning Under Imperfect CSI
Metehan Karatas, Subhrakanti Dey, Christian Rohner +1
Federated learning in vehicular edge networks faces major challenges in efficient resource allocation, largely due to high vehicle mobility and the presence of imperfect channel st…
Machine Learning for Spectrum Sharing: A Survey
Francisco R. V. Guimarães, José Mairton B. da Silva, Charles Casimiro Cavalcante +3
The 5th generation (5G) of wireless systems is being deployed with the aim to provide many sets of wireless communication services, such as low data rates for a massive amount of d…
Computing Functions Over-the-Air Using Digital Modulations
Saeed Razavikia, Jose Mairton Barros da Silva, Carlo Fischione
Over-the-air computation (AirComp) is a known technique in which wireless devices transmit values by analog amplitude modulation so that a function of these values is computed over…
Federated Learning Using Three-Operator ADMM
Shashi Kant, José Mairton B. da Silva, Gabor Fodor +3
Federated learning (FL) has emerged as an instance of distributed machine learning paradigm that avoids the transmission of data generated on the users' side. Although data are not…
Blind Asynchronous Over-the-Air Federated Edge Learning
Saeed Razavikia, Jaume Anguera Peris, Jose Mairton B. da Silva +1
Federated Edge Learning (FEEL) is a distributed machine learning technique where each device contributes to training a global inference model by independently performing local comp…
Simultaneous Wireless Information and Power Transfer for Federated Learning
José Mairton B. da Silva, Konstantinos Ntougias, Ioannis Krikidis +2
In the Internet of Things, learning is one of most prominent tasks. In this paper, we consider an Internet of Things scenario where federated learning is used with simultaneous tra…
Dynamic Clustering in Federated Learning
Yeongwoo Kim, Ezeddin Al Hakim, Johan Haraldson +3
In the resource management of wireless networks, Federated Learning has been used to predict handovers. However, non-independent and identically distributed data degrade the accura…
Full-Duplex and Dynamic-TDD: Pushing the Limits of Spectrum Reuse in Multi-Cell Communications
José Mairton B. da Silva, Gustav Wikström, Ratheesh K. Mungara +1
Although in cellular networks full-duplex and dynamic time-division duplexing promise increased spectrum efficiency, their potential is so far challenged by increased interference.…
Wireless for Machine Learning
Henrik Hellström, José Mairton B. da Silva, Mohammad Mohammadi Amiri +4
As data generation increasingly takes place on devices without a wired connection, machine learning (ML) related traffic will be ubiquitous in wireless networks. Many studies have…
How to Split UL/DL Antennas in Full-Duplex Cellular Networks
José Mairton B. da Silva, Hadi Ghauch, Gábor Fodor +1
To further improve the potential of full-duplex communications, networks may employ multiple antennas at the base station or user equipment. To this end, networks that employ curre…
On the Spectral Efficiency and Fairness in Full-Duplex Cellular Networks
Jose Mairton B. da Silva, Gabor Fodor, Carlo Fischione
To increase the spectral efficiency of wireless networks without requiring full-duplex capability of user devices, a potential solution is the recently proposed three-node full-dup…
Distributed Spectral Efficiency Maximization in Full-Duplex Cellular Networks
Jose Mairton B. da Silva, Yuzhe Xu, Gabor Fodor +1
Three-node full-duplex is a promising new transmission mode between a full-duplex capable wireless node and two other wireless nodes that use half-duplex transmission and reception…
Performance Analysis of Network-Assisted Two-Hop D2D Communications
Jose Mairton B. da Silva, Gabor Fodor, Tarcisio F. Maciel
Network-assisted single-hop device-to-device (D2D) communication can increase the spectral and energy efficiency of cellular networks by taking advantage of the proximity, reuse, a…