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About

About

Rúben Queirós completed in 2020 The MSc degree in Electrical and Computer Engineering at the Faculty of Engineering of the University of Porto, Portugal. He is currently a PhD candidate in the Doctoral Program of Electrical and Computer Engineering, in the same institution. He has been an Assistant Researcher at INESC TEC since 2020, in the area of Wireless Networks (WiN). He has participated in the SMART open call project and the EU research project InterConnect. His research interests include Wi-Fi, Rate Adaptation, Reinforcement Learning and Flying Networks.

Interest
Topics
Details

Details

001
Publications

2022

Wi-Fi Rate Adaptation using a Simple Deep Reinforcement Learning Approach

Authors
Queiros, R; Almeida, EN; Fontes, H; Ruela, J; Campos, R;

Publication
2022 27TH IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (IEEE ISCC 2022)

Abstract
The increasing complexity of recent Wi-Fi amendments is making optimal Rate Adaptation (RA) a challenge. The use of classic algorithms or heuristic models to address RA is becoming unfeasible due to the large combination of configuration parameters along with the variability of the wireless channel. We propose a simple Deep Reinforcement Learning approach for the automatic RA in Wi-Fi networks, named Data-driven Algorithm for Rate Adaptation (DARA). DARA is standard-compliant. It dynamically adjusts the Wi-Fi Modulation and Coding Scheme (MCS) solely based on the observation of the Signal-to-Noise Ratio (SNR) of the received frames at the transmitter. Our simulation results show that DARA achieves higher throughput when compared with Minstrel High Throughput (HT)

Supervised
thesis

2022

Utilização de Reinforcement Learning para otimização de ligações Wi-Fi no contexto de redes voadoras

Author
Gabriella Fernandes Pantaleão

Institution
UP-FEUP

2022

On the Performance Impact of Computational Delays of RL-Based Networking Algorithms through Improved ns-3 Digital Twins

Author
João Paulo Ferreira Pinto

Institution
UP-FEUP

2022

Analysis and Optimisation of Computational Delays in Reinforcement Learning-based Wi-Fi Rate Adaptation

Author
Ricardo Jorge Espirito Santo Trancoso

Institution
UP-FEUP

2022

Using Deep Reinforcement Learning Techniques to Optimize the Throughput of Wi-Fi Links

Author
Héber Miguel Severino Ribeiro

Institution
UP-FEUP

2022

Rate Adaptation Algorithm using Reinforcement Learning for Delay Minimisation in a Wi-Fi Link

Author
José Manuel de Sousa Magalhães

Institution
UP-FEUP