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About

About

Helder Fontes received the MSc degree in 2010 and Ph.D. degree in 2019, both in Informatics Engineering at the Faculty of Engineering of the University of Porto, Portugal. He is the coordinator of the Wireless Networks (WiN) area at INESC TEC and since 2009 he has participated in multiple national and EU research projects, including SITMe, HiperWireless, FP7 SUNNY, H2020 ResponDrone, DECARBONIZE, FLY.PT and Fed4FIRE+ SIMBED, SIMBED+ and SMART open call projects. He has been advisor of 10+ MSc theses on wireless networking simulation, emulation, and experimentation. His research interests include wireless networking simulation, emulation, and experimentation in the scope of emerging scenarios such as airborne and maritime, with special focus on repeatability and reproducibility of experiments using digital twins of wireless testbeds.

Interest
Topics
Details

Details

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Publications

2022

Machine Learning Based Propagation Loss Module for Enabling Digital Twins of Wireless Networks in ns-3

Authors
Almeida, EN; Rushad, M; Kota, SR; Nambiar, A; Harti, HL; Gupta, C; Waseem, D; Santos, G; Fontes, H; Campos, R; Tahiliani, MP;

Publication
WNS3 2022: 2022 Workshop on ns-3, Virtual Event, USA, June 22 - 23, 2022

Abstract

2022

ResponDrone - A Situation Awareness Platform for First Responders

Authors
Friedrich, M; Lieb, TJ; Temme, A; Almeida, EN; Coelho, A; Fontes, H;

Publication
AIAA/IEEE Digital Avionics Systems Conference - Proceedings

Abstract

2022

An Algorithm for Placing and Allocating Communications Resources Based on Slicing-aware Flying Access and Backhaul Networks

Authors
Coelho, A; Rodrigues, J; Fontes, H; Campos, R; Ricardo, M;

Publication
IEEE ACCESS

Abstract

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

2021

Reproducible MIMO operation in ns-3 using trace-based wi-fi rate adaptation

Authors
Lamela, V; Fontes, H; Ruela, J; Ricardo, M; Campos, R;

Publication
WNS3 2021: 2021 Workshop on ns-3, Virtual Event, USA

Abstract
Today, wireless networks are operating in increasingly complex environments, impacting the evaluation and validation of new networking solutions. Simulation, although fully controllable and easily reproducible, depends on simplified physical layer and channel models, which often produce optimistic results. Experimentation is also influenced by external random phenomena and limited testbed scale and availability, resulting in hardly repeatable and reproducible results. Previously, we have proposed the Trace-based Simulation (TS) approach to address the problem. TS uses traces of radio link quality and position of nodes to accurately reproduce past experiments in ns-3. Yet, in its current version, TS is not compatible with scenarios where Multiple-In-Multiple-Out (MIMO) is used. This is especially relevant since ns-3 assumes perfectly independent MIMO radio streams. In this paper, we introduce the Trace-based Wi-Fi Station Manager Model, which is capable of reproducing the Rate Adaptation of past Wi-Fi experiments, including the number of effective radio streams used. To validate the proposed model, the network throughput was measured in different experiments performed in the w-iLab.t testbed, considering Single-In-Single-Out (SISO) and MIMO operation using IEEE 802.11a/n/ac standards. The experimental results were then compared with the network throughput achieved using the improved TS and Pure Simulation (PS) approaches, validating the new proposed model and confirming its relevance to reproduce experiments previously executed in real environments. © 2021 ACM.

Supervised
thesis

2022

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

Author
José Manuel de Sousa Magalhães

Institution
UP-FEUP

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

Data-driven Traffic Generation Model for Digital Twins of Wireless Networks

Author
Catarina Mouro de Sousa

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