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About

Rui Campos has a PhD degree in Electrical and Computers Engineering in 2011, from University of Porto. Currently, he leads the “Wireless Networks” research area (http://win.inescporto.pt) of the Centre for Telecommunications and Multimedia consisting of 30 researchers, and he is an IEEE Senior Member. He has coordinated several research projects, including: SIMBED in Fed4FIRE+ Open Call 3, UGREEN, BLUECOM+, MareCom, MTGrid, the WiFIX action approved in CONFINE Open Call 1, Mare-Fi, Under-Fi, ReCoop, and HiperWireless. Rui Campos has participated in several research projects, including the following European projects: H2020 Fed4FIRE+, H2020 RAWFIE, FP7 SUNNY, FP7 CONFINE, FP6 Ambient Networks Phase 1, and FP6 Ambient Networks Phase 2. His research interests include medium access control, radio resource management, mobility management, and network auto-configuration in emerging wireless networks, with special focus on flying networks, maritime networks, and underwater networks.

Interest
Topics
Details

Details

033
Publications

2021

Joint Traffic-Aware UAV Placement and Predictive Routing for Aerial Networks

Authors
Almeida, EN; Coelho, A; Ruela, J; Campos, R; Ricardo, M;

Publication
CoRR

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
ACM International Conference Proceeding Series

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.

2021

Traffic-aware Gateway Placement for High-capacity Flying Networks

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

Publication
2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring)

Abstract

2021

A Fast Gateway Placement Algorithm for Flying Networks

Authors
Santos, G; Martins, J; Coelho, A; Ricardo, M; Campos, R;

Publication
CoRR

Abstract

2020

Height Optimization in Aerial Networks for Enhanced Broadband Communications at Sea

Authors
Teixeira, FB; Campos, R; Ricardo, M;

Publication
IEEE Access

Abstract

Supervised
thesis

2020

Topology Control of Flying Backhaul Mesh Networks

Author
Eduardo Nuno Moreira Soares de Almeida

Institution
UP-FEUP

2020

Centralized Routing for Flying Backhaul Networks

Author
André Filipe Coelho

Institution
UP-FEUP

2020

Multi-technology Flying Access Network for Disaster Management Scenarios

Author
Rúben Miguel Rei Queirós

Institution
INESCTEC

2020

Multi-Technology Flying Access Network for Disaster Management Scenarios

Author
Rúben Miguel Rei Queirós

Institution
INESCTEC

2020

Trace-based ns3-gym Reinforcement Learning Environment Framework for Wireless Networks

Author
Gonçalo Regueiras dos Santos

Institution
UP-FEUP