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About

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

2023

Traffic-aware gateway placement and queue management in flying networks

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

Publication
AD HOC NETWORKS

Abstract
Unmanned Aerial Vehicles (UAVs) have emerged as adequate platforms to carry communications nodes, including Wi-Fi Access Points and cellular Base Stations. This has led to the concept of flying networks composed of UAVs as a flexible and agile solution to provide on-demand wireless connectivity anytime, anywhere. However, state of the art works have been focused on optimizing the placement of the access network providing connectivity to ground users, overlooking the backhaul network design. In order to improve the overall Quality of Service (QoS) offered to ground users, the placement of Flying Gateways (FGWs) and the size of the queues configured in the UAVs need to be carefully defined to meet strict performance requirements. The main contribution of this article is a traffic-aware gateway placement and queue management (GPQM) algorithm for flying networks. GPQM takes advantage of knowing in advance the positions of the UAVs and their traffic demand to determine the FGW position and the queue size of the UAVs, in order to maximize the aggregate throughput and provide stochastic delay guarantees. GPQM is evaluated by means of ns-3 simulations, considering a realistic wireless channel model. The results demonstrate significant gains in the QoS offered when GPQM is used.

2023

On the Analysis of Computational Delays in Reinforcement Learning-based Rate Adaptation Algorithms

Authors
Trancoso, R; Queirós, R; Fontes, H; Campos, R;

Publication
CoRR

Abstract

2023

Wireless technologies towards 6G

Authors
Campos, R; Ricardo, M; Pouttu, A; Correia, LM;

Publication
EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING

Abstract
This Special Issue originates from the international conference 2021 Joint EuCNC & 6G Summit (Joint European Conference on Networks and Communications and 6G Summit), which was held in June 2021 in virtual format. The Technical Programme Chairs of the conference selected the best papers and invited authors to submit an extended version of their paper by at least one-third of their length. Only the top ranked papers were invited to this Special Issue, in order to fulfil its purpose. The main target was to collect and present quality research contributions in the most recent activities related to technologies, systems and networks beyond 5G. Through this Special Issue, the state-of-the-art is presented and the new challenges highlighted, regarding the latest advances on systems and network perspectives that are already being positioned beyond 5G, bridging as well with the evolution of 5G, including applications and trials. Therefore, the motivation for this Special Issue is to present the latest and finest results on the evolution of research of mobile and wireless communications, coming, but not exclusively (since Joint EuCNC & 6G Summit is a conference open to the whole research community), from projects co-financed by the European Commission within its R&D programmes.

2023

Wireless technologies towards 6G

Authors
Campos, R; Ricardo, M; Pouttu, A; Correia, LM;

Publication
EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING

Abstract
This Special Issue originates from the international conference 2021 Joint EuCNC & 6G Summit (Joint European Conference on Networks and Communications and 6G Summit), which was held in June 2021 in virtual format. The Technical Programme Chairs of the conference selected the best papers and invited authors to submit an extended version of their paper by at least one-third of their length. Only the top ranked papers were invited to this Special Issue, in order to fulfil its purpose. The main target was to collect and present quality research contributions in the most recent activities related to technologies, systems and networks beyond 5G. Through this Special Issue, the state-of-the-art is presented and the new challenges highlighted, regarding the latest advances on systems and network perspectives that are already being positioned beyond 5G, bridging as well with the evolution of 5G, including applications and trials. Therefore, the motivation for this Special Issue is to present the latest and finest results on the evolution of research of mobile and wireless communications, coming, but not exclusively (since Joint EuCNC & 6G Summit is a conference open to the whole research community), from projects co-financed by the European Commission within its R&D programmes.

2023

Position-Based Machine Learning Propagation Loss Model Enabling Fast Digital Twins of Wireless Networks in ns-3

Authors
Almeida, EN; Fontes, H; Campos, R; Ricardo, M;

Publication
PROCEEDINGS OF THE 2023 WORKSHOP ON NS-3, WNS3 2023

Abstract
Digital twins have been emerging as a hybrid approach that combines the benefits of simulators with the realism of experimental testbeds. The accurate and repeatable set-ups replicating the dynamic conditions of physical environments, enable digital twins of wireless networks to be used to evaluate the performance of next-generation networks. In this paper, we propose the Position-based Machine Learning Propagation Loss Model (P-MLPL), enabling the creation of fast and more precise digital twins of wireless networks in ns-3. Based on network traces collected in an experimental testbed, the P-MLPL model estimates the propagation loss suffered by packets exchanged between a transmitter and a receiver, considering the absolute node's positions and the traffic direction. The P-MLPL model is validated with a test suite. The results show that the P-MLPL model can predict the propagation loss with a median error of 2.5 dB, which corresponds to 0.5x the error of existing models in ns-3. Moreover, ns-3 simulations with the P-MLPL model estimated the throughput with an error up to 2.5 Mbit/s, when compared to the real values measured in the testbed.

Supervised
thesis

2022

Traffic-aware Management of Communications Resources in Flying Networks

Author
André Filipe Pinto Coelho

Institution
UP-FEUP

2022

Topology Control of Flying Backhaul Mesh Networks

Author
Eduardo Nuno Moreira Soares de Almeida

Institution
UP-FEUP

2022

A MAC Layer for Underwater Radio Communications

Author
Filipe Borges Teixeira

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

Slicing-Aware Flying Communications Network

Author
João Cristiano Mourão Rodrigues

Institution
UP-FEUP