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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

029
Publications

2023

Traffic-aware Gateway Placement and Queue Management in Flying Networks

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

Publication
AD HOC NETWORKS

Abstract

2022

Joint Energy and Performance Aware Relay Positioning in Flying Networks

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

Publication
IEEE ACCESS

Abstract
<p>Unmanned Aerial Vehicles (UAVs) have emerged as suitable platforms for transporting and positioning communications nodes on demand, including Wi-Fi Access Points and cellular Base Stations. This paved the way for the deployment of flying networks capable of temporarily providing wireless connectivity and reinforcing the coverage and capacity of existing networks anywhere, anytime. Several solutions have been proposed in the literature for the positioning of UAVs that act as Flying Access Points (FAPs). Yet, the positioning of Flying Communications Relays (FCRs) in charge of forwarding the traffic to/from the Internet has not received equal attention. A major challenge in flying networks is the UAVs endurance. Since the UAVs are typically powered by on-board batteries with limited capacity, whose energy is used for communications and propulsion, the UAVs need to land frequently for recharging or replacing their batteries, limiting the flying network availability. State of the art works are focused on optimizing both the flying network performance and the energy-efficiency from the communications point of view, but do not consider the energy spent for the UAV propulsion. Yet, the energy spent for communications is typically negligible when compared with the energy spent for the UAV propulsion.</p><p>In order to address the FCR UAV positioning and energy-efficiency challenges, we have proposed the Energy-aware RElay Positioning (EREP) algorithm. EREP defines the trajectory and speed of the FCR UAV that minimize the energy spent for the UAV propulsion. However, since EREP considers a theoretical radio propagation model for computing the minimum Signal-to-Noise Radio (SNR) values that allow to meet the FAPs traffic demand, this may lead to network performance degradation in real-world networking scenarios, especially due to the FCR UAV movement. In this article, we propose the Energy and Performance Aware relay Positioning (EPAP) algorithm. Built upon the EREP algorithm, EPAP defines target performance-aware SNR values for the wireless links established between the FCR UAV and the FAPs and, based on that, computes the trajectory to be completed by the FCR UAV, so that the energy spent for the UAV propulsion is minimized. EPAP was evaluated in terms of both the flying network performance and the FCR UAV endurance, considering multiple networking scenarios. Simulation results show gains up to 25% in the FCR UAV endurance, while not compromising the Quality of Service offered by the flying network.</p>

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

Traffic-Aware UAV Placement Using a Generalizable Deep Reinforcement Learning Methodology

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

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

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

Supervised
thesis

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

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

Acoustic Networking for Controlling Underwater Data Mules

Author
Mariam Ahmed Osman Ahmed Mohamed

Institution
UP-FEUP