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Sobre

Sobre

André Coelho obteve um doutoramento em Telecomunicações em 2023 e um mestrado em Engenharia Eletrotécnica e de Computadores em 2016, ambos pela Universidade do Porto, Portugal. Atualmente, é investigador no grupo de investigação de Redes Sem Fios (WiN) do Centro de Telecomunicações e Multimédia (CTM) do INESC TEC.

Desde que se juntou ao INESC TEC em 2015, André Coelho tem estado ativamente envolvido em vários projetos de investigação nacionais e europeus, incluindo NEXUS, PRODUTECH R3, Test Bed 5G & Digital Transformation, CONVERGE, OVERWATCH, ResponDrone, InterConnect, RAWFIE, WISE, 5Go e CHIC. Também fez parte da equipa de orientação de mais de 20 estudantes de mestrado e licenciatura.

Os seus interesses de investigação incluem a gestão de recursos de comunicações para garantias de Qualidade de Serviço em redes sem fios emergentes. Tem um interesse especial em redes voadoras formadas por Veículos Aéreos Não Tripulados (UAVs).

Tópicos
de interesse
Detalhes

Detalhes

004
Publicações

2023

Traffic-aware gateway placement and queue management in flying networks

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

Publicação
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.

2022

Joint Energy and Performance Aware Relay Positioning in Flying Networks

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

Publicação
IEEE ACCESS

Abstract
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 coverage and capacity of existing networks. Several solutions have been proposed for the positioning of UAVs acting 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. In addition, state of the art works are focused on optimizing both the flying network performance and the energy-efficiency from the communications point of view, leaving aside a relevant component: the energy spent for the UAV propulsion. We propose the Energy and Performance Aware relay Positioning (EPAP) algorithm. EPAP defines target performance-aware Signal-to-Noise Ratio (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.

2022

ResponDrone - A Situation Awareness Platform for First Responders

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

Publicação
AIAA/IEEE Digital Avionics Systems Conference - Proceedings

Abstract
Short reaction times are among the most important factors in preventing casualties or providing first assistance to potential victims during large scale natural disasters. Consequently, first response teams must quickly gain a comprehensive overview and thus situation awareness of the disaster situation. To address this challenge, the ResponDrone-platform was developed within the scope of the ResponDrone project. A fleet of unmanned aerial vehicles provides critical information from the disaster site to the first response teams in real-time and can act as a communications relays in areas with disrupted communications infrastructure. The unmanned aerial vehicles are commanded via a web-based multi-mission control system. Data sharing between the individual components is realized via a web-based cloud platform. The ResponDrone platform's capabilities were successfully tested and validated within the scope of several flight and simulation trials. This paper describes the components that were developed, integrated into a system-of-systems and demonstrated during the ResponDrone project and explains how the components work together in order to execute task-based multi-UAV missions. Further, the results of the validation trials are presented and an outlook on the next steps for further exploitation of the ResponDrone platform is given. © 2022 IEEE.

2022

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

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

Publicação
IEEE ACCESS

Abstract
Flying networks, composed of Unmanned Aerial Vehicles (UAVs) acting as mobile Base Stations and Access Points, have emerged to provide on-demand wireless connectivity, especially due to their positioning capability. Still, existing solutions are focused on improving aggregate network performance using a best-effort approach. This may compromise the use of multiple services with different performance requirements. Network slicing has emerged in 5G networks to address the problem, allowing to meet different Quality of Service (QoS) levels on top of a shared physical network infrastructure. However, Mobile Network Operators typically use fixed Base Stations to satisfy the requirements of different network slices, which may not be feasible due to limited resources and the dynamism of some scenarios.We propose an algorithm for enabling the joint placement and allocation of communications resources in Slicing-aware Flying Access and Backhaul networks- SurFABle. SurFABle allows the computation of the amount of communications resources needed, namely the number of UAVs acting as Flying Access Points and Flying Gateways, and their placement. The performance evaluation carried out by means of ns-3 simulations and an experimental testbed shows that SurFABle makes it possible to meet heterogeneous QoS levels of multiple network slices using the minimum number of UAVs.

2022

Obstacle-aware On-demand 5G Network using a Mobile Robotic Platform

Autores
Maia, D; Coelho, A; Ricardo, M;

Publicação
2022 18TH INTERNATIONAL CONFERENCE ON WIRELESS AND MOBILE COMPUTING, NETWORKING AND COMMUNICATIONS (WIMOB)

Abstract
5G has become increasingly popular nowadays, mainly due to its characteristics which enable high data rates and low latency. At the same time, mobile robotic platforms, such as drones and robots, appeared as suitable platforms to carry radio stations, enabling the on-demand placement of 5G communications cells. The main contribution of this paper is an obstacle-aware on-demand 5G network. The proposed solution consists of a 5G radio station (gNB) carried by a mobile robotic platform capable of providing obstacle-aware wireless connectivity to 5G User Equipments (UEs), leveraged by a novel virtual network function - On-Demand Mobility Management Function (ODMMF). ODMMF is designed to integrate the 5G Core network and it allows to monitor the radio conditions provided to the served UEs, while enabling the positioning of the mobile robotic platform remotely by taking advantage of the visual information provided by on-board video cameras. The proposed solution was validated using an experimental prototype, under a representative networking scenario.

Teses
supervisionadas

2022

Control and Positioning of a 5G Radio Access Node Deployed in a Mobile Robotic Platform

Autor
David Miguel de Almeida Coimbra Maia

Instituição
UP-FEUP

2022

Slicing-Aware Flying Communications Network

Autor
João Cristiano Mourão Rodrigues

Instituição
UP-FEUP

2020

Gateway Positioning in Flying Networks

Autor
Hugo Daniel Teixeira Rodrigues

Instituição
UP-FEUP

2019

Routing for Flying Networks using Software-Defined Networking

Autor
André Duarte Correia de Oliveira

Instituição
UP-FEUP

2019

Network Planning Model for NB-IoT

Autor
Renato Mendes da Cruz

Instituição
UP-FEUP