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About

About

André Coelho obtained a Ph.D. in Telecommunications in 2023 and an M.Sc. in Electrical and Computer Engineering in 2016, both from the University of Porto, Portugal. Currently, he is a researcher in the Wireless Networks (WiN) research group of the Centre for Telecommunications and Multimedia (CTM) at INESC TEC.

Since joining INESC TEC in 2015, André Coelho has been actively involved in several national and European research projects, including NEXUS, PRODUTECH R3, Test Bed 5G & Digital Transformation, CONVERGE, OVERWATCH, ResponDrone, InterConnect, RAWFIE, WISE, 5Go, and CHIC. He has also been part of the supervision team of 20+ master's and undergraduate students.

His research interests include the management of communications resources for Quality of Service guarantees in emerging wireless networks. He has a special interest in flying networks formed by Unmanned Aerial Vehicles (UAVs).

Interest
Topics
Details

Details

  • Name

    André Filipe Coelho
  • Role

    Assistant Researcher
  • Since

    02nd November 2015
004
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.

2022

Joint Energy and Performance Aware Relay Positioning in Flying Networks

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

Publication
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

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

Publication
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

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

Publication
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

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

Publication
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.

Supervised
thesis

2022

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

Author
David Miguel de Almeida Coimbra Maia

Institution
UP-FEUP

2022

Slicing-Aware Flying Communications Network

Author
João Cristiano Mourão Rodrigues

Institution
UP-FEUP

2020

Gateway Positioning in Flying Networks

Author
Hugo Daniel Teixeira Rodrigues

Institution
UP-FEUP

2019

Network Planning Model for NB-IoT

Author
Renato Mendes da Cruz

Institution
UP-FEUP

2019

Routing for Flying Networks using Software-Defined Networking

Author
André Duarte Correia de Oliveira

Institution
UP-FEUP