Wirelesslab




 
Fall-2020 NSERC USRA Internship Grants
The Wireless Lab at the EMT Centre of INRS


About the Wireless Lab, the EMT Centre, and INRS The Wireless Lab, located at the heart of downtown Montreal, is part of the Centre Énergie Matériaux et Télécommunications (EMT) of the Institut national de la recherche scientifique (INRS), a top-tier graduate-level university in Canada and one of the best in all its areas of specialty. That is according to consistant ranking (always 1st or 2nd, year after year) in terms of all normalized metrics that assess each university's research performance, impact and training at the graduate levels as well as the scope of its collaborative R&D with industry.
Objective NSERC Undergraduate Student Research Awards (USRA) grants are meant to nurture your interest and fully develop your potential for a research career in the natural sciences and engineering. They are also meant to encourage you to undertake graduate studies in these fields. If you would like to gain research work experience that complements your studies in an academic setting, these awards can provide you with financial support through your host institution.
Eligibility To be eligible to apply for an award, you must, by the submission deadline:
  • Be a Canadian citizen or permanent resident of Canada;
  • Be registered in a bachelor's degree program at an eligible institution;
  • Have obtained, over the previous years of study, at least a second class cumulative average.
Moreover, please be advised of the following provisions:
  • If you already hold a bachelor's degree and are studying toward a second bachelor's degree, you may still apply for this award;
  • You may hold only one USRA per fiscal year (April 1 to March 31);
  • You may hold a maximum of three USRAs throughout your undergraduate university career.
To hold an award, you must:
  • Have completed all the course requirements of at least the first year of university study (or two academic terms) of your bachelor's degree;
  • Have been registered in at least one of the two terms immediately before holding the award in a bachelor's degree program at an eligible institution;
  • Not have started a program of graduate studies in the natural sciences or engineering at any time;
  • Be engaged on a full-time basis in research and development activities in the natural sciences or engineering during the tenure of the award.
How to
Apply
  • Cover letter describing the work, courses or experiments that motivate you to join a research team at INRS;
  • Curriculum vitae;
  • Up-to-date official transcripts for completed academic terms by the time of application;
  • Part 1 of Form 202 must be completed by students using the NSERC Online System, to which an official transcript for completed academic terms must be attached. Part II of Form 202 must be completed by the research supervisor, prof. Sofiène Affes, the Team Leader of the Wireless Lab.
Selection
Criteria
  • Academic excellence (academic record, duration of previous studies, scholarships and awards);
  • Research ability or potential (relevance of work experience and academic training to the field of the proposed research, quality and originality of contributions to research and development, referees' assessments).
Duration
  • The duration of the award is 16 consecutive weeks on a full-time basis;
  • You may hold an award at any time during the year as permitted by your academic program;
  • Tenure may start on a date acceptable to both you and your host institution.
Value
  • These awards have a value of $4,500 from NSERC for a full 16-week period;
  • INRS/The Wireless Lab will supplement the amount of the award by 25% up to a total of $5,625.
Application Deadline Submit your application - after coordination with the Team Leader of the Wireless Lab (cf. below) - to Mrs. Carolyne Hebert at the Postdoctoral & Graduate Studies Office (PGSO) of INRS. Application should be submitted no later than Monday 21 September 2020.
Important Notice Should you opt for joining the Wireless Lab, you have to - prior to submitting your application to the PGSO - contact ASAP the Team Leader, prof. Sofiène Affes, to seek his endorsement and coordinate with him ahead of the deadline. Please do so no later than Friday 18 September 2020 at 17:00 PM EDT.

Please make sure that you indicate in your motivation letter: i) your intention to apply for this specific scholarship program; as well as your choice for ii) prof. Sofiène Affes; and for iii) one or more of the projects described below if you wish to work on the research topics proposed by his team under his supervision at the Wireless Lab.
Projects Proposed by the Wireless Lab
Introduction:
One of the key technologies that have emerged in recent years is the exploitation of unmanned aerial vehicles (UAVs) or drones in different applications ranging from the detection of hazardous materials in closed environments to the temporary deployment of flying base stations (also known as high-altitude platforms or HAPs) in future 5G and beyond networks. However, multiple challenges need to be addressed, including as one key example the accurate localization and synchronization of the UAVs. The problem becomes even more challenging in networks that deploy a large number of UAVs in swarm formations. Indeed, UAV swarms have to make their own decisions based on the information they share with each other. The aim of this project is to implement a fully synchronized swarm of UAVs or drones and to test its robustness to multiple scenarios requiring strict avoidance of obstacles indoor. The idea is to investigate new nature- or bio-inspired so-called “population-based” optimization techniques to ensure a fully functional swarm.

Project Outline:
In this project, we aim to develop a new synchronization scheme for a swarm of drones or UAVs flying indoor in the presence of obstacles.
In the first phase of this project, we will build a peer-to-peer communication protocol that allows the relaying of multiple key parameters such as the RSSI and propagation delay. This type information will be fed to reinforcement learning technique that ensure the synchronization between the UAVs. A potential extension to this work is swarm synchronization in a heterogeneous setting – of great interest in Internet of things (IoT) applications – involving the cooperation between the swarm of UAVs or drones and ground vehicles.
In the second phase of this project, we will focus on assessing the performance of the newly proposed solutions under realistic scenarios. In this testing phase, we will use crazyflie drones in different swarm formations.
In the third and final phase of this project, we will evaluate the extension of the proposed synchronization scheme to the heterogeneous setting above. In this phase, we will combine the swarm of crazyflie drones with other moving units on the ground (e.g., rover robots).

Required Skills:
The candidate should have a strong background in:
  • Python/MATLAB programming languages;
  • Arduino;
  • Linux operating system (e.g., Ubuntu distribution).
Introduction:
Indoor localization is very often a daunting task, especially over non-line-of-sight (NLOS) transmission links. Many solutions have been so far proposed in the literature. Most promising ones rely on the so-called fingerprinting scheme combined with machine learning and, hence, require an offline process referred to as learning phase that needs to be reconducted each time the user moves from one environment to another. An interesting solution alternatively exploits the estimates of both the directions of arrivals (DOAs) and the propagation time delays (TDs) for localization. Such technique, however, is sensitive to the online estimation of a moving user.

Project Outline:
In this project, we aim to develop a new online localization solution for moving users in indoor scenarios.
In the first phase of this project, we will investigate the improvement of Monte Carlo based joint DOAs and TDs estimation technique using a population based optimization solutions.
In the second phase of this project, we will focus on assessing the performance of the localization technique in a realistic environment. The DOAs and delays will later be fed to a localization technique to provide position estimates.
In the third phase of this project, we will focus on the assessment of the new localization technique in realistic environments that involve use of multiple unmanned aerial vehicles (UAVs). In this case, we will conduct two types of experiments. The first one uses Wi-Fi cards (e.g., Intel NIC and Atheros) mounted on a scientific-type drone (i.e., DJI Matrix). The second will exploit nano-drones (i.e., crazyflie) with their own “Loco Positioning” system.

Required Skills:
The candidate should have a strong background in:
  • C/C++/Python/MATLAB programming languages;
  • Linux operating system (e.g., Ubuntu distribution).
Basic knowledge of the IEEE 802.11xx PHY/MAC standards is recommended.
Introduction:
Channel parameter estimation plays a crucial role in wireless communication systems. Parameters such carrier frequency and timing offsets can be exploited for synchronization purposes. Other parameters such as direction of arrival are well suited for localization. Most existing works very often rely on theoretical assumptions that still need to be tested using practical hardware equipment. One possible interesting solution is to exploit off-the-shelf Wi-Fi cards already integrated in today’s computers. These cards (e.g., Intel NIC and Atheros) require a specific driver to be installed in order to obtain the channel state information (CSI). However, such configuration could turn out to be impracticable for testing. Indeed, each of Wi-Fi cards mentioned above requires a full desktop which can a difficult task for evaluation of scenarios including mobile users.

Project Outline:
In this project, we aim to use the a different type Atheros cards to create a network of multiple nodes for the testing of localization and channel parameter estimation techniques previously developed by our the team at the Wireless Lab.
In the first phase of this project, we aim to create a fully working network using different Atheros cards equipped on Arduino boards. This step includes the successful implementation of modified drivers, testing and monitoring the transmitted and received packets, and most importantly extracting the CSI using the modified drivers.
In the second phase of this project, we will focus on analyzing the extracted CSI at each receiving node. The CSI will be used to test compatible localization and channel parameter estimation techniques previously developed by our team.
In the third and final phase of this project, we will focus on adapting the Atheros card driver to combine the set Arduino boards with other moving units on the ground (e.g., rover robots that are also equipped with Arduino boards).

Required Skills:
The candidate should have a strong background in:
  • Wireless communications and signal processing;
  • Arduino API;
  • C/C++ programming languages;
  • Linux operating system (e.g., Ubuntu distribution).
Basic knowledge of the IEEE 802.11xx PHY/MAC standards is recommended.

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