Job Description

PhD co-directors: E. Veronica Belmega (UGE, ESIEE Paris), Anne Savard (IMT Nord Europe)
Collaborators: Rodrigo C. de Lamare (PUC-Rio, Rio de Janeiro, Brazil and Univ. of York, UK), Dinh-Thuy Phan Huy (Orange Chatillon)

1. PhD scientific context and objectives

The energy consumption of the Information and communication technologies (ICT) sector – the backbone of our modern and digital society – has become a global and major issue.
In this context, jointly with reconfigurable intelligent surfaces (RIS), backscattering communications have attracted a lot of attention thanks to their ability to shape the wireless
environment to increase network capacity in a sustainable manner. Backscattering, as opposed to classical relaying, does not introduce additional electromagnetic waves, having thus zero added electromagnetic field exposure, and relies on low-cost and low-energy consumption devices (no RF active components), which can either send information by riding on the ambient RF signals or harvest their energy for operations.

In our prior work, we have derived the fundamental rate regions achievable in a multi-user non-orthogonal multiple access (NOMA) network assisted by a backscatter device and then
optimized its energy efficiency under minimum quality of service constraints. We have also investigated multiple backscatter devices assuming that they do not send any information, but are in full cooperative mode.

In this PhD project, the main goal is to move towards multiple separate or joined backscattering devices, which form reflective intelligent surfaces (RIS), that can transmit their own information while enhancing the ambient wireless communications. Also, we will explicitly consider in our new models, and optimize, the harvesting capabilities of the backscattering/RIS devices. Thus, our main objectives are:
OBJ1. Derive the fundamental achievable Shannon rates in multi-user, multi-backscatter/RIS networks via information theory;
OBJ2. Develop efficient algorithms that jointly tune the transmit strategy (input covariance matrices, power allocation over the users and carriers) and the backscattering/RIS strategy
(reflection coefficients, energy harvesting) via machine learning and optimization.

Two types of contributions are targeted within the two objectives: i) fundamental: derivation of information theoretical achievable Shannon rates when they are not readily available; ii)
algorithmic: design of efficient optimization algorithms to tune the transmission strategies jointly with that of the backscattering/RIS devices. The obtained results will be published in top-tier international journals (IEEE Trans. on Wireless Commun, IEEE Trans. on Signal Processing, IEEE Trans. on Green Commun. and Networking) and international conferences (IEEE ICC, IEEE GLOBECOM, etc).

2. PhD environment

The 3-year PhD candidate is funded within the PEPR 5G project on the "Development of advanced technologies for 5G and future networks”.
The PhD candidate will receive a gross salary of around 2k euro per month.
The PhD candidate will enroll in the Université Gustave Eiffel (UGE) doctoral school and will have to pay a relatively modest registration fee (around 400-500 euro per year).
The PEPR 5G project budget includes further PhD related expenses such as: participation to international conferences, short mobilities, publication fees, portable PC, etc.

3. How to apply?

The applicants should hold a Master degree (BAC+5) and have a strong background in either electrical engineering (with a focus on telecommunications and/or signal processing) or applied mathematics. A good English level in writing, reading and speaking is also required. Finally, having a strong mathematical background and/or computer literacy skills (Python, C++, MatLab, etc.) is a definite plus.

Applications will be received via the online application form below until the position is suitably filled.
NB: no applications will be received via email.

The application dossier should include: a short motivation letter (1 page max), an academic oriented CV (2 pages max), the academic track records for the M.Sc. and B.Sc. (post-BAC)
including rankings, Master diploma or equivalent, and two relevant reference letters.

Online application form:

Job Information

Anne Savard
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Noisy-le-Grand, Seine-Saint-Denis, France
Closing Date
June 30, 2024