5 Oct 2023Job Information
Engineering » Communication engineering
First Stage Researcher (R1)
15 Dec 2023 - 22:00 (Europe/Paris)
Type of Contract
Is the job funded through the EU Research Framework Programme?
Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?
Resource allocation techniques based on machine learning for optimizing the performance of massive cell-free MIMO in 6G and beyond networks
Wireless communication systems are currently under pressure due to increasing data consumption by individuals and widespread teleworking. To address this issue, a number of disruptive technologies need to be implemented in future 6G and beyond standards. One of these major technologies is the cell-free paradigm, based on the elimination of the concept of subdividing coverage areas into cells. In the cell-free context, a large number of access points (APs) are distributed over a large geographical area to optimally serve all users present in the zone. These APs are connected to a central processing unit (CPU) via wired or wireless links. Cell-free Massive MIMO (CF-mMIMO) is a generalization of 5G Massive MIMO (Mutiple Input Multiple Output), enabling more uniform coverage and increased connectivity for users thanks to the proximity and diversity of APs. However, these systems require the implementation of new resource management techniques that are appropriate to the context of distributed deployment, and that take into account several constraints like limited power consumption, low latency and high Quality of Service (QoS).
The aim of this internship is to propose new techniques for optimizing B5G and 6G communications to enable power-efficient and spectrum-efficient massive access. Adequate interference management is essential to achieve this goal. Novel optimization strategies will be introduced so as to reduce the energy consumption of communications while guaranteeing a required QoS and fairness level to users. Non-orthogonal multiple access (NOMA), recently introduced in 5G, will also be considered. This technique consists of allocating two or more users to the same spectral/temporal resource through appropriate power multiplexing. By properly optimizing the assignment of users and their power in the cell-free context, it will be possible to achieve important trade-offs between the spectral and energy efficiencies of the systems on the one hand, and between the capacities achieved and the level of fairness of the services offered on the other.
The studied CF-mMIMO system will be assisted by Intelligent Reflecting Surfaces (IRS) which constitute a very promising solution for improving the link quality and enhance system performance. Additionally, machine learning tools will be leveraged for building efficient solutions to overcome the problems associated with high complexity and latency.
Keywords: Cell-free networks, massive MIMO systems, Non orthogonal multiple access, resource allocation, optimization, machine learning.
Duration:4 to 6 month, preferably starting during February 2024.
Internship allowance:around 600 Euros / month
Internship Location:Institut National des Sciences Appliquées (INSA)
20 Av. des Buttes de Coësmes, 35700 Rennes, France
The candidate must be in the final stages of obtaining an engineering and/or Master's degree in Telecommunications, Electricity-Electronics or other related fields.
Knowledge requirements include Mobile Communications, Signal Processing, Machine Learning, and Matlab programming.
Please send a CV, a motivation letter, copies of all academic records and grades (preferably with rankings), and (optionally) a recommendation letter to:
Joumana Farah: [email protected]
Matthieu Crussière: [email protected]
Only complete applications will be considered.
A remote interview will be scheduled for shortlisted candidates after examination of their application.
Possibility of pursuing a doctoral thesis
Funding is available to pursue the internship subject as a doctoral thesis. This will depend on the quality of the work carried out during the internship.Requirements
Engineering » Communication engineering
Master Degree or equivalent
Additional Information Work Location(s)
Number of offers available
INSA / IETR
GeofieldWhere to apply
https: // www. insa-rennes.fr
20 avenue des buttes de Coësmes