Joint Radar and Communications in Massive MIMO Systems

Leuven - PhD
More than two weeks ago

You will be architecting a revolutionary radar-communication system where both functionalities support each other!


Pushed by ever increasing requirements in throughput, mobility and ubiquity, wireless communications are constantly evolving towards more and more complex systems, serving and localizing a huge number of human and non-human users.

Massive MIMO is an emerging wireless network architecture featuring a large number of antennas at the base station (or access point). These antennas can serve many users simultaneously. A massive MIMO system presents great advantages in terms of communication performance, robustness and availability.

The concept of reuse of the communication hardware for radar functionality is also emerging. It is based on the observation that the RF, analog and signal processing blocks of the communication and radar systems are relatively similar. This radar functionality can then be used for localization of terminals and of non-cooperating targets.

The purpose of this PhD research is to explore how the many transceivers and antennas of a massive MIMO systems can be used to form a very high-performance radar. Several challenges, such as antenna spacing, coherency and centralized vs distributed signal processing have to be overcome in order to deliver high quality radar outputs. Once these challenges are solved, the research will also focus on optimizing the radar and communications functionalities, for enhanced performance and novel modes of operation.           

The successful PhD candidate will be part of a large IMEC team working on the research, implementation and prototyping of future communications and radar systems: experts in digital, analog and mm-wave ASIC design, wireless communications and radar systems, PHY processing, MAC and higher layers, radar signal processing, machine learning.

Required background: Signal processing, Optimization. Desired: Wireless systems, Radar systems

Type of work: 90% modeling/simulation, 10% literature

Supervisor: Sofie Pollin

Daily advisor: Andre Bourdoux

The reference code for this position is 2020-095. Mention this reference code in your application.


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