PhD - Leuven | Just now
Over the last decades, communication networks have grown exponentially, starting with low-rate applications such as voice calls and now offering high-speed mobile internet based on 4G, 5G and soon 6G deployments. Over the generations, expanding networks have embraced new frequency bands in order to meet increasing user throughput demands.
In the cellular world, frequency ranges (FRx) have been defined, corresponding to different carrier frequencies. First applications used FR1 (up to 6 GHz), then FR2 was defined in the mm-wave frequencies (24 - 53 GHz). While mm-wave frequencies offer more bandwidth, some concerns on technology readiness and long-range path loss or indoor propagation are slowing down its adoption. Hence, the industry is now looking at intermediate frequencies in the so-called FR3 band (7 - 24 GHz) where new spectrum is made available.
This band offers a promising trade-off between additional capacity and sufficient coverage, but it also brings many research challenges, related to the following points:
As a PhD student, you will seek fundamental understanding and propose novel solutions related to those challenges. You will understand the differences in channel propagation and hardware implementation constraints across the FR3 band. You will propose novel transceiver architectures and communication algorithms offering flexibility and the best power-performance trade-offs. You will also investigate how they could be developed to accommodate very different scenarios, either based on real-time reconfigurability or by developing a set of solutions tuned to different scenarios. AI tools may complement models to guide the selection and optimization of a different architectures at each specific site.
You will be part of a large imec community working on the research, implementation and prototyping of future communications systems with experts in wireless communication, signal processing, digital, analog and mm-wave design, and machine learning. This is a unique opportunity to develop innovative, multi-disciplinary technology and shape future wireless networks. You will publish your research in top-level journals and conferences.
Required background: Electrical engineer with expertise in wireless communications and signal processing. Knowledge of channel modelling and hardware implementation constraints is a plus. Proficiency with Matlab or Python.
Type of work: 20% literature and theory, 60% modelling and simulation, 20% design/experimental
Supervisor: Sofie Pollin
Co-supervisor: Claude Desset
Daily advisor: Claude Desset
The reference code for this position is 2026-213. Mention this reference code on your application form.