Channel, Environment and Target Modeling for Joint Communication and Sensing in Microwave and Millimeter-Wave Frequency Bands

It is anticipated that Joint Communications and Sensing (JC&S) or Integrated Communications and Sensing (ICAS) will be a new pillar of future 6G and beyond wireless communications networks. This is motivated by the need to add perception to the wireless networks in order to enable many high level functionalities such as environment monitoring, environment mapping, security/surveillance, people and crowd monitoring, and many more, finding applications in smart home, smart building, smart city, smart factory, e-health, automotive, transportation, etc..

These two disciplines – wireless communications and radar – have until recently been treated separately and so was the channel and environment modelling. In wireless communications, the channel modelling was typically stochastic, deterministic or hybrid with some statistical link to the geometry of the channel. This enabled to model multipath channels without explicit link to a given geometry. Radar modelling was most often done with the assumption of line-of-sight channels and targets were modelled as static or fluctuating (Swerling models).

However, since the same transmit and receive antennas will be used for communications and sensing (radar), it becomes important to use a common model for both where the channel geometry is fully and explicitly taken into account. Then the wireless channel features can be mapped correctly in the radar detection or 3D imaging coordinates. In addition, the bandwidth (which is large at mm-waves) has an impact on both the propagation and the target modelling since it determines how much the physical features are resolved.

The selected PhD candidate will propose and develop a unified channel model for JC&S/ICAS such that the geometry of the channel, both the static and moving parts, thus including the environment and targets, are properly and consistently modelled, taking all-dimensions into account (time, space, frequency, bandwidth). Two frequency bands will be considered: FR3 and D-band. The work requires some propagation channel and/or target measurements. A possible extension could be to use machine learning (e.g. generative AI) to generate a large number of channel/environment/targets. 

As a PhD student you will be part of a large IMEC department working on the research, implementation and prototyping of future wireless communications and radar systems composed by experts in digital, analog and mm-wave design, radar and wireless communication systems, signal processing, machine learning algorithms. You will work in a team of propagation and channel modelling experts. You will publish your research in top-level journals and conferences.