/Holographic radio architectures and signal processing for future high-throughput near-field communications

Holographic radio architectures and signal processing for future high-throughput near-field communications

Leuven | More than two weeks ago

You will be architecting a novel paradigm of communications
Driven by new emerging applications such as augmented reality, virtual reality, backhauling, and broadband access, the future wireless connectivity landscape towards 6G and beyond will support a wide a range of applications with very-high-throughput requirements. Such stringent requirements make the radio access design very challenging. The traditional approaches to increase the wireless data rate are increasing the bandwidth and resorting to multi-input, multi-output (MIMO) techniques. The former is not scalable beyond a few GHz of bandwidth and the latter is often impossible in the sub-THz bands that do not feature rich multipath, which is needed to have a significant channel rank.

A completely different approach, yet largely unexplored, is to resort to MIMO near-field communications, dubbed as holographic radio. The near-field propagation can hold up to a significant range especially in high-frequency bands. Because transmission in the near field implies spherical waves instead of plane waves, the channel matrix can have a high rank even for point-to-point links. Hence, high throughput can be achieved with moderate bandwidth even in a point-to-point link because multiple independent streams can be sent in parallel.

Your mission for this PhD will be to define a performant - yet realistic - system concept and architecture of MIMO near-field communications and to develop the associated physical layer algorithms, leveraging the specific structure of the channel. You will have to deal with multi-dimensional trade-offs encompassing large antenna count, complexity, theoretical bounds, hardware impairments, to name a few. To support this research, you will develop a detailed simulation environment in Matlab and/or Python. It will be used to evaluate the system performance and optimize the different building blocks of the system. Importantly, it will need a specific channel model for the near-field propagation. The way the near-field channel compares to other MIMO schemes (traditional MIMO exploiting channel diversity, LOS-MIMO, ...) will strengthen the theoretical foundations of this communication scheme. This research may also include experimentation and measurements on a communication testbed.
As a PhD student, you will be part of a large IMEC team working on the research, implementation and prototyping of future communications systems composed of experts in digital, analog and mm-wave design, wireless communication systems, signal processing and machine learning, channel measurements and modelling. 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: Signal processing for wireless communications. Knowledge of channel modelling and optimization techniques is a plus. Proficiency with Matlab or Python.

Type of work: 10% literature and theory, 80% design, modelling and simulation, 10% design/experimental

Supervisor: Sofie Pollin

Co-supervisor: Andre Bourdoux

Daily advisor: Claude Desset

The reference code for this position is 2025-091. Mention this reference code on your application form.

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