Building extreme-throughput wireless communication systems for 6G

Leuven - PhD
More than two weeks ago

You will design the fastest and most energy-efficient wireless communication systems of the future.


Over the last decades, wireless communications have evolved in order to support an ever-increasing throughput thanks to higher bandwidth, spatial multiplexing, and improved implementation of high-speed communication schemes. In order to achieve 100 Gbps or more, novel solutions are required to go beyond what is offered by 5G networks and by the latest WLAN standards such as 802.11ax/ay.

Investigating frequencies above 100 GHz will be necessary in order to provide a sufficient bandwidth. However, this comes with specific challenges, requiring large multiple-antenna systems using MU-MIMO or hybrid beamforming approaches in order to overcome the specific propagation characteristics. Simultaneously we must manage the huge implementation complexity, power consumption and sensitivity to non-idealities of such systems.

Together with higher throughput, new applications will require guarantees on quality-of-service. This includes minimal latency for applications such as augmented reality, robustness in mobile scenarios, and simultaneous support for multiple users in office and outdoor scenarios. This will require to combine the high-throughput physical-layer pipeline with adaptive MAC protocols.


This PhD will build on imec's experience of high-throughput mm-wave communication systems and identify the key components to investigate based on state-of-the-art literature and assessment of the expected link and system power consumption in future systems. Novel waveforms, signal processing blocks and system architectures will be simulated primarily in Matlab in order to evaluate the system performance and optimize the different components. This research may be combined with experiments and measurement on our communication testbed.

Required background: Electrical Engineering, Signal Processing for Communications

Type of work: 60% modeling/simulation, 20% literature/theory, 20% experimental

Supervisor: Sofie Pollin

Daily advisor: Claude Desset

The reference code for this position is 2020-094. Mention this reference code on your application form.


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