/Advanced Signal Processing in Cell-free Massive MIMO for Ultra-Reliable 6G Wireless Communication Systems

Advanced Signal Processing in Cell-free Massive MIMO for Ultra-Reliable 6G Wireless Communication Systems

PhD - Leuven | More than two weeks ago

You will be carrying out groundbreaking fundamental and applied research to architect the high-speed, ultra-reliable and low-latency 6G wireless communications networks of tomorrow!

Motivated by the new era of automation and the explosion of the IoT, the future wireless connectivity landscape of 6G and beyond will feature low-complexity high-throughput, ultra-reliable and low-latency wireless communication systems. Such stringent requirements make the radio access design very challenging and some fundamental performance / complexity tradeoffs must be made. Example of such requirements are packet error rate in motion of 10-9 or lower with latency in the order of few µs-ms. In building up such robust wireless systems, a radically new radio access architecture is needed consisting of a large number of distributed access nodes that cooperate to meet the target quality of service. For instance, cell-free massive MIMO systems, through coherent transmission, allow channel hardening by coherently beaming distributed signals towards the mobile terminals.

However, there are several research challenges that need to be addressed first and require a multi-dimensional co-optimization such that these distributed systems become practical and reliable. In fact, cell-free massive MIMO systems present huge challenges in fronthauling, synchronization, beamforming, load balancing and interference management, resource and user scheduling and their interplay, to name a few. Furthermore, in indoor dynamic environments accurate tracking and proactive network reconfigurations is needed to avoid outage scenarios, yet in relatively fast closed loop.

The purpose of this PhD is to explore the tradeoffs in this complex cross-disciplinary multidimensional design space and to propose robust signal processing for the PHY and low-MAC including (but not limited to) adaptive distributed MIMO beamforming, distributed synchronization through serial wired fronthauling architectures, and low-MAC resource allocation. The physical layer complexity that depends on the underlying signal processing, must comply with boundary conditions imposed by HW technology and the FH capabilities resulting in NP-hard multidimensional design. The theoretical models and algorithms will be further tested and refined in realistic indoor environments with the goal to improve the complexity-performance trade-offs.  Motivated by the real-time deployments of cell-free massive MIMO and given the intrinsic complexity embedded in some of the designs and optimizations, the research will be moved towards hiring ideas from artificial neural networks to replace the complex design problems with a well-trained deep neural network, especially, for devising low-complexity radio resource allocation solutions.              

Because of the multidisciplinary nature of this PhD research, the PhD candidate will be part of a large IMEC team working on the research, end-to-end implementation and prototyping of future high-speed communications systems: experts in digital, analog and mm-wave ASIC design, wireless/radar communications systems, PHY processing, MAC and higher layers, high-speed fronthaul networks, machine learning and optimization. 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, Wireless systems, Matlab and/or Python

Type of work: 20% theory/literature, 70% simulation, 10% experimentation

Supervisor: Ingrid Moerman

Daily advisor: Mamoun Guenach

The reference code for this position is 2023-078. Mention this reference code on your application form.

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