Energy-Efficiency enhancement in cell-free massive MIMO based 6G networks

Published : 18 January 2022

An alternative network infrastructure is appealing as the ultimate enabler of energy-efficiency (EE) and spectral-efficiency (SE), it is called cell-free massive MIMO (CF-mMIMO). In this latter, the cell boundaries are avoided and many access points (APs) share the different antennas at the (virtual) base station. Consequently, it results in smaller and lighter radio modules with only few antennas per AP.

However, cell-free massive MIMO can be economically attractive only if its implementation is based on low-cost hardware that, however, generates severe hardware imperfections (HWIs). Such HWIs affect the system performance and it is considered as the major bottleneck in cell-free massive MIMO systems in practice.

The main goal of the Postdoc is to explore the potentiality of distributed optimization methods and machine learning (ML) algorithms to achieve up substantial energy saving gains, compared to the existing literature, by mitigating HWIs in power-efficient RF transceivers. The postdoc will investigate sophisticated and comprehensive digital signal processing solutions to achieve substantial energy-efficiency enhancement in CF-mMIMO, by mitigating HWIs in power-efficient transceivers.

The candidate should have a PhD degree in Telecommunications, low layers. She/he should have diverse skills in signal processing, machine learning and mathematics. Some knowledge of massive MIMO systems are desirable. Programming software: Matlab, Python.

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