In this paper, a novel hybrid architecture is proposed combining expert knowledge for
optimal power allocation and deep artificial neural networks (ANN) to address the access …

Drawing on the notion of parallel interference cancellation, this paper formulates a one-shot
linear receiver for the uplink of centralized, possibly cloud-based, radio access networks (C …

This letter applies a feedforward neural network trained in an unsupervised fashion to the
problem of optimizing the transmit powers in centralized radio access networks operating on …

Learning-based downlink power control in cell-free massive multiple-input multiple-output
(CFmMIMO) systems offers a promising alternative to conventional iterative optimization …

The downlink power control is challenging in a cell-free massive multiple-input multiple-
output (CFmMIMO) system because of the non-convexity of the problem. This paper …

The thesis delves into the intricacies of resource optimization in both massive Multiple-Input
Multiple-Output (MIMO) and cell-free massive MIMO (CFmMIMO) systems, which are pivotal …

Cell-free Massive MIMO is thought to be a potential technology to meet the high demands
and growing users in B5G networks and towards 6G wireless networks. The cell-free …

This paper proposes a novel real-time and low-complexity solution for the joint power
allocation and access point scheduling problem in the uplink cell-free massive multiple-input …