Fifth generation (5G) mobile communication systems have entered the stage of commercial
deployment, providing users with new services, improved user experiences as well as a host …

Machine learning (ML) which is a subset of artificial intelligence is expected to unlock the
potential of challenging large-scale problems in conventional massive multiple-input …

The deployment of fifth-generation (5G) broadband wireless cellular networks has enabled
the support of highly demanding applications, paving the way towards global broadband …

In this paper, we propose a deep learning based sphere decoding (SD) scheme to reduce
the detection complexity for the multiple-input multiple-output (MIMO) communication …

Wireless systems must be resilient to jamming attacks. Existing mitigation methods based on
multi-antenna processing require knowledge of the jammer's transmit characteristics that …

This paper proposes a deep learning algorithm to decode spheres in order to solve the multi-
input multi-output (MIMO) receiver's detection problem. The modified K and K1 sphere …

Deep learning shows immense potential for strengthening the cyber-resilience of renewable
energy supply chains. However, research gaps in comprehensive benchmarks, real-world …

Blind modulation recognition (BMR) has been proposed as a promising approach for
massive multiple-input multiple-output (M-MIMO) systems to support massive user …

In this paper, we investigate the design of statistically robust detectors for multi-input multi-
output (MIMO) systems subject to imperfect channel state information (CSI). A robust …

Model-driven machine learning for signal detection in the physical layer of mobile
communication systems combines well-known detector structures with learned parameters …