In this paper, a neural network based Multiple-Input-Multiple-Output (MIMO) algorithm is
presented. The algorithm is specifically designed to be integrated in a coded MIMO-OFDM …

In this paper, we propose two deep-learning based uplink channel estimation approaches
that can utilize not only high-resolution-ADC-quantized but also low-resolution-ADC …

This paper considers a multiple-input multiple-output system with low-resolution analog-to-
digital converters (ADCs). In this system, we propose a novel communication framework that …

A new wave of wireless services, including virtual reality, autonomous driving and Internet of
Things, is driving the design of new generations of wireless systems to deliver ultra-high …

We consider an uplink multiuser multiple-input multiple-output (MU-MIMO) system with one-
bit analog-to-digital converters (ADCs). In this system, the construction of a low-complexity …

This paper investigates the optimal signal detection problem with a particular interest in
large-scale multiple-input multiple-output (MIMO) systems. The problem is NP-hard and can …

Multiuser multiple-input multiple-output (MU-MIMO) transmission techniques have been
popularly used to improve the spectral efficiency and user experience. However, due to the …

The belief propagation (BP) algorithm exhibits outstanding detection performance for the
multiple-input multiple-output (MIMO) transmission. However, this algorithm may fail to …

In this study, we consider the application of deep learning (DL) to tabu search (TS) detection
in large multiple-input multiple-output (MIMO) systems. First, we propose a deep neural …

In this paper, we propose two deep learning (DL) based receiver schemes in uplink multiple-
input multiple-output (MIMO) systems. In the first scheme, we design a pilot-assisted MIMO …