We consider the use of deep neural network (DNN) to develop a decision-directed (DD)-
channel estimation (CE) algorithm for multiple-input multiple-output (MIMO)-space-time …

In frequency division duplex massive MIMO systems, one critical challenge is that the
mobiles need to feed back a large downlink channel matrix to the base station, creating …

This paper presents a deep learning-aided iterative detection algorithm for massive
overloaded multiple-input multiple-output (MIMO) systems where the number of transmit …

In recent times, artificial intelligence (AI) has gained considerable attention as a highly
promising technology for enhancing the performance of multiple-input multiple-output …

The combination of cell-free massive multiple-input multiple-output (MIMO) systems along
with millimeter-wave (mmWave) bands is indeed one of most promising technological …

Deep learning (DL) provides a framework for designing new communication systems that
embrace practical impairments. In this paper, we present an exploration of DL as applied to …

Traditional channel estimation algorithms such as minimum mean square error (MMSE) are
widely used in massive multiple-input multiple-output (MIMO) systems, but require a matrix …

The channel hardening-exploiting message passing detection (MPD) algorithm achieves
good performance in large-scale multiple-input multiple-output (MIMO) systems. However …

In MIMO-OFDM systems, pilot design and estimation algorithm jointly determine the
reliability and effectiveness of pilot-based channel estimation methods. In order to improve …

Reconfigurable Intelligent Surface (RIS) is considered as an energy-efficient solution for
future wireless communication networks due to its fast and low-cost configuration. In this …