… frequency-division multiplexing (OFDM) receiver that exploits … [10] considered a mmWave
massive MIMO system that … for a massive MIMO system that comprises a massive MIMO base-…

… Basically, noise and interference are the major issues in the MIMO OFDM systems…
MIMO-OFDM. The main aim of the paper is to develop the fast MUD and CE algorithm in …

… —Machine learning (ML) can be used in various ways to improve multi-user multiple-input
multiple-output (MUMIMO) … frequency-division multiplexing (OFDM) signal structure to improve …

… To circumvent this fundamental constraint, we design a machine learning (ML)-based
time-division duplex scheme in which channel state information (CSI) can be obtained by …

… Machine learning algorithms, which make no mathematical assumptions and use only past
… in MIMO-OFDM systems. In this paper we propose a novel machine learning algorithm based …

… The random guided search based GAs have been shown to perform well in numerous
global search and optimization problems, such as machine learning [307]–[309], adaptive …

… Abstract—This paper proposes a deep learning approach to channel sensing and downlink
… This paper shows that by using a learning approach to design the analog sensing and the …

… Deep-Learning is a part of a broader family of machine learning methods based on learning
representations of data. Researchers in this area are mainly concerned about how to make …

… His research interests include wireless communications, machine learning, and sparse/…
His research interests include communications and information theory, machine learning, and …

… In recent years, challenges to traditional methods have emerged that use data-based
approaches relying on machine learning [15]–[19]. A popular scheme is machine learningbased …