Millimeter wave (mmWave) communications have recently attracted large research interest,
since the huge available bandwidth can potentially lead to the rates of multiple gigabit per …

This paper proposes a model-driven deep learning (MDDL)-based channel estimation and
feedback scheme for wideband millimeter-wave (mmWave) massive hybrid multiple-input …

Sparse representation can efficiently model signals in different applications to facilitate
processing. In this article, we will discuss various applications of sparse representation in …

In this paper, we consider the spectrum sharing planning problem for a full-duplex
unmanned aerial vehicle (UAV) relaying systems with underlaid device-to-device (D2D) …

Channel feedback is essential in frequency division duplexing (FDD) massive multiple-input
multiple-output (MIMO) systems. Unfortunately, prior work on multiuser MIMO has shown that …

Cell-free system where a group of base stations (BSs) cooperatively serves users has
received much attention as a promising technology for the future wireless systems. In order …

User scheduling (US) is the process of dynamic selection of the set of active users out of all
available users to serve in each time slot. This is done to optimize the system performance …

Due to the ability of feature extraction, deep learning (DL)-based methods have been
recently applied to channel state information (CSI) compression feedback in massive …

The massive multiple-input multiple-output (MIMO) technology considerably enhances the
spectral efficiency of a wireless communication system. However, it suffers from substantial …

This paper demonstrates the implementation of a space–frequency line coded-orthogonal
frequency-division multiplexing (SFLC-OFDM) system. The SFLC-OFDM system utilizes …