With the development of intelligent networks such as the Internet of Things, network scales
are becoming increasingly larger, and network environments increasingly complex, which …

The envisioned sixth-generation (6G) of wireless communications is expected to give rise to
the necessity of connecting very large quantities of heterogeneous wireless devices, which …

This paper considers massive access in massive multiple-input multiple-output (MIMO)
systems and proposes an adaptive active user detection and channel estimation scheme …

In this work, we consider direction-of-arrival (DoA) estimation in the presence of extreme
noise using Deep Learning (DL). In particular, we introduce a Convolutional Neural Network …

Sparse representation has attracted much attention from researchers in fields of signal
processing, image processing, computer vision, and pattern recognition. Sparse …

Millimeter wave (mmWave) signals experience orders-of-magnitude more pathloss than the
microwave signals currently used in most wireless applications and all cellular systems …

Used to analyze the time-evolution of fluid flows, dynamic mode decomposition (DMD) has
quickly gained traction in the fluids community. However, the existing DMD literature focuses …

In this paper, we study the problem of user activity detection and large-scale fading
coefficient estimation in a random access wireless uplink with a massive MIMO base station …

This paper proposes a spatially common sparsity based adaptive channel estimation and
feedback scheme for frequency division duplex based massive multi-input multi-output …

To fully utilize the spatial multiplexing gains or array gains of massive MIMO, the channel
state information must be obtained at the transmitter side (CSIT). However, conventional …