Deep learning has gained great popularity due to its widespread success on many inference
problems. We consider the application of deep learning to the sparse linear inverse …

We develop a broadband channel estimation algorithm for millimeter wave (mmWave)
multiple input multiple output (MIMO) systems with few-bit analog-to-digital converters …

This comprehensive and engaging textbook introduces the basic principles and techniques
of signal processing, from the fundamental ideas of signals and systems theory to real-world …

Hybrid analog/digital architectures and receivers with low-resolution analog-to-digital
converters (ADCs) are two low power solutions for wireless systems with large antenna …

Channel estimation is one of the main challenges for implementing reconfigurable intelligent
surface (RIS)-aided communication system with a large number of antennas at the base …

In this paper, we research the multiuser detection (MUD) in a new Spatial Modulation
Multiple-Input-Multiple-Output (SM-MIMO) system, whose Base Station (BS) is equipped with …

The generalized linear model (GLM), where a random vector x is observed through a noisy,
possibly nonlinear, function of a linear transform output z= Ax, arises in a range of …

The generalized approximate message passing (GAMP) algorithm is an efficient method of
MAP or approximate-MMSE estimation of x observed from a noisy version of the transform …

The hardware cost and power consumption of a massive multiple-input multiple-output
(MIMO) system can be remarkably reduced by using a very low-resolution analog-to-digital …

Binary measurements arise naturally in a variety of statistics and engineering applications.
They may be inherent to the problem-for example, in determining the relationship between …