Background/Objectives: The increase in patients with type 2 diabetes, coupled with the
development of complications caused by the same disease is an alarming aspect for the …

This paper characterizes the performance of massive multiuser spatial modulation MIMO
systems, when a regularized form of the least-squares method is used for detection. For a …

In this paper, we consider the problem of recovering a sparse signal from noisy linear
measurements using the so called LASSO formulation. We assume a correlated Gaussian …

In this paper, we consider the problem of recovering a binary phase shift keying (BPSK)
modulated signal in a massive multiple-input-multiple-output (MIMU) system. The recovery …

We propose in this work to employ the Box-LASSO, a variation of the popular LASSO
method, as a low-complexity decoder in a massive multiple-input multiple-output (MIMO) …

This paper provided a comprehensive analysis of sparse signal estimation from noisy and
possibly underdetermined linear observations in the high-dimensional asymptotic regime …

The generalized penalized constrained regression (G-PCR) is a penalized model for high-
dimensional linear inverse problems with structured features. This paper presents a sharp …

This paper considers the problem of symbol detection in massive multiple-input multiple-
output (MIMO) wireless communication systems. We consider hard-thresholding preceeded …

In this work, the authors present an asymptotic high‐dimensional analysis of the regularised
zero‐forcing receiver in terms of its mean‐squared error (MSE) and bit error rate (BER) …

L0-regularized problems relate to applications in various fields, but their combinatorial
nature makes them challenging to address. Research efforts in this area have primarily …