Extremely large-scale multiple-input-multiple-output (XL-MIMO), which offers vast spatial
degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth …

Mathematical optimization is now widely regarded as an indispensable modeling and
solution tool for the design of wireless communications systems. While optimization has …

Learning to optimize (L2O) is an emerging approach that leverages machine learning to
develop optimization methods, aiming at reducing the laborious iterations of hand …

In this paper, we investigate the model-driven deep learning (DL) for MIMO detection. In
particular, the MIMO detector is specially designed by unfolding an iterative algorithm and …

The standard linear regression (SLR) problem is to recover a vector x 0 from noisy linear
observations y= Ax 0+ w. The approximate message passing (AMP) algorithm proposed by …

In this paper, we propose a model-driven deep learning network for multiple-input multiple-
output (MIMO) detection. The structure of the network is specially designed by unfolding the …

The emerging orthogonal time frequency space (OTFS) modulation technique has shown its
superiority to the current orthogonal frequency division multiplexing (OFDM) scheme, in …

Traditional symbol detection algorithms either perform poorly or are impractical to implement
for Massive Multiple-Input Multiple-Output (MIMO) systems. Recently, several learning …

Over the last decade or so, Approximate Message Passing (AMP) algorithms have become
extremely popular in various structured high-dimensional statistical problems. Although the …

Recently proposed orthogonal time frequency space (OTFS) modulation has been
considered as a promising candidate for accommodating various emerging communication …