In this letter, we propose a deep learning (DL)-based channel estimation scheme for the
massive multiple-input multiple-output (MIMO) system. Unlike existing studies, we develop …

This paper proposes a deep learning-based channel estimation method for multi-cell
interference-limited massive MIMO systems, in which base stations equipped with a large …

This letter proposes a deep learning-based pilot design scheme to minimize the sum mean
square error (MSE) of channel estimation for multi-user distributed massive multiple-input …

Channel estimation is one of the key issues in practical massive multiple-input multiple-
output (MIMO) systems. Compared with conventional estimation algorithms, deep learning …

Millimeter-wave massive multiple-input multiple-output (MIMO) can use a lens antenna array
to considerably reduce the number of radio frequency (RF) chains, but channel estimation is …

Massive multiple-input multiple-output (MIMO) is one of the most promising techniques for
next generation wireless communications due to its superior capability to provide high …

This letter considers uplink massive MIMO systems with 1-bit analog-to-digital converters
(ADCs) and develops a deep-learning based channel estimation framework. In this …

This letter proposes a low-complexity deep-learning-based direction-of-arrival (DOA)
estimation method for a hybrid massive multiple-input multiple-output (MIMO) system with a …

In this paper, we propose a data-driven deep learning (DL) approach to jointly design the
pilot signals and channel estimator for wideband massive multiple-input multiple-output …

A critical bottleneck of massive multiple-input multiple-output (MIMO) system is the huge
training overhead caused by downlink transmission, like channel estimation, downlink …