In this letter, we propose an efficient off-grid sparse Bayesian learning (SBL) algorithm to
estimate the near-field (NF) channel in ultra-scale massive multiple-input multiple-output …

Numerical evidence suggests that compressive sensing (CS) approaches for wideband
massive MIMO channel estimation can achieve very good performance with limited training …

This paper addresses wideband channel estimation in an uplink massive multiple-input
multiple-output (MIMO) system, which consists of multiple single-antenna users and a base …

We investigate wideband uplink channel estimation for a multi-user (MU) multiple-input
single-output (MISO) OFDM system, in which the base station (BS) is equipped with an …

The problem of wideband massive MIMO channel estimation is considered. Targeting for
low complexity algorithms as well as small training overhead, a compressive sensing (CS) …

To address the challenging problem of downlink channel estimation with low pilot overhead
in massive multiple-input multiple-output (MIMO) systems, an empirical Bayesian block …

This letter focuses on the problem of uplink channel estimation with the reduced fronthaul
overhead in cell-free massive multiple-input multiple-output (mMIMO) systems. First, we …

Pilot contamination posts a fundamental limit on the performance of massive multiple-input-
multiple-output (MIMO) antenna systems due to failure in accurate channel estimation. To …

This paper proposes a hierarchical sparse estimation of spatial non-stationarity channel for
uplink massive multiple-input multiple-output (MIMO) systems without prior information …

Extremely large-scale massive MIMO (XL-MIMO) has been reviewed as a promising
technology for future wireless communications. The deployment of XL-MIMO, especially at …