Phase noise (PN) introduced by the oscillator at the base station and user side severely
degrades the channel estimation performance. This paper investigates the impact of PN on …

In Massive multiple-input multiple-output (MIMO) systems, channel estimation is crucial. The
large size of the antennas causes a significant pilot and feedback overhead, making it …

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) …

We consider angular-domain channel estimation in massive MIMO systems using one-bit
analog-to-digital converters (ADCs) with various thresholding schemes at the receivers. We …

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 …

Massive MIMO uses a large number of antennas to increase the spectral efficiency (SE)
through spatial multiplexing of users, which requires accurate channel state information. It is …

Massive MIMO has been adopted for 5G communications due to its wide spectrum and
energy efficiency. To realize its potential performance, however, accurate channel state …

Massive MIMO is a promising technology to improve both the spectrum efficiency and the
energy efficiency. The key problem that impacts the throughput of a massive MIMO system is …

This paper addresses the problem of massive multiple-input multiple-output (MIMO) channel
estimation in the presence of impulsive noise. In the literature, a sparse Bayesian learning …

By exploiting the sparsity of the channel in the delay and angle domains, compressed
sensing (CS) algorithms can be used for channel estimation of massive multiple‐input …