We study the problem of downlink channel estimation in multi-user massive multiple input
multiple output (MIMO) systems. To this end, we consider the use of Bayesian compressive …

We consider downlink channel estimation in massive multiple input multiple output (MIMO)
systems using a Bayesian compressive sensing (BCS) approach. BCS exploits the sparse …

To reduce the pilot overhead of downlink channel estimation in massive multiple-input-
multiple-output (MIMO) systems, a sparse recovery algorithm relying on the vector …

Recently, compressive sensing based massive multiple input multiple output (MIMO)
channel estimation (CE) has attracted intensive research interest. By exploiting the …

To cope with the bottlenecks of the high computational complexity and excessive inter-
connection communication in the conventional centralized baseband processing …

We propose an efficient sparse channel estimation algorithm based on the compressed
sensing (CS) approach for large scale multi-user (MU) MIMO systems. The proposed …

In this letter, we propose a new channel estimation scheme for downlink channels in
massive multiple-input multiple-output systems, where orthogonal frequency-division …

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 …

In this paper, channel estimation problem for downlink massive multi-input multi-output
(MIMO) system is considered. Motivated by the observation that channels in massive MIMO …