The sparse channel estimation which sufficiently exploits the inherent sparsity of wireless
channels, is capable of improving the channel estimation performance with less pilot …

Accurate channel estimation with small pilot overhead is vital to improve the capacity and
reliability of massive MIMO systems. Recently, compressed sensing has been applied to …

Massive MIMO (multiple-input-multiple-output) is one of the key technologies of 5G mobile
cellular networks, which can form a huge antenna array by providing a large number of …

In massive MIMO systems, the channel shows a spatial non-stationarity that has a significant
impact on the design of sparse channel estimation scheme based on compressive sensing …

Aiming at a massive multi-input multi-output (MIMO) system with unknown channel path
number, a sparse adaptive compressed sensing channel estimation algorithm is proposed …

The pilot overhead provides fundamental limits on the performance of massive multiple-
input multiple-output (MIMO) systems. This is because the performance of such systems is …

The joint sparsity of uplink channels in massive multi‐input–multi‐output (MIMO) systems is
explored and a block sparse model is proposed for joint channel estimation. The block …

Downlink channel estimation with low pilot overhead is an important and challenging
problem in massive multiple‐input–multiple‐output (MIMO) systems due to the substantially …

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

In this study, a new greedy‐based algorithm for sparse channel estimation in frequency‐
division duplexing massive multiple‐input multiple‐output (MIMO) systems is introduced …