… channel sparsification based approach, which is shortened as S-EP. The key idea is to sparsify
the channel … an uplink M-MIMO system employing M antennas at the base station (BS) to …

… This allows us to estimate the users’ DL channel covariance matrix from UL pilots without …
a novel sparsifying precoder in order to maximize the rank of the effective sparsified channel …

… In Section II, we present the massive MIMO system model with uplink channel training and
data transmission, followed by asymptotic analysis on the channel covariance matrix and the …

… for transforming a MIMO channel model into a channel with a sparse … a MIMO channel
signal in the form of a Markov process. Hence, it becomes possible to use simple iterative MIMO …

… two new compression methods for channel feedback in massive MIMO systems using the
fact that highly correlated CSI can be represented in a sparse form. For a sparsifying basis, we …

… by introducing a sparsifying dictionary for the channel vector … A dictionary-learning based
approach for sparse channel … -DL sparsifying dictionary which allows for compressed channel …

… channel sparsifying hybrid precoding (RCSHP) design to reduce the signaling overhead
of channel estimation and the hardware cost and power consumption at the base station (BS), …

… massive MIMO system can serve various users simultaneously in the same time-frequency
block, due to the large … link and joint channel sparsity, the design of sparsifying matrix F is very …

… Due to this effect, known as beam squint, the conventional channel model is no longer
applicable for mmWave massive MIMO systems. In this paper, we study channel estimation under …

… DP-UPA Channel Model We consider a single-cell massive MIMO system where the base
station is equipped with an Mx × My × 2 dual-polarized uniform planar array (DP-UPA) serving …