… 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 …

… 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 …

… 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), …

… 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 …

… 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 …

… Throughout this chapter, we develop the idea of active channel sparsification (ACS), which
… channel training. This is done by designing a joint precoder that projects the user channels …

… 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 …

… estimation, we compare the performance of CS-based DL channel estimation when different
sparsifying matrices are applied. The training pilots in A is generated as iid CN(0,ρd/N), so …