… sparsity prior, our method can bring a considerable computational complexity reduction and
achieve better accuracy for the massive MIMO … first present the massive MIMO channel model…

… model having two sparsity components: commonly shared sparsity and individual … sparsity
model to better capture the group sparse structure in practical multi-user massive MIMO …

… In [20], the authors utilized the temporal correlations between user transmissions to propose
a dynamic compressive sensing based (DCS-based) algorithm for the burst-sparsity model. …

… This paper describes a robust sparse Bayesian learning approach for DOA estimation in the
… dimensional burst prior. Note that a simple burst prior has been proposed for massive MIMO …

… is to utilize the sparse structure of the massive MIMO-OFDM … In [6], a burst LASSO algorithm
is developed by considering … Dai, “Exploiting burst-sparsity in massive MIMO with partial …

… MU is separable and contains the same outliers. Then, we combine the channel sparsity with
the sparse … Liu, and HC So, “Non-uniform burst-sparsity learning for massive MIMO channel …

… In particular, a burst LASSO algorithm was developed for robust channel estimation in massive
MIMO … the burst-sparse structure of the channel [23]. They also developed a P-CSPI aided …

… in adjacent time slots, there are two sparsity models, ie, burstsparsity structure and frame-wise
joint sparsity structure [22]. The burst-sparsity structure is in line with the scenario where …

… of angular domain channel in massive MIMO is additionally … by sparse Bayesian learning
with the double-sparsity feature in … -uniform burst-sparsity learning for massive MIMO channel …

… explosion in data-traffic demand and services. Compared to 4G MIMO technologies, massive
MIMO can offer large … TDD and FDD operation modes for massive MIMO, and discuss their …