… In Section 2, we introduce the system and sparse channel models, also construct sensing
matrix as the training signal. In Section 3, the proposed greedy and iterative algorithm which …

… The correlation of the channel support over time as well as the burst sparsity property
have been leveraged in [18] to estimate the downlink channel matrix. In this paper, we have …

… Time-Varying Massive MIMO Channel Model We consider a single-cell massive MIMO-OTFS …
Dai, “Exploiting burst-sparsity in massive MIMO with partial channel support information,” …

… bursting nature, sparse active user detection (SAUD) is an efficient enabler towards efficient
active user detection. However, the sparsity … of massive random access to a massive MIMO …

… This feature which is well-known as angular-sparsity in the massive MIMO … burst and
individual support in the channel matrix, a generic and but yet more complex massive MIMO …

… the massive MIMO, in addition to the codeword sparsity, we further exploit the channel sparsity
and user sparsity in … The proposed receiver algorithms for both MIMO and massive MIMO …

… massive multiple input multiple output (MIMO) systems using a Bayesian compressive
sensing (BCS) approach. BCS exploits the sparse … the massive MIMO channel has a block-sparse …

… -uniform burst sparsity… massive MIMO channel which has a clustered sparse structure in the
angular domain as shown in [20], [21]. To this end, as in [18], [19], we assume that the sparse …

… , common sparse structure [11], [19], burst sparse … sparse angular reciprocity between the
downlink and uplink channels is another sophisticated structure sparsity of the massive MIMO …

… 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 …