Abstract
Massive multiple-input multiple-output (massive MIMO) systems, employing very large number of antennas, are attended to yield higher spectrum and energy efficiencies. However, as in basic MIMO, these gains cannot be achieved without accurate channel estimation. With a large number of antennas, the channel estimation is much more requested since its complexity is significantly increased. In this paper, by exploiting the common sparsity properties of massive MIMO channels, we propose a sparsity adaptive subspace pursuit (SASP) algorithm for the massive MIMO channels recovery with unknown sparsity.
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