  Doubly selective (DS) channel estimation in largescale multiple-input
multiple-output (MIMO) systems is a challenging problem due to the requirement
of unaffordable pilot overheads and prohibitive complexity. In this paper, we
propose a novel distributed compressive sensing (DCS) based channel estimation
scheme to solve this problem. In the scheme, we introduce the basis expansion
model (BEM) to reduce the required channel coefficients and pilot overheads.
And due to the common sparsity of all the transmit-receive antenna pairs in
delay domain, we estimate the BEM coefficients by considering the DCS
framework, which has a simple linear structure with low complexity. Further
more, a linear smoothing method is proposed to improve the estimation accuracy.
Finally, we conduct various simulations to verify the validity of the proposed
scheme and demonstrate the performance gains of the proposed scheme compared
with conventional schemes.
