  Downlink channel estimation with low pilot overhead is an important and
challenging problem in large-scale MIMO systems due to the substantially
increased MIMO channel dimension. In this letter, we propose a block iterative
support detection (block-ISD) based algorithm for downlink channel estimation
to reduce the pilot overhead, which is achieved by fully exploiting the block
sparsity inherent in the block-sparse equivalent channel derived from the
spatial correlations of MIMO channels. Furthermore, unlike conventional
compressive sensing (CS) algorithms that rely on prior knowledge of the
sparsity level, block-ISD relaxes this demanding requirement and is thus more
practically appealing. Simulation results demonstrate that block-ISD yields
better normalized mean square error (NMSE) performance than classical CS
algorithms, and achieve a reduction of 84% pilot overhead than conventional
channel estimation techniques.
