  In this paper, we study joint antenna activity detection, channel estimation,
and multiuser detection for massive multiple-input multiple-output (MIMO)
systems with general spatial modulation (GSM). We first establish a
double-sparsity massive MIMO model by considering the channel sparsity of the
massive MIMO channel and the signal sparsity of GSM. Based on the
double-sparsity model, we formulate a blind detection problem. To solve the
blind detection problem, we develop message-passing based blind
channel-and-signal estimation (BCSE) algorithm. The BCSE algorithm basically
follows the affine sparse matrix factorization technique, but with critical
modifications to handle the double-sparsity property of the model. We show that
the BCSE algorithm significantly outperforms the existing blind and
training-based algorithms, and is able to closely approach the genie bounds
(with either known channel or known signal). In the BCSE algorithm, short
pilots are employed to remove the phase and permutation ambiguities after
sparse matrix factorization. To utilize the short pilots more efficiently, we
further develop the semi-blind channel-and-signal estimation (SBCSE) algorithm
to incorporate the estimation of the phase and permutation ambiguities into the
iterative message-passing process. We show that the SBCSE algorithm
substantially outperforms the counterpart algorithms including the BCSE
algorithm in the short-pilot regime.
