  In this paper, we propose a joint pilot design and channel estimation scheme
based on the deep learning (DL) technique for multiuser multiple-input multiple
output (MIMO) channels. To this end, we construct a pilot designer using
two-layer neural networks (TNNs) and a channel estimator using deep neural
networks (DNNs), which are jointly trained to minimize the mean square error
(MSE) of channel estimation. To effectively reduce the interference among the
multiple users, we also use the successive interference cancellation (SIC)
technique in the channel estimation process. The numerical results demonstrate
that the proposed scheme considerably outperforms the state-of-the-art linear
minimum mean square error (LMMSE) based channel estimation scheme.
