  Channel state information at the transmitter (CSIT) is essential for
frequency-division duplexing (FDD) massive MIMO systems, but conventional
solutions involve overwhelming overhead both for downlink channel training and
uplink channel feedback. In this letter, we propose a joint CSIT acquisition
scheme to reduce the overhead. Particularly, unlike conventional schemes where
each user individually estimates its own channel and then feed it back to the
base station (BS), we propose that all scheduled users directly feed back the
pilot observation to the BS, and then joint CSIT recovery can be realized at
the BS. We further formulate the joint CSIT recovery problem as a low-rank
matrix completion problem by utilizing the low-rank property of the massive
MIMO channel matrix, which is caused by the correlation among users. Finally,
we propose a hybrid low-rank matrix completion algorithm based on the singular
value projection to solve this problem. Simulations demonstrate that the
proposed scheme can provide accurate CSIT with lower overhead than conventional
schemes.
