  Channel estimation in the RIS-aided massive multiuser multiple-input
single-output (MU-MISO) wireless communication systems is challenging due to
the passive feature of RIS and the large number of reflecting elements that
incur high channel estimation overhead. To address this issue, we propose a
novel cascaded channel estimation strategy with low pilot overhead by
exploiting the sparsity and the correlation of multiuser cascaded channels in
millimeter-wave massive MISO systems. Based on the fact that the phsical
positions of the BS, the RIS and users may not change in several or even tens
of consecutive channel coherence blocks, we first estimate the full channel
state information (CSI) including all the angle and gain information in the
first coherence block, and then only re-estimate the channel gains in the
remaining coherence blocks with much less pilot overhead. In the first
coherence block, we propose a two-phase channel estimation method, in which the
cascaded channel of one typical user is estimated in Phase I based on the
linear correlation among cascaded paths, while the cascaded channels of other
users are estimated in Phase II by utilizing the partial CSI of the common base
station (BS)-RIS channel obtained in Phase I. The total theoretical minimum
pilot overhead in the first coherence block is $8J-2+(K-1)\left\lceil
(8J-2)/L\right\rceil $, where $K$, $L$ and $J$ denote the numbers of users,
paths in the BS-RIS channel and paths in the RIS-user channel, respectively. In
each of the remaining coherence blocks, the minimum pilot overhead is $JK$.
Moreover, the training phase shift matrices at the RIS are optimized to improve
the estimation performance.
