  This paper investigates downlink channel estimation in frequency-division
duplex (FDD)-based massive multiple-input multiple-output (MIMO) systems. To
reduce the overhead of downlink channel estimation and uplink feedback in FDD
systems, cascaded precoding has been used in massive MIMO such that only a
low-dimensional effective channel needs to be estimated and fed back. On the
other hand, traditional channel estimations can hardly achieve the minimum
mean-square-error (MMSE) performance due to lack of the a priori knowledge of
the channels. In this paper, we design and analyze a strategy for downlink
channel estimation based on the parametric model in massive MIMO with cascaded
precoding. For a parametric model, channel frequency responses are expressed
using the path delays and the associated complex amplitudes. The path delays of
uplink channels are first estimated and quantized at the base station, then fed
forward to the user equipment (UE) through a dedicated feedforward link. In
this manner, the UE can obtain the a priori knowledge of the downlink channel
in advance since it has been demonstrated that the downlink and the uplink
channels can have identical path delays. Our analysis and simulation results
show that the proposed approach can achieve near-MMSE performance.
