  Millimeter wave is a promising technology for the next generation of wireless
systems. As it is well-known for its high path loss, the systems working in
this spectrum tend to exploit the shorter wavelength to equip the transceivers
with a large number of antennas to overcome the path loss issue. The large
number of antennas leads to large channel matrices and consequently a
challenging channel estimation problem. The channel estimation algorithms that
have been proposed so far either neglect the probability of estimation error or
require a high feedback overload from receivers to ensure the target
probability of estimation error. In this paper, we propose a multi-stage
adaptive channel estimation algorithm called robust adaptive multi-feedback
(RAF). The algorithm is based on using the estimated channel coefficient to
predict a lower bound for the required number of measurements. Our simulations
demonstrate that compared with existing algorithms, RAF can achieve the desired
probability of estimation error while on average reducing the feedback overhead
by 75.5% and the total channel estimation time by 14%.
