  Large MIMO transceivers are integral components of next-generation wireless
networks. However, for such systems to be practical, their channel estimation
process needs to be fast and reliable. Although several solutions for fast
estimation of sparse channels do exist, there is still a gap in understanding
the fundamental limits governing this problem. Specifically, we need to better
understand the lower bound on the number of measurements under which accurate
channel estimates can be obtained. This work bridges that knowledge gap by
deriving a tight asymptotic lower bound on the number of measurements. This not
only helps develop a better understanding for the sparse MIMO channel
estimation problem, but it also provides a benchmark for evaluating current and
future solutions.
