  Massive MIMO systems are well-suited for mm-Wave communications, as large
arrays can be built with reasonable form factors, and the high array gains
enable reasonable coverage even for outdoor communications. One of the main
obstacles for using such systems in frequency-division duplex mode, namely the
high overhead for the feedback of channel state information (CSI) to the
transmitter, can be mitigated by the recently proposed JSDM (Joint Spatial
Division and Multiplexing) algorithm. In this paper we analyze the performance
of this algorithm in some realistic propagation channels that take into account
the partial overlap of the angular spectra from different users, as well as the
sparsity of mm-Wave channels. We formulate the problem of user grouping for two
different objectives, namely maximizing spatial multiplexing, and maximizing
total received power, in a graph-theoretic framework. As the resulting problems
are numerically difficult, we proposed (sub optimum) greedy algorithms as
efficient solution methods. Numerical examples show that the different
algorithms may be superior in different settings.We furthermore develop a new,
"degenerate" version of JSDM that only requires average CSI at the transmitter,
and thus greatly reduces the computational burden. Evaluations in propagation
channels obtained from ray tracing results, as well as in measured outdoor
channels show that this low-complexity version performs surprisingly well in
mm-Wave channels.
