  Massive MIMO is considered as one of the key enablers of the next generation
5G networks.With a high number of antennas at the BS, both spectral and energy
efficiencies can be improved. Unfortunately, the downlink channel estimation
overhead scales linearly with the number of antenna. This does not create
complications in Time Division Duplex (TDD) systems since the channel estimate
of the uplink direction can be directly utilized for link adaptation in the
downlink direction. However, this channel reciprocity is unfeasible for the
Frequency Division Duplex (FDD) systems where different physical transmission
channels are existent for the uplink and downlink. In the aim of reducing the
amount of Channel State Information (CSI) feedback for FDD systems, the
promising method of two stage beamforming transmission was introduced. The
performance of this transmission scheme is however highly influenced by the
users grouping and selection mechanisms. In this paper, we first introduce a
new similarity measure coupled with a novel clustering technique to achieve the
appropriate users partitioning. We also use graph theory to develop a low
complexity groups scheduling scheme that outperforms currently existing methods
in both sum-rate and throughput fairness. This performance gain is demonstrated
through computer simulations.
