  Hybrid beamforming (HB) has been widely studied for reducing the number of
costly radio frequency (RF) chains in massive multiple-input multiple-output
(MIMO) systems. However, previous works on HB are limited to a single user
equipment (UE) or a single group of UEs, employing the frequency-flat
first-level analog beamforming (AB) that cannot be applied to multiple groups
of UEs served in different frequency resources in an orthogonal
frequency-division multiplexing (OFDM) system. In this paper, a novel HB
algorithm with unified AB based on the spatial covariance matrix (SCM)
knowledge of all UEs is proposed for a massive MIMO-OFDM system in order to
support multiple groups of UEs. The proposed HB method with a much smaller
number of RF chains can achieve more than 95% performance of full digital
beamforming. In addition, a novel practical subspace construction (SC)
algorithm based on partial channel state information is proposed to estimate
the required SCM. The proposed SC method can offer more than 97% performance of
the perfect SCM case. With the proposed methods, significant cost and power
savings can be achieved without large loss in performance. Furthermore, the
proposed methods can be applied to massive MIMO-OFDM systems in both
time-division duplex and frequency-division duplex.
