  Massive multiple-input multiple-output (mMIMO) communications are one of the
enabling technologies of 5G and beyond networks. While prior work indicates
that mMIMO networks employing time division duplexing have a significant
capacity growth potential, deploying mMIMO in frequency division duplexing
(FDD) networks remains problematic. The two main difficulties in FDD networks
are the scalability of the downlink reference signals and the overhead
associated with the required uplink feedback for channel state information
(CSI) acquisition. To address these difficulties, most existing methods utilize
assumptions on the radio environment such as channel sparsity or angular
reciprocity. In this work, we propose a novel cooperative method for a scalable
and low-overhead approach to FDD mMIMO under the so-called grid-of-beams
architecture. The key idea behind our scheme lies in the exploitation of the
near-common signal propagation paths that are often found across several mobile
users located in nearby regions, through a coordination mechanism. In doing so,
we leverage the recently specified device-to-device communications capability
in 5G networks. Specifically, we design beam selection algorithms capable of
striking a balance between CSI acquisition overhead and multi-user interference
mitigation. The selection exploits statistical information, through so-called
covariance shaping. Simulation results demonstrate the effectiveness of the
proposed algorithms, which prove particularly well-suited to rapidly-varying
channels with short coherence time.
