  Massive multi-user multiple-input multiple-output (MU-MIMO) systems enable
high spatial resolution, high spectral efficiency, and improved link
reliability compared to traditional MIMO systems due to the large number of
antenna elements deployed at the base station (BS). Nevertheless, conventional
massive MU-MIMO BS transceiver designs rely on centralized linear precoding
algorithms, which entail high interconnect data rates and a prohibitive
complexity at the centralized baseband processing unit. In this paper, we
consider an MU-MIMO system, where each user device is served with multiple
independent data streams in the downlink. To address the aforementioned
challenges, we propose a novel decentralized BS architecture, and develop a
novel decentralized precoding algorithm based on eigen-zero-forcing (EZF). Our
proposed approach relies on parallelizing the baseband processing tasks across
multiple antenna clusters at the BS, while minimizing the interconnection
requirements between the clusters, and is shown to closely approach the
performance of centralized EZF.
