  One of the first widespread uses of multi-user multiple-input multiple-output
(MU-MIMO) is in 5G networks, where each base station has an advanced antenna
system (AAS) that is connected to the baseband unit (BBU) with a
capacity-constrained fronthaul. In the AAS configuration, multiple passive
antenna elements and radio units are integrated into a single box. This paper
considers precoded downlink transmission over a single-cell MU-MIMO system. We
study optimized linear precoding for AAS with a limited-capacity fronthaul,
which requires the precoding matrix to be quantized. We propose a new precoding
design that is aware of the fronthaul quantization and minimizes the
mean-squared error at the receiver side. We compute the precoding matrix using
a sphere decoding (SD) approach. We also propose a heuristic low-complexity
approach to quantized precoding. This heuristic is computationally efficient
enough for massive MIMO systems. The numerical results show that our proposed
precoding significantly outperforms quantization-unaware precoding and other
previous approaches in terms of the sum rate. The performance loss for our
heuristic method compared to quantization-aware precoding is insignificant
considering the complexity reduction, which makes the heuristic method feasible
for real-time applications. We consider both perfect and imperfect channel
state information.
