  In this manuscript we tackle the problem of semi-distributed user selection
with distributed linear precoding for sum rate maximization in multiuser
multicell systems. A set of adjacent base stations (BS) form a cluster in order
to perform coordinated transmission to cell-edge users, and coordination is
carried out through a central processing unit (CU). However, the message
exchange between BSs and the CU is limited to scheduling control signaling and
no user data or channel state information (CSI) exchange is allowed. In the
considered multicell coordinated approach, each BS has its own set of cell-edge
users and transmits only to one intended user while interference to
non-intended users at other BSs is suppressed by signal steering (precoding).
We use two distributed linear precoding schemes, Distributed Zero Forcing (DZF)
and Distributed Virtual Signal-to-Interference-plus-Noise Ratio (DVSINR).
Considering multiple users per cell and the backhaul limitations, the BSs rely
on local CSI to solve the user selection problem. First we investigate how the
signal-to-noise-ratio (SNR) regime and the number of antennas at the BSs affect
the effective channel gain (the magnitude of the channels after precoding) and
its relationship with multiuser diversity. Considering that user selection must
be based on the type of implemented precoding, we develop metrics of
compatibility (estimations of the effective channel gains) that can be computed
from local CSI at each BS and reported to the CU for scheduling decisions.
Based on such metrics, we design user selection algorithms that can find a set
of users that potentially maximizes the sum rate. Numerical results show the
effectiveness of the proposed metrics and algorithms for different
configurations of users and antennas at the base stations.
