  This paper presents a study on multiple-antenna interference channels,
accounting for general overhead as a function of the number of users and
antennas in the network. The model includes both perfect and imperfect channel
state information based on channel estimation in the presence of noise. Three
low complexity methods are proposed for reducing the impact of overhead in the
sum network throughput by partitioning users into orthogonal groups. The first
method allocates spectrum to the groups equally, creating an imbalance in the
sum rate of each group. The second proposed method allocates spectrum unequally
among the groups to provide rate fairness. Finally, geographic grouping is
proposed for cases where some receivers do not observe significant interference
from other transmitters. For each partitioning method, the optimal solution not
only requires a brute force search over all possible partitions, but also
requires full channel state information, thereby defeating the purpose of
partitioning. We therefore propose greedy methods to solve the problems,
requiring no instantaneous channel knowledge. Simulations show that the
proposed greedy methods switch from time-division to interference alignment as
the coherence time of the channel increases, and have a small loss relative to
optimal partitioning only at moderate coherence times.
